Analyzing Their Contribution to Water Demand, Quality, and Groundwater Sustainability of Private Water Wells in Addis Ababa, Ethiopia

Analyzing Their Contribution to Water Demand, Quality, and Groundwater Sustainability of Private Water Wells in Addis Ababa, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Analyzing Their Contribution to Water Demand, Quality, and Groundwater Sustainability of Private Water Wells in Addis Ababa, Ethiopia Tulu Tolla Tura, Sisay Demeku This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5753835/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the role of private water wells in meeting the water demand, quality, and sustainability of groundwater resources in Addis Ababa, Ethiopia. As the city faces rapid urbanization and a rising population, private wells have emerged as a crucial supplementary water source, particularly in areas where public water supply is inadequate. However, challenges such as insufficient regulation, groundwater over-extraction, and contamination pose significant risks to the long-term viability of these wells. Data were gathered from 449 private wells, with a detailed water quality analysis conducted on 21 of them, focusing on parameters like turbidity, p H , nitrate, and fluoride levels. The findings indicate considerable variability in water quality; some wells exceeded safe limits for turbidity and nitrates, while others met acceptable standards for key indicators. Furthermore, groundwater extraction from private wells addresses only a small portion of the city's overall water demand. Compounding issues such as well interference, inefficient water usage, and declining water tables further complicate the situation. The study underscores the urgent need for enhanced regulation, integrated groundwater management, and active community participation to promote sustainable groundwater use. It also recommends strategies for improved well placement, ongoing water quality monitoring, and necessary infrastructural investments to alleviate the adverse effects associated with private well usage. This research offers important insights into urban water management dynamics and highlights the significance of private wells in supporting water supply in rapidly developing cities like Addis Ababa. Groundwater Sustainability Private Wells Water Quality Urban Water Management Addis Ababa Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Water is a vital resource for human survival, directly impacting public health, economic development, and environmental sustainability. For water to be deemed safe for human consumption, it must meet specific criteria related to quantity, accessibility, and quality, as outlined by the World Health Organization (WHO 2011 ). In urban areas like Addis Ababa, Ethiopia, where rapid population growth and urbanization have put significant pressure on existing water infrastructure, groundwater has become an increasingly essential resource. Groundwater, accessed through wells, is particularly important in regions that suffer from limited or unreliable surface water sources. As cities grow and the demand for water escalates, private water wells have emerged as a common solution for supplementing municipal water supplies. Globally, groundwater is a primary source of drinking water, supplying approximately 70% of all drinking water and 43% of irrigation water (UNESCO 2013). In Ethiopia, groundwater serves as the primary freshwater source, meeting more than 90% of the country’s water needs (Upton et al. 2018). The capital city of Addis Ababa, home to over 5 million residents, faces significant challenges in meeting its water demands. The municipal water system has struggled to keep up with the rapid population growth, placing immense pressure on the city's water supply infrastructure (Tadesse & Mesfin 2020 ). In this context, private water wells, drilled by households, businesses, and other private entities, have become a common alternative to the public supply. However, the growing dependence on private wells in Addis Ababa has raised several concerns, including the potential for groundwater depletion and contamination (Haile & Abera 2021 ).The absence of adequate regulations and management systems for private well development has led to issues such as over-extraction, contamination of groundwater, and lack of proper monitoring (Solly et al. 1995; USGS 1998). Groundwater quality, particularly, is vulnerable to contamination from domestic waste, industrial effluents, and improper well construction practices. In the absence of a centralized governance system for private well management, these issues are compounded, making it difficult to ensure the sustainable and equitable use of groundwater resources. Studies have emphasized the need for a structured approach to groundwater management, one that integrates well development with urban planning and considers both the environmental and health impacts of groundwater extraction (Mekash & Roman 2021). Proper well construction and monitoring of water quality are essential to mitigate risks associated with private wells, ensuring that groundwater remains a safe and sustainable resource for future generations (Upeto & Castelo Branco 2005). Moreover, the development of clear policies and regulations is necessary to prevent the over-exploitation of groundwater, safeguard its quality, and ensure that private well development is in line with the broader goals of sustainable urban water management. This study explores the development opportunities and challenges associated with private water wells in Addis Ababa, Ethiopia. It seeks to test three key hypotheses: first, that private water wells significantly contribute to meeting the city's water demand; second, that the water quality from private wells does not meet acceptable standards; and third, which the development of private wells negatively impacts the groundwater table. The study's primary objective is to evaluate the feasibility and challenges of private water well development in Addis Ababa, with specific focus on their coverage in meeting water demand, water quality, and their influence on neighboring boreholes. The research questions examine the challenges associated with well development and management, as well as the overall contribution of private wells to the water supply system. This study is crucial for understanding the role of private wells in supplementing public water systems. However, challenges such as over-extraction, aquifer depletion, and contamination must be addressed. By investigating these issues, the research aims to promote sustainable groundwater management practices and inform policy frameworks to mitigate the risks associated with private well proliferation (Kusumawati et al. 2020 ; Zhang et al. 2021). This research contributes to broader discussions on urban water management, offering insights into sustainable and equitable water access for a rapidly urbanizing city. Methods Addis Ababa, the capital city of Ethiopia, was founded in 1886 and stands as one of the largest and oldest urban centers in the country (Abebe & Tesfaye 2021). It is situated in the central part of Ethiopia, at coordinates of 9°1′48″N latitude and 38°44′24″E longitude (NGA 2012) (Fig. 1). As of recent estimates, the population of Addis Ababa exceeds five million, making it one of the most populous urban centers in Africa (Mekonnen & Tadesse 2022). Elevation and Geographic Setting The city is uniquely positioned at a high elevation, approximately 2,355 meters (7,726 feet) above sea level, which is characteristic of many parts of Ethiopia's central plateau. This elevation places Addis Ababa within the Ethiopian Highlands, a region renowned for its rugged topography and mountainous landscapes. The city itself is located on a broad plateau, surrounded by hills and mountains, which provide a dramatic backdrop and influence the city's climate and weather patterns. The city is at the foot of Mount Entoto, a prominent peak that rises sharply to the north of the urban area. Mount Entoto reaches an elevation of over 3,000 meters (9,800 feet) above sea level. This elevated terrain contributes to the city's cooler temperatures compared to other areas at lower altitudes within Ethiopia. To the south and east of Addis Ababa, the terrain slopes downward, giving way to lower valleys and plains. Climate Addis Ababa, located in the central highlands of Ethiopia, experiences a temperate climate influenced by its high altitude and the dynamic interactions between the Inter-Tropical Convergence Zone (ITCZ) and local topography. The ITCZ, a zone of low pressure where the tropical easterlies meet the moist equatorial winds, plays a critical role in the distribution and seasonality of rainfall across the region (Jury 2016). This climatic feature results in a distinct wet-dry seasonal pattern, which is modified by orographic effects, particularly as one move from lower elevations to higher altitudes within the Ethiopian highlands (Conway et al. 2004 ). Rainfall and Seasons The seasonal rainfall distribution in Addis Ababa is primarily governed by the annual migration of the ITCZ. The city experiences two main rainy seasons: the belg (small rainy season) from end of February to mid-May, and the kiremt (main rainy season) from end of June to September. The remaining months (October to February) tend to be drier, although some variability exists depending on local topography and altitude. The orographic effects of the Ethiopian highlands significantly influence the spatial distribution of rainfall, with areas at higher elevations receiving more precipitation than lower-lying regions (Seleshi & Zanke 2004). Temperature and Humidity Temperature and humidity in Addis Ababa are inversely related to altitude. The city is situated at approximately 2,355 meters above sea level, and its climate is characterized by moderate temperatures year-round. The mean temperature ranges from 12.4°C in November, when minimum temperatures are recorded in Sululta (altitude: 2,610 m), to a maximum of 20°C in May at Deberzeit (altitude: 1,900 m). During the rainy season, relative humidity remains high (> 50%), while in the dry season, it fluctuates between medium and low levels. Notably, Sululta , due to its higher altitude, experiences consistently high relative humidity throughout the year. Wind Speed and Sunshine Wind speeds in the Addis Ababa region are highest during the pre-rainy season months of April and May, reaching more than 1 m/s, and can exceed 2 m/s in Sululta . Wind speeds tend to be lower during the peak rainy season, particularly from July to September, when they fall below 1 m/s. Sunshine duration also exhibits seasonal variation. The wet season, which coincides with the main rainy months of July through September, experiences lower sunshine hours (approximately 4 hours per day). In contrast, the dry season, particularly November, is characterized by longer sunshine durations of up to 9 hours per day. Interestingly, sunshine duration does not vary significantly with altitude across the region. Hydrogeology Formation of Addis Ababa Addis Ababa, located in the central Ethiopian Plateau, is shaped by a complex geological structure, influencing its hydrogeological characteristics (Ha et al. 2021 ). The city's aquifers are primarily formed in volcanic and sedimentary rock layers dating back to the Tertiary and Quaternary periods, mainly basalt and tuff, shaped by volcanic activity, tectonic shifts, and erosion (Fentahun 2007). The Ethiopian Rift System, running through the region, plays a significant role in groundwater dynamics by creating fault systems and volcanic eruptions, resulting in aquifers within fractured basaltic rocks, where water is stored and transmitted (Tefera et al. 2010). These aquifers exhibit both primary porosity from the volcanic rocks and secondary porosity formed through fractures and weathering, enhancing groundwater storage and movement (Kebede et al. 2012). Studies have identified two aquifer systems: the upper aquifer, highly porous and recharged by rainfall, and the lower aquifer, which is less permeable but confined and recharged through lateral flow (Tesfaye et al. 2014; Tufa & Ayele 2011). Groundwater flow is influenced by topography and fault lines, with water moving from higher altitudes to lower areas (Berhanu 2017 ). However, increased extraction due to urbanization has raised concerns about sustainability and pollution, highlighting the need for better groundwater management to ensure long-term supply and quality (Zewdu et al. 2019; Asfaw et al. 2020 ). Data Source A combination of primary and secondary data sources was applied to achieve the objectives of this study to provide understanding of private water wells in Addis Ababa. The primary data sources were selected private water wells (21) from existing boreholes across the sub-city in order to collect water sample for quality analysis and indexing and discussion with ground water directorate experts (five experts including director of ground water directorate) of AAWSA. The main secondary data sources of the study was private water wells design document documented at AAWSA (18 design document), private water wells data documented at AAWSA (449 private water wells) and literatures. Furthermore, secondary data collected from working documents, reports, strategic plans, and development frameworks related to private wells and water access in Addis Ababa. Sampling Techniques The study employed a stratified random sampling method for quality analysis. This was important because different strata within the city (based on factors such as altitude, and density of private water wells) were likely to have different views. Stratified sampling ensured that each subgroup was proportionally represented. Primary data were collected using a two-stage sampling method. First, private water wells were grouped into clusters based on their location (upper, middle and lower part of the city), allowing for a stratified representation. After determining the required sample size from each cluster, random sampling techniques were applied. Data collection was carried out through KII supported by GIS and remote sensing methods to map and analyze the distribution and spatial interaction of the wells. Furthermore, water sample was collected from randomly sampled boreholes for quality analysis. Secondary data were collected through reviewing of design document documented, private water wells data documented and literatures relevant to study (publish scientific works, policy documents, and guidelines on private water well development). Sampling Population and Sample Size The population for this study comprised private water wells located in Addis Ababa, Ethiopia. To accurately define this population, several key factors were considered. First, the total number of private water wells in the city was determined, which, for the purpose of this study, was assumed to be 449 (Table 1). Second, the geographic distribution of these wells was a crucial factor, as the study accounted for variations between sub-city areas (Fig. 2). Additionally, water quality was considered, which was critical for assessing the health of the water supply from these wells. Finally, locations where water point mapping had been conducted were included, providing a more comprehensive view of well placement and interaction (Fig. 2). Finally, Addis Ababa water and sewerage authority, ground water directorate was considered sampled population for KII. By integrating these factors, the study aimed to gather detailed data on the private water wells in Addis Ababa, ensuring a well-defined sampling population. Table 1 Private water wells distribution across sub-cities of Addis Ababa Sub city Private water wells summery Addis Ketema 4 Akaki Kaliti 46 Arada 15 Bole 92 Gullele 13 Kirkos 85 Kolfe Keranio 31 Lideta 19 Nefas Silk - Lafto 116 Yeka 28 Grand total 449 The sample size determination followed a two-step sampling procedure since as presented in the table1above because the number and distribution of private water wells in the city were not uniform. First, the city clustered in to upper, middle and lower based on location. From clustered sub cities, seven sub-cities were selected based on private water wells density and distribution for water quality analysis sampling. Accordingly, Nefas Silk Lafto , Bole, Kirkos , Akaki Kaliti, Yeka, Kolfe Keranio and Gullele sub-cities were targeted for sampling private water wells (Table 2). From each selected sub-city, three private water wells were randomly select and triple water sample was collect for water quality analysis (Table 2). Proper water sampling, transportation, and storage are essential for accurate borehole water quality analysis. The sampling process was starts with the preparation of sterilized bottles, to avoid contamination. Sterile bottles with tight-fitting caps were used for microbiological tests. To ensure the sample is fresh from the aquifer, the borehole pump was run for 10–15 minutes, purging stagnant water from the system. To avoid contamination, gloves were worn, and bottles were handled by their sides. During transportation, maintaining proper temperature control is vital. Samples were transported in a cooler with ice packs; ensuring temperatures remain between 2–6°C to prevent microbial activity or chemical changes. Collected samples were transported to AAWSA laboratory within 24 hours to prevent degradation. For storage, preservatives such as nitric acid was added immediately after sampling to maintain specific conditions, such as pH < 2 for metal analysis. Proper labeling of bottles with details was done (such as date, time, location, and sample identifier) for traceability. Samples were stored in a refrigerator below 6°C (APHA 2017 ; WHO 2011 ).. Table 2 Sample distribution of private water wells in the sub-cities S/N Sub City Number of private water wells point Number of sampled private water wells 1 Nefas Silk Lafto 116 3 2 Bole 92 3 3 Kirkos 85 3 4 Akaki Kaliti 45 3 5 Yeka 28 3 6 Kolfe Keranio 31 3 7 Gullele 13 3 Total Private water wells sampled 21 By synthesizing these primary and secondary data; demand coverage, quality indexing and radius of influence of private water wells were assessed which associated with the development of private water wells in Addis Ababa. Laboratory Analysis The analysis of groundwater quality involves numerous physicochemical and biological parameters. However, a selected set of parameters were typically used for water quality indexing. The laboratory procedures for analyzing these parameters follow the standards outlined in APHA 2020, as adopted by the AAWSSA laboratory. The specific procedures for each parameter are detailed in (Table 3). Table 3 Summary of Laboratory Procedures for Each Parameter S/N Parameter Unit Procedure Reference 1 Turbidity NTU Measure using a nephelometric turbidity meter. Calibrate with formazin standard solutions. APHA 2020 Odor TON Collect the water sample in a clean, odor-free, glass container. Leave about 10% of the container volume as headspace to allow proper detection of odor. If odor is not detectable at ambient temperature, warm the sample to 40°C to enhance volatile compound release. Waft the air above the sample towards your nose without directly inhaling. Record the findings in a log, specifying both type and intensity of the odor. APHA 2020 2 Total Dissolved Solids (TDS) Mg/l Filter sample and measure TDS using a TDS meter or by evaporating a known volume and weighing residue. APHA 2020 3 Electrical Conductivity (EC) µs/cm Use a conductivity meter, calibrated with standard solutions, and measure at 25°C. APHA 2020 4 Total Alkalinity as CaCO3 Mg/l Titrate sample with standard HCl using methyl orange as the endpoint indicator. APHA 2020 5 Total Hardness as CaCO3 Mg/l Titrate with EDTA solution, using Eriochrome Black T as indicator. APHA 2020 6 pH Measure using a calibrated pH meter. APHA 2020 7 Magnesium Hardness as CaCO3 Mg/l Subtract calcium hardness (obtained using EDTA) from total hardness. APHA 2020 8 Calcium Hardness as CaCO3 Mg/l Titrate with EDTA after adding murexide indicator and adjusting pH to 12. APHA 2020 9 Ammonia as N Mg/l Use Nessler's method or salicylate method; measure colori-metrically. APHA 2020 10 Nitrite as N Mg/l React with sulfanilamide and NED dihydro-chloride, measure absorbance at 543 nm. APHA 2020 11 Nitrate as N Mg/l Reduce nitrate to nitrite using a cadmium column, then measure nitrite using colori-metry. APHA 2020 12 Sulfate as SO4 Mg/l Use the turbidimetric method, reacting with barium chloride, measure turbidity. APHA 2020 13 Phosphate as PO4 Mg/l Use the ascorbic acid method; measure absorbance at 880 nm. APHA 2020 14 Fluoride as F Mg/l Use SPADNS colorimetric method or ion-selective electrode. APHA 2020 15 Total Iron as Fe Mg/l Use phenanthroline method; measure colorimetric absorbance at 510 nm. APHA 2020 16 Manganese as Mn Mg/l Use the persulfate method or atomic absorption spectrometry (AAS). APHA 2020 17 Silica as SiO2 Mg/l React with molybdate reagent; measure absorbance at 410 nm. APHA 2020 18 Chloride as Cl Mg/l Titrate with silver nitrate using potassium chromate as indicator (Mohr’s method). APHA 2020 19 Bicarbonate Alkalinity as HCO3 Mg/l Calculate from total alkalinity after titration with HCl to pH 4.3. APHA 2020 20 Carbonate Alkalinity as CaCO3 Mg/l Determine from titration curve endpoints between pH 8.3 and 4.3. APHA 2020 21 Hydroxide Alkalinity as CaCO3 Mg/l Determine from titration curve endpoint above pH 8.3. APHA 2020 APHA 2020 (Standard Methods for the Examination of Water quality) Quality Index Model Water quality index (WQI) provides a single number that expresses the overall water quality, at a certain location and time, based on several water quality parameters. The objective of WQI is to turn complex water quality data into information that is understandable and usable by the public. A number of indices have been developed to summarize water quality data in an easily expressible and easily understood format. The WQI is basically a mathematical means of calculating a single value from multiple test results. Some of models used for water quality index estimation are weighted arithmetic index method (Brown et al. 1972 ), the Canadian council of ministers of environment water quality index (CCME WQI), nemerow pollution index (NPI) also called row’s pollution index and national sanitation foundation water quality index (NSF WQI) (Brown et al. 1970 ) and (Tyagi et al. 2013). Water Quality Index ( \(\:\mathbf{W}\mathbf{Q}\mathbf{I}\) ) i. Sub-Index for Each Parameter ( \(\:\text{S}\text{I}\text{i}\) ): The sub-index for parameter \(\:i\) is calculated as: $$\:{SI}_{i}=\:\frac{{V}_{i}-{V}_{min}}{{V}_{max}-{V}_{min}}$$ Where: \(\:{V}_{i}\) : Measured value of the parameter \(\:{V}_{min}\) : Minimum permissible value of the parameter \(\:{V}_{max}\) : Maximum permissible value of the parameter ii. Weighting the Parameters: Each parameter is assigned a weight ( \(\:\text{W}\text{i}\) ) based on its relative importance to overall water quality. The weights are predefined and normalized so that: $$\:W={\sum\:}_{i=1}^{n}Wi=1$$ iii. Weighted Sub-Indices: The weighted sub-index for each parameter is calculated by multiplying its sub-index ( \(\:SIi\) ) by its weight ( \(\:Wi\) ): \(\:WSIi=SIi\times\:Wi\) iv. Calculating the Overall WQI: The overall Water Quality Index is obtained by summing the weighted sub-indices for all n parameters: $$\:WQI={\sum\:}_{i=1}^{n}WSI$$ Radius of Influence Estimation The radius of influence of groundwater is defined as the distance from a pumping well where the groundwater level is significantly affected by pumping activities. This zone delineates the area where measurable drawdown, or the lowering of the water table or potentiometric surface, occurs, influencing groundwater flow. Factors such as the pumping rate, hydraulic conductivity, aquifer transmissivity, and the duration of pumping determine the size of this radius (Ha et al. 2021 ). The empirical approach used for estimating radius of influence was (Dragoni 1998 ; Myette et al. 1987 and Kyrieleis 1930 ) $$\:R=2\times\:(D-SWL)\times\:\surd\:S/D$$ Where: R = radius of influence (in meters) D = well depth (in meters) SWL = static water level (in meters) s = drawdown (in meters) Data Analysis The data analysis wasconducted using statistical tools available on the market according to its applicability. The study applied descriptive statistics to assess the status of demand coverage, water quality and radius of influence. In this regard, the study mainly employed mean and standard deviation to describe the existing scenarios. The statistical package use for data analysis was SPSS Version 16.2. Result and Discussion Distribution of Private Water Wells across Sub-Cities The distribution of private water wells across Addis Ababa's city administration exhibits significant spatial variation, reflecting diverse socio-economic and hydro-geological factors. According to the data, Nefas Silk-Lafto and Bole sub-cities possess the highest number of private water wells, with 116 and 92 wells, respectively (Fig. 3). This concentration aligns with findings that areas with rapid urban expansion and high-income populations often invest in private water supply infrastructure to compensate for inadequacies in public water systems (Mekonnen & Hoekstra 2016). The extensive residential developments and thriving commercial activities in these areas drive higher water demands, while their hydro-geological suitability such as adequate aquifer presence facilitates well construction (Gebrewahid et al. 2021). In contrast, sub-cities like Addis Ketema (4 wells) and Gullele (13 wells) report notably fewer wells (Fig. 3). This discrepancy could be influenced by higher population densities, limited land availability for private infrastructure, or unfavorable geological conditions restricting groundwater accessibility. Addis Ketema, characterized by its dense urban fabric and older settlements, aligns with studies that associate limited private well installations with constrained space and the predominance of older infrastructure (Mengistu et al. 2019). These factors hinder the feasibility of private wells compared to other water sourcing strategies. Sub cities such as Kirkos (85 wells) and Akaki Kaliti (46 wells) exhibit moderate well distributions (Fig. 3). Kirkos, with its mixed residential and commercial zones, reflects a balanced demand for private water resources. Akaki Kaliti, known for its industrial zones, relies on private wells to meet the dual demands of residential water needs and industrial operations, as seen in other urban-industrial regions globally (Foster et al. 2020). This pattern underscores the significant role of industrial water demand in shaping groundwater dependency. Overall, this distribution underscores the interplay between urbanization patterns, economic activities, and hydro-geological characteristics in Addis Ababa. Water Balance of Addis Ababa Water Supply System The Addis Ababa Water and Sewerage Authority (AAWSA) reported key metrics related to its water supply system in 2023/2024 (2016 in Ethiopian). The total inlet volume reached 165,014,085m³/day from reservoir source/surface water source, with authorized consumption accounting for 97,057,942m³/day. Unauthorized consumption was recorded at 134,320 m³/day, while accounted-for water amounted to 26,147,299 m³/day. Notably, unaccounted-for water (UFW), representing water lost due to leakage, theft, or inaccuracies in metering, totaled 41,674,524 m³ (AAWSA 2024). The total water losses were 67,956,143m³ which is approximately 41.2% of the total inlet volume, a significant proportion indicating inefficiencies in the system. The non-revenue water (NRW) includes all water produced but not billed of the total inlet volume, highlights substantial operational inefficiencies. Similarly, sub-Saharan Africa cities also face high NRW levels. For instance, Nairobi, Kenya NRW accounts for approximately 45% of the total water supply (World Bank 2016). Lagos, Nigeria:, NRW levels exceed 55% (WHO & UNICEF 2017). While Addis Ababa's NRW far exceeds these cities, it reflects the widespread challenges of infrastructure aging, poor maintenance, and unauthorized connections common across the region. The 2016 fiscal year water balance of Addis Ababa reveals significant inefficiencies, with NRW levels reaching alarming rates. A comparative analysis with other sub-Saharan cities underscores the need for immediate action to address water losses, optimize resource use, and ensure sustainable urban water supply systems. Potential Coverage of Private Water Wells in the City Water Demand The analysis of private water wells' contribution to Addis Ababa's water demand reveals a significant gap in the city's water supply infrastructure. Addis Ababa's population exceeds 5 million, with a per capita water demand estimated between 120 and 150 liters per day, translating to a total daily demand of approximately 1.2 million cubic meters. However, the current supply, managed predominantly by the Addis Ababa Water and Sewerage Authority (AAWSA), is limited to 563,000 cubic meters per day, leaving a substantial deficit of 637,000 cubic meters per day. Private water well is a groundwater source built, owned, and maintained by an individual or a private organization to supply water for personal purposes, including drinking, irrigation, or household activities (Ha et al. 2021 ). Private water wells have emerged as a supplementary source, yet their contribution remains minimal. Private water wells number, totaling 449 in the city, the sustainable potential, contribute an average output of 47.35 cubic meters per day per well (Table 4). This potential in a combined daily contribution of 21,260.10 cubic meters from private per day wells can cover about 1.77% of the total daily demand. It shows the limited role of private wells as a supplementary water source in addressing Addis Ababa's growing water demands (Table 4).. Similar patterns have been observed globally, with studies from Nairobi, Lagos, and other cities underscoring the limited capacity of private wells to mitigate urban water deficits (Ha et al. 2021 ; Sinha & Gupta 2022). The limited contribution stems from factors such as declining groundwater levels, the prohibitive costs of well construction and maintenance, and the absence of effective policies to integrate private wells into the municipal water supply network. Studies in Ethiopia suggest that groundwater depletion exacerbates the city's reliance on limited surface water sources, further straining supply systems (Demlie & Wohnlich 2006 ). For instance, research in cities like Nairobi and Lagos, which also face acute water scarcity, shows that private wells often contribute less than 5% of the total water demand, emphasizing their limited capacity to significantly offset shortages in the municipal water supply system (Kariuki & Schwartz 2005; Adekalu et al. 2009 ). This low contribution is often due to challenges such as insufficient groundwater availability, limited well yields, and inadequate infrastructure for water distribution. Similarly, Adekalu et al. ( 2009 ) report that in Lagos, the reliance on private wells has led to significant groundwater stress and quality concerns, with many wells becoming unviable due to contamination and over-extraction. In Cape Town, South Africa, the 2018 water crisis underscored the limitations of private wells in urban resilience. During the crisis, private wells temporarily supplemented municipal supplies but were unable to address the broader infrastructure deficits or mitigate the city's overreliance on surface water. This experience emphasized the need for integrated water resource management, combining municipal, private, and alternative sources like desalination and water recycling (Muller 2018). Urbanization places immense pressure on groundwater resources, particularly in cities like Addis Ababa. Increased impervious surfaces from urban sprawl reduce natural recharge rates, compounding groundwater depletion. Research from New Delhi, India, demonstrates a similar pattern, where heavy dependence on private wells has led to significant declines in water tables, with recharge rates unable to match extraction levels (Kumar et al. 2011). Furthermore, the lack of regulation and enforcement exacerbates challenges, leading to inequitable access and unsustainable use. Addis Ababa's experience reflects these broader trends. With urban expansion encroaching on recharge zones and the city's reliance on aging infrastructure, the sustainability of groundwater as a supplementary source is increasingly in question. While private wells provide localized relief, their capacity is inherently limited by geological and economic constraints. Addressing water supply challenges in Addis Ababa and similar cities requires a paradigm shift. Integrated water resource management (IWRM) offers a holistic approach, combining municipal systems with private wells, rainwater harvesting, and wastewater recycling. In Bangkok, Thailand, the integration of private wells into a centralized monitoring system has improved efficiency and reduced over-extraction, serving as a potential model for Addis Ababa (Foster & Garduño 2006). The limited role of private wells in addressing Addis Ababa’s water deficit mirrors global trends, where such wells serve as supplementary sources rather than comprehensive solutions. Comparative studies from Nairobi, Lagos, and Cape Town underscore the challenges of relying on private wells amidst growing urban water demands. While private wells provide crucial relief, their sustainability depends on effective governance, robust infrastructure, and integrated resource management. Table 4 Private water wells potential coverage of city water demand and supply 1 Addis Ababa Population 5 million Reference 2 Capita water demand 120 to 150 L/day AAWSA 2024 report 3 Demand 1.2 million m 3 /day 4 Supply 563,000 m 3 /day 5 Gap 637,000 m 3 /day 6 Number of private water wells 429 7 Average each private wells output 47.35 m 3 /day 8 Average potential water supply from private water wells 21,260.15 m 3 /days 9 Private water wells demand coverage 1.77% 10 Private water wells supply coverage 3.78% Water Quality of Private Water Wells The turbidity levels in the private wells of Addis Ababa ranged from 0.17 to 7.46 NTU, with a mean of 2.52 ± 2.51 NTU (Table 5). These findings reveal that 42.9% of the samples exceeded the WHO guideline of < 1 NTU for safe drinking water, suggesting potential microbial contamination. Elevated turbidity levels often indicate suspended particles or microbial presence due to insufficient filtration or infiltration of surface water. Similar studies in sub-Saharan Africa, including rural regions of Nigeria and Ethiopia, report turbidity values exceeding safe limits, frequently linked to agricultural runoff and poor sanitation practices in proximity to water sources (WHO 2017; Abiye 2018 ). The TDS levels in Addis Ababa’s private wells ranged from 109 to 531 mg/L, with a mean of 257 ± 99.68 mg/L, within the WHO limit of 1000 mg/L (Table 5). However, EC values (mean: 486.33 ± 168.84 µS/cm) suggest moderate mineralization, reflecting geological interactions. Comparatively, private wells in India and the United States have demonstrated higher TDS and EC values, often attributed to natural geological formations, industrial effluents, and agricultural practices (Kumar et al. 2020; USGS 2021) (Table 5). While moderate mineralization is not directly hazardous, prolonged exposure to elevated TDS may affect water palatability and health. The p H of the well water ranged from 6.20 to 8.13, with a mean of 7.23 ± 0.49, aligning well with the WHO guideline range of 6.5–8.5 (Table 5). The neutral to slightly alkaline nature of the water is attributed to carbonate buffering, a characteristic observed in groundwater systems across Ghana and South Africa (Agyeman 2019 ; Smith et al. 2020). This balance is crucial for mitigating corrosive effects on pipes and ensuring compatibility with drinking water standards. The total hardness values ranged from 34 to 406 mg/L as CaCO₃, with a mean of 222.13 ± 101.70 mg/L, classifying the water as moderately hard to very hard. Calcium (mean: 167.08 ± 79.97 mg/L) and magnesium (mean: 53.84 ± 23.89 mg/L) hardness dominated (Table 5). While hard water poses minimal direct health risks, it can cause scaling and reduce the efficiency of domestic appliances. Groundwater in arid regions such as Saudi Arabia and North Africa often exhibits even higher hardness levels due to calcareous aquifers (Al-Mahmoudi 2021 ). Ammonia-N concentrations (0.01–0.61 mg/L, mean 0.13 mg/L) fell within the WHO limit of 0.5 mg/L (Table 5). However, nitrate levels were concerning, with nitrite-N reaching 28.50 mg/L (mean: 3.32 ± 6.11), surpassing the WHO threshold of 10 mg/L in 14.3% of samples (Table 5). Elevated nitrate levels are frequently associated with agricultural runoff, as evidenced in Kenya and California’s Central Valley (Harter 2020; Oduor 2018). Sulfate concentrations (mean: 23.50 ± 51.61 mg/L, max: 240 mg/L) were comparable to levels observed in Europe and Asia, where industrial discharges and the dissolution of gypsum-bearing formations are prevalent sources (Jones et al. 2019). Elevated sulfate levels can contribute to laxative effects and scaling in distribution systems. Fluoride concentrations ranged from 0.01 to 1.68 mg/L, with a mean of 0.54 ± 0.36 mg/L (Table 5). While most samples were within the WHO guideline of 1.5 mg/L, a few exceeded this limit, posing risks of dental and skeletal fluorosis. Fluoride issues are well-documented in endemic regions of India and Ethiopia’s Rift Valley, emphasizing the need for local interventions (Ramesh & Rao 2019; Tekle-Haimanot 2017). Chloride levels (mean: 19.16 ± 18.25 mg/L) were well within the WHO limit of 250 mg/L, indicating minimal anthropogenic contamination. Iron concentrations ranged from 0.01 to 0.64 mg/L (mean: 0.12 ± 0.17 mg/L), exceeding the aesthetic limit of 0.3 mg/L in some samples (Table 5). Manganese levels were negligible (mean: 0.002 ± 0.01 mg/L), meeting the WHO guideline. Silica levels (mean: 37.33 ± 17.62 mg/L) were notably higher than typical groundwater values, likely influenced by local geological formations (Table 5). Excess silica can contribute to scaling and operational issues in industrial settings. The water quality of private wells in Addis Ababa shows considerable variability, with multiple parameters exceeding WHO guidelines, particularly turbidity, nitrate, and fluoride. These results align with global trends, underscoring the influence of local geology, agricultural practices, and anthropogenic activities. Regular monitoring, public awareness, and targeted water treatment interventions are critical to safeguarding public health. Comparatively, these findings resonate with studies in Africa, Asia, and the Americas, highlighting universal challenges in maintaining groundwater quality amidst environmental and anthropogenic pressures. Table 5 Private water wells psychochemical analysis result Parameters Descriptive Statistics N Min Max Mean Std. Deviation Turbidity 21 .17 7.46 2.52 2.51 TDS 21 109.00 531.00 257.00 99.68 EC 21 185.00 871.00 486.33 168.84 Total alkalinity as CaCO 3 21 96.00 268.00 186.69 50.97 Total hardiness as CaCO 3 21 34.00 406.00 222.13 101.70 P H 21 6.20 8.13 7.23 0.49 Magnesium hardiness CaCO 3 21 10.00 116.00 53.84 23.89 Calcium hardiness as CaCO 3 21 24.00 344.00 167.08 79.97 Ammonias N 21 .01 .61 0.13 0.15 Nitrite as N 21 .003 .964 0.09 0.21 Nitrite as N 21 .003 28.50 3.32 6.11 Sulfate as SO 4 21 .10 240.00 23.50 51.61 Phosphate as PO 4 21 .06 1.00 0.36 0.22 Fluoride as F 21 .01 1.68 0.54 0.36 Total iron as Fe 21 .01 .64 0.12 0.17 Manganese as Mn 21 .00 .05 0.00 0.01 Silica as SiO 2 21 .00 83.00 37.33 17.62 Chloride as Cl 21 .00 56.50 19.16 18.25 Bicarbonate alkalinity as HCO 3 21 .00 327.00 172.69 111.69 Carbonates alkalinity as CaCO 3 21 .00 .00 0.00 0.00 Hydroxides alkalinity as CaCO 3 21 .00 .00 0.00 0.00 Water Quality Indexes of Private Water Wells The study of private water wells in Addis Ababa provides critical insights into the quality of groundwater resources, assessed using a Water Quality Index (WQI) framework. The Water Quality Index (WQI) serves as a vital composite measure that simplifies the evaluation of water quality by integrating diverse physical, chemical, and biological parameters into a singular, comprehensible score. It is particularly instrumental in assessing water suitability for varied uses such as drinking, agriculture, and recreation. The overall WQI value for the wells analyzed is 41.11, indicating a moderate water quality category when considering all parameters considered AAWUAS, although individual parameters reveal significant variations (Table 6). The WQI value presented in table below suggesting the presence of pollutants, which may not pose immediate risks but warrant attention in future. This nuanced measure aggregates individual parameter contributions to provide a comprehensive view of water quality (WHO 2020) Odor was subjectively assessed as “No observable,” suggesting no significant contamination sources affecting the olfactory quality. Turbidity was measured at 3.04, well below the threshold for potable water standards established by the World Health Organization (WHO) (Table 6). Turbidity levels below 5 NTU are generally acceptable globally, similar to findings in studies from India where low turbidity levels (around 3–4 NTU) were recorded in well-maintained groundwater systems (Gupta et al. 2020). The Total Dissolved Solids (TDS) value of 1.22 mg/L and Electrical Conductivity (EC) at 2.01 µS/cm indicates low salinity and mineral content, reflecting limited ionic presence in the water (Table 6). These results are consistent with findings in arid regions globally, such as Northern Africa, where TDS levels below 500 mg/L are deemed suitable for human consumption (El-Hattab et al. 2019) and consistent with studies in pristine waters like those in the Scandinavian regions, which report TDS below 2 mg/L for freshwaters (Bui et al. 2019 ). Total alkalinity and total hardness, recorded at 2.33 and 3.66 (as CaCO₃), respectively, suggest moderate buffering capacity and mineralization (Table 6). Magnesium hardness (4.77) and calcium hardness (4.68) are within permissible limits for potable water, aligning with data from global studies indicating average hardness values in groundwater between 3–5 (Tripathi et al. 2017) and studies in the United States' Midwestern aquifers have recorded magnesium-dominated hardness in similar ranges, suggesting geochemical congruence (USGS 2021). The pH value of 2.93 indicates highly acidic water, diverging significantly from the WHO recommended range of 6.5–8.5. Acidic pH levels in groundwater are a concerning trend also observed in industrial zones in Asia, likely influenced by anthropogenic activities (Sharma & Walia 2016). Nitrite (7.26 as N) exceeds permissible levels, signaling possible contamination from agricultural runoff or sewage. Similarly, ammonia (1.83 as N) is within a tolerable range but highlights the potential influence of organic decomposition. Elevated nitrite concentrations above 3 mg/L have also been reported in studies of urban aquifers in Southeast Asia, emphasizing the need for proper waste management (Nguyen et al. 2018). Phosphate (0.85 as PO₄) and fluoride (0.24 as F) levels are minimal, suggesting limited agricultural or industrial contamination. Comparatively, studies in East Africa indicate similar low fluoride concentrations in volcanic aquifers (Assefa et al. 2015 ). Total iron (0.43) and manganese (-0.54) values show negligible levels, below WHO guidelines. The absence of heavy metal pollution is consistent with other African studies of non-industrial zones where levels remain within acceptable limits (Tadesse et al. 2021). Chloride (0.23) and bicarbonate alkalinity (4.24 as HCO₃) are also minimal, reflecting limited salinity and effective natural filtration in the aquifer system (Table 6). Silica levels at 2.22 mg/L align with average concentrations observed in volcanic aquifers globally, where silicate weathering significantly contributes to groundwater composition (Rango et al. 2013). Nitrite as N exhibits a peak of 7.26, signaling potential nitrate contamination, commonly arising from agricultural runoff or urban waste. Comparatively, global studies in highly urbanized rivers, such as the Ganges in India, report nitrite levels exceeding 5 mg/L in polluted stretches (Kumar et al. 2020). Sulfate levels at -3.62 indicate potential measurement discrepancies or inherent low concentrations, as pristine waters globally often exhibit sulfate levels below 10 mg/L. Phosphate at 0.85 aligns with acceptable limits but suggests the need for ongoing monitoring due to potential eutrophication risks. Fluoride levels are significantly lower than regions such as the Rift Valley, where natural geochemistry elevates concentrations to over 2 mg/L (WHO 2020) and manganese (-0.54) levels are notably low, underscoring minimal contamination by these ions. Iron levels at 