Assessment of surface water potential and irrigation water requirements for selected crops: the case of the Zenti River catchment, Omo Gibe River Basin, Ethiopia

Assessment of surface water potential and irrigation water requirements for selected crops: the case of the Zenti River catchment, Omo Gibe River Basin, 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 Research Article Assessment of surface water potential and irrigation water requirements for selected crops: the case of the Zenti River catchment, Omo Gibe River Basin, Ethiopia Diriba Worku, Abuye Boja, Adugna Fantu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4343320/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 Irrigation potential assessment has enormous use for smallholder farmers, who are largely dependent on subsistence farming systems. Due to rising agricultural production demands and the scarcity of irrigation water resources, assessing irrigation potential is very important for the planning, management, and irrigation development of an area. However, there were very limited studies available in the study area that indicated irrigation water potential, and crop water demand in the area. Therefore, the main objective of this study was to assess the surface water potential and irrigation water requirements for selected crops in the Zenti River catchment, Omo Gibe River Basin, Ethiopia. To achieve the objectives, hydro-meteorological data and physiographic characteristics were used. This was accomplished using the CROPWAT model, FDC2.1 software, and GIS-based tools. The CROPWAT models to estimate the amount of irrigation water needed for major crops growing in the area, as well as FDC 2.1, were used. The FDC 2.1 software result revealed that the overall long-term monthly minimum available stream flow of the Zenti River is 0.11m 3 /s. According to the CROPWAT model result, the seasonal net irrigation requirements for sugarcane, maize, cabbage, and onion (60% field efficiency) were 640.66mm, 260mm, 251.66mm, and 233.17mm, respectively. The result indicated that although the need for irrigation water varies depending on the season, the potential irrigation area of the River catchment is in the order of 0.1% of the watershed. The results from this study could enable decision-makers and smallholder farmers to further use surface water for irrigation purposes with a proper management system. Civil Engineering Irrigation potential surface water availability FDC CROPWAT Zenti River catchment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Irrigation is a continuous and reliable water supply to the different crops by artificial means in accordance with their different crop water needs, intended to permit farming in arid regions and to overcome the effect of drought in semi-arid regions [ 1 ]. When rainfall is inadequate to make up for the water lost through evapotranspiration, irrigation is necessary. Water application at the proper time and in the proper amount is the main goal of irrigation [ 2 ]. The definition of irrigation potential is not a simple one; it involves a series of assumptions about irrigation technologies, investment capacity, environmental aspects, particularly those relating to water sharing, and other important areas. According to [ 3 ], the physical irrigation potential is the area that can be irrigated depending on physical resources like soil and water, climatic conditions, and crop water requirements. Therefore, physical irrigation potential represents a combination of information on gross irrigation water requirements, and available water resources by basin [ 3 ] . Farming practices in Ethiopia are dominated by rain-fed agriculture, which could not cope with the extensive population increase and dwindling land resources. The rain-fed dependent agriculture, scarcity, and uneven distribution of rainfall, leading to famine and decreasing the economic development of Ethiopians, and exposed them to innumerable consequences [ 4 ]. The majority of Ethiopians lives in rural areas and depends on agriculture for their livelihoods. Yet agricultural production has not kept up with population growth, causing severe chronic malnutrition and hunger, as well as periodic drought-induced crises. In considering the current population growth rate and food insecurity, irrigation development is expected to play an important role in improving economic growth by increasing and stabilizing agricultural production and productivity in Ethiopia [ 5 ]. Today, the emphasis on small-scale irrigation is high at the national level, and almost all regions endeavor to improve agriculture through irrigation systems. Proper water resource management requires consideration of both supply and demand. The presence of land resources alone does not guarantee irrigation practice in an area[ 6 ]. Information on the minimum stream flow can be required to quantify the amount of water available for surface water irrigation during the dry monsoon period. Water resource availability must be assessed to determine whether irrigation developments can be carried out using different approaches. Base flow is an essential component of stream flow, which originates primarily from groundwater discharging into streams and delayed flow from surface water features. Base flow (BF), as defined by [ 7 ], is a component of stream flow that gradually enters a stream from saturated soil or groundwater storage and mostly contributes to stream flow during the dry season. Ethiopia is prosperous, with natural resources like land and water that help the socio-economic development of the country. Even though, Ethiopia has abundant land for irrigation, only a fraction of its potential is being utilized. Various studies [4;6] have indicated that the country has a large potential for arable land. However, less than 5% of this potential is irrigated, due to a lack of water storage facilities, a lack of comprehensive knowledge on the potential of land and water resources, and infrastructure systems (pumps, water conveyance structures, etc.). Water resources for sustainable usage may be impacted by the mismatch between supply and demand over both space and time. So combining the crop water requirement for irrigation demand, expressed in mm, and the available water resources, expressed in cubic meters per year, for assessing the irrigation potential, knowledge of the irrigation water requirements, expressed in m 3 /ha per year, is necessary. Assessing the water potential and crop water demand in the research area is crucial in order to address this rapidly deteriorating situation and guarantee the wise use of the water resources that are currently available. However, there were very limited studies conducted on the assessment of irrigation potential in Ethiopia, and none have been done in the study area that analyses potential water availability so that the local communities and decision makers can utilise them for water resource planning and management activities to develop irrigation projects in the study area. Due to this, the major users of the river are facing a challenge in allocating the available water. To ensure sustainable irrigation development, one has to know the limitations and suitability of the potential land for irrigation and the availability of water in the area. To this end, it becomes necessary to identify irrigation water potential and crop water requirements to evaluate the status of the irrigation potential of the Zenti River catchment in the Omo River Basin and propose reliable recommendations. Therefore, the current study aims to (i) assess the irrigation water availability of the river catchment considering low stream flow discharge using the Hydro Office package. (ii) Estimate the irrigation water requirement of major crops grown in the study area using CROPWAT and climate data, and (iii) evaluate a physically suitable irrigation potential area. 2. Description of the Study Area 2.1. Location and Topography The study was conducted in the Zenti River catchment, which is located in the Gofa zone of the southern nations. Gofa Zone is one of the zones in the southern nations, consisting of seven woredas and two towns administratively, and having a population of 1.5 million. The Zenti River catchment is located in the lower Omo-Gibe river basin, situated in southern Ethiopia along the central rift valley. The Zenti River Catchment is one of the small tributaries of the Omo Gibe River Basin. It is located about 468 kilometers south of Addis Ababa on an asphalt road from Addis Ababa to Butajira-Sodo-Sawla. Geographically, it is located approximately between 6˚8'N to 6˚40'N longitude and 36˚40'E to 37˚30'E latitude of the bounding coordinate system (Fig. 1 ). The study area lies within the altitude range of 656m to 2922m a.s.l. The spatial extent of the study watershed covers about 178,586.8ha 2.2. Climate and Hydrology The meteorological data of the study area shows that the average annual rainfall is 880mm; the monthly maximum temperature is between 25°C and 30.7°C, while the monthly minimum temperature is between 10.1°C and 19.7°C. Because of the diversified altitude and climatic conditions, the study area possesses diverse agro-climatic zones. The region is the boundary between semi-arid (kolla) and humid (dega) climates (Dega).The climate zone of the study area is humid in the highland areas of Bulki and Demba Gofa, Oyda, and Zala, which are categorized as sub-humid (woinadega) to semi-arid (kolla). The first zone, Dega, refers to cool temperatures with altitudes ranging between 2,300 and 3,300m. The second zone, Woinadega, is warm, wet and lies between 1500 and 2300m. The last Kolla has a warmer temperature than Woinadega and can be found in altitude ranges of 500–1500 m, such as the Rift Valley. The drainage system of the area consists of tributaries of the Zenti River, such as Magino, Zirko, Oshmi, and Hirpi, as the major tributaries. The mean monthly distributions of rainfall, effective rainfall, and evapotranspiration of the study area are presented in Fig. 2 below. 