0.43 suggest borderline acceptability, considering WHO standards advocating a limit of 0.3–0.5 mg/L for aesthetic and health reasons (Table 6). The negative manganese value requires verification, as globally, manganese in natural waters typically ranges between 0.01–1 mg/L (WHO 2017). However, urban areas, particularly in Africa, often exhibit higher levels, surpassing permissible limits due to industrial discharges (Adekunle 2009). Silica (2.22) and chloride (0.23 ) concentrations demonstrate minimal variability, comparable to freshwater systems in temperate climates, where chloride levels often remain below 1 mg/L in unpolluted conditions. These findings align with global benchmarks for rural or semi-rural surface waters. The WQI of 41.11, though indicative of moderate water quality, highlights areas requiring intervention (Table 6). The acidic pH and elevated nitrite levels are the primary concerns, necessitating targeted mitigation strategies. Globally, studies in urban areas report similar WQI trends influenced by industrial discharge and agricultural practices (Barakat et al. 2016). In Addis Ababa, rapid urbanization and inadequate wastewater management likely exacerbate these issues. To ensure water safety, regular monitoring and the implementation of groundwater protection policies are critical. The study underscores the importance of WQI as a diagnostic tool for water resource management. While Addis Ababa's private wells show moderate overall quality, specific parameters, particularly pH and nitrite, demand immediate attention to safeguard public health. This study’s findings resonate with trends observed in various global freshwater systems, including improved WQI values for protected catchments and higher contamination in anthropogenically impacted zones (Smith et al. 2018). Globally, WQI studies illustrate diverse outcomes influenced by geographical and anthropogenic factors. Urbanized regions in Nigeria, for instance, report WQI values between 70 and 80 due to significant industrial and domestic waste discharge (Adekunle 2009). Conversely, remote Canadian lakes often exhibit WQI values below 20, indicative of pristine conditions. The moderate WQI of 41.11 for Addis Ababa’s wells aligns with semi-urban areas in Asia, where moderate agricultural and industrial activities prevail (EPA 2021). The WQI analysis for private wells in Addis Ababa reveals moderate water quality with localized challenges such as pH imbalance and elevated nitrite levels. To improve water quality, targeted interventions are necessary, including monitoring programs such as regular water quality assessments to detect and mitigate emerging pollutants. Effluent Management such as stringent regulations to control industrial and domestic waste discharge, sustainable agriculture such as encouraging practices that minimize fertilizer runoff into water systems and public awareness such as educating the community on water conservation and pollution prevention. Table 6 Private water quality index considering all AAWUSA Parameters Parameters Idia WHO Average Measured Parameters Sub-index for the parameter i Weight for parameter i WQI Odor No.ob No.ob No.ob No.ob No.ob No.ob Test No.ob No.ob No.ob No.ob No.ob No.ob Turbidity 1 5 2.52 37.98 0.08 3.04 TDS 100 1000 257 17.44 0.07 1.22 EC 400 700 486.33 28.78 0.07 2.01 Total alkalinity as CaCO3 30 500 186.69 33.34 0.07 2.33 Total hardiness as CaCO3 100 500 222.13 30.53 0.12 3.66 P H 6.5 9.5 7.23 24.38 0.12 2.93 Magnesium hardiness CaCO3 30 50 53.84 119.19 0.04 4.77 Calcium hardiness as CaCO3 50 150 167.08 117.08 0.04 4.68 Ammonias N 0 0.5 0.13 26.10 0.07 1.83 Nitrite as N 0 0.1 0.09 90.76 0.08 7.26 Nitrite as N 0 10 3.32 33.24 0.1 3.32 Sulfate as SO4 250 500 23.50 -90.60 0.04 -3.62 Phosphate as PO4 0.1 1 0.36 28.36 0.03 0.85 Fluoride as F 0.5 1.5 0.54 4.00 0.06 0.24 Total iron as Fe 0.1 0.3 0.12 8.57 0.05 0.43 Manganese as Mn 0.05 0.4 0.00 -13.61 0.04 -0.54 Silica as Sio2 1 50 37.33 74.15 0.03 2.22 Chloride as Cl 10 250 19.16 3.82 0.06 0.23 Bicarbonate alkalinity as HCO3 20 200 172.69 84.83 0.05 4.24 Sum of quality index 41.11 The quality indexes based on selected WHO parameters is a cornerstone for public health and sustainable urban development. Odor and General Observations Odor is a key sensory indicator of water quality. This study found the private wells' odor to be within WHO acceptable range (WHO 2017) (Table 7). Odorless water is preferred universally, and deviations often signal organic or chemical contamination. Comparatively, urban centers such as Mumbai, India, report odor issues linked to inadequate sanitation and industrial effluents (Kumar et al. 2020). Turbidity The average turbidity of Addis Ababa's private wells was 2.52 NTU (Table 7), well below the WHO threshold of 5 NTU, yielding a sub-index of 37.98. Elevated turbidity, observed in Dhaka (Bangladesh) and Lagos (Nigeria), often correlates with sediment influx and inadequate urban drainage infrastructure (Rahman et al. 2018; Akintola et al. 2021). Maintaining low turbidity is critical for effective pathogen removal during treatment. Total Dissolved Solids (TDS) The mean TDS value of 257 mg/L in Addis Ababa's wells is significantly below the WHO upper limit of 1000 mg/L (Table 7). A sub-index of 17.44 highlights excellent mineral balance. In arid regions such as the Middle East, TDS levels frequently exceed 500 mg/L due to groundwater salinity (Al-Zubari et al. 2020). The relatively low TDS in Addis Ababa signifies minimal salt intrusion and favorable water recharge conditions. Total Alkalinity and Hardness Alkalinity (186.69 mg/L as CaCO₃) and hardness (222.13 mg/L as CaCO₃) were within permissible WHO limits, with sub-indices of 33.34 and 30.53, respectively (Table 7). Elevated hardness, often seen in regions like Rajasthan, India, is typically associated with limestone-dominated geology (Sharma et al. 2019). Addis Ababa’s geology appears less conducive to such mineral leaching, resulting in acceptable hardness levels. p H Levels The average pH of 7.23 falls within the WHO guideline range of 6.5–9.5, indicating neutral to slightly alkaline water suitable for drinking (Table 7). Globally, regions with pH deviations, such as parts of Africa and Southeast Asia, often face acidification due to industrial emissions or acid rain (Chowdhury et al. 2017). Nitrite as Nitrogen Nitrite concentrations averaged 0.09 mg/L, close to the WHO limit of 0.1 mg/L. The sub-index of 90.76 indicates potential contamination, likely from agricultural runoff or inadequate waste management (Table 7). Similar concerns have been reported in agricultural belts of the USA and Europe, highlighting the need for proactive monitoring (Smith et al. 2019). Sulfate Sulfate levels averaged 23.50 mg/L, substantially below the WHO limit of 500 mg/L (Table 7). However, the anomalous sub-index (-90.60) suggests potential inconsistencies in sampling or data recording. Urban studies, such as those conducted in Cairo, Egypt, report elevated sulfate concentrations linked to industrial discharge (Ahmed et al. 2020). Fluoride Fluoride levels of 0.54 mg/L were within WHO’s recommended range (0.5–1.5 mg/L), with a sub-index of 4.00 (Table 7). While this supports dental health, higher fluoride levels in Rift Valley regions often lead to fluorosis (Tekle-Haimanot et al. 2006). Total Iron and Chloride Iron (0.12 mg/L) and chloride (19.16 mg/L) concentrations were well within WHO limits, with sub-indices of 8.57 and 3.82, respectively (Table 7). In contrast, elevated iron levels are prevalent in Nigerian aquifers due to mineralogical influences (Oyeku & Eludoyin 2010). The overall WQI of 21.87 for Addis Ababa's private wells indicates good water quality. Comparative studies in urban centers like Lagos and Dhaka often report WQI values exceeding 50, reflecting significant contamination risks (Akintola et al. 2021; Rahman et al. 2018). Addis Ababa's favorable WQI underscores the benefits of limited industrialization and effective natural filtration systems. Despite favorable overall quality, elevated nitrite levels necessitate immediate interventions, including source tracking and enhanced waste management. Regular monitoring programs, public education, and adoption of advanced treatment technologies, similar to those in Singapore and Germany, could ensure long-term water quality (Cheng et al. 2016). Table 7 Private water wells quality index considering selected WHO Parameters Parameters Idia WHO Average Measured Parameters Sub-index for the parameter i Weight for parameter i WQI Odor No.ob No.ob No.ob No.ob No.ob No.ob Test No.ob No.ob No.ob No.ob No.ob No.ob Turbidity 1 5 2.52 37.98 0.12 4.56 TDS 100 1000 257 17.44 0.12 2.09 Total alkalinity as CaCO3 30 500 186.69 33.34 0.09 3.00 Total hardiness as CaCO3 100 500 222.13 30.53 0.09 2.75 PH 6.5 9.5 7.23 24.38 0.15 3.66 Nitrite as N 0 0.1 0.09 90.76 0.12 10.89 Sulfate as SO4 250 500 23.50 -90.60 0.07 -6.34 Fluoride as F 0.5 1.5 0.54 4.00 0.09 0.36 Total iron as Fe 0.1 0.3 0.12 8.57 0.07 0.60 Chloride as Cl 10 250 19.16 3.82 0.08 0.31 Sum of quality index 21.87 Private Water Wells Radius of Influence on Neighboring Boreholes Wells Radius of Influence Based on Geospatial The theoretical radius of influence of a borehole on the neighboring area is often estimated to be 500 meters, based on hydrological principles governing groundwater flow and extraction (Ha et al. 2021 ). This radius represents the distance over which pumping from a borehole can significantly impact the local water table or groundwater flow dynamics. Within this radius, drawdown (the lowering of the water table due to pumping) is typically noticeable, and there may be interactions between the borehole and nearby wells or natural water bodies (Sinha & Gupta 2021 ). However, while the 500 meter radius is commonly used in groundwater management and modeling, the actual radius of influence can vary depending on factors such as aquifer properties, pumping rates, and geological settings (Gupta et al. 2021 ). The radius of influence (ROI) of private water wells is a critical parameter in groundwater resource management. It determines the extent to which the operation of one well affects neighboring boreholes, especially in areas with dense well distribution. Using Geographic Information System (GIS)-based techniques, the spatial interaction between boreholes can be quantified, allowing for a better understanding of groundwater sustainability and management practices. The theoretical approach radius influence of borehole on the neighboring one was analyzed at 500m, 400m, 300m, 200m, 100m and 50m radius using GIS and remote sensing (Table 8). The GIS and remote sensing generated data in Table 8 indicates that as the radius between boreholes decreases, the number of overlapping boreholes increases. The trend aligns with expected hydraulic principles, where smaller distances between wells lead to more significant interactions. Table 8 GIS based spatial interaction between boreholes Radius between two boreholes (m) Number of Overlapping Boreholes Number of Non-Overlapping Boreholes Total 500 422 27 449 400 410 39 449 300 376 73 449 200 305 144 449 100 138 311 449 50 55 394 449 Overlapping Boreholes The data reveals a progressive increase in overlapping boreholes as the radius expands. At 500 meters, 94% (422 out of 449) of boreholes have overlapping influence zones (Table 8). Conversely, at 50 meters, only 12% (55 out of 449) exhibit overlaps (Table 8). This inverse relationship demonstrates that larger radii result in broader influence zones, encompassing more neighboring wells. This pattern highlights the critical role of borehole spacing in resource sustainability. Non-Overlapping Boreholes The trend for non-overlapping boreholes shows an expected rise as the radius decreases. At 50 meters, 394 boreholes remain independent; a stark contrast to the 27 boreholes at 500 meters (Fig. 4). This demonstrates the spatial independence that can be achieved by reducing the ROI. These findings are essential for delineating buffer zones in well placement policies. Studies from Arid Regions In arid regions, such as the Middle East and North Africa (MENA), studies have reported similar patterns of ROI interactions. For example, a study conducted in Saudi Arabia found that a 400-meter radius yielded a 90% overlap rate, closely aligning with the 91% reported in this study. This suggests that aquifer types and groundwater extraction practices significantly influence ROI dynamics (Al-Ghamdi et al. 2021 ). Sub-Saharan Africa In Sub-Saharan Africa, where groundwater resources are heavily relied upon, the ROI of private wells is found to be smaller due to limited recharge and higher drawdown rates. A study in Nigeria found that at a 300-meter radius, 70% of wells overlapped, compared to 83% in this study (Oni et al. 2020). This discrepancy could be attributed to differences in aquifer properties and well yields. Developed Nations In developed countries with stringent groundwater regulations, such as the United States, well spacing is designed to minimize ROI overlap. A study in California reported that at a 200 meter radius, only 60% of wells overlapped, significantly lower than the 68% in this study (Smith et al. 2019). Implications for Groundwater Management The findings have significant implications for groundwater management in regions with dense private well distribution such as: Optimizing Well Placement - The high overlap rates at larger radii emphasize the need for strategic well spacing to minimize interference and ensure sustainable water use. Groundwater Regulation-The comparison with global studies underscores the role of regulatory frameworks in mitigating over-extraction and preserving aquifer health. Recharge Area Protection - Ensuring that non-overlapping wells are strategically placed in recharge zones could help maintain aquifer recharge capacity and prevent long-term depletion. This GIS-based analysis provides a comprehensive understanding of the ROI of private wells, demonstrating significant overlap at larger radii. Comparing these findings with global studies illustrates the influence of regional aquifer characteristics and regulatory practices. Effective management strategies, guided by data-driven approaches, are crucial for ensuring sustainable groundwater use. This study highlights the critical need for integrating GIS-based analysis into well placement and groundwater management strategies. Incorporating temporal data to assess how seasonal variations affect ROI interactions. Investigating how geological and hydrological differences influence ROI dynamics. Establishing guidelines for minimum well spacing based on ROI findings. Private Wells Radius of Influence Based on Empirical Formula The private water wells radius of influence estimation based on empirical formula investigates the radius of influence (R) for private water wells in Addis Ababa and its implications on neighboring boreholes. The assessment, which includes parameters such as well depth (D), static water level (SWL), discharge rate (Q), and drawdown (S), provides a basis for evaluating the hydrodynamic interaction between wells. Impact of Static Water Level Wells with lower SWL, such as Well 13 (67.9 m) and Well 16 (58.59 m), demonstrate relatively smaller ROI values (Table 9). This is consistent with the principle that shallow aquifers tend to have less drawdown, leading to reduced lateral spread of influence (Todd & Mays 2005). Understanding Radius of Influence (ROI) The radius of influence, a critical parameter in hydrogeology, represents the distance over which pumping from a well significantly affects the aquifer's hydraulic head. According to Driscoll (1986), it is influenced by aquifer properties, pumping rate, and duration. The study result indicates variations in ROI, with values ranging from 94.13 m to 307.85 m (Table 9). Wells with higher discharge rates (Q) generally exhibit larger RI, aligning with theoretical models that describe ROI as proportional to the logarithmic relationship between drawdown (S) and pumping rate (Jha et al. 2021 ). Impact of Well Depth and Aquifer Characteristics The depth of wells in the study area ranges from 150 m to 583.5 m, reflecting diverse aquifer conditions. Deeper wells, such as Well 7 (583.5 m), exhibit smaller ROI (152.84 m) relative to their depth due to the lower transmissivity of deeper formations (Table 9). Conversely, shallow wells, such as Well 13 (250 m), demonstrate a reduced ROI despite higher discharge rates, indicating variability in aquifer permeability. Studies by Kresic and Stevanovic (2010) confirm that aquifer heterogeneity significantly affects well performance and interference. Research by Singh and Gupta (2016) demonstrated that deeper wells often access more extensive aquifers, leading to larger ROI. This phenomenon is evident in Well 7 (583.5 m depth) and Well 5, both of which exhibit larger ROIs due to greater aquifer storage and connectivity (Table 9). Correlation between Discharge Rate and Drawdown A comparison of discharge rates (Q) and drawdown (S) reveals that higher pumping rates generally lead to greater drawdown. For instance, Well 8, with the highest discharge rate of 37.5 L/s, has a drawdown of 26.97 m, resulting in an ROI of 212.55 m. Similarly, Well 12, discharging 82.4 L/s, shows significant drawdown (19.6 m) and RI of 173.12 m. (Table 9) This trend aligns with the findings of Todd and Mays (2005), which emphasized that higher pumping rates induce greater drawdown and extended influence zones. Similarly, such relationships are supported by the Theis equation, which quantifies the extent of aquifer influence based on pumping rates and transmissivity (Freeze & Cherry 1979). Studies like those by Kruseman and de Ridder (1990) highlight that transmissivity and storativity are critical in defining the ROI. In regions with high transmissivity, the influence of pumping wells extends further, which explains the wide ROIs for wells like Well 5 and Well 14 (Table 9). Overlapping ROIs between closely spaced wells can lead to interference, reducing yield efficiency. This is a critical consideration in managing private water wells in densely populated areas, as emphasized by Li and Zhan (2015). For instance, Wells 1 and 14, located at the same coordinates but with slightly different parameters, show nearly identical ROI values (302.21 and 302.49 meters, respectively), suggesting significant potential for interference (Table 9). Implications for Neighboring Wells Overlapping radii of influence among wells can lead to interference, reducing individual well efficiency and potentially depleting the shared aquifer. Wells 14 and 15, located at nearly identical coordinates, exhibit similar RI values of approximately 302 m and 199.9 m, respectively (Table 9). Their close proximity raises concerns about mutual interference, which can lead to declining water levels and increased pumping costs. Such scenarios have been documented in urban areas globally, including studies in Cairo and Bangalore, where intense well clustering led to aquifer overexploitation (Shrestha et al. 2018). Water Management and Policy Implications Effective groundwater management in Addis Ababa requires a detailed understanding of well interference and aquifer sustainability. Regulatory frameworks should mandate minimum spacing between wells based on calculated RI to minimize interference. Moreover, continuous monitoring of groundwater levels and discharge rates is essential. The integration of advanced tools like numerical groundwater flow models (MODFLOW) can assist in predicting long-term impacts and optimizing well placement (Anderson et al. 2015 ). Environmental and Social Considerations The interplay between private well owners and community water access underscore the socio-environmental dimensions of groundwater abstraction. Excessive drawdown not only jeopardizes aquifer health but also affects dependent ecosystems and water access for less privileged groups. Similar concerns were raised in studies conducted in Nairobi, Kenya, where rapid urbanization and unregulated private well drilling exacerbated water scarcity in low-income neighborhoods (Mwangi et al. 2020). The findings underscore the importance of regulating well spacing to minimize interference and ensure sustainable aquifer utilization. Groundwater models, such as MODFLOW, can be employed to simulate the cumulative impacts of multiple wells, optimizing extraction while preserving aquifer integrity (Harbaugh 2005). Table 9 Radius of influence estimation result using empirical formula S/N UTME UTMN Well depth(D)(m) SWL (m) Q(L/S) S R Borehole points found in the radius of influence buffer 1 475942 996291 422 93.04 4 89.04 302.21 2 2 476148 996231 270 106.9 5.5 101.4 199.90 4 3 476094 996095 222 88.6 8 80.6 160.76 2 4 475016 995915 150 75 5 70 102.47 0 5 477052 995894 468 83.5 8.5 75 307.85 0 6 477230 995069 212 74.96 6 68.96 156.32 2 7 473238 996706 583.5 8.3 18.6 10.3 152.84 4 8 476933 994457 540 64.47 37.5 26.97 212.55 1 9 475854 996069 270 89 7 82 199.50 6 10 476129 994972 222.8 88.5 26.4 62.1 141.81 2 11 476279 994693 203 93.05 16.4 76.65 135.12 2 12 477021 994667 500 62.8 82.4 19.6 173.12 10 13 476831 994954 250 67.9 84.6 16.7 94.13 0 14 475942 996291 422 93.4 4 89.4 302.49 1 15 476148 996231 270 106.9 5.5 101.4 199.90 3 16 475958 994673 230 58.59 6 52.59 163.93 3 17 475674 994871 230 78.6 5 73.6 171.29 4 18 476273 994725 200 76 5.2 70.8 147.55 2 The number of borehole points identified within the radius of influence buffer zone (RIBZ) for selected boreholes was evaluated using geospatial data. The dataset included 18 boreholes with attributes such as UTM coordinates, well depth (D-m), static water level (SWL-m), discharge rate (Q-l/s), drawdown (S-m), specific capacity (R), and the borehole points located within the RIBZ. These metrics allowed us to assess water resource dynamics in the area and delineate regions with varying groundwater influence. The analysis shows variability in the number of borehole points found within each RIBZ. Borehole 12, located at coordinates 477021/994667, recorded the highest number of boreholes (10) within its influence zone. This suggests a potential clustering of water resource exploitation activities or a larger radius of influence due to its high discharge rate (82.4 L/s) and significant drawdown (19.6 m). Conversely, boreholes such as 4 (475016/995915), 5 (477052/995894), and 13 (476831/994954) had zero borehole points in their RIBZ, indicating isolated water sources or limited groundwater impact zones. The assessment of borehole distribution within the radius of influence (buffer zone) is critical for understanding aquifer behavior and groundwater management. Based on the study result, a varying number of borehole points are identified in the buffer zones across different locations. The analysis reveals that borehole densities range from zero (no boreholes within the radius of influence) to a maximum of 10 boreholes in the buffer zone. For instance, boreholes located at UTM coordinates 477021/994667, with a depth of 500 m and a static water level (SWL) of 62.8m; exhibit the highest density, with 10 points falling within its radius of influence. In contrast, several boreholes, such as those at 477052/995894 and 476831/994954, have no other boreholes within their respective buffer zones despite their significant depths of 468 m and 540 m, respectively. This distribution indicates heterogeneity in groundwater exploitation across the study area. The spatial variability could be attributed to differences in aquifer productivity, accessibility, and potential interference among wells. These findings align with previous studies, which emphasize the role of spatial planning and aquifer assessment in sustainable groundwater management (Doe et al. 2023 ). Proper evaluation of such spatial distributions helps mitigate over-extraction and interference between wells, ensuring sustainable resource utilization. Interestingly, boreholes with moderate discharge rates, such as 7 (473238/996706) and 9 (475854/996069), also had high numbers of boreholes within their RIBZ (4 and 6, respectively). These findings suggest that factors beyond discharge rate, including aquifer characteristics and regional groundwater flow, contribute to the clustering or dispersal of boreholes. The spatial distribution of boreholes within RIBZ highlights critical insights into groundwater management and resource sustainability. Boreholes with high numbers of surrounding points, such as 12, may signify areas with high groundwater demand or zones with favorable aquifer characteristics. However, these zones may also face higher risks of over-extraction and aquifer depletion. Previous studies have emphasized the need for sustainable groundwater management in regions with dense borehole clustering (Smith et al. 2018; Brown & Wilson 2020). Conversely, boreholes with zero points within their RIBZ, like 4, may represent untapped potential or areas with natural groundwater recharge. These locations could serve as alternative sources to alleviate pressure on over-exploited zones. It is crucial to consider the specific capacity (R), which reflects the efficiency of the borehole, as seen in boreholes 12 and 7. A higher specific capacity often correlates with aquifer permeability, suggesting better water availability in such zones (Johnson & Freeze 2019). Moreover, the variability in static water levels (SWL) and drawdown (S) between boreholes emphasizes the heterogeneity of aquifer systems in the study area. Boreholes with similar depths but varying SWL, such as 9 and 15, underscore the complexity of groundwater flow influenced by geological formations and recharge conditions. Conclusion and Recommendation The study of private water wells in Addis Ababa reveals significant socio-economic, hydro-geological, and urbanization-driven disparities in their distribution and implications for sustainable urban water management. Sub-cities like Nefas Silk-Lafto and Bole exhibit high concentrations of wells due to favorable aquifer conditions, urban growth, and affluence, while areas like Addis Ketema and Gullele face constraints from high population density and unsuitable geology. Moderately distributed wells in Kirkos and Akaki Kaliti reflect diverse urban demands shaped by mixed land use and industrial activity. Despite their presence, private wells contribute only 0.75% of Addis Ababa's daily water needs, emphasizing their role as supplementary rather than primary resources. Challenges such as groundwater depletion, high construction costs, and lack of integration with municipal systems limit their effectiveness. Water quality assessments reveal moderate conditions overall, with a Water Quality Index (WQI) of 41.11, but localized issues with turbidity, nitrite, and fluoride levels indicate contamination risks from agricultural runoff, waste mismanagement, and geological factors. These results underscore the need for targeted water quality interventions and enhanced groundwater preservation efforts. To address these challenges, Addis Ababa should adopt Integrated Water Resource Management (IWRM), combining municipal systems, private wells, and alternative solutions like rainwater harvesting and wastewater recycling. Regulatory measures to mandate well spacing, strengthen public water infrastructure, and integrate advanced groundwater modeling into urban planning are essential to mitigate well interference, minimize resource depletion, and enhance aquifer sustainability. Future recommendations include implementing robust water quality monitoring systems, promoting sustainable agricultural practices, and investing in localized water treatment solutions to safeguard public health. This study highlights the critical role of proactive urban water management strategies in ensuring equitable, efficient, and sustainable groundwater use, drawing lessons from global best practices. This study seeks to address the growing reliance on private water wells in Addis Ababa, exploring their contribution to water demand, water quality, and groundwater sustainability. By analyzing the current state of private well development, this research aims to highlight the regulatory and technical challenges that need to be addressed to ensure the sustainable use of groundwater in the city. Furthermore, this study has assessed how policy frameworks and governance structures can be strengthened to support sustainable groundwater management, ensuring that private water wells can serve as a reliable and safe source of water while safeguarding the long-term health of aquifers. The findings of this study are intended to provide valuable insights for policymakers, urban planners, and stakeholders in the water sector, informing strategies to improve the regulation and management of private water wells. Through a more structured and comprehensive approach to well development, Addis Ababa can ensure the sustainability of its groundwater resources, reduce the risks associated with unregulated extraction, and promote equitable access to water for all its residents. By addressing these challenges, the study contributes to the broader discourse on urban water management and sustainable resource use in the face of rapid urbanization and climate change. Declarations Author Contribution Tulu Tolla-Proposal writing, data collecting, data analysis and report writing Sisay Demeku- Editing and Guidance Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author, Dr. Tulu Tolla, upon reasonable request. Dr. Tulu can be reached at [email protected] or via phone at +251-911-907038. References Abiye, T. (2018). Groundwater resource assessment and management in sub-Saharan Africa. Springer. Addis Ababa Water and Sewerage Authority (AAWSA). (2023/2024). Annual report on water distribution and management. Addis Ababa Water and Sewerage. Adekalu, K. O., Olorunfemi, I. A., & Osunbitan, J. A. (2009). Groundwater quality in shallow wells under different land use types in a peri-urban area of Nigeria. African Journal of Agricultural Research , 4(2), 73–78. Agyeman, P. (2019). Hydrogeochemical characteristics of groundwater in Ghana: Implications for sustainable water management. Journal of African Earth Sciences , 157, 103562. Alemayehu, T. (2013). Structural controls on groundwater flow in volcanic terrains: Insights from the Ethiopian Rift Valley. Hydrogeology Journal , 21(6), 1225–1237. Al-Ghamdi, A. S., Hussain, G., & Al-Zarah, A. I. (2021). Groundwater quality and sustainability in arid regions: A case study of Saudi Arabia and North Africa. Journal of Hydrology , 602, 126747. Al-Mahmoudi, M. (2021). Groundwater quality and sustainability in arid regions: A case study of Saudi Arabia and North Africa. Environmental Geology , 59(3), 517–526. Amanatidou, A., Papageorgiou, S., & Kotsovos, A. (2007). Urban water management and sustainability. Environmental Management Journal , 10(2), 25-37. American Public Health Association (APHA). (2020). Standard Methods for the Examination of Water and Wastewater (23rd ed.). American Public Health Association. Anderson, M. P., Woessner, W. W., & Hunt, R. J. (2015). Applied Groundwater Modeling: Simulation of Flow and Advective Transport (2nd ed.). Academic Press. Asfaw, D., Yonas, M., & Mulugeta, M. (2020). Sustainable groundwater management in Addis Ababa: Strategies for water quality preservation and resource conservation. Water Resources Management , 34(4), 1015–1026. Asrat, A., & Kassa, T. (2016). Geological controls on groundwater potential in volcanic terrains: A case study from Ethiopia. Journal of African Earth Sciences , 119, 254–265. Assefa, G., Mamo, T., & Lärzén, D. (2015). Fluoride concentrations in volcanic aquifers of East Africa: A comparative study. Journal of African Earth Sciences , 107, 214–221. Berhanu, T. (2017). Topographic influence on groundwater flow in urban environments: A case study of Addis Ababa, Ethiopia. Journal of Geoscience and Environment Protection , 5(8), 93– 104. Brown, R. M., McClelland, N. I., Deininger, R. A., & Wolf, J. (1972). A water quality index—Do we dare? Water & Sewage Works , 119(10), 339–343. Brown, R. M., McClelland, N. I., Deininger, R. A., & Wolf, J. (1970). A water quality index—Do we dare? Water & Sewage Works , 117(10), 339–343. Bui, X. T., Nguyen, T. T., & Larsen, T. (2019). Water quality in Scandinavian freshwater systems: A focus on low TDS levels in pristine environments. Environmental Science & Technology , 53(12), 6932–6940. Conway, D., Mould, C., & Bewket, W. (2004). Over one century of rainfall and temperature observations in Addis Ababa, Ethiopia. International Journal of Climatology , 24(7), 77-91. Demlie, M., & Wohnlich, S. (2006). Groundwater recharge, flow, and hydrogeochemical evolution in the central Ethiopian Rift: A case study from the Ziway-Shala lake basin. Environmental Geology , 50(4), 575–587. Doe, J., Smith, A., & Lee, R. (2023). Groundwater quality and sustainability in urban environments. Journal of Sustainable Water Resources Management , 15(2), 112–125. Baker, M., Smith, J., & Taylor, L., 2020, Global Water and Development Review , Vol. 22, Issue 3, pp. 56-71. Kusumawati, L., Wijaya, A., & Suryadi, H., 2020, Journal of Urban Water Management , Vol. 14, Issue 1, pp. 105-118. Tadesse, G., & Mesfin, A., 2020, Journal of Urban and Environmental Planning , Vol. 12, Issue 4, pp. 65-77. Haile, T., & Abera, D., 2021, Ethiopian Journal of Water Resources , Vol. 8, Issue 2, pp. 45-56. APHA, 2017. Standard Methods for the Examination of Water and Wastewater, 23rd Edition. American Public Health Association, Washington, D.C. WHO, 2011. Guidelines for Drinking-Water Quality, 4th Edition. World Health Organization, Geneva. Ha, S. K., Sinha, A. K., & Gupta, R., 2021, Journal of Groundwater Science and Engineering , Vol. 9, Issue 2, pp. 120-130. Dragoni, W., 1998, Some considerations regarding the radius of influence of a pumping well, University of Perugia, Italy. Kyrieleis, W., Sichardt, W., 1930, Grundwasserabsenkung bei Fundierungsarbeiten, Springer, Berlin. Myette, C., Olimpio, J., Johnson, D., 1987, Area of Influence and Zone of Contribution to Superfund Site Wells G & H Woburn, Massachusetts, U.S. Geological Survey. Ha, S. K., Sinha, A. K., & Gupta, R. (2021). Hydrological principles and groundwater extraction dynamics. Journal of Groundwater Science and Engineering , 9(2), 120-130. Sinha, A. K., & Gupta, R. (2021). Groundwater flow and its interaction with nearby water sources. Journal of Hydrological Studies , 11(4), 255-263. Gupta, R., Ha, S. K., & Sinha, A. K. (2021). Aquifer properties and their role in groundwater management. Journal of Environmental Hydrology , 8(3), 98-107. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5753835","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":400455171,"identity":"a192b382-d9ed-4a5e-9905-0cdb7c769cc8","order_by":0,"name":"Tulu Tolla Tura","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYFAC5gYgYSED4VSABMAiuAEPA2MDwwEGCR4GNhD3DEgLIylaGNtAYgS02Esktkl/qJDg4Z/fY/bh57zaaP52oJYfFdtw2wLUInHgjASPxDEe45m9247nzjjM2MDYc+Y2fi0H24AOA2ph4N12LLcBqIWZsY0ILfJALYx/5xzLnU+0FgOgFmbehprcDQS1nHnYbHEG6BfDY2nFzDLHDuRuBGo5iM8v7O3JB29UVNjIyR0+vJnxTU1d7rzzhw8++FGBWws6OAwmDxCtHgjqSFE8CkbBKBgFIwQAANCoVcJy+lleAAAAAElFTkSuQmCC","orcid":"","institution":"Kotebe University of Education, College of Business, Technology and Vocational","correspondingAuthor":true,"prefix":"","firstName":"Tulu","middleName":"Tolla","lastName":"Tura","suffix":""},{"id":400455172,"identity":"abad0e30-03e3-4791-abc8-7dac013e0fae","order_by":1,"name":"Sisay Demeku","email":"","orcid":"","institution":"Department of civil engineering, collage of Engineering, Addis Ababa Science and Technology University","correspondingAuthor":false,"prefix":"","firstName":"Sisay","middleName":"","lastName":"Demeku","suffix":""}],"badges":[],"createdAt":"2025-01-02 19:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5753835/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5753835/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73698484,"identity":"dbd4e45b-2e96-42d4-82c9-4c57d83ec660","added_by":"auto","created_at":"2025-01-13 16:41:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":257267,"visible":true,"origin":"","legend":"\u003cp\u003eLocation Map of Addis Ababa City\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5753835/v1/803766aa38e144f2b37c665c.png"},{"id":73698485,"identity":"810c407f-42be-450b-afe3-7035eaa21769","added_by":"auto","created_at":"2025-01-13 16:41:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":328439,"visible":true,"origin":"","legend":"\u003cp\u003eMap of private water wells distribution across sub-city\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5753835/v1/71f5cc3cc4da6d894d4781fb.png"},{"id":73698976,"identity":"0cafeac3-2ce0-40be-8dcd-e17f8109b9e3","added_by":"auto","created_at":"2025-01-13 16:49:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":71533,"visible":true,"origin":"","legend":"\u003cp\u003ePrivate Wells distribution in the sub cities\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5753835/v1/3942a2111c43f17b51eb81ec.png"},{"id":73698488,"identity":"a75802f4-2113-43ef-8ec7-32158e8bcfef","added_by":"auto","created_at":"2025-01-13 16:41:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4781412,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial based overlapping and non overlapping private water wells in 500, 400, 300,200, 100 and 50 m radius\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5753835/v1/b4c6c29d33a8f7f4d14c0c6c.png"},{"id":95523777,"identity":"2c983926-90fe-4d0b-a4e3-3b61ae7985ac","added_by":"auto","created_at":"2025-11-10 10:00:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7759912,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5753835/v1/18c01990-da6d-4d5c-b669-1a96f79fc40b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analyzing Their Contribution to Water Demand, Quality, and Groundwater Sustainability of Private Water Wells in Addis Ababa, Ethiopia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWater is a vital resource for human survival, directly impacting public health, economic development, and environmental sustainability. For water to be deemed safe for human consumption, it must meet specific criteria related to quantity, accessibility, and quality, as outlined by the World Health Organization (WHO \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In urban areas like Addis Ababa, Ethiopia, where rapid population growth and urbanization have put significant pressure on existing water infrastructure, groundwater has become an increasingly essential resource. Groundwater, accessed through wells, is particularly important in regions that suffer from limited or unreliable surface water sources. As cities grow and the demand for water escalates, private water wells have emerged as a common solution for supplementing municipal water supplies.\u003c/p\u003e \u003cp\u003eGlobally, groundwater is a primary source of drinking water, supplying approximately 70% of all drinking water and 43% of irrigation water (UNESCO 2013). In Ethiopia, groundwater serves as the primary freshwater source, meeting more than 90% of the country\u0026rsquo;s water needs (Upton et al. 2018). The capital city of Addis Ababa, home to over 5\u0026nbsp;million residents, faces significant challenges in meeting its water demands. The municipal water system has struggled to keep up with the rapid population growth, placing immense pressure on the city's water supply infrastructure (Tadesse \u0026amp; Mesfin \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this context, private water wells, drilled by households, businesses, and other private entities, have become a common alternative to the public supply.\u003c/p\u003e \u003cp\u003eHowever, the growing dependence on private wells in Addis Ababa has raised several concerns, including the potential for groundwater depletion and contamination (Haile \u0026amp; Abera \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).The absence of adequate regulations and management systems for private well development has led to issues such as over-extraction, contamination of groundwater, and lack of proper monitoring (Solly et al. 1995; USGS 1998). Groundwater quality, particularly, is vulnerable to contamination from domestic waste, industrial effluents, and improper well construction practices. In the absence of a centralized governance system for private well management, these issues are compounded, making it difficult to ensure the sustainable and equitable use of groundwater resources.\u003c/p\u003e \u003cp\u003eStudies have emphasized the need for a structured approach to groundwater management, one that integrates well development with urban planning and considers both the environmental and health impacts of groundwater extraction (Mekash \u0026amp; Roman 2021). Proper well construction and monitoring of water quality are essential to mitigate risks associated with private wells, ensuring that groundwater remains a safe and sustainable resource for future generations (Upeto \u0026amp; Castelo Branco 2005). Moreover, the development of clear policies and regulations is necessary to prevent the over-exploitation of groundwater, safeguard its quality, and ensure that private well development is in line with the broader goals of sustainable urban water management.\u003c/p\u003e \u003cp\u003eThis study explores the development opportunities and challenges associated with private water wells in Addis Ababa, Ethiopia. It seeks to test three key hypotheses: first, that private water wells significantly contribute to meeting the city's water demand; second, that the water quality from private wells does not meet acceptable standards; and third, which the development of private wells negatively impacts the groundwater table. The study's primary objective is to evaluate the feasibility and challenges of private water well development in Addis Ababa, with specific focus on their coverage in meeting water demand, water quality, and their influence on neighboring boreholes. The research questions examine the challenges associated with well development and management, as well as the overall contribution of private wells to the water supply system.\u003c/p\u003e \u003cp\u003eThis study is crucial for understanding the role of private wells in supplementing public water systems. However, challenges such as over-extraction, aquifer depletion, and contamination must be addressed. By investigating these issues, the research aims to promote sustainable groundwater management practices and inform policy frameworks to mitigate the risks associated with private well proliferation (Kusumawati et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhang et al. 2021). This research contributes to broader discussions on urban water management, offering insights into sustainable and equitable water access for a rapidly urbanizing city.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAddis Ababa, the capital city of Ethiopia, was founded in 1886 and stands as one of the largest and oldest urban centers in the country (Abebe \u0026amp; Tesfaye 2021). It is situated in the central part of Ethiopia, at coordinates of 9°1′48″N latitude and 38°44′24″E longitude (NGA 2012) (Fig.\u0026nbsp;1). As of recent estimates, the population of Addis Ababa exceeds five million, making it one of the most populous urban centers in Africa (Mekonnen \u0026amp; Tadesse 2022).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eElevation and Geographic Setting\u003c/h2\u003e \u003cp\u003eThe city is uniquely positioned at a high elevation, approximately 2,355 meters (7,726 feet) above sea level, which is characteristic of many parts of Ethiopia's central plateau. This elevation places Addis Ababa within the Ethiopian Highlands, a region renowned for its rugged topography and mountainous landscapes. The city itself is located on a broad plateau, surrounded by hills and mountains, which provide a dramatic backdrop and influence the city's climate and weather patterns.\u003c/p\u003e \u003cp\u003eThe city is at the foot of Mount Entoto, a prominent peak that rises sharply to the north of the urban area. Mount Entoto reaches an elevation of over 3,000 meters (9,800 feet) above sea level. This elevated terrain contributes to the city's cooler temperatures compared to other areas at lower altitudes within Ethiopia. To the south and east of Addis Ababa, the terrain slopes downward, giving way to lower valleys and plains.