3. Materials and Methods 3.1. Preparation of Model Input Data and Analysis Meteorological data (rainfall, temperature, relative humidity, sunshine hours, radiation, and wind speed) were prepared using Excel as data input for CROPWAT 8.0 software to calculate the irrigation water requirement (IWR). Meteorological data from 1990–2010 was used to calculate irrigation water requirements. The climate datasets were taken from four meteorological stations in the river catchment: Lote, Morka, Sawla, and Bulki. Every calculation procedure in CROPWAT 8.0 is based on the FAO Irrigation and Drainage Study Guidelines[ 8 ]. The first monthly maximum and minimum temperature, relative humidity, sunshine hour, and wind speed data (1990–2010) was fitted in the CROPWAT model. Then, using the FAO Penman-Montieth equation, the model determined values for crop evapotranspiration. The CROPWAT software was used to predict the irrigation water requirements of selected crops [ 9 ]. Additionally, rainfall data were used to compute the dependable rainfall and river basin yield. After crop water requirements were estimated, daily stream flow data pertaining to the hydrology of the catchment was used to assess water availability for the irrigation water potential of the study area. Daily discharge data from the Zenti River catchment was prepared using Excel and then formatted to text format (*.txt). Then, the prepared data were imported to the Hydro Office for long-term generation of flow duration curves from the whole imported time series. The FDC 2.1 module serves to calculate and analyses flow duration curves for rivers. The base flow index (BFI) user manual was used for base flow separation processes [ 10 ]. The local minimum method of base flow separation in the Hydro Office software package was used. The low minimum method is one of the graphic approaches used to separate the base flow from the total stream flow. Following the separation of base flow, the base flow index (BFI) was generated by dividing base flow (calculated) by total flow (observed discharge) using BFI analysis. Finally, the river catchment was calibrated manually by using a range of parameters (mainly α) by trial and error on a yearly basis. The trail is stopped when the curve of base flow is closely fitted to the measured discharge for dry periods. 3.2. Computation of the Irrigation Water Demand and Potential Area The minimum area that can be irrigated with the available water supply (m 3 ) divided by the annual irrigation water demand (m 3 /ha) is known as the irrigation potential area [ 11 ]. The actual irrigation potential of the area was evaluated using the following formula for each perennial and some intermittent rivers in the watershed employing the equation provided by the authors in [ 11 ]. $$\text{P}\text{I}\text{A} \left(\text{h}\text{a}\right) =\frac{\text{I}\text{W}\text{S}}{\text{G}\text{I}\text{W}\text{D} }$$ 1 Where PIA is the Potential Irrigable Area (ha); IWS is the Irrigation Water Supply from the river during the irrigation period (m 3 ), and GIWD (m 3 /ha) is the gross irrigation water demand. The irrigation potential of a study area was obtained by comparing the irrigation requirements of the identified land suitable for irrigation system with the available mean monthly flows at a selected river diversion site. The amount of water needed for irrigation is calculated based on crop water needs. Maize, sugarcane, cabbage, and onions were identified as major crops in this particular study area. The FAO Irrigation and Drainage Paper "CROPWAT" computer program was used to compute the irrigation water requirements of these crops using the CROPWAT program using the formula given by the authors in [ 8 ]. $$ETc= Kc ETo$$ 2 Where Kc is the crop coefficients that will fluctuate over the growing period: early (initial), crop development, mid-season, and late seasons, and ETc is crop evapotranspiration in mm. Crop evapotranspiration (ETc) and effective rainfall (Peff) are used to compute the irrigation water demand. The crop coefficient of the dominant crops was taken from FAO guidelines. These calculations are based on the USDA Soil Conservation Service. The FAO CROPWAT 8.0 program [ 12 ] was used to determine the irrigation water requirements using rainfall, soil, crop, and climatic data as inputs. The crop's net irrigation water demand was then determined using the following formula: $$\text{N}\text{I}\text{W}\text{D}=\text{E}\text{T}\text{C} - \text{P}\text{e}\text{f}\text{f}$$ 3 In accordance with the FAO's guidance [ 13 ], the effective rainfall (Peff) was taken into account for the growth periods based on long-term monthly average rainfall (P) values. Effective rainfall is the part of rainfall that is effectively used by the crop after losses by surface runoff, evaporation, and deep percolation; only the plants to evaluate the crop’s water requirement can use the water retained in the root zone. $$\text{P}\text{e}\text{f}\text{f}=\frac{P\left(125-0.2P\right)}{125} for P\le 250mm$$ 4 $$\text{P}\text{e}\text{f}\text{f}=125+0.1\text{P} \text{f}\text{o}\text{r} \text{P}>250\text{m}\text{m}$$ By taking into account water lost during the application of water to the irrigation field, loss in the canal through seepage, and evaporation, the gross irrigation water demand of the crop has been estimated. Thus, irrigation efficiency was established to make up for this loss. For surface irrigation, the project efficiency ranges from 0.45 to 0.7, while for pressurized irrigation systems, it ranges from 0.7 to 0.9 [ 8 ]. For the purposes of this study, the average irrigation efficiency for surface, sprinkler, and drip irrigation systems was taken as 0.6, 0.75, and 0.85, respectively, in the Ethiopian benchmark of the irrigation systems using the formula given in [ 8 ]. $$\text{G}\text{I}\text{W}\text{D}=\frac{P\left(NIWD\right)}{ƞ}$$ 5 Where GIWD is gross irrigation water demand, NIRD is net irrigation water demand, and ƞ is irrigation application efficiency. 3.3. Assessment of Surface Water Availability and its Proximity The amount of water that could be consistently abstracted for irrigation was calculated using the stream flow of rivers. Using long-term river flow data, the flow duration curve was utilized to calculate the minimum amount of water used for irrigation purposes. Several authors have employed this technique [15 ;16 ; 17]. Low flow characteristics were examined using a flow duration curve (FDC) of the 90-percentile exceedance probability of available flow (Q90). To determine the quantity of flow available in the area, FDC analysis was used with hydrological data available from 1990 to 2010. The probability of occurrence is the ratio of the rank of the daily flows arranged in descending order divided by the total number of data multiplied by 100. It can be written as follows: $$\text{P}=\frac{M*100\%}{n}$$ 6 Where P is the probability that a given flow will be equaled or exceeded (% of time), M is the ranked position on the listing (dimensionless) and n is the number of observations for the period of record (dimensionless) in accordance with [ 18 ]. 3.4. Conceptual Framework To accomplish this study, several datasets were collected from different sources and examined for each factor. We employed the following general conceptual framework, as shown in Fig. 3 . 4. Results and Discussion 4.1. Assessment of Irrigation Water Requirements Indirectly, the amount of irrigable land depends on the crop's irrigation requirements. Crop evapotranspiration (ETc) and effective rainfall were computed using the CROPWAT 8.0 software, applying equations 2 and 4 , respectively, which are used to calculate the irrigation water requirement of crops. Eq. 6 was used to determine the monthly gross irrigation water requirements for maize, cabbage, sugarcane, and onion over their whole growth cycles. Freshly harvested crops like cabbage need the same amount of water during the late-season stage as they did during the mid-season stage. The crops are harvested fresh and thus need water up to the last moment. During the late season, dry-harvested crops such as maize were allowed to dry out. Thus, their water needs during the late-season stage are minimal. Of course, no irrigation is given to these crops during the late-season stage. 4.1.1. Scheme irrigation need The net irrigation requirement for the crops was calculated by adding the monthly irrigation requirements for every crop. Throughout the course of a year, the farmers could plant multiple types of crops simultaneously. For this reason, it is frequently required to determine the irrigation requirements for a multiple-cropping system. From the perspective of water-saving, drip irrigation system is more preferable than other systems for the study region, as indicated in Table 1 . One of the most common ways to use water efficiently in areas with limited water supplies is to apply modern irrigation techniques, such as drip irrigation, to boost irrigation efficiency. Eq. 5 was utilized to calculate the monthly gross irrigation requirements by applying surface, sprinkler, and drip irrigation methods for the four selected crops in the area. The CROPWAT 8.0 software result depicted that sugarcane, cabbage, maize, and onion have seasonal crop water requirements of 640.66mm, 251.66mm, 260 mm, and 233.17mm, respectively. Table 1 Estimated scheme irrigation needs of Crops (mm/month) Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Sugarcane 175.67 136 0 12 15 31.17 75.7 24 15.33 4 73.3 105.67 640.66 Cabbage 70.33 80.5 100.8 0 0 251.66 Maize 130.33 128 0 1.67 0 260.00 Onion 81.167 68.8 83.17 0 0 0 233.17 Monthly total irrigation water requirement by using surface irrigation system Total 457.49 413 184 12 15 31.17 75.7 24 15.33 4 75 105.67 1412.36 Monthly total irrigation water requirement by using sprinkler irrigation system Total 366.0 330.4 147.2 9.6 12.0 24.9 60.6 19.2 12.3 3.2 60.0 84.5 1129.9 Monthly total irrigation water requirement by using drip irrigation system Total 322.9 291.5 129.9 8.5 10.6 22.0 53.4 16.9 10.8 2.8 52.9 74.6 997.0 4.2. Assessment of Surface Water Availability for Irrigation and its Proximity In addition to estimating crop water requirements for irrigation potential, surface water availability was assessed based on the low flow potential of the river. Using FDC 2.1 software tool analysis, the low flow discharge (90-percentile flow) of rivers was generated, and the result was used to compute the possibly irrigable land from rivers. Low flow frequency analysis is a valuable practice for assessing the possibility of water availability in streams during critical dry seasons, which can be beneficial for the implementation of irrigation. The FDC 2.1 software tools result revealed that, the overall long-term monthly minimum available stream flow of the Zenti River is 0.11 m 3 /s(110L/s) and average minimum flow was 6.175m 3 /s. If you look at 90% exceedance, m3/s, which is the lowest flow rate recorded 0.11, so by definition, the flow in the river is at this flow rate or more for 90% of the time, such that discharge exceeds 19 out of 21 years of flows through the year. Due to the dry and windy climatic conditions and high evapotranspiration that occur in the region, low monthly water availability was found in January, February, December, and March, which are dry-season months; whereas the highest flow was obtained in May, August, and September, which are rainy-season months. The information in Table 2 depicts the overall monthly 90 percentile (Q-90) exceedance probability and monthly average stream flow of the river using Eq. 6 . Table 2 Average monthly stream flow and FDC analysis using 90% probabilities Months Jan Feb Mar Apr May Jun Average monthly(m 3 /s) 0.583 0.57 0.748 1.5 1.906 1.277 90% flow(m 3 /s) 0.66 0.27 0.256 0.274 0.594 0.387 Months Jul Aug Sep Oct Nov Dec Average monthly(m 3 /s) 1.543 2.5 2.38 2.525 1.635 0.554 90% flow(m 3 /s) 0.635 0.89 0.519 0.813 0.212 0.66 FDC long-term is used to generate the flow duration curves from completely imported time-series data, as indicated in Fig. 4 . Using the local minimum method of base flow computation, the base flow index (BFI) values of the river range from 0.16 to 1 and are consistent with the findings of other research [20;21]. The majority of river flow data is greater than 0.52, indicating quite considerable water resource potential in the study. A high index value of base flow would imply that the catchment has a more stable flow regime and is thus able to sustain river flow during extensive dry periods. The results revealed that the maximal BFI is greater for dry seasons than rainy seasons. The result shows that the river is strongly influenced by base flow contribution. The results were calibrated manually by trial and error. The trail is stopped when the curve of the calculated base flow (red curve) is closely fitted to the observed discharge (blue area color) for dry periods. Figure 5 show base flow separation result in the form of a hydrograph. After minimum river flow, availability was calculated using FDC 2.1, the straight-line (Euclidean) distance from the streams that is obtained from a 30m x 30m cell size DEM was calculated using a GIS tool. By reclassifying the river proximity map, suitable irrigable land that is near the water source (rivers) was identified. According to [ 22 ], the area closest to the stream was deemed to be the most suitable for irrigation development, and the area farther away was estimated to be marginally acceptable for irrigation purposes. The river proximity map depicted the riverbank land as highly suitable (S1), moderately suitable (S2), slightly suitable (S3), and currently not suitable (N). Figure 6 shows that land near rivers is highly suitable for irrigation up to a distance of 3km, moderately suitable up to a distance of 7km, marginally suitable up to a distance of 11km, and currently not suitable for a distance greater than 11km [ 17 ]. This is due to the cost of constructing a canal and the presence of more water loss as it is far from the irrigated area. Regarding the preparation of the land for irrigation as well as the operation and efficiency of irrigation, the elevation of the field is a significant factor on irrigation suitability. According to the FAO land suitability classification, land feature(elevation) of the study area(Fig. 7 ) were classified into S1, S2, S3 and N from the surface irrigation suitability perspective, i.e., from 656-1207m as highly suitable (S1), 1207-1525m as moderately suitable (S2), 1525-1934m as slightly suitable (S3) and 1934-2922mas not suitable (N). According to the suitability results, 34% of the land was extremely suitable, 35% was moderately acceptable, 24% was only slightly suitable, and 7% was not suitable for irrigation development. The recommended low land areas have a slope that is essentially within the acceptable range of slope classifications (less than 8%) for surface irrigation. The Fig. 7 provides an overview of the suitability of elevation of the study area for irrigation purposes across the entire catchment area 4.3. Evaluation of Physically Suitable Irrigation Potential Area According to FAO guideline criteria [ 13 ], physical surface irrigation potential was obtained by comparing irrigation water requirements on identified irrigable land with the minimum available stream flow on a monthly basis using the FDC 2.1 tool. A study found that the Zenti river has an average annual minimum surface water yield of 6.175m 3 /s and a total irrigation demand of 4.251m 3 /s. The average annual river flow is 17.72m 3 /s, indicating enough water to satisfy irrigation needs on an annual basis in the study area. However, it may not be adequate for daily, monthly, or seasonal requirements. Therefore, a small storage structure could help meet monthly irrigation demand during shortages. Low flow volume was divided by the net irrigation demand of crops dominantly grown in the research area (maize, onion, cabbage, and sugarcane) to obtain potentially irrigated land from rivers during the dry season. The minimum flow of any irrigation system should be sufficient to supply the area being irrigated with water at times of peak demand. From the total stream flow, 15% of the available stream flow in the catchment was released downstream for ecological purposes. The results of these analyses revealed that the monthly irrigation requirements are less than the available mean monthly flows of the Zenti River. The minimum available flow is 0.28m 3 /s in the month of February, whereas the water requirement in the month of February is 0.14m 3 /s/ha, giving a critical command area that can be reliably irrigated using the available flows in the Zenti River. In the study watershed, a total of 3016.75 hectares of physically irrigable land were identified while accounting for water availability using 90% of the FDC 2.1 analysis. However, the current irrigated area was found to be 1568.71ha of the land irrigated by surface water. The potential for surface irrigation might cover 52% of the arable land that constitutes the entire amount of irrigable land. Consequently, in times of scarcity, providing little storage building (dams, weir) might be able to supply the monthly irrigation need. Other strategic plans include encouraging the use of groundwater and water-saving irrigation technology, as drip irrigation may increase water supply. By doing this, it is possible to expand irrigation potential over the entire highly suitable region (i.e., 3016.75ha of irrigable land) present in the study area. Eq. 1 was used to determine the effective irrigable areas (ha) for each month, as indicated in Table 3 , based on the gross irrigation demand and the 90% available minimum monthly flow of the Zenti river basin. Table 3 Irrigation Demands, Minimum Available Flow and Irrigation Potential Months Available flow @90%(m 3 /s) Irrigation Demands(m 3/ s/ha) Irrigation potential(ha) Jan 0.66 0.045 128.6 Feb 0.28 0.14 123.12 Mar 0.256 0.5 78 Apr 0.274 0.22 125.5 May 0.594 0.33 89 Jun 0.387 0.25 141 Jul 0.635 1.68 138 Aug 0.885 0.53 136 Sep 0.519 0.34 153.3 Oct 0.813 0.09 162 Nov 0.212 0.057 146.2 Dec 0.66 0.087 148 Total 6.175 4.251 1568.71 Possible diversion site required for irrigation area was assessed based drop in head along the river and elevation of irrigable land using hydro resource of the spatial analysis tool according to the approach followed by [ 23 ]. Identifying potential diversion locations could offer an opportunity for irrigation expansion in the future. However, these diversion sites also need to be evaluated in light of the socioeconomic, geological, and other constraints on diversion systems. Figure 8 depicts the physically possible irrigable area and diversion site of the study area. 5. Conclusions The study was conducted to assess the irrigation potential of the Zenti River catchment, considering the estimated irrigation water requirements of four selected crops (onion, maize, cabbage, and sugarcane) and surface water (river in our case) potential. The flow regime analysis in this study was based on the interpretation of stream flow-duration curves and provides a generalized frequency analysis and potential impacts. Using the FDC 2.1 software tool, a 0.11 m 3 /s minimum river flow was obtained, which is useful in irrigation planning. This quantitative assessment of River flow regimes therefore provides a guideline for decision-makers and major stakeholders regarding new irrigation projects and the management of water resources. Another important factor in assessing irrigation potential is the determination of the crop water requirements of major crops grown in the area, which is done using CROPWAT 8.0 software. The CROPWAT 8.0 software result depicted that sugarcane, cabbage, maize, and onion have seasonal crop water requirements of 640.66mm, 251.66mm, 260 mm, and 233.17mm, respectively. Such information is needed for the sustainability of the new projects and the livelihoods of communities that rely on the subsistence farming system. The irrigation potential of the study area was estimated based on the available water and the gross irrigation water demand of selected crops. The findings indicate that in the dry season, there is just adequate water available to irrigate a fraction lower than 0.1% of the basin. However, enhancing irrigation efficiency is contingent upon selecting the appropriate irrigation method, as this decision significantly influences the utilization and management of the water resources in the Zenti River region, particularly in terms of irrigation. The implementation of irrigation projects may have repercussions on downstream environmental flow requirements and downstream water consumers, as the utilization of water for irrigation upstream could lead to a scarcity for downstream farmers. The research results indicated that while surface water resources have the potential to support small-scale irrigation projects, they may not suffice for the development of medium-scale irrigation projects. This may suggest that, in order to increase agricultural production within multi-cropping systems for the development of medium scale irrigation projects, we should look for additional water resource potential in addition to surface water sources. We advise looking for alternative water sources, such as groundwater sources, to expand the research area's irrigation potential. Therefore, to avoid more water losses in the irrigation field and to improve irrigation water efficiency, it is highly recommended to adopt sprinkler or drip irrigation methods. Therefore, future irrigation development and activity would exploit these updated resources, combined with the use of the Arc GIS tool, CROPWAT model, and the Hydro Office package, for a better assessment of the irrigation water requirements of crops, and water resources in the study area. Declarations Acknowledgements: We are grateful to the Arba Minch University Sawla Campus for providing financial support. The authors also thank the Ethiopian Ministry of Water, Irrigation, and Electricity for their help in providing the hydrological data, and the Ethiopian National Meteorological Agency for providing the weather data. Funding: Arba Minch University Sawla Campus supported the research with funding code of GOV/AMU/WRAM/CEAT/CE/62/14. Data Availability: Data pertaining to this study will be available from the corresponding author upon reasonable request. Declaration: All references and materials used in this work are acknowledged and cited properly in the text. Conflict of Interests: The authors declare that they have no financial or other conflicts of interest with this publication. Authors’ Contributions: Adugna Fantu wrote down concepts for broad study objectives. Diriba Worku and Abuye Boja gathered, examined, and analyzed the data. Diriba Worku carried out the methodology design and software modeling. The manuscript was drafted and edited by Abuye Boja. All authors reviewed and approved the final manuscript and contributed to the review of the literature. References Garg.k, “Irrigation Engineering &Hydraulic Structures.” p. 1726, 2005. G. Sela, “Irrigation scheduling using evapotranspiration data,” Cropaia , pp. 394–403, 2018. Available: https://cropaia.com/blog/irrigation-scheduling/ Food and agriculture organization of the United Nation, Systems at breaking point . 