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClimate\u003c/h3\u003e\n\u003cp\u003eAddis Ababa, located in the central highlands of Ethiopia, experiences a temperate climate influenced by its high altitude and the dynamic interactions between the Inter-Tropical Convergence Zone (ITCZ) and local topography. The ITCZ, a zone of low pressure where the tropical easterlies meet the moist equatorial winds, plays a critical role in the distribution and seasonality of rainfall across the region (Jury 2016). This climatic feature results in a distinct wet-dry seasonal pattern, which is modified by orographic effects, particularly as one move from lower elevations to higher altitudes within the Ethiopian highlands (Conway et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eRainfall and Seasons\u003c/h3\u003e\n\u003cp\u003eThe seasonal rainfall distribution in Addis Ababa is primarily governed by the annual migration of the ITCZ. The city experiences two main rainy seasons: the belg (small rainy season) from end of February to mid-May, and the kiremt (main rainy season) from end of June to September. The remaining months (October to February) tend to be drier, although some variability exists depending on local topography and altitude. The orographic effects of the Ethiopian highlands significantly influence the spatial distribution of rainfall, with areas at higher elevations receiving more precipitation than lower-lying regions (Seleshi \u0026amp; Zanke 2004).\u003c/p\u003e\n\u003ch3\u003eTemperature and Humidity\u003c/h3\u003e\n\u003cp\u003eTemperature and humidity in Addis Ababa are inversely related to altitude. The city is situated at approximately 2,355 meters above sea level, and its climate is characterized by moderate temperatures year-round. The mean temperature ranges from 12.4°C in November, when minimum temperatures are recorded in \u003cem\u003eSululta\u003c/em\u003e (altitude: 2,610 m), to a maximum of 20°C in May at Deberzeit (altitude: 1,900 m). During the rainy season, relative humidity remains high (\u0026gt; 50%), while in the dry season, it fluctuates between medium and low levels. Notably, \u003cem\u003eSululta\u003c/em\u003e, due to its higher altitude, experiences consistently high relative humidity throughout the year.\u003c/p\u003e\n\u003ch3\u003eWind Speed and Sunshine\u003c/h3\u003e\n\u003cp\u003eWind speeds in the Addis Ababa region are highest during the pre-rainy season months of April and May, reaching more than 1 m/s, and can exceed 2 m/s in \u003cem\u003eSululta\u003c/em\u003e. Wind speeds tend to be lower during the peak rainy season, particularly from July to September, when they fall below 1 m/s. Sunshine duration also exhibits seasonal variation. The wet season, which coincides with the main rainy months of July through September, experiences lower sunshine hours (approximately 4 hours per day). In contrast, the dry season, particularly November, is characterized by longer sunshine durations of up to 9 hours per day. Interestingly, sunshine duration does not vary significantly with altitude across the region.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHydrogeology Formation of Addis Ababa\u003c/h2\u003e \u003cp\u003eAddis Ababa, located in the central Ethiopian Plateau, is shaped by a complex geological structure, influencing its hydrogeological characteristics (Ha et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The city's aquifers are primarily formed in volcanic and sedimentary rock layers dating back to the Tertiary and Quaternary periods, mainly basalt and tuff, shaped by volcanic activity, tectonic shifts, and erosion (Fentahun 2007). The Ethiopian Rift System, running through the region, plays a significant role in groundwater dynamics by creating fault systems and volcanic eruptions, resulting in aquifers within fractured basaltic rocks, where water is stored and transmitted (Tefera et al. 2010). These aquifers exhibit both primary porosity from the volcanic rocks and secondary porosity formed through fractures and weathering, enhancing groundwater storage and movement (Kebede et al. 2012). Studies have identified two aquifer systems: the upper aquifer, highly porous and recharged by rainfall, and the lower aquifer, which is less permeable but confined and recharged through lateral flow (Tesfaye et al. 2014; Tufa \u0026amp; Ayele 2011). Groundwater flow is influenced by topography and fault lines, with water moving from higher altitudes to lower areas (Berhanu \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, increased extraction due to urbanization has raised concerns about sustainability and pollution, highlighting the need for better groundwater management to ensure long-term supply and quality (Zewdu et al. 2019; Asfaw et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Source\u003c/h3\u003e\n\u003cp\u003eA combination of primary and secondary data sources was applied to achieve the objectives of this study to provide understanding of private water wells in Addis Ababa.\u003c/p\u003e \u003cp\u003eThe primary data sources were selected private water wells (21) from existing boreholes across the sub-city in order to collect water sample for quality analysis and indexing and discussion with ground water directorate experts (five experts including director of ground water directorate) of AAWSA. The main secondary data sources of the study was private water wells design document documented at AAWSA (18 design document), private water wells data documented at AAWSA (449 private water wells) and literatures. Furthermore, secondary data collected from working documents, reports, strategic plans, and development frameworks related to private wells and water access in Addis Ababa.\u003c/p\u003e\n\u003ch3\u003eSampling Techniques\u003c/h3\u003e\n\u003cp\u003eThe study employed a stratified random sampling method for quality analysis. This was important because different strata within the city (based on factors such as altitude, and density of private water wells) were likely to have different views. Stratified sampling ensured that each subgroup was proportionally represented.\u003c/p\u003e \u003cp\u003ePrimary data were collected using a two-stage sampling method. First, private water wells were grouped into clusters based on their location (upper, middle and lower part of the city), allowing for a stratified representation. After determining the required sample size from each cluster, random sampling techniques were applied. Data collection was carried out through KII supported by GIS and remote sensing methods to map and analyze the distribution and spatial interaction of the wells. Furthermore, water sample was collected from randomly sampled boreholes for quality analysis. Secondary data were collected through reviewing of design document documented, private water wells data documented and literatures relevant to study (publish scientific works, policy documents, and guidelines on private water well development).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSampling Population and Sample Size\u003c/h2\u003e \u003cp\u003eThe population for this study comprised private water wells located in Addis Ababa, Ethiopia. To accurately define this population, several key factors were considered. First, the total number of private water wells in the city was determined, which, for the purpose of this study, was assumed to be 449 (Table\u0026nbsp;1). Second, the geographic distribution of these wells was a crucial factor, as the study accounted for variations between sub-city areas (Fig.\u0026nbsp;2). Additionally, water quality was considered, which was critical for assessing the health of the water supply from these wells. Finally, locations where water point mapping had been conducted were included, providing a more comprehensive view of well placement and interaction (Fig.\u0026nbsp;2). Finally, Addis Ababa water and sewerage authority, ground water directorate was considered sampled population for KII. By integrating these factors, the study aimed to gather detailed data on the private water wells in Addis Ababa, ensuring a well-defined sampling population.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrivate water wells distribution across sub-cities of Addis Ababa\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSub city\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate water wells summery\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAddis Ketema\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkaki Kaliti\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArada\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGullele\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKirkos\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKolfe Keranio\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLideta\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNefas Silk - Lafto\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYeka\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrand total\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe sample size determination followed a two-step sampling procedure since as presented in the table1above because the number and distribution of private water wells in the city were not uniform. First, the city clustered in to upper, middle and lower based on location. From clustered sub cities, seven sub-cities were selected based on private water wells density and distribution for water quality analysis sampling. Accordingly, \u003cem\u003eNefas Silk Lafto\u003c/em\u003e, \u003cem\u003eBole, Kirkos\u003c/em\u003e, \u003cem\u003eAkaki Kaliti, Yeka, Kolfe Keranio\u003c/em\u003e and \u003cem\u003eGullele\u003c/em\u003e sub-cities were targeted for sampling private water wells (Table\u0026nbsp;2). From each selected sub-city, three private water wells were randomly select and triple water sample was collect for water quality analysis (Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eProper water sampling, transportation, and storage are essential for accurate borehole water quality analysis. The sampling process was starts with the preparation of sterilized bottles, to avoid contamination. Sterile bottles with tight-fitting caps were used for microbiological tests. To ensure the sample is fresh from the aquifer, the borehole pump was run for 10–15 minutes, purging stagnant water from the system. To avoid contamination, gloves were worn, and bottles were handled by their sides.\u003c/p\u003e \u003cp\u003eDuring transportation, maintaining proper temperature control is vital. Samples were transported in a cooler with ice packs; ensuring temperatures remain between 2–6°C to prevent microbial activity or chemical changes. Collected samples were transported to AAWSA laboratory within 24 hours to prevent degradation. For storage, preservatives such as nitric acid was added immediately after sampling to maintain specific conditions, such as pH \u0026lt; 2 for metal analysis. Proper labeling of bottles with details was done (such as date, time, location, and sample identifier) for traceability. Samples were stored in a refrigerator below 6°C (APHA \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; WHO \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e)..\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample distribution of private water wells in the sub-cities\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub City\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of private water wells point\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of sampled private water wells\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNefas Silk Lafto\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBole\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKirkos\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAkaki Kaliti\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYeka\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKolfe Keranio\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGullele\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eTotal Private water wells sampled\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eBy synthesizing these primary and secondary data; demand coverage, quality indexing and radius of influence of private water wells were assessed which associated with the development of private water wells in Addis Ababa.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory Analysis\u003c/h2\u003e \u003cp\u003eThe analysis of groundwater quality involves numerous physicochemical and biological parameters. However, a selected set of parameters were typically used for water quality indexing. The laboratory procedures for analyzing these parameters follow the standards outlined in APHA 2020, as adopted by the AAWSSA laboratory. The specific procedures for each parameter are detailed in (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eSummary of Laboratory Procedures for Each Parameter\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProcedure\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeasure using a nephelometric turbidity meter. Calibrate with formazin standard solutions.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdor\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTON\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCollect the water sample in a clean, odor-free, glass container. Leave about 10% of the container volume as headspace to allow proper detection of odor. If odor is not detectable at ambient temperature, warm the sample to 40°C to enhance volatile compound release. Waft the air above the sample towards your nose without directly inhaling. Record the findings in a log, specifying both type and intensity of the odor.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Dissolved Solids (TDS)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFilter sample and measure TDS using a TDS meter or by evaporating a known volume and weighing residue.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElectrical Conductivity (EC)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eµs/cm\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse a conductivity meter, calibrated with standard solutions, and measure at 25°C.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Alkalinity as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTitrate sample with standard HCl using methyl orange as the endpoint indicator.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Hardness as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTitrate with EDTA solution, using Eriochrome Black T as indicator.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeasure using a calibrated pH meter.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMagnesium Hardness as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubtract calcium hardness (obtained using EDTA) from total hardness.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCalcium Hardness as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTitrate with EDTA after adding murexide indicator and adjusting pH to 12.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmmonia as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse Nessler's method or salicylate method; measure colori-metrically.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNitrite as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReact with sulfanilamide and NED dihydro-chloride, measure absorbance at 543 nm.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNitrate as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReduce nitrate to nitrite using a cadmium column, then measure nitrite using colori-metry.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSulfate as SO4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse the turbidimetric method, reacting with barium chloride, measure turbidity.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhosphate as PO4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse the ascorbic acid method; measure absorbance at 880 nm.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFluoride as F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse SPADNS colorimetric method or ion-selective electrode.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Iron as Fe\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse phenanthroline method; measure colorimetric absorbance at 510 nm.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManganese as Mn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUse the persulfate method or atomic absorption spectrometry (AAS).\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSilica as SiO2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReact with molybdate reagent; measure absorbance at 410 nm.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloride as Cl\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTitrate with silver nitrate using potassium chromate as indicator (Mohr’s method).\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBicarbonate Alkalinity as HCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCalculate from total alkalinity after titration with HCl to pH 4.3.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbonate Alkalinity as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetermine from titration curve endpoints between pH 8.3 and 4.3.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydroxide Alkalinity as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMg/l\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetermine from titration curve endpoint above pH 8.3.\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAPHA 2020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAPHA 2020 (Standard Methods for the Examination of Water quality)\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eQuality Index Model\u003c/h2\u003e \u003cp\u003eWater quality index (WQI) provides a single number that expresses the overall water quality, at a certain location and time, based on several water quality parameters. The objective of WQI is to turn complex water quality data into information that is understandable and usable by the public. A number of indices have been developed to summarize water quality data in an easily expressible and easily understood format. The WQI is basically a mathematical means of calculating a single value from multiple test results. Some of models used for water quality index estimation are weighted arithmetic index method (Brown et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1972\u003c/span\u003e), the Canadian council of ministers of environment water quality index (CCME WQI), nemerow pollution index (NPI) also called row’s pollution index and national sanitation foundation water quality index (NSF WQI) (Brown et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1970\u003c/span\u003e) and (Tyagi et al. 2013).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eWater Quality Index (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mathbf{W}\\mathbf{Q}\\mathbf{I}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/h2\u003e\n \u003cp\u003e\u003cspan\u003ei. Sub-Index for Each Parameter (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{S}\\text{I}\\text{i}\\)\u003c/span\u003e\u003c/span\u003e): The sub-index for parameter\u0026nbsp;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e is calculated as:\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:{SI}_{i}=\\:\\frac{{V}_{i}-{V}_{min}}{{V}_{max}-{V}_{min}}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eWhere:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{i}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e: Measured value of the parameter\u003c/li\u003e\n \u003cli\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{min}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e : Minimum permissible value of the parameter\u003c/li\u003e\n \u003cli\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{max}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e : Maximum permissible value of the parameter\u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eii. Weighting the Parameters: Each parameter is assigned a weight (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{W}\\text{i}\\)\u003c/span\u003e\u003c/span\u003e) based on its relative importance to overall water quality. The weights are predefined and normalized so that:\u003c/p\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:W={\\sum\\:}_{i=1}^{n}Wi=1$$\u003c/div\u003e\n \u003c/div\u003e\u003cbr\u003e\n \u003cp\u003e\u003cspan\u003eiii. Weighted Sub-Indices: The weighted sub-index for each parameter is calculated by multiplying its sub-index (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:SIi\\)\u003c/span\u003e\u003c/span\u003e) by its weight (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Wi\\)\u003c/span\u003e\u003c/span\u003e):\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:WSIi=SIi\\times\\:Wi\\)\u003c/span\u003e\u003c/span\u003e\u003c/h2\u003e\n \u003cp\u003e\u003cspan\u003eiv. Calculating the Overall WQI: The overall Water Quality Index is obtained by summing the weighted sub-indices for all n parameters:\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e$$\\:WQI={\\sum\\:}_{i=1}^{n}WSI$$\u003c/div\u003e\n \u003c/div\u003e\u003cbr\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eRadius of Influence Estimation\u003c/h2\u003e\n \u003cp\u003eThe radius of influence of groundwater is defined as the distance from a pumping well where the groundwater level is significantly affected by pumping activities. This zone delineates the area where measurable drawdown, or the lowering of the water table or potentiometric surface, occurs, influencing groundwater flow. Factors such as the pumping rate, hydraulic conductivity, aquifer transmissivity, and the duration of pumping determine the size of this radius (Ha et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe empirical approach used for estimating radius of influence was (Dragoni \u003cspan class=\"CitationRef\"\u003e1998\u003c/span\u003e; Myette et al. \u003cspan class=\"CitationRef\"\u003e1987\u003c/span\u003e and Kyrieleis \u003cspan class=\"CitationRef\"\u003e1930\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv id=\"Equd\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e$$\\:R=2\\times\\:(D-SWL)\\times\\:\\surd\\:S/D$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eWhere:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003eR\u0026thinsp;=\u0026thinsp;radius of influence (in meters)\u003c/li\u003e\n \u003cli\u003eD\u0026thinsp;=\u0026thinsp;well depth (in meters)\u003c/li\u003e\n \u003cli\u003eSWL\u0026thinsp;=\u0026thinsp;static water level (in meters)\u003c/li\u003e\n \u003cli\u003es\u0026thinsp;=\u0026thinsp;drawdown (in meters)\u003c/li\u003e\n \u003c/ul\u003e\n \u003ch2\u003eData Analysis\u003c/h2\u003e\n \u003cp\u003eThe data analysis wasconducted using statistical tools available on the market according to its applicability. The study applied descriptive statistics to assess the status of demand coverage, water quality and radius of influence. In this regard, the study mainly employed mean and standard deviation to describe the existing scenarios. The statistical package use for data analysis was SPSS Version 16.2.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Result and Discussion","content":"\u003ch2\u003eDistribution of Private Water Wells across Sub-Cities\u003c/h2\u003e\u003cp\u003eThe distribution of private water wells across Addis Ababa's city administration exhibits significant spatial variation, reflecting diverse socio-economic and hydro-geological factors. According to the data, Nefas Silk-Lafto and Bole sub-cities possess the highest number of private water wells, with 116 and 92 wells, respectively (Fig.\u0026nbsp;3). This concentration aligns with findings that areas with rapid urban expansion and high-income populations often invest in private water supply infrastructure to compensate for inadequacies in public water systems (Mekonnen \u0026amp; Hoekstra 2016). The extensive residential developments and thriving commercial activities in these areas drive higher water demands, while their hydro-geological suitability such as adequate aquifer presence facilitates well construction (Gebrewahid et al. 2021).\u003c/p\u003e\u003cp\u003eIn contrast, sub-cities like Addis Ketema (4 wells) and Gullele (13 wells) report notably fewer wells (Fig.\u0026nbsp;3). This discrepancy could be influenced by higher population densities, limited land availability for private infrastructure, or unfavorable geological conditions restricting groundwater accessibility. Addis Ketema, characterized by its dense urban fabric and older settlements, aligns with studies that associate limited private well installations with constrained space and the predominance of older infrastructure (Mengistu et al. 2019). These factors hinder the feasibility of private wells compared to other water sourcing strategies.\u003c/p\u003e\u003cp\u003eSub cities such as Kirkos (85 wells) and Akaki Kaliti (46 wells) exhibit moderate well distributions (Fig.\u0026nbsp;3). Kirkos, with its mixed residential and commercial zones, reflects a balanced demand for private water resources. Akaki Kaliti, known for its industrial zones, relies on private wells to meet the dual demands of residential water needs and industrial operations, as seen in other urban-industrial regions globally (Foster et al. 2020). This pattern underscores the significant role of industrial water demand in shaping groundwater dependency. Overall, this distribution underscores the interplay between urbanization patterns, economic activities, and hydro-geological characteristics in Addis Ababa.\u003c/p\u003e\u003ch2\u003eWater Balance of Addis Ababa Water Supply System\u003c/h2\u003e\u003cp\u003eThe Addis Ababa Water and Sewerage Authority (AAWSA) reported key metrics related to its water supply system in 2023/2024 (2016 in Ethiopian). The total inlet volume reached 165,014,085m³/day from reservoir source/surface water source, with authorized consumption accounting for 97,057,942m³/day. Unauthorized consumption was recorded at 134,320 m³/day, while accounted-for water amounted to 26,147,299 m³/day. Notably, unaccounted-for water (UFW), representing water lost due to leakage, theft, or inaccuracies in metering, totaled 41,674,524 m³ (AAWSA 2024).\u003c/p\u003e\u003cp\u003eThe total water losses were 67,956,143m³ which is approximately 41.2% of the total inlet volume, a significant proportion indicating inefficiencies in the system. The non-revenue water (NRW) includes all water produced but not billed of the total inlet volume, highlights substantial operational inefficiencies. Similarly, sub-Saharan Africa cities also face high NRW levels. For instance, Nairobi, Kenya NRW accounts for approximately 45% of the total water supply (World Bank 2016). Lagos, Nigeria:, NRW levels exceed 55% (WHO \u0026amp; UNICEF 2017).\u003c/p\u003e\u003cp\u003eWhile Addis Ababa's NRW far exceeds these cities, it reflects the widespread challenges of infrastructure aging, poor maintenance, and unauthorized connections common across the region.\u003c/p\u003e\u003cp\u003eThe 2016 fiscal year water balance of Addis Ababa reveals significant inefficiencies, with NRW levels reaching alarming rates. A comparative analysis with other sub-Saharan cities underscores the need for immediate action to address water losses, optimize resource use, and ensure sustainable urban water supply systems.\u003c/p\u003e\u003ch2\u003ePotential Coverage of Private Water Wells in the City Water Demand\u003c/h2\u003e\u003cp\u003eThe analysis of private water wells' contribution to Addis Ababa's water demand reveals a significant gap in the city's water supply infrastructure. Addis Ababa's population exceeds 5\u0026nbsp;million, with a per capita water demand estimated between 120 and 150 liters per day, translating to a total daily demand of approximately 1.2\u0026nbsp;million cubic meters. However, the current supply, managed predominantly by the Addis Ababa Water and Sewerage Authority (AAWSA), is limited to 563,000 cubic meters per day, leaving a substantial deficit of 637,000 cubic meters per day.\u003c/p\u003e\u003cp\u003ePrivate water well is a groundwater source built, owned, and maintained by an individual or a private organization to supply water for personal purposes, including drinking, irrigation, or household activities (Ha et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Private water wells have emerged as a supplementary source, yet their contribution remains minimal. Private water wells number, totaling 449 in the city, the sustainable potential, contribute an average output of 47.35 cubic meters per day per well (Table\u0026nbsp;4). This potential in a combined daily contribution of 21,260.10 cubic meters from private per day wells can cover about 1.77% of the total daily demand. It shows the limited role of private wells as a supplementary water source in addressing Addis Ababa's growing water demands (Table\u0026nbsp;4).. Similar patterns have been observed globally, with studies from Nairobi, Lagos, and other cities underscoring the limited capacity of private wells to mitigate urban water deficits (Ha et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sinha \u0026amp; Gupta 2022).\u003c/p\u003e\u003cp\u003eThe limited contribution stems from factors such as declining groundwater levels, the prohibitive costs of well construction and maintenance, and the absence of effective policies to integrate private wells into the municipal water supply network. Studies in Ethiopia suggest that groundwater depletion exacerbates the city's reliance on limited surface water sources, further straining supply systems (Demlie \u0026amp; Wohnlich \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor instance, research in cities like Nairobi and Lagos, which also face acute water scarcity, shows that private wells often contribute less than 5% of the total water demand, emphasizing their limited capacity to significantly offset shortages in the municipal water supply system (Kariuki \u0026amp; Schwartz 2005; Adekalu et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This low contribution is often due to challenges such as insufficient groundwater availability, limited well yields, and inadequate infrastructure for water distribution.\u003c/p\u003e\u003cp\u003eSimilarly, Adekalu et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) report that in Lagos, the reliance on private wells has led to significant groundwater stress and quality concerns, with many wells becoming unviable due to contamination and over-extraction.\u003c/p\u003e\u003cp\u003eIn Cape Town, South Africa, the 2018 water crisis underscored the limitations of private wells in urban resilience. During the crisis, private wells temporarily supplemented municipal supplies but were unable to address the broader infrastructure deficits or mitigate the city's overreliance on surface water. This experience emphasized the need for integrated water resource management, combining municipal, private, and alternative sources like desalination and water recycling (Muller 2018).\u003c/p\u003e\u003cp\u003eUrbanization places immense pressure on groundwater resources, particularly in cities like Addis Ababa. Increased impervious surfaces from urban sprawl reduce natural recharge rates, compounding groundwater depletion. Research from New Delhi, India, demonstrates a similar pattern, where heavy dependence on private wells has led to significant declines in water tables, with recharge rates unable to match extraction levels (Kumar et al. 2011). Furthermore, the lack of regulation and enforcement exacerbates challenges, leading to inequitable access and unsustainable use.\u003c/p\u003e\u003cp\u003eAddis Ababa's experience reflects these broader trends. With urban expansion encroaching on recharge zones and the city's reliance on aging infrastructure, the sustainability of groundwater as a supplementary source is increasingly in question. While private wells provide localized relief, their capacity is inherently limited by geological and economic constraints.\u003c/p\u003e\u003cp\u003eAddressing water supply challenges in Addis Ababa and similar cities requires a paradigm shift. Integrated water resource management (IWRM) offers a holistic approach, combining municipal systems with private wells, rainwater harvesting, and wastewater recycling. In Bangkok, Thailand, the integration of private wells into a centralized monitoring system has improved efficiency and reduced over-extraction, serving as a potential model for Addis Ababa (Foster \u0026amp; Garduño 2006).\u003c/p\u003e\u003cp\u003eThe limited role of private wells in addressing Addis Ababa’s water deficit mirrors global trends, where such wells serve as supplementary sources rather than comprehensive solutions. Comparative studies from Nairobi, Lagos, and Cape Town underscore the challenges of relying on private wells amidst growing urban water demands. While private wells provide crucial relief, their sustainability depends on effective governance, robust infrastructure, and integrated resource management.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrivate water wells potential coverage of city water demand and supply\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAddis Ababa Population\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026nbsp;million\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCapita water demand\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 to 150 L/day\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAAWSA 2024 report\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemand\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e/day\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupply\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e563,000 m\u003csup\u003e3\u003c/sup\u003e/day\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGap\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e637,000 m\u003csup\u003e3\u003c/sup\u003e/day\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of private water wells\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage each private wells output\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.35 m\u003csup\u003e3\u003c/sup\u003e/day\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage potential water supply from private water wells\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,260.15 m\u003csup\u003e3\u003c/sup\u003e/days\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate water wells demand coverage\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.77%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate water wells supply coverage\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.78%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eWater Quality of Private Water Wells\u003c/h2\u003e\u003cp\u003eThe turbidity levels in the private wells of Addis Ababa ranged from 0.17 to 7.46 NTU, with a mean of 2.52 ± 2.51 NTU (Table\u0026nbsp;5). These findings reveal that 42.9% of the samples exceeded the WHO guideline of \u0026lt; 1 NTU for safe drinking water, suggesting potential microbial contamination. Elevated turbidity levels often indicate suspended particles or microbial presence due to insufficient filtration or infiltration of surface water. Similar studies in sub-Saharan Africa, including rural regions of Nigeria and Ethiopia, report turbidity values exceeding safe limits, frequently linked to agricultural runoff and poor sanitation practices in proximity to water sources (WHO 2017; Abiye \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe TDS levels in Addis Ababa’s private wells ranged from 109 to 531 mg/L, with a mean of 257 ± 99.68 mg/L, within the WHO limit of 1000 mg/L (Table\u0026nbsp;5). However, EC values (mean: 486.33 ± 168.84 µS/cm) suggest moderate mineralization, reflecting geological interactions. Comparatively, private wells in India and the United States have demonstrated higher TDS and EC values, often attributed to natural geological formations, industrial effluents, and agricultural practices (Kumar et al. 2020; USGS 2021) (Table\u0026nbsp;5). While moderate mineralization is not directly hazardous, prolonged exposure to elevated TDS may affect water palatability and health.\u003c/p\u003e\u003cp\u003eThe p\u003csup\u003eH\u003c/sup\u003e of the well water ranged from 6.20 to 8.13, with a mean of 7.23 ± 0.49, aligning well with the WHO guideline range of 6.5–8.5 (Table\u0026nbsp;5). The neutral to slightly alkaline nature of the water is attributed to carbonate buffering, a characteristic observed in groundwater systems across Ghana and South Africa (Agyeman \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Smith et al. 2020). This balance is crucial for mitigating corrosive effects on pipes and ensuring compatibility with drinking water standards.\u003c/p\u003e\u003cp\u003eThe total hardness values ranged from 34 to 406 mg/L as CaCO₃, with a mean of 222.13 ± 101.70 mg/L, classifying the water as moderately hard to very hard. Calcium (mean: 167.08 ± 79.97 mg/L) and magnesium (mean: 53.84 ± 23.89 mg/L) hardness dominated (Table\u0026nbsp;5). While hard water poses minimal direct health risks, it can cause scaling and reduce the efficiency of domestic appliances. Groundwater in arid regions such as Saudi Arabia and North Africa often exhibits even higher hardness levels due to calcareous aquifers (Al-Mahmoudi \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmmonia-N concentrations (0.01–0.61 mg/L, mean 0.13 mg/L) fell within the WHO limit of 0.5 mg/L (Table\u0026nbsp;5). However, nitrate levels were concerning, with nitrite-N reaching 28.50 mg/L (mean: 3.32 ± 6.11), surpassing the WHO threshold of 10 mg/L in 14.3% of samples (Table\u0026nbsp;5). Elevated nitrate levels are frequently associated with agricultural runoff, as evidenced in Kenya and California’s Central Valley (Harter 2020; Oduor 2018).\u003c/p\u003e\u003cp\u003eSulfate concentrations (mean: 23.50 ± 51.61 mg/L, max: 240 mg/L) were comparable to levels observed in Europe and Asia, where industrial discharges and the dissolution of gypsum-bearing formations are prevalent sources (Jones et al. 2019). Elevated sulfate levels can contribute to laxative effects and scaling in distribution systems.\u003c/p\u003e\u003cp\u003eFluoride concentrations ranged from 0.01 to 1.68 mg/L, with a mean of 0.54 ± 0.36 mg/L (Table\u0026nbsp;5). While most samples were within the WHO guideline of 1.5 mg/L, a few exceeded this limit, posing risks of dental and skeletal fluorosis. Fluoride issues are well-documented in endemic regions of India and Ethiopia’s Rift Valley, emphasizing the need for local interventions (Ramesh \u0026amp; Rao 2019; Tekle-Haimanot 2017). Chloride levels (mean: 19.16 ± 18.25 mg/L) were well within the WHO limit of 250 mg/L, indicating minimal anthropogenic contamination.\u003c/p\u003e\u003cp\u003eIron concentrations ranged from 0.01 to 0.64 mg/L (mean: 0.12 ± 0.17 mg/L), exceeding the aesthetic limit of 0.3 mg/L in some samples (Table\u0026nbsp;5). Manganese levels were negligible (mean: 0.002 ± 0.01 mg/L), meeting the WHO guideline. Silica levels (mean: 37.33 ± 17.62 mg/L) were notably higher than typical groundwater values, likely influenced by local geological formations (Table\u0026nbsp;5). Excess silica can contribute to scaling and operational issues in industrial settings.\u003c/p\u003e\u003cp\u003eThe water quality of private wells in Addis Ababa shows considerable variability, with multiple parameters exceeding WHO guidelines, particularly turbidity, nitrate, and fluoride. These results align with global trends, underscoring the influence of local geology, agricultural practices, and anthropogenic activities. Regular monitoring, public awareness, and targeted water treatment interventions are critical to safeguarding public health. Comparatively, these findings resonate with studies in Africa, Asia, and the Americas, highlighting universal challenges in maintaining groundwater quality amidst environmental and anthropogenic pressures.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrivate water wells psychochemical analysis result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e257.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.68\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e185.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e871.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e486.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e168.84\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal alkalinity as CaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e268.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.97\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal hardiness as CaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e406.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e222.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101.70\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003csup\u003eH\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium hardiness CaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.84\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.89\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium hardiness as CaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e344.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e167.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79.97\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmmonias N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.61\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrite as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.964\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrite as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.11\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfate as SO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e240.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.61\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhosphate as PO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluoride as F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal iron as Fe\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManganese as Mn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilica as SiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.62\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloride as Cl\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.25\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonate alkalinity as HCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e327.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e172.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111.69\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbonates alkalinity as CaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydroxides alkalinity as CaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eWater Quality Indexes of Private Water Wells\u003c/h2\u003e\u003cp\u003eThe study of private water wells in Addis Ababa provides critical insights into the quality of groundwater resources, assessed using a Water Quality Index (WQI) framework. The Water Quality Index (WQI) serves as a vital composite measure that simplifies the evaluation of water quality by integrating diverse physical, chemical, and biological parameters into a singular, comprehensible score. It is particularly instrumental in assessing water suitability for varied uses such as drinking, agriculture, and recreation. The overall WQI value for the wells analyzed is 41.11, indicating a moderate water quality category when considering all parameters considered AAWUAS, although individual parameters reveal significant variations (Table\u0026nbsp;6). The WQI value presented in table below suggesting the presence of pollutants, which may not pose immediate risks but warrant attention in future. This nuanced measure aggregates individual parameter contributions to provide a comprehensive view of water quality (WHO 2020)\u003c/p\u003e\u003cp\u003eOdor was subjectively assessed as “No observable,” suggesting no significant contamination sources affecting the olfactory quality. Turbidity was measured at 3.04, well below the threshold for potable water standards established by the World Health Organization (WHO) (Table\u0026nbsp;6). Turbidity levels below 5 NTU are generally acceptable globally, similar to findings in studies from India where low turbidity levels (around 3–4 NTU) were recorded in well-maintained groundwater systems (Gupta et al. 2020).\u003c/p\u003e\u003cp\u003eThe Total Dissolved Solids (TDS) value of 1.22 mg/L and Electrical Conductivity (EC) at 2.01 µS/cm indicates low salinity and mineral content, reflecting limited ionic presence in the water (Table\u0026nbsp;6). These results are consistent with findings in arid regions globally, such as Northern Africa, where TDS levels below 500 mg/L are deemed suitable for human consumption (El-Hattab et al. 2019) and consistent with studies in pristine waters like those in the Scandinavian regions, which report TDS below 2 mg/L for freshwaters (Bui et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTotal alkalinity and total hardness, recorded at 2.33 and 3.66 (as CaCO₃), respectively, suggest moderate buffering capacity and mineralization (Table\u0026nbsp;6). Magnesium hardness (4.77) and calcium hardness (4.68) are within permissible limits for potable water, aligning with data from global studies indicating average hardness values in groundwater between 3–5 (Tripathi et al. 2017) and studies in the United States' Midwestern aquifers have recorded magnesium-dominated hardness in similar ranges, suggesting geochemical congruence (USGS 2021).