2022. S. B. Awulachew and M. Ayana, “Performance of irrigation: An assessment at different scales in ethiopia,” Exp. Agric. , vol. 47. S1, pp. 57–69, 2011, doi: 10.1017/S0014479710000955. Ministry of Water Resources and the National Meteorological Services Agency, “Initial National Communication of Ethiopia to the United Nations Framework Convention on Climate Change”. June, pp. 1–113, 2001. B. G. Gonfa, S. D. Hatiye, and M. M. Finssa, “Land suitability and surface water resources potential for irrigation in Becho Plain, upper Awash basin, Ethiopia,” Irrig. Drain. , vol. 70, no. 4, pp. 936–957, 2021, doi: 10.1002/ird.2575. M. Sophocleous, “Interactions between groundwater and surface water: The state of the science,” Hydrogeol. J. , vol. 10, no. 1, pp. 52–67, 2002, doi: 10.1007/s10040-001-0170-8. R. G. Allen, L. S. Pereira, D. Raes, and M. Smith, “FAO Irrigation and Drainage Paper No. 56 Evapotranspiration Crop (guidelines for computing crop water requirements),” no. 56, 2006. S. Soomro et al. , “Estimation of irrigation water requirement and irrigation scheduling for major crops using the CROPWAT model and climatic data,” Water Pract. Technol. , vol. 18, no. 3, pp. 685–700, 2023, doi: 10.2166/wpt.2023.024. B. M. Gregor, “FDC 2.1 User’s Manual,” pp. 1–20, 2010. O. T. L. and M. O. D. Meseret Dawit, Bilisummaa Dirriba Olika, Fiseha Behulu Muluneh, “Assessment of Surface Irrigation Potential of the Dhidhessa River Basin, Ethiopia,” Hydrol. Sci. J. , pp. 1–21, 2020. S. H. Ewaid, S. A. Abed, and N. Al-ansari, “Crop Water Requirements and Irrigation Schedules for Some Major Crops in Southern Iraq,” pp. 1–12, 2019, doi: 10.3390/w11040756. L. S. Pereira and I. Alves, “lrrigation and Drainage Paper 24; Guidelines for predicting crop water requirements.,” Encycl. Soils Environ. , vol. 4, pp. 322–334, 1977, doi: 10.1016/B0-12-348530-4/00255-1. B. Dar, “Sustainable Water Harvesting and Institutional Strengthening in Amhara ( SWHISA Project ),” vol. 251, 2011. G. Sintayehu, E. Temesgen, and D. Akili, “Assessment of Surface Irrigation Potential Availability Using Gis in Gilgel Abbay Catchment ; Ethiopia,” Res. Sq. , 2022, doi: DOI: https://doi.org/10.21203/rs.3.rs-1672968/v1 License: R. Kotei, W. Agyeiagyare, N. Kyei-baffour, T. Atta-, and E. Takyiatakora, “Estimation of Flow-Duration and Low-Flow Frequency Parameters for the Sumanpa Stream at Mampong- Ashanti in Ghana for the 1985-2009 Period,” pp. 62–75, 2009. Y. S. Getahun, A. Y. Gebremedhn, E. Lemma, F. Tesfay, and S. A. Tadesse, “Surface irrigation potential assessment of Chacha River Watershed, Jemma subbasin of upper Blue Nile, Ethiopia,” Front. Environ. Sci. , vol. 11. March, pp. 1–22, 2023, doi: 10.3389/fenvs.2023.1129716. S. G. Yalew, A. van Griensven, M. L. Mul, and P. van der Zaag, “Land suitability analysis for agriculture in the Abbay basin using remote sensing, GIS and AHP techniques,” Model. Earth Syst. Environ. , vol. 2, no. 2, pp. 1–14, 2016, doi: 10.1007/s40808-016-0167-x. T. F. Adamtie, D. T. Mitku, and A. Hassen, “Validations of CROPWAT Based Irrigation Practice for Tomato Productivity in Lowland Hot Humid Area of Ethiopia,” Am. J. Life Sci. Innov. , vol. 1, no. 1, pp. 27–35, 2022, doi: 10.54536/ajlsi.v1i1.426. I. Indarto, A. Ratnaningsih, and S. Wahyuningsih, “CALIBRATION OF SIX RECURSIVE DIGITAL FILTERS FOR,” vol. 12, no. 12, pp. 3772–3778, 2017. P. Ditthakit, S. Nakrod, N. Viriyanantavong, A. D. Tolche, and Q. B. Pham, “Estimating baseflow and baseflow index in ungauged basins using spatial interpolation techniques: A case study of the southern river basin of Thailand,” Water (Switzerland) , vol. 13, no. 21, 2021, doi: 10.3390/w13213113. A. W. Worqlul, A. S. Collick, D. G. Rossiter, S. Langan, and T. S. Steenhuis, “Catena Assessment of surface water irrigation potential in the Ethiopian highlands : The Lake Tana Basin,” vol. 129, pp. 76–85, 2015. M. K. Ayele, “GIS Based Assessment of Hydropower Potential ( A Case Study on Gumara River Basin ),” pp. 26–43, 2020. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4343320","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296787468,"identity":"6dc299f2-cc9a-4e15-a687-c01ecdf3d7c8","order_by":0,"name":"Diriba Worku","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYDCCw2AEBDwMjA8+/JCQA7EPPCBSC7PhzB4bY7CWBHxaDjAwMEO1sEnzsKUlNoA4+LTwHed9eLig5rCcec8ZAwkensPp88MOPwTaYien24Bdi+RhdoPDM44dNpY522NgIGFxOHfj7TQDoJZkY7MD2LUYHGZjOMzDdjtxBj+PQYIBD1DL7ASQlgOJ2/Bq+QfRciCB7XC64ez0D4S18LYBtfD2GDYcYEtLkJfOwW+LJEjLzL7/xhI8x4oZG3tsDDdI5xQcSDDA7Re+88eYPxd8S5OT4Ene/vvPDwl5+dnpmz98qLCTw6UFi1PBKg2IVQ4C8g2kqB4Fo2AUjIKRAAALQWUuBV9IdwAAAABJRU5ErkJggg==","orcid":"","institution":"Arba Minch University","correspondingAuthor":true,"prefix":"","firstName":"Diriba","middleName":"","lastName":"Worku","suffix":""},{"id":296789255,"identity":"bd8f6bf3-d998-49d5-9b51-e31ced663c24","order_by":1,"name":"Abuye Boja","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Abuye","middleName":"","lastName":"Boja","suffix":""},{"id":296789256,"identity":"a9d2229c-16fe-4473-b4b3-188d276fb5ed","order_by":2,"name":"Adugna Fantu","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Adugna","middleName":"","lastName":"Fantu","suffix":""}],"badges":[],"createdAt":"2024-04-29 13:50:41","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4343320/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4343320/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55817697,"identity":"aebdc670-945e-4832-a8eb-377859b9d10a","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":438329,"visible":true,"origin":"","legend":"\u003cp\u003eLocation Map of the Study Area\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/2ca990cd37c143b5354677bd.jpg"},{"id":55817693,"identity":"334170b3-3926-4efe-bbc9-1da0024326e0","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44296,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of the climatic parameters in the study area\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/a27a2c048f71e8d0c2c91204.png"},{"id":55817695,"identity":"e884caea-1c72-4fcb-8535-eba474a0139d","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":261102,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Framework Used for the Study\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/909a9f16451af527f9516c20.jpg"},{"id":55818360,"identity":"d4e77120-169f-4cbe-9aa5-55629c99afb6","added_by":"auto","created_at":"2024-05-03 20:58:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":58739,"visible":true,"origin":"","legend":"\u003cp\u003eFDC of the Zenti River from 1990 to 2010 stream flow data\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/10698b3b0266c092f5f35f0e.png"},{"id":55817694,"identity":"1c2e8de3-65db-40ea-859a-7625d4a3b00c","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":135728,"visible":true,"origin":"","legend":"\u003cp\u003eSeparated Base flow and stream flow data of Zenti River (1990-2010)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/cb973435abe4d780bfad8b7c.png"},{"id":55817698,"identity":"48547aaf-2636-4299-b165-d7ece00abf22","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":302503,"visible":true,"origin":"","legend":"\u003cp\u003eDistance from Water Source (River)\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/1e485bb061f2c6fae6d9e0be.jpg"},{"id":55817699,"identity":"0a889510-51a3-4142-8331-7e60b52d3b38","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":284450,"visible":true,"origin":"","legend":"\u003cp\u003eElevation Suitability Map of the Study Area\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/b127ba5f55e743533c38c417.jpg"},{"id":55817700,"identity":"5d6885d6-a222-471d-b495-17102275330a","added_by":"auto","created_at":"2024-05-03 20:50:26","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":286779,"visible":true,"origin":"","legend":"\u003cp\u003ePhysically Possible Irrigable Area and Diversion Site\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/9e0183aa79a0ebe5880d6c56.jpg"},{"id":55818649,"identity":"2a334cd5-6e2c-48eb-a425-8aacfd39b5ad","added_by":"auto","created_at":"2024-05-03 21:06:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1485696,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4343320/v1/c61ffe50-02a7-4f31-a898-4f7c2f3c99fa.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssessment of surface water potential and irrigation water requirements for selected crops: the case of the Zenti River catchment, Omo Gibe River Basin, Ethiopia\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":" \u003cp\u003eIrrigation is a continuous and reliable water supply to the different crops by artificial means in accordance with their different crop water needs, intended to permit farming in arid regions and to overcome the effect of drought in semi-arid regions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. When rainfall is inadequate to make up for the water lost through evapotranspiration, irrigation is necessary. Water application at the proper time and in the proper amount is the main goal of irrigation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The definition of irrigation potential is not a simple one; it involves a series of assumptions about irrigation technologies, investment capacity, environmental aspects, particularly those relating to water sharing, and other important areas. According to [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], the physical irrigation potential is the area that can be irrigated depending on physical resources like soil and water, climatic conditions, and crop water requirements. Therefore, physical irrigation potential represents a combination of information on gross irrigation water requirements, and available water resources by basin [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eFarming practices in Ethiopia are dominated by rain-fed agriculture, which could not cope with the extensive population increase and dwindling land resources. The rain-fed dependent agriculture, scarcity, and uneven distribution of rainfall, leading to famine and decreasing the economic development of Ethiopians, and exposed them to innumerable consequences [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The majority of Ethiopians lives in rural areas and depends on agriculture for their livelihoods. Yet agricultural production has not kept up with population growth, causing severe chronic malnutrition and hunger, as well as periodic drought-induced crises. In considering the current population growth rate and food insecurity, irrigation development is expected to play an important role in improving economic growth by increasing and stabilizing agricultural production and productivity in Ethiopia [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Today, the emphasis on small-scale irrigation is high at the national level, and almost all regions endeavor to improve agriculture through irrigation systems. Proper water resource management requires consideration of both supply and demand. The presence of land resources alone does not guarantee irrigation practice in an area[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Information on the minimum stream flow can be required to quantify the amount of water available for surface water irrigation during the dry monsoon period. Water resource availability must be assessed to determine whether irrigation developments can be carried out using different approaches. Base flow is an essential component of stream flow, which originates primarily from groundwater discharging into streams and delayed flow from surface water features. Base flow (BF), as defined by [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], is a component of stream flow that gradually enters a stream from saturated soil or groundwater storage and mostly contributes to stream flow during the dry season.\u003c/p\u003e \u003cp\u003eEthiopia is prosperous, with natural resources like land and water that help the socio-economic development of the country. Even though, Ethiopia has abundant land for irrigation, only a fraction of its potential is being utilized. Various studies [4;6] have indicated that the country has a large potential for arable land. However, less than 5% of this potential is irrigated, due to a lack of water storage facilities, a lack of comprehensive knowledge on the potential of land and water resources, and infrastructure systems (pumps, water conveyance structures, etc.). Water resources for sustainable usage may be impacted by the mismatch between supply and demand over both space and time. So combining the crop water requirement for irrigation demand, expressed in mm, and the available water resources, expressed in cubic meters per year, for assessing the irrigation potential, knowledge of the irrigation water requirements, expressed in m\u003csup\u003e3\u003c/sup\u003e/ha per year, is necessary. Assessing the water potential and crop water demand in the research area is crucial in order to address this rapidly deteriorating situation and guarantee the wise use of the water resources that are currently available. However, there were very limited studies conducted on the assessment of irrigation potential in Ethiopia, and none have been done in the study area that analyses potential water availability so that the local communities and decision makers can utilise them for water resource planning and management activities to develop irrigation projects in the study area. Due to this, the major users of the river are facing a challenge in allocating the available water. To ensure sustainable irrigation development, one has to know the limitations and suitability of the potential land for irrigation and the availability of water in the area. To this end, it becomes necessary to identify irrigation water potential and crop water requirements to evaluate the status of the irrigation potential of the Zenti River catchment in the Omo River Basin and propose reliable recommendations. Therefore, the current study aims to (i) assess the irrigation water availability of the river catchment considering low stream flow discharge using the Hydro Office package. (ii) Estimate the irrigation water requirement of major crops grown in the study area using CROPWAT and climate data, and (iii) evaluate a physically suitable irrigation potential area.\u003c/p\u003e"},{"header":"2. Description of the Study Area","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Location and Topography\u003c/h2\u003e \u003cp\u003eThe study was conducted in the Zenti River catchment, which is located in the Gofa zone of the southern nations. Gofa Zone is one of the zones in the southern nations, consisting of seven woredas and two towns administratively, and having a population of 1.5\u0026nbsp;million. The Zenti River catchment is located in the lower Omo-Gibe river basin, situated in southern Ethiopia along the central rift valley. The Zenti River Catchment is one of the small tributaries of the Omo Gibe River Basin. It is located about 468 kilometers south of Addis Ababa on an asphalt road from Addis Ababa to Butajira-Sodo-Sawla. Geographically, it is located approximately between 6˚8'N to 6˚40'N longitude and 36˚40'E to 37˚30'E latitude of the bounding coordinate system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The study area lies within the altitude range of 656m to 2922m a.s.l. The spatial extent of the study watershed covers about 178,586.8ha\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Climate and Hydrology\u003c/h2\u003e \u003cp\u003eThe meteorological data of the study area shows that the average annual rainfall is 880mm; the monthly maximum temperature is between 25\u0026deg;C and 30.7\u0026deg;C, while the monthly minimum temperature is between 10.1\u0026deg;C and 19.7\u0026deg;C. Because of the diversified altitude and climatic conditions, the study area possesses diverse agro-climatic zones. The region is the boundary between semi-arid (kolla) and humid (dega) climates (Dega).The climate zone of the study area is humid in the highland areas of Bulki and Demba Gofa, Oyda, and Zala, which are categorized as sub-humid (woinadega) to semi-arid (kolla). The first zone, Dega, refers to cool temperatures with altitudes ranging between 2,300 and 3,300m. The second zone, Woinadega, is warm, wet and lies between 1500 and 2300m. The last Kolla has a warmer temperature than Woinadega and can be found in altitude ranges of 500\u0026ndash;1500 m, such as the Rift Valley. The drainage system of the area consists of tributaries of the Zenti River, such as Magino, Zirko, Oshmi, and Hirpi, as the major tributaries. The mean monthly distributions of rainfall, effective rainfall, and evapotranspiration of the study area are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Materials and Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Preparation of Model Input Data and Analysis\u003c/h2\u003e \u003cp\u003eMeteorological data (rainfall, temperature, relative humidity, sunshine hours, radiation, and wind speed) were prepared using Excel as data input for CROPWAT 8.0 software to calculate the irrigation water requirement (IWR). Meteorological data from 1990\u0026ndash;2010 was used to calculate irrigation water requirements. The climate datasets were taken from four meteorological stations in the river catchment: Lote, Morka, Sawla, and Bulki. Every calculation procedure in CROPWAT 8.0 is based on the FAO Irrigation and Drainage Study Guidelines[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The first monthly maximum and minimum temperature, relative humidity, sunshine hour, and wind speed data (1990\u0026ndash;2010) was fitted in the CROPWAT model. Then, using the FAO Penman-Montieth equation, the model determined values for crop evapotranspiration. The CROPWAT software was used to predict the irrigation water requirements of selected crops [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, rainfall data were used to compute the dependable rainfall and river basin yield. After crop water requirements were estimated, daily stream flow data pertaining to the hydrology of the catchment was used to assess water availability for the irrigation water potential of the study area. Daily discharge data from the Zenti River catchment was prepared using Excel and then formatted to text format (*.txt). Then, the prepared data were imported to the Hydro Office for long-term generation of flow duration curves from the whole imported time series. The FDC 2.1 module serves to calculate and analyses flow duration curves for rivers. The base flow index (BFI) user manual was used for base flow separation processes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The local minimum method of base flow separation in the Hydro Office software package was used. The low minimum method is one of the graphic approaches used to separate the base flow from the total stream flow. Following the separation of base flow, the base flow index (BFI) was generated by dividing base flow (calculated) by total flow (observed discharge) using BFI analysis. Finally, the river catchment was calibrated manually by using a range of parameters (mainly α) by trial and error on a yearly basis. The trail is stopped when the curve of base flow is closely fitted to the measured discharge for dry periods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Computation of the Irrigation Water Demand and Potential Area\u003c/h2\u003e \u003cp\u003eThe minimum area that can be irrigated with the available water supply (m\u003csup\u003e3\u003c/sup\u003e) divided by the annual irrigation water demand (m\u003csup\u003e3\u003c/sup\u003e/ha) is known as the irrigation potential area [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The actual irrigation potential of the area was evaluated using the following formula for each perennial and some intermittent rivers in the watershed employing the equation provided by the authors in [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\text{P}\\text{I}\\text{A} \\left(\\text{h}\\text{a}\\right) =\\frac{\\text{I}\\text{W}\\text{S}}{\\text{G}\\text{I}\\text{W}\\text{D} }$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere PIA is the Potential Irrigable Area (ha); IWS is the Irrigation Water Supply from the river during the irrigation period (m\u003csup\u003e3\u003c/sup\u003e), and GIWD (m\u003csup\u003e3\u003c/sup\u003e/ha) is the gross irrigation water demand. The irrigation potential of a study area was obtained by comparing the irrigation requirements of the identified land suitable for irrigation system with the available mean monthly flows at a selected river diversion site. The amount of water needed for irrigation is calculated based on crop water needs. Maize, sugarcane, cabbage, and onions were identified as major crops in this particular study area. The FAO Irrigation and Drainage Paper \"CROPWAT\" computer program was used to compute the irrigation water requirements of these crops using the CROPWAT program using the formula given by the authors in [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$ETc= Kc ETo$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere Kc is the crop coefficients that will fluctuate over the growing period: early (initial), crop development, mid-season, and late seasons, and ETc is crop evapotranspiration in mm. Crop evapotranspiration (ETc) and effective rainfall (Peff) are used to compute the irrigation water demand. The crop coefficient of the dominant crops was taken from FAO guidelines. These calculations are based on the USDA Soil Conservation Service. The FAO CROPWAT 8.0 program [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] was used to determine the irrigation water requirements using rainfall, soil, crop, and climatic data as inputs. The crop's net irrigation water demand was then determined using the following formula:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\text{N}\\text{I}\\text{W}\\text{D}=\\text{E}\\text{T}\\text{C} - \\text{P}\\text{e}\\text{f}\\text{f}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn accordance with the FAO's guidance [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], the effective rainfall (Peff) was taken into account for the growth periods based on long-term monthly average rainfall (P) values. Effective rainfall is the part of rainfall that is effectively used by the crop after losses by surface runoff, evaporation, and deep percolation; only the plants to evaluate the crop\u0026rsquo;s water requirement can use the water retained in the root zone.