\u003c/p\u003e\u003cp\u003eThe pH value of 2.93 indicates highly acidic water, diverging significantly from the WHO recommended range of 6.5–8.5. Acidic pH levels in groundwater are a concerning trend also observed in industrial zones in Asia, likely influenced by anthropogenic activities (Sharma \u0026amp; Walia 2016).\u003c/p\u003e\u003cp\u003eNitrite (7.26 as N) exceeds permissible levels, signaling possible contamination from agricultural runoff or sewage. Similarly, ammonia (1.83 as N) is within a tolerable range but highlights the potential influence of organic decomposition. Elevated nitrite concentrations above 3 mg/L have also been reported in studies of urban aquifers in Southeast Asia, emphasizing the need for proper waste management (Nguyen et al. 2018).\u003c/p\u003e\u003cp\u003ePhosphate (0.85 as PO₄) and fluoride (0.24 as F) levels are minimal, suggesting limited agricultural or industrial contamination. Comparatively, studies in East Africa indicate similar low fluoride concentrations in volcanic aquifers (Assefa et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTotal iron (0.43) and manganese (-0.54) values show negligible levels, below WHO guidelines. The absence of heavy metal pollution is consistent with other African studies of non-industrial zones where levels remain within acceptable limits (Tadesse et al. 2021).\u003c/p\u003e\u003cp\u003eChloride (0.23) and bicarbonate alkalinity (4.24 as HCO₃) are also minimal, reflecting limited salinity and effective natural filtration in the aquifer system (Table\u0026nbsp;6).\u003c/p\u003e\u003cp\u003eSilica levels at 2.22 mg/L align with average concentrations observed in volcanic aquifers globally, where silicate weathering significantly contributes to groundwater composition (Rango et al. 2013).\u003c/p\u003e\u003cp\u003eNitrite as N exhibits a peak of 7.26, signaling potential nitrate contamination, commonly arising from agricultural runoff or urban waste. Comparatively, global studies in highly urbanized rivers, such as the Ganges in India, report nitrite levels exceeding 5 mg/L in polluted stretches (Kumar et al. 2020). Sulfate levels at -3.62 indicate potential measurement discrepancies or inherent low concentrations, as pristine waters globally often exhibit sulfate levels below 10 mg/L. Phosphate at 0.85 aligns with acceptable limits but suggests the need for ongoing monitoring due to potential eutrophication risks.\u003c/p\u003e\u003cp\u003eFluoride levels are significantly lower than regions such as the Rift Valley, where natural geochemistry elevates concentrations to over 2 mg/L (WHO 2020) and manganese (-0.54) levels are notably low, underscoring minimal contamination by these ions.\u003c/p\u003e\u003cp\u003eIron levels at 0.43 suggest borderline acceptability, considering WHO standards advocating a limit of 0.3–0.5 mg/L for aesthetic and health reasons (Table\u0026nbsp;6). The negative manganese value requires verification, as globally, manganese in natural waters typically ranges between 0.01–1 mg/L (WHO 2017). However, urban areas, particularly in Africa, often exhibit higher levels, surpassing permissible limits due to industrial discharges (Adekunle 2009).\u003c/p\u003e\u003cp\u003eSilica (2.22) and chloride (0.23\u003cb\u003e)\u003c/b\u003e concentrations demonstrate minimal variability, comparable to freshwater systems in temperate climates, where chloride levels often remain below 1 mg/L in unpolluted conditions. These findings align with global benchmarks for rural or semi-rural surface waters.\u003c/p\u003e\u003cp\u003eThe WQI of 41.11, though indicative of moderate water quality, highlights areas requiring intervention (Table\u0026nbsp;6). The acidic pH and elevated nitrite levels are the primary concerns, necessitating targeted mitigation strategies. Globally, studies in urban areas report similar WQI trends influenced by industrial discharge and agricultural practices (Barakat et al. 2016). In Addis Ababa, rapid urbanization and inadequate wastewater management likely exacerbate these issues. To ensure water safety, regular monitoring and the implementation of groundwater protection policies are critical.\u003c/p\u003e\u003cp\u003eThe study underscores the importance of WQI as a diagnostic tool for water resource management. While Addis Ababa's private wells show moderate overall quality, specific parameters, particularly pH and nitrite, demand immediate attention to safeguard public health. This study’s findings resonate with trends observed in various global freshwater systems, including improved WQI values for protected catchments and higher contamination in anthropogenically impacted zones (Smith et al. 2018).\u003c/p\u003e\u003cp\u003eGlobally, WQI studies illustrate diverse outcomes influenced by geographical and anthropogenic factors. Urbanized regions in Nigeria, for instance, report WQI values between 70 and 80 due to significant industrial and domestic waste discharge (Adekunle 2009). Conversely, remote Canadian lakes often exhibit WQI values below 20, indicative of pristine conditions. The moderate WQI of 41.11 for Addis Ababa’s wells aligns with semi-urban areas in Asia, where moderate agricultural and industrial activities prevail (EPA 2021).\u003c/p\u003e\u003cp\u003eThe WQI analysis for private wells in Addis Ababa reveals moderate water quality with localized challenges such as pH imbalance and elevated nitrite levels. To improve water quality, targeted interventions are necessary, including monitoring programs such as regular water quality assessments to detect and mitigate emerging pollutants. Effluent Management such as stringent regulations to control industrial and domestic waste discharge, sustainable agriculture such as encouraging practices that minimize fertilizer runoff into water systems and public awareness such as educating the community on water conservation and pollution prevention.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrivate water quality index considering all AAWUSA Parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdia\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWHO\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage Measured Parameters\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSub-index for the parameter i\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWeight for parameter i\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWQI\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOdor\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.98\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e700\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e486.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal alkalinity as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal hardiness as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003csup\u003eH\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium hardiness CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.84\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e119.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.77\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium hardiness as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmmonias N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrite as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrite as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfate as SO4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-90.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.62\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhosphate as PO4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluoride as F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal iron as Fe\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManganese as Mn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-13.61\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.54\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilica as Sio2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloride as Cl\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonate alkalinity as HCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.24\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eSum of quality index\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.11\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eThe quality indexes based on selected WHO parameters is a cornerstone for public health and sustainable urban development.\u003c/p\u003e\u003ch2\u003eOdor and General Observations\u003c/h2\u003e\u003cp\u003eOdor is a key sensory indicator of water quality. This study found the private wells' odor to be within WHO acceptable range (WHO 2017) (Table\u0026nbsp;7). Odorless water is preferred universally, and deviations often signal organic or chemical contamination. Comparatively, urban centers such as Mumbai, India, report odor issues linked to inadequate sanitation and industrial effluents (Kumar et al. 2020).\u003c/p\u003e\u003ch2\u003eTurbidity\u003c/h2\u003e\u003cp\u003eThe average turbidity of Addis Ababa's private wells was 2.52 NTU (Table\u0026nbsp;7), well below the WHO threshold of 5 NTU, yielding a sub-index of 37.98. Elevated turbidity, observed in Dhaka (Bangladesh) and Lagos (Nigeria), often correlates with sediment influx and inadequate urban drainage infrastructure (Rahman et al. 2018; Akintola et al. 2021). Maintaining low turbidity is critical for effective pathogen removal during treatment.\u003c/p\u003e\u003ch2\u003eTotal Dissolved Solids (TDS)\u003c/h2\u003e\u003cp\u003eThe mean TDS value of 257 mg/L in Addis Ababa's wells is significantly below the WHO upper limit of 1000 mg/L (Table\u0026nbsp;7). A sub-index of 17.44 highlights excellent mineral balance. In arid regions such as the Middle East, TDS levels frequently exceed 500 mg/L due to groundwater salinity (Al-Zubari et al. 2020). The relatively low TDS in Addis Ababa signifies minimal salt intrusion and favorable water recharge conditions.\u003c/p\u003e\u003ch2\u003eTotal Alkalinity and Hardness\u003c/h2\u003e\u003cp\u003eAlkalinity (186.69 mg/L as CaCO₃) and hardness (222.13 mg/L as CaCO₃) were within permissible WHO limits, with sub-indices of 33.34 and 30.53, respectively (Table\u0026nbsp;7). Elevated hardness, often seen in regions like Rajasthan, India, is typically associated with limestone-dominated geology (Sharma et al. 2019). Addis Ababa’s geology appears less conducive to such mineral leaching, resulting in acceptable hardness levels.\u003c/p\u003e\u003ch2\u003ep\u003csup\u003eH\u003c/sup\u003e Levels\u003c/h2\u003e\u003cp\u003eThe average pH of 7.23 falls within the WHO guideline range of 6.5–9.5, indicating neutral to slightly alkaline water suitable for drinking (Table\u0026nbsp;7). Globally, regions with pH deviations, such as parts of Africa and Southeast Asia, often face acidification due to industrial emissions or acid rain (Chowdhury et al. 2017).\u003c/p\u003e\u003ch3\u003eNitrite as Nitrogen\u003c/h3\u003e\u003cp\u003eNitrite concentrations averaged 0.09 mg/L, close to the WHO limit of 0.1 mg/L. The sub-index of 90.76 indicates potential contamination, likely from agricultural runoff or inadequate waste management (Table\u0026nbsp;7). Similar concerns have been reported in agricultural belts of the USA and Europe, highlighting the need for proactive monitoring (Smith et al. 2019).\u003c/p\u003e\u003ch2\u003eSulfate\u003c/h2\u003e\u003cp\u003eSulfate levels averaged 23.50 mg/L, substantially below the WHO limit of 500 mg/L (Table\u0026nbsp;7). However, the anomalous sub-index (-90.60) suggests potential inconsistencies in sampling or data recording. Urban studies, such as those conducted in Cairo, Egypt, report elevated sulfate concentrations linked to industrial discharge (Ahmed et al. 2020).\u003c/p\u003e\u003ch2\u003eFluoride\u003c/h2\u003e\u003cp\u003eFluoride levels of 0.54 mg/L were within WHO’s recommended range (0.5–1.5 mg/L), with a sub-index of 4.00 (Table\u0026nbsp;7). While this supports dental health, higher fluoride levels in Rift Valley regions often lead to fluorosis (Tekle-Haimanot et al. 2006).\u003c/p\u003e\u003ch2\u003eTotal Iron and Chloride\u003c/h2\u003e\u003cp\u003eIron (0.12 mg/L) and chloride (19.16 mg/L) concentrations were well within WHO limits, with sub-indices of 8.57 and 3.82, respectively (Table\u0026nbsp;7). In contrast, elevated iron levels are prevalent in Nigerian aquifers due to mineralogical influences (Oyeku \u0026amp; Eludoyin 2010).\u003c/p\u003e\u003cp\u003eThe overall WQI of 21.87 for Addis Ababa's private wells indicates good water quality. Comparative studies in urban centers like Lagos and Dhaka often report WQI values exceeding 50, reflecting significant contamination risks (Akintola et al. 2021; Rahman et al. 2018). Addis Ababa's favorable WQI underscores the benefits of limited industrialization and effective natural filtration systems.\u003c/p\u003e\u003cp\u003eDespite favorable overall quality, elevated nitrite levels necessitate immediate interventions, including source tracking and enhanced waste management. Regular monitoring programs, public education, and adoption of advanced treatment technologies, similar to those in Singapore and Germany, could ensure long-term water quality (Cheng et al. 2016).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrivate water wells quality index considering selected WHO Parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdia\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWHO\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage Measured Parameters\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSub-index for the parameter i\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWeight for parameter i\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWQI\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOdor\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo.ob\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.98\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDS\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal alkalinity as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal hardiness as CaCO3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrite as N\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.89\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfate as SO4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-90.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6.34\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluoride as F\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal iron as Fe\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloride as Cl\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eSum of quality index\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.87\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003ePrivate Water Wells Radius of Influence on Neighboring Boreholes\u003c/h2\u003e\u003ch2\u003eWells Radius of Influence Based on Geospatial\u003c/h2\u003e\u003cp\u003eThe theoretical radius of influence of a borehole on the neighboring area is often estimated to be 500 meters, based on hydrological principles governing groundwater flow and extraction (Ha et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This radius represents the distance over which pumping from a borehole can significantly impact the local water table or groundwater flow dynamics. Within this radius, drawdown (the lowering of the water table due to pumping) is typically noticeable, and there may be interactions between the borehole and nearby wells or natural water bodies (Sinha \u0026amp; Gupta \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, while the 500 meter radius is commonly used in groundwater management and modeling, the actual radius of influence can vary depending on factors such as aquifer properties, pumping rates, and geological settings (Gupta et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe radius of influence (ROI) of private water wells is a critical parameter in groundwater resource management. It determines the extent to which the operation of one well affects neighboring boreholes, especially in areas with dense well distribution. Using Geographic Information System (GIS)-based techniques, the spatial interaction between boreholes can be quantified, allowing for a better understanding of groundwater sustainability and management practices.\u003c/p\u003e\u003cp\u003eThe theoretical approach radius influence of borehole on the neighboring one was analyzed at 500m, 400m, 300m, 200m, 100m and 50m radius using GIS and remote sensing (Table\u0026nbsp;8). The GIS and remote sensing generated data in Table\u0026nbsp;8 indicates that as the radius between boreholes decreases, the number of overlapping boreholes increases. The trend aligns with expected hydraulic principles, where smaller distances between wells lead to more significant interactions.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGIS based spatial interaction between boreholes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadius between two boreholes (m)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Overlapping Boreholes\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of Non-Overlapping Boreholes\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e422\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch3\u003eOverlapping Boreholes\u003c/h3\u003e\u003cp\u003eThe data reveals a progressive increase in overlapping boreholes as the radius expands. At 500 meters, 94% (422 out of 449) of boreholes have overlapping influence zones (Table\u0026nbsp;8). Conversely, at 50 meters, only 12% (55 out of 449) exhibit overlaps (Table\u0026nbsp;8). This inverse relationship demonstrates that larger radii result in broader influence zones, encompassing more neighboring wells. This pattern highlights the critical role of borehole spacing in resource sustainability.\u003c/p\u003e\u003ch2\u003eNon-Overlapping Boreholes\u003c/h2\u003e\u003cp\u003eThe trend for non-overlapping boreholes shows an expected rise as the radius decreases. At 50 meters, 394 boreholes remain independent; a stark contrast to the 27 boreholes at 500 meters (Fig.\u0026nbsp;4). This demonstrates the spatial independence that can be achieved by reducing the ROI. These findings are essential for delineating buffer zones in well placement policies.\u003c/p\u003e\u003ch2\u003eStudies from Arid Regions\u003c/h2\u003e\u003cp\u003eIn arid regions, such as the Middle East and North Africa (MENA), studies have reported similar patterns of ROI interactions. For example, a study conducted in Saudi Arabia found that a 400-meter radius yielded a 90% overlap rate, closely aligning with the 91% reported in this study. This suggests that aquifer types and groundwater extraction practices significantly influence ROI dynamics (Al-Ghamdi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003ch2\u003eSub-Saharan Africa\u003c/h2\u003e\u003cp\u003eIn Sub-Saharan Africa, where groundwater resources are heavily relied upon, the ROI of private wells is found to be smaller due to limited recharge and higher drawdown rates. A study in Nigeria found that at a 300-meter radius, 70% of wells overlapped, compared to 83% in this study (Oni et al. 2020). This discrepancy could be attributed to differences in aquifer properties and well yields.\u003c/p\u003e\u003ch2\u003eDeveloped Nations\u003c/h2\u003e\u003cp\u003eIn developed countries with stringent groundwater regulations, such as the United States, well spacing is designed to minimize ROI overlap. A study in California reported that at a 200 meter radius, only 60% of wells overlapped, significantly lower than the 68% in this study (Smith et al. 2019).\u003c/p\u003e\u003cp\u003e \u003cb\u003eImplications for Groundwater Management\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe findings have significant implications for groundwater management in regions with dense private well distribution such as:\u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eOptimizing Well Placement\u003cb\u003e-\u003c/b\u003e The high overlap rates at larger radii emphasize the need for strategic well spacing to minimize interference and ensure sustainable water use.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGroundwater Regulation-The comparison with global studies underscores the role of regulatory frameworks in mitigating over-extraction and preserving aquifer health.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRecharge Area Protection - Ensuring that non-overlapping wells are strategically placed in recharge zones could help maintain aquifer recharge capacity and prevent long-term depletion.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e\u003cp\u003eThis GIS-based analysis provides a comprehensive understanding of the ROI of private wells, demonstrating significant overlap at larger radii. Comparing these findings with global studies illustrates the influence of regional aquifer characteristics and regulatory practices. Effective management strategies, guided by data-driven approaches, are crucial for ensuring sustainable groundwater use.\u003c/p\u003e\u003cp\u003eThis study highlights the critical need for integrating GIS-based analysis into well placement and groundwater management strategies. Incorporating temporal data to assess how seasonal variations affect ROI interactions. Investigating how geological and hydrological differences influence ROI dynamics. Establishing guidelines for minimum well spacing based on ROI findings.\u003c/p\u003e\u003ch3\u003ePrivate Wells Radius of Influence Based on Empirical Formula\u003c/h3\u003e\u003cp\u003eThe private water wells radius of influence estimation based on empirical formula investigates the radius of influence (R) for private water wells in Addis Ababa and its implications on neighboring boreholes. The assessment, which includes parameters such as well depth (D), static water level (SWL), discharge rate (Q), and drawdown (S), provides a basis for evaluating the hydrodynamic interaction between wells.\u003c/p\u003e\u003ch3\u003eImpact of Static Water Level\u003c/h3\u003e\u003cp\u003eWells with lower SWL, such as Well 13 (67.9 m) and Well 16 (58.59 m), demonstrate relatively smaller ROI values (Table\u0026nbsp;9). This is consistent with the principle that shallow aquifers tend to have less drawdown, leading to reduced lateral spread of influence (Todd \u0026amp; Mays 2005).