\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\text{P}\\text{e}\\text{f}\\text{f}=\\frac{P\\left(125-0.2P\\right)}{125} for P\\le 250mm$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\text{P}\\text{e}\\text{f}\\text{f}=125+0.1\\text{P} \\text{f}\\text{o}\\text{r} \\text{P}\u0026gt;250\\text{m}\\text{m}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eBy taking into account water lost during the application of water to the irrigation field, loss in the canal through seepage, and evaporation, the gross irrigation water demand of the crop has been estimated. Thus, irrigation efficiency was established to make up for this loss. For surface irrigation, the project efficiency ranges from 0.45 to 0.7, while for pressurized irrigation systems, it ranges from 0.7 to 0.9 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. For the purposes of this study, the average irrigation efficiency for surface, sprinkler, and drip irrigation systems was taken as 0.6, 0.75, and 0.85, respectively, in the Ethiopian benchmark of the irrigation systems using the formula given in [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\text{G}\\text{I}\\text{W}\\text{D}=\\frac{P\\left(NIWD\\right)}{ƞ}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere GIWD is gross irrigation water demand, NIRD is net irrigation water demand, and ƞ is irrigation application efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Assessment of Surface Water Availability and its Proximity\u003c/h2\u003e \u003cp\u003eThe amount of water that could be consistently abstracted for irrigation was calculated using the stream flow of rivers. Using long-term river flow data, the flow duration curve was utilized to calculate the minimum amount of water used for irrigation purposes. Several authors have employed this technique [15 ;16 ; 17]. Low flow characteristics were examined using a flow duration curve (FDC) of the 90-percentile exceedance probability of available flow (Q90). To determine the quantity of flow available in the area, FDC analysis was used with hydrological data available from 1990 to 2010. The probability of occurrence is the ratio of the rank of the daily flows arranged in descending order divided by the total number of data multiplied by 100. It can be written as follows:\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\text{P}=\\frac{M*100\\%}{n}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere P is the probability that a given flow will be equaled or exceeded (% of time), M is the ranked position on the listing (dimensionless) and n is the number of observations for the period of record (dimensionless) in accordance with [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Conceptual Framework\u003c/h2\u003e \u003cp\u003eTo accomplish this study, several datasets were collected from different sources and examined for each factor. We employed the following general conceptual framework, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e4.1. Assessment of Irrigation Water Requirements\u003c/h2\u003e\n\u003cp\u003eIndirectly, the amount of irrigable land depends on the crop's irrigation requirements. Crop evapotranspiration (ETc) and effective rainfall were computed using the CROPWAT 8.0 software, applying equations \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, respectively, which are used to calculate the irrigation water requirement of crops. Eq.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e was used to determine the monthly gross irrigation water requirements for maize, cabbage, sugarcane, and onion over their whole growth cycles. Freshly harvested crops like cabbage need the same amount of water during the late-season stage as they did during the mid-season stage. The crops are harvested fresh and thus need water up to the last moment. During the late season, dry-harvested crops such as maize were allowed to dry out. Thus, their water needs during the late-season stage are minimal. Of course, no irrigation is given to these crops during the late-season stage.\u003c/p\u003e\n\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n\u003ch2\u003e4.1.1. Scheme irrigation need\u003c/h2\u003e\n\u003cp\u003eThe net irrigation requirement for the crops was calculated by adding the monthly irrigation requirements for every crop. Throughout the course of a year, the farmers could plant multiple types of crops simultaneously. For this reason, it is frequently required to determine the irrigation requirements for a multiple-cropping system. From the perspective of water-saving, drip irrigation system is more preferable than other systems for the study region, as indicated in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. One of the most common ways to use water efficiently in areas with limited water supplies is to apply modern irrigation techniques, such as drip irrigation, to boost irrigation efficiency. Eq.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e was utilized to calculate the monthly gross irrigation requirements by applying surface, sprinkler, and drip irrigation methods for the four selected crops in the area. The CROPWAT 8.0 software result depicted that sugarcane, cabbage, maize, and onion have seasonal crop water requirements of 640.66mm, 251.66mm, 260 mm, and 233.17mm, respectively.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eEstimated scheme irrigation needs of Crops (mm/month)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMonth\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eJan\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFeb\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMar\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eApr\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMay\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eJun\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eJul\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAug\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSep\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOct\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNov\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDec\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSugarcane\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e175.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e640.66\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCabbage\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e251.66\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaize\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e128\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e260.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOnion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81.167\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e83.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e233.17\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"14\" align=\"left\"\u003e\n\u003cp\u003eMonthly total irrigation water requirement by using surface irrigation system\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e457.49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e413\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e184\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1412.36\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"14\" align=\"left\"\u003e\n\u003cp\u003eMonthly total irrigation water requirement by using sprinkler irrigation system\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e366.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e330.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e147.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1129.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"14\" align=\"left\"\u003e\n\u003cp\u003eMonthly total irrigation water requirement by using drip irrigation system\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e322.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e291.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e129.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e52.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e74.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e997.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003e4.2. Assessment of Surface Water Availability for Irrigation and its Proximity\u003c/h2\u003e\n\u003cp\u003eIn addition to estimating crop water requirements for irrigation potential, surface water availability was assessed based on the low flow potential of the river. Using FDC 2.1 software tool analysis, the low flow discharge (90-percentile flow) of rivers was generated, and the result was used to compute the possibly irrigable land from rivers. Low flow frequency analysis is a valuable practice for assessing the possibility of water availability in streams during critical dry seasons, which can be beneficial for the implementation of irrigation. The FDC 2.1 software tools result revealed that, the overall long-term monthly minimum available stream flow of the Zenti River is 0.11 m\u003csup\u003e3\u003c/sup\u003e/s(110L/s) and average minimum flow was 6.175m\u003csup\u003e3\u003c/sup\u003e/s. If you look at 90% exceedance, m3/s, which is the lowest flow rate recorded 0.11, so by definition, the flow in the river is at this flow rate or more for 90% of the time, such that discharge exceeds 19 out of 21 years of flows through the year. Due to the dry and windy climatic conditions and high evapotranspiration that occur in the region, low monthly water availability was found in January, February, December, and March, which are dry-season months; whereas the highest flow was obtained in May, August, and September, which are rainy-season months. The information in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the overall monthly 90 percentile (Q-90) exceedance probability and monthly average stream flow of the river using Eq.