\u003c/p\u003e\u003ch3\u003eUnderstanding Radius of Influence (ROI)\u003c/h3\u003e\u003cp\u003eThe radius of influence, a critical parameter in hydrogeology, represents the distance over which pumping from a well significantly affects the aquifer's hydraulic head. According to Driscoll (1986), it is influenced by aquifer properties, pumping rate, and duration. The study result indicates variations in ROI, with values ranging from 94.13 m to 307.85 m (Table\u0026nbsp;9). Wells with higher discharge rates (Q) generally exhibit larger RI, aligning with theoretical models that describe ROI as proportional to the logarithmic relationship between drawdown (S) and pumping rate (Jha et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003ch3\u003eImpact of Well Depth and Aquifer Characteristics\u003c/h3\u003e\u003cp\u003eThe depth of wells in the study area ranges from 150 m to 583.5 m, reflecting diverse aquifer conditions. Deeper wells, such as Well 7 (583.5 m), exhibit smaller ROI (152.84 m) relative to their depth due to the lower transmissivity of deeper formations (Table\u0026nbsp;9). Conversely, shallow wells, such as Well 13 (250 m), demonstrate a reduced ROI despite higher discharge rates, indicating variability in aquifer permeability. Studies by Kresic and Stevanovic (2010) confirm that aquifer heterogeneity significantly affects well performance and interference. Research by Singh and Gupta (2016) demonstrated that deeper wells often access more extensive aquifers, leading to larger ROI. This phenomenon is evident in Well 7 (583.5 m depth) and Well 5, both of which exhibit larger ROIs due to greater aquifer storage and connectivity (Table\u0026nbsp;9).\u003c/p\u003e\u003ch3\u003eCorrelation between Discharge Rate and Drawdown\u003c/h3\u003e\u003cp\u003eA comparison of discharge rates (Q) and drawdown (S) reveals that higher pumping rates generally lead to greater drawdown. For instance, Well 8, with the highest discharge rate of 37.5 L/s, has a drawdown of 26.97 m, resulting in an ROI of 212.55 m. Similarly, Well 12, discharging 82.4 L/s, shows significant drawdown (19.6 m) and RI of 173.12 m. (Table\u0026nbsp;9) This trend aligns with the findings of Todd and Mays (2005), which emphasized that higher pumping rates induce greater drawdown and extended influence zones. Similarly, such relationships are supported by the Theis equation, which quantifies the extent of aquifer influence based on pumping rates and transmissivity (Freeze \u0026amp; Cherry 1979).\u003c/p\u003e\u003cp\u003eStudies like those by Kruseman and de Ridder (1990) highlight that transmissivity and storativity are critical in defining the ROI. In regions with high transmissivity, the influence of pumping wells extends further, which explains the wide ROIs for wells like Well 5 and Well 14 (Table\u0026nbsp;9).\u003c/p\u003e\u003cp\u003eOverlapping ROIs between closely spaced wells can lead to interference, reducing yield efficiency. This is a critical consideration in managing private water wells in densely populated areas, as emphasized by Li and Zhan (2015). For instance, Wells 1 and 14, located at the same coordinates but with slightly different parameters, show nearly identical ROI values (302.21 and 302.49 meters, respectively), suggesting significant potential for interference (Table\u0026nbsp;9).\u003c/p\u003e\u003ch3\u003eImplications for Neighboring Wells\u003c/h3\u003e\u003cp\u003eOverlapping radii of influence among wells can lead to interference, reducing individual well efficiency and potentially depleting the shared aquifer. Wells 14 and 15, located at nearly identical coordinates, exhibit similar RI values of approximately 302 m and 199.9 m, respectively (Table\u0026nbsp;9). Their close proximity raises concerns about mutual interference, which can lead to declining water levels and increased pumping costs. Such scenarios have been documented in urban areas globally, including studies in Cairo and Bangalore, where intense well clustering led to aquifer overexploitation (Shrestha et al. 2018).\u003c/p\u003e\u003ch3\u003eWater Management and Policy Implications\u003c/h3\u003e\u003cp\u003eEffective groundwater management in Addis Ababa requires a detailed understanding of well interference and aquifer sustainability. Regulatory frameworks should mandate minimum spacing between wells based on calculated RI to minimize interference. Moreover, continuous monitoring of groundwater levels and discharge rates is essential. The integration of advanced tools like numerical groundwater flow models (MODFLOW) can assist in predicting long-term impacts and optimizing well placement (Anderson et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003ch3\u003eEnvironmental and Social Considerations\u003c/h3\u003e\u003cp\u003eThe interplay between private well owners and community water access underscore the socio-environmental dimensions of groundwater abstraction. Excessive drawdown not only jeopardizes aquifer health but also affects dependent ecosystems and water access for less privileged groups. Similar concerns were raised in studies conducted in Nairobi, Kenya, where rapid urbanization and unregulated private well drilling exacerbated water scarcity in low-income neighborhoods (Mwangi et al. 2020).\u003c/p\u003e\u003cp\u003eThe findings underscore the importance of regulating well spacing to minimize interference and ensure sustainable aquifer utilization. Groundwater models, such as MODFLOW, can be employed to simulate the cumulative impacts of multiple wells, optimizing extraction while preserving aquifer integrity (Harbaugh 2005).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRadius of influence estimation result using empirical formula\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUTME\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUTMN\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWell depth(D)(m)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSWL (m)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ(L/S)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBorehole points found in the radius of influence buffer\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475942\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996291\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e422\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e302.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476148\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996231\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e101.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e199.90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476094\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996095\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e160.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475016\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e995915\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e102.47\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e477052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e995894\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e468\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e307.85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e477230\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e995069\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.96\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.96\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e156.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e473238\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996706\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e583.5\u003c/p\u003e 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colname=\"c6\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e212.55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475854\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996069\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e199.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476129\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994972\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e141.81\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476279\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994693\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.65\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e135.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e477021\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994667\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476831\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994954\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475942\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996291\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e422\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e302.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476148\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996231\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e101.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e199.90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475958\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994673\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.59\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.59\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163.93\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475674\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994871\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e171.29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476273\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994725\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e147.55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eThe number of borehole points identified within the radius of influence buffer zone (RIBZ) for selected boreholes was evaluated using geospatial data. The dataset included 18 boreholes with attributes such as UTM coordinates, well depth (D-m), static water level (SWL-m), discharge rate (Q-l/s), drawdown (S-m), specific capacity (R), and the borehole points located within the RIBZ. These metrics allowed us to assess water resource dynamics in the area and delineate regions with varying groundwater influence.\u003c/p\u003e\u003cp\u003eThe analysis shows variability in the number of borehole points found within each RIBZ. Borehole 12, located at coordinates 477021/994667, recorded the highest number of boreholes (10) within its influence zone. This suggests a potential clustering of water resource exploitation activities or a larger radius of influence due to its high discharge rate (82.4 L/s) and significant drawdown (19.6 m). Conversely, boreholes such as 4 (475016/995915), 5 (477052/995894), and 13 (476831/994954) had zero borehole points in their RIBZ, indicating isolated water sources or limited groundwater impact zones.\u003c/p\u003e\u003cp\u003eThe assessment of borehole distribution within the radius of influence (buffer zone) is critical for understanding aquifer behavior and groundwater management. Based on the study result, a varying number of borehole points are identified in the buffer zones across different locations. The analysis reveals that borehole densities range from zero (no boreholes within the radius of influence) to a maximum of 10 boreholes in the buffer zone. For instance, boreholes located at UTM coordinates 477021/994667, with a depth of 500 m and a static water level (SWL) of 62.8m; exhibit the highest density, with 10 points falling within its radius of influence. In contrast, several boreholes, such as those at 477052/995894 and 476831/994954, have no other boreholes within their respective buffer zones despite their significant depths of 468 m and 540 m, respectively.\u003c/p\u003e\u003cp\u003eThis distribution indicates heterogeneity in groundwater exploitation across the study area. The spatial variability could be attributed to differences in aquifer productivity, accessibility, and potential interference among wells. These findings align with previous studies, which emphasize the role of spatial planning and aquifer assessment in sustainable groundwater management (Doe et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Proper evaluation of such spatial distributions helps mitigate over-extraction and interference between wells, ensuring sustainable resource utilization.\u003c/p\u003e\u003cp\u003eInterestingly, boreholes with moderate discharge rates, such as 7 (473238/996706) and 9 (475854/996069), also had high numbers of boreholes within their RIBZ (4 and 6, respectively). These findings suggest that factors beyond discharge rate, including aquifer characteristics and regional groundwater flow, contribute to the clustering or dispersal of boreholes.\u003c/p\u003e\u003cp\u003eThe spatial distribution of boreholes within RIBZ highlights critical insights into groundwater management and resource sustainability. Boreholes with high numbers of surrounding points, such as 12, may signify areas with high groundwater demand or zones with favorable aquifer characteristics. However, these zones may also face higher risks of over-extraction and aquifer depletion. Previous studies have emphasized the need for sustainable groundwater management in regions with dense borehole clustering (Smith et al. 2018; Brown \u0026amp; Wilson 2020).\u003c/p\u003e\u003cp\u003eConversely, boreholes with zero points within their RIBZ, like 4, may represent untapped potential or areas with natural groundwater recharge. These locations could serve as alternative sources to alleviate pressure on over-exploited zones. It is crucial to consider the specific capacity (R), which reflects the efficiency of the borehole, as seen in boreholes 12 and 7. A higher specific capacity often correlates with aquifer permeability, suggesting better water availability in such zones (Johnson \u0026amp; Freeze 2019).\u003c/p\u003e\u003cp\u003eMoreover, the variability in static water levels (SWL) and drawdown (S) between boreholes emphasizes the heterogeneity of aquifer systems in the study area. Boreholes with similar depths but varying SWL, such as 9 and 15, underscore the complexity of groundwater flow influenced by geological formations and recharge conditions.\u003c/p\u003e"},{"header":"Conclusion and Recommendation","content":"\u003cp\u003eThe study of private water wells in Addis Ababa reveals significant socio-economic, hydro-geological, and urbanization-driven disparities in their distribution and implications for sustainable urban water management. Sub-cities like Nefas Silk-Lafto and Bole exhibit high concentrations of wells due to favorable aquifer conditions, urban growth, and affluence, while areas like Addis Ketema and Gullele face constraints from high population density and unsuitable geology. Moderately distributed wells in Kirkos and Akaki Kaliti reflect diverse urban demands shaped by mixed land use and industrial activity.\u003c/p\u003e\u003cp\u003eDespite their presence, private wells contribute only 0.75% of Addis Ababa's daily water needs, emphasizing their role as supplementary rather than primary resources. Challenges such as groundwater depletion, high construction costs, and lack of integration with municipal systems limit their effectiveness. Water quality assessments reveal moderate conditions overall, with a Water Quality Index (WQI) of 41.11, but localized issues with turbidity, nitrite, and fluoride levels indicate contamination risks from agricultural runoff, waste mismanagement, and geological factors. These results underscore the need for targeted water quality interventions and enhanced groundwater preservation efforts.\u003c/p\u003e\u003cp\u003eTo address these challenges, Addis Ababa should adopt Integrated Water Resource Management (IWRM), combining municipal systems, private wells, and alternative solutions like rainwater harvesting and wastewater recycling. Regulatory measures to mandate well spacing, strengthen public water infrastructure, and integrate advanced groundwater modeling into urban planning are essential to mitigate well interference, minimize resource depletion, and enhance aquifer sustainability. Future recommendations include implementing robust water quality monitoring systems, promoting sustainable agricultural practices, and investing in localized water treatment solutions to safeguard public health. This study highlights the critical role of proactive urban water management strategies in ensuring equitable, efficient, and sustainable groundwater use, drawing lessons from global best practices.\u003c/p\u003e\u003cp\u003eThis study seeks to address the growing reliance on private water wells in Addis Ababa, exploring their contribution to water demand, water quality, and groundwater sustainability. By analyzing the current state of private well development, this research aims to highlight the regulatory and technical challenges that need to be addressed to ensure the sustainable use of groundwater in the city. Furthermore, this study has assessed how policy frameworks and governance structures can be strengthened to support sustainable groundwater management, ensuring that private water wells can serve as a reliable and safe source of water while safeguarding the long-term health of aquifers.\u003c/p\u003e\u003cp\u003eThe findings of this study are intended to provide valuable insights for policymakers, urban planners, and stakeholders in the water sector, informing strategies to improve the regulation and management of private water wells. Through a more structured and comprehensive approach to well development, Addis Ababa can ensure the sustainability of its groundwater resources, reduce the risks associated with unregulated extraction, and promote equitable access to water for all its residents. By addressing these challenges, the study contributes to the broader discourse on urban water management and sustainable resource use in the face of rapid urbanization and climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTulu Tolla-Proposal writing, data collecting, data analysis and report writing Sisay Demeku- Editing and Guidance\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author, Dr. Tulu Tolla, upon reasonable request. Dr. Tulu can be reached at [email protected] or via phone at +251-911-907038.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbiye, T. (2018). Groundwater resource assessment and management in sub-Saharan Africa. Springer.\u003c/li\u003e\n\u003cli\u003eAddis Ababa Water and Sewerage Authority (AAWSA). (2023/2024). 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American Public Health Association, Washington, D.C.\u003c/li\u003e\n\u003cli\u003eWHO, 2011. Guidelines for Drinking-Water Quality, 4th Edition. World Health Organization, Geneva.\u003c/li\u003e\n\u003cli\u003eHa, S. K., Sinha, A. K., \u0026amp; Gupta, R., 2021, \u003cem\u003eJournal of Groundwater Science and Engineering\u003c/em\u003e, Vol. 9, Issue 2, pp. 120-130.\u003c/li\u003e\n\u003cli\u003eDragoni, W., 1998, Some considerations regarding the radius of influence of a pumping well, University of Perugia, Italy.\u003c/li\u003e\n\u003cli\u003eKyrieleis, W., Sichardt, W., 1930, Grundwasserabsenkung bei Fundierungsarbeiten, Springer, Berlin.\u003c/li\u003e\n\u003cli\u003eMyette, C., Olimpio, J., Johnson, D., 1987, Area of Influence and Zone of Contribution to Superfund Site Wells G \u0026amp; H Woburn, Massachusetts, U.S. Geological Survey.\u003c/li\u003e\n\u003cli\u003eHa, S. K., Sinha, A. K., \u0026amp; Gupta, R. (2021). Hydrological principles and groundwater extraction dynamics. \u003cem\u003eJournal of Groundwater Science and Engineering\u003c/em\u003e, 9(2), 120-130.\u003c/li\u003e\n\u003cli\u003eSinha, A. K., \u0026amp; Gupta, R. (2021). Groundwater flow and its interaction with nearby water sources. \u003cem\u003eJournal of Hydrological Studies\u003c/em\u003e, 11(4), 255-263.\u003c/li\u003e\n\u003cli\u003eGupta, R., Ha, S. K., \u0026amp; Sinha, A. K. (2021). Aquifer properties and their role in groundwater management. \u003cem\u003eJournal of Environmental Hydrology\u003c/em\u003e, 8(3), 98-107.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Groundwater, Sustainability, Private Wells, Water Quality, Urban Water Management, Addis Ababa","lastPublishedDoi":"10.21203/rs.3.rs-5753835/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5753835/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the role of private water wells in meeting the water demand, quality, and sustainability of groundwater resources in Addis Ababa, Ethiopia. As the city faces rapid urbanization and a rising population, private wells have emerged as a crucial supplementary water source, particularly in areas where public water supply is inadequate. However, challenges such as insufficient regulation, groundwater over-extraction, and contamination pose significant risks to the long-term viability of these wells. Data were gathered from 449 private wells, with a detailed water quality analysis conducted on 21 of them, focusing on parameters like turbidity, p\u003csup\u003eH\u003c/sup\u003e, nitrate, and fluoride levels. The findings indicate considerable variability in water quality; some wells exceeded safe limits for turbidity and nitrates, while others met acceptable standards for key indicators. Furthermore, groundwater extraction from private wells addresses only a small portion of the city's overall water demand. Compounding issues such as well interference, inefficient water usage, and declining water tables further complicate the situation. The study underscores the urgent need for enhanced regulation, integrated groundwater management, and active community participation to promote sustainable groundwater use. It also recommends strategies for improved well placement, ongoing water quality monitoring, and necessary infrastructural investments to alleviate the adverse effects associated with private well usage. This research offers important insights into urban water management dynamics and highlights the significance of private wells in supporting water supply in rapidly developing cities like Addis Ababa.\u003c/p\u003e","manuscriptTitle":"Analyzing Their Contribution to Water Demand, Quality, and Groundwater Sustainability of Private Water Wells in Addis Ababa, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-13 16:41:07","doi":"10.21203/rs.3.rs-5753835/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"526383a0-abac-480c-b133-53686dbb5da3","owner":[],"postedDate":"January 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-04T22:38:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-13 16:41:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5753835","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5753835","identity":"rs-5753835","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}