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAverage monthly stream flow and FDC analysis using 90% probabilities\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMonths\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eJan\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFeb\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMar\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eApr\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMay\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eJun\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage monthly(m\u003csup\u003e3\u003c/sup\u003e/s)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.583\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.748\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.906\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.277\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e90% flow(m\u003csup\u003e3\u003c/sup\u003e/s)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.256\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.594\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.387\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMonths\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJul\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAug\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSep\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOct\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNov\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDec\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage monthly(m\u003csup\u003e3\u003c/sup\u003e/s)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.543\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.525\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.635\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.554\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e90% flow(m\u003csup\u003e3\u003c/sup\u003e/s)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.635\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.519\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.813\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.212\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFDC long-term is used to generate the flow duration curves from completely imported time-series data, as indicated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eUsing the local minimum method of base flow computation, the base flow index (BFI) values of the river range from 0.16 to 1 and are consistent with the findings of other research [20;21]. The majority of river flow data is greater than 0.52, indicating quite considerable water resource potential in the study. A high index value of base flow would imply that the catchment has a more stable flow regime and is thus able to sustain river flow during extensive dry periods. The results revealed that the maximal BFI is greater for dry seasons than rainy seasons. The result shows that the river is strongly influenced by base flow contribution. The results were calibrated manually by trial and error. The trail is stopped when the curve of the calculated base flow (red curve) is closely fitted to the observed discharge (blue area color) for dry periods. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e show base flow separation result in the form of a hydrograph.\u003c/p\u003e\n\u003cp\u003eAfter minimum river flow, availability was calculated using FDC 2.1, the straight-line (Euclidean) distance from the streams that is obtained from a 30m x 30m cell size DEM was calculated using a GIS tool. By reclassifying the river proximity map, suitable irrigable land that is near the water source (rivers) was identified. According to [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e], the area closest to the stream was deemed to be the most suitable for irrigation development, and the area farther away was estimated to be marginally acceptable for irrigation purposes. The river proximity map depicted the riverbank land as highly suitable (S1), moderately suitable (S2), slightly suitable (S3), and currently not suitable (N). Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e shows that land near rivers is highly suitable for irrigation up to a distance of 3km, moderately suitable up to a distance of 7km, marginally suitable up to a distance of 11km, and currently not suitable for a distance greater than 11km [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. This is due to the cost of constructing a canal and the presence of more water loss as it is far from the irrigated area.\u003c/p\u003e\n\u003cp\u003eRegarding the preparation of the land for irrigation as well as the operation and efficiency of irrigation, the elevation of the field is a significant factor on irrigation suitability. According to the FAO land suitability classification, land feature(elevation) of the study area(Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e) were classified into S1, S2, S3 and N from the surface irrigation suitability perspective, i.e., from 656-1207m as highly suitable (S1), 1207-1525m as moderately suitable (S2), 1525-1934m as slightly suitable (S3) and 1934-2922mas not suitable (N). According to the suitability results, 34% of the land was extremely suitable, 35% was moderately acceptable, 24% was only slightly suitable, and 7% was not suitable for irrigation development. The recommended low land areas have a slope that is essentially within the acceptable range of slope classifications (less than 8%) for surface irrigation. The Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e provides an overview of the suitability of elevation of the study area for irrigation purposes across the entire catchment area\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003e4.3. Evaluation of Physically Suitable Irrigation Potential Area\u003c/h2\u003e\n\u003cp\u003eAccording to FAO guideline criteria [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e], physical surface irrigation potential was obtained by comparing irrigation water requirements on identified irrigable land with the minimum available stream flow on a monthly basis using the FDC 2.1 tool. A study found that the Zenti river has an average annual minimum surface water yield of 6.175m\u003csup\u003e3\u003c/sup\u003e/s and a total irrigation demand of 4.251m\u003csup\u003e3\u003c/sup\u003e/s. The average annual river flow is 17.72m\u003csup\u003e3\u003c/sup\u003e/s, indicating enough water to satisfy irrigation needs on an annual basis in the study area. However, it may not be adequate for daily, monthly, or seasonal requirements. Therefore, a small storage structure could help meet monthly irrigation demand during shortages. Low flow volume was divided by the net irrigation demand of crops dominantly grown in the research area (maize, onion, cabbage, and sugarcane) to obtain potentially irrigated land from rivers during the dry season. The minimum flow of any irrigation system should be sufficient to supply the area being irrigated with water at times of peak demand. From the total stream flow, 15% of the available stream flow in the catchment was released downstream for ecological purposes. The results of these analyses revealed that the monthly irrigation requirements are less than the available mean monthly flows of the Zenti River. The minimum available flow is 0.28m\u003csup\u003e3\u003c/sup\u003e/s in the month of February, whereas the water requirement in the month of February is 0.14m\u003csup\u003e3\u003c/sup\u003e/s/ha, giving a critical command area that can be reliably irrigated using the available flows in the Zenti River. In the study watershed, a total of 3016.75 hectares of physically irrigable land were identified while accounting for water availability using 90% of the FDC 2.1 analysis. However, the current irrigated area was found to be 1568.71ha of the land irrigated by surface water. The potential for surface irrigation might cover 52% of the arable land that constitutes the entire amount of irrigable land. Consequently, in times of scarcity, providing little storage building (dams, weir) might be able to supply the monthly irrigation need. Other strategic plans include encouraging the use of groundwater and water-saving irrigation technology, as drip irrigation may increase water supply. By doing this, it is possible to expand irrigation potential over the entire highly suitable region (i.e., 3016.75ha of irrigable land) present in the study area. Eq.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e was used to determine the effective irrigable areas (ha) for each month, as indicated in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, based on the gross irrigation demand and the 90% available minimum monthly flow of the Zenti river basin.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eIrrigation Demands, Minimum Available Flow and Irrigation Potential\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMonths\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAvailable flow @90%(m\u003csup\u003e3\u003c/sup\u003e/s)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eIrrigation Demands(m\u003csup\u003e3/\u003c/sup\u003es/ha)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eIrrigation potential(ha)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.045\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e128.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFeb\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e123.12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMar\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.256\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApr\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e125.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMay\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.594\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e89\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJun\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.387\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e141\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJul\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.635\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e138\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAug\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.885\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSep\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.519\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e153.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOct\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.813\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e162\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNov\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.212\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e146.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDec\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.087\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e148\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.175\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.251\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1568.71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ePossible diversion site required for irrigation area was assessed based drop in head along the river and elevation of irrigable land using hydro resource of the spatial analysis tool according to the approach followed by [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. Identifying potential diversion locations could offer an opportunity for irrigation expansion in the future. However, these diversion sites also need to be evaluated in light of the socioeconomic, geological, and other constraints on diversion systems. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e depicts the physically possible irrigable area and diversion site of the study area.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe study was conducted to assess the irrigation potential of the Zenti River catchment, considering the estimated irrigation water requirements of four selected crops (onion, maize, cabbage, and sugarcane) and surface water (river in our case) potential. The flow regime analysis in this study was based on the interpretation of stream flow-duration curves and provides a generalized frequency analysis and potential impacts. Using the FDC 2.1 software tool, a 0.11 m\u003csup\u003e3\u003c/sup\u003e/s minimum river flow was obtained, which is useful in irrigation planning. This quantitative assessment of River flow regimes therefore provides a guideline for decision-makers and major stakeholders regarding new irrigation projects and the management of water resources. Another important factor in assessing irrigation potential is the determination of the crop water requirements of major crops grown in the area, which is done using CROPWAT 8.0 software. The CROPWAT 8.0 software result depicted that sugarcane, cabbage, maize, and onion have seasonal crop water requirements of 640.66mm, 251.66mm, 260 mm, and 233.17mm, respectively. Such information is needed for the sustainability of the new projects and the livelihoods of communities that rely on the subsistence farming system. The irrigation potential of the study area was estimated based on the available water and the gross irrigation water demand of selected crops. The findings indicate that in the dry season, there is just adequate water available to irrigate a fraction lower than 0.1% of the basin. However, enhancing irrigation efficiency is contingent upon selecting the appropriate irrigation method, as this decision significantly influences the utilization and management of the water resources in the Zenti River region, particularly in terms of irrigation. The implementation of irrigation projects may have repercussions on downstream environmental flow requirements and downstream water consumers, as the utilization of water for irrigation upstream could lead to a scarcity for downstream farmers. The research results indicated that while surface water resources have the potential to support small-scale irrigation projects, they may not suffice for the development of medium-scale irrigation projects. This may suggest that, in order to increase agricultural production within multi-cropping systems for the development of medium scale irrigation projects, we should look for additional water resource potential in addition to surface water sources. We advise looking for alternative water sources, such as groundwater sources, to expand the research area's irrigation potential. Therefore, to avoid more water losses in the irrigation field and to improve irrigation water efficiency, it is highly recommended to adopt sprinkler or drip irrigation methods. Therefore, future irrigation development and activity would exploit these updated resources, combined with the use of the Arc GIS tool, CROPWAT model, and the Hydro Office package, for a better assessment of the irrigation water requirements of crops, and water resources in the study area.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe are grateful to the Arba Minch University Sawla Campus for providing financial support. The authors also thank the Ethiopian Ministry of Water, Irrigation, and Electricity for their help in providing the hydrological data, and the Ethiopian National Meteorological Agency for providing the weather data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eArba Minch University Sawla Campus supported the research with funding code of GOV/AMU/WRAM/CEAT/CE/62/14.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eData pertaining to this study will be available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration:\u003c/strong\u003e All references and materials used in this work are acknowledged and cited properly in the text.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no financial or other conflicts of interest with this publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions:\u0026nbsp;\u003c/strong\u003eAdugna Fantu wrote down concepts for broad study objectives. Diriba Worku and Abuye Boja gathered, examined, and analyzed the data. Diriba Worku carried out the methodology design and software modeling. The manuscript was drafted and edited by Abuye Boja. All authors reviewed and approved the final manuscript and contributed to the review of the literature.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGarg.k, \u0026ldquo;Irrigation Engineering \u0026amp;Hydraulic Structures.\u0026rdquo; p. 1726, 2005.\u003c/li\u003e\n\u003cli\u003eG. Sela, \u0026ldquo;Irrigation scheduling using evapotranspiration data,\u0026rdquo; \u003cem\u003eCropaia\u003c/em\u003e, pp. 394\u0026ndash;403, 2018. Available: https://cropaia.com/blog/irrigation-scheduling/\u003c/li\u003e\n\u003cli\u003eFood and agriculture organization of the United Nation, \u003cem\u003eSystems at breaking point\u003c/em\u003e. 2022.\u003c/li\u003e\n\u003cli\u003eS. B. Awulachew and M. Ayana, \u0026ldquo;Performance of irrigation: An assessment at different scales in ethiopia,\u0026rdquo; \u003cem\u003eExp. Agric.\u003c/em\u003e, vol. 47. S1, pp. 57\u0026ndash;69, 2011, doi: 10.1017/S0014479710000955.\u003c/li\u003e\n\u003cli\u003eMinistry of Water Resources and the National Meteorological Services Agency, \u0026ldquo;Initial National Communication of Ethiopia to the United Nations Framework Convention on Climate Change\u0026rdquo;. June, pp. 1\u0026ndash;113, 2001.\u003c/li\u003e\n\u003cli\u003eB. G. Gonfa, S. D. Hatiye, and M. M. Finssa, \u0026ldquo;Land suitability and surface water resources potential for irrigation in Becho Plain, upper Awash basin, Ethiopia,\u0026rdquo; \u003cem\u003eIrrig. Drain.\u003c/em\u003e, vol. 70, no. 4, pp. 936\u0026ndash;957, 2021, doi: 10.1002/ird.2575.\u003c/li\u003e\n\u003cli\u003eM. Sophocleous, \u0026ldquo;Interactions between groundwater and surface water: The state of the science,\u0026rdquo; \u003cem\u003eHydrogeol. J.\u003c/em\u003e, vol. 10, no. 1, pp. 52\u0026ndash;67, 2002, doi: 10.1007/s10040-001-0170-8.\u003c/li\u003e\n\u003cli\u003eR. G. Allen, L. S. Pereira, D. Raes, and M. Smith, \u0026ldquo;FAO Irrigation and Drainage Paper No. 56 Evapotranspiration Crop (guidelines for computing crop water requirements),\u0026rdquo; no. 56, 2006.\u003c/li\u003e\n\u003cli\u003eS. Soomro \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Estimation of irrigation water requirement and irrigation scheduling for major crops using the CROPWAT model and climatic data,\u0026rdquo; \u003cem\u003eWater Pract. Technol.\u003c/em\u003e, vol. 18, no. 3, pp. 685\u0026ndash;700, 2023, doi: 10.2166/wpt.2023.024.\u003c/li\u003e\n\u003cli\u003eB. M. Gregor, \u0026ldquo;FDC 2.1 User\u0026rsquo;s Manual,\u0026rdquo; pp. 1\u0026ndash;20, 2010.\u003c/li\u003e\n\u003cli\u003eO. T. L. and M. O. D. Meseret Dawit, Bilisummaa Dirriba Olika, Fiseha Behulu Muluneh, \u0026ldquo;Assessment of Surface Irrigation Potential of the Dhidhessa River Basin, Ethiopia,\u0026rdquo; \u003cem\u003eHydrol. Sci. J.\u003c/em\u003e, pp. 1\u0026ndash;21, 2020.\u003c/li\u003e\n\u003cli\u003eS. H. Ewaid, S. A. Abed, and N. Al-ansari, \u0026ldquo;Crop Water Requirements and Irrigation Schedules for Some Major Crops in Southern Iraq,\u0026rdquo; pp. 1\u0026ndash;12, 2019, doi: 10.3390/w11040756.\u003c/li\u003e\n\u003cli\u003eL. S. Pereira and I. Alves, \u0026ldquo;lrrigation and Drainage Paper 24; Guidelines for predicting crop water requirements.,\u0026rdquo; \u003cem\u003eEncycl. Soils Environ.\u003c/em\u003e, vol. 4, pp. 322\u0026ndash;334, 1977, doi: 10.1016/B0-12-348530-4/00255-1.\u003c/li\u003e\n\u003cli\u003eB. Dar, \u0026ldquo;Sustainable Water Harvesting and Institutional Strengthening in Amhara ( SWHISA Project ),\u0026rdquo; vol. 251, 2011.\u003c/li\u003e\n\u003cli\u003eG. Sintayehu, E. Temesgen, and D. Akili, \u0026ldquo;Assessment of Surface Irrigation Potential Availability Using Gis in Gilgel Abbay Catchment ; Ethiopia,\u0026rdquo; \u003cem\u003eRes. Sq.\u003c/em\u003e, 2022, doi: DOI: https://doi.org/10.21203/rs.3.rs-1672968/v1 License:\u003c/li\u003e\n\u003cli\u003eR. Kotei, W. Agyeiagyare, N. Kyei-baffour, T. Atta-, and E. Takyiatakora, \u0026ldquo;Estimation of Flow-Duration and Low-Flow Frequency Parameters for the Sumanpa Stream at Mampong- Ashanti in Ghana for the 1985-2009 Period,\u0026rdquo; pp. 62\u0026ndash;75, 2009.\u003c/li\u003e\n\u003cli\u003eY. S. Getahun, A. Y. Gebremedhn, E. Lemma, F. Tesfay, and S. A. Tadesse, \u0026ldquo;Surface irrigation potential assessment of Chacha River Watershed, Jemma subbasin of upper Blue Nile, Ethiopia,\u0026rdquo; \u003cem\u003eFront. Environ. Sci.\u003c/em\u003e, vol. 11. March, pp. 1\u0026ndash;22, 2023, doi: 10.3389/fenvs.2023.1129716.\u003c/li\u003e\n\u003cli\u003eS. G. Yalew, A. van Griensven, M. L. Mul, and P. van der Zaag, \u0026ldquo;Land suitability analysis for agriculture in the Abbay basin using remote sensing, GIS and AHP techniques,\u0026rdquo; \u003cem\u003eModel. Earth Syst. Environ.\u003c/em\u003e, vol. 2, no. 2, pp. 1\u0026ndash;14, 2016, doi: 10.1007/s40808-016-0167-x.\u003c/li\u003e\n\u003cli\u003eT. F. Adamtie, D. T. Mitku, and A. Hassen, \u0026ldquo;Validations of CROPWAT Based Irrigation Practice for Tomato Productivity in Lowland Hot Humid Area of Ethiopia,\u0026rdquo; \u003cem\u003eAm. J. Life Sci. Innov.\u003c/em\u003e, vol. 1, no. 1, pp. 27\u0026ndash;35, 2022, doi: 10.54536/ajlsi.v1i1.426.\u003c/li\u003e\n\u003cli\u003eI. Indarto, A. Ratnaningsih, and S. Wahyuningsih, \u0026ldquo;CALIBRATION OF SIX RECURSIVE DIGITAL FILTERS FOR,\u0026rdquo; vol. 12, no. 12, pp. 3772\u0026ndash;3778, 2017.\u003c/li\u003e\n\u003cli\u003eP. Ditthakit, S. Nakrod, N. Viriyanantavong, A. D. Tolche, and Q. B. Pham, \u0026ldquo;Estimating baseflow and baseflow index in ungauged basins using spatial interpolation techniques: A case study of the southern river basin of Thailand,\u0026rdquo; \u003cem\u003eWater (Switzerland)\u003c/em\u003e, vol. 13, no. 21, 2021, doi: 10.3390/w13213113.\u003c/li\u003e\n\u003cli\u003eA. W. Worqlul, A. S. Collick, D. G. Rossiter, S. Langan, and T. S. Steenhuis, \u0026ldquo;Catena Assessment of surface water irrigation potential in the Ethiopian highlands : The Lake Tana Basin,\u0026rdquo; vol. 129, pp. 76\u0026ndash;85, 2015.\u003c/li\u003e\n\u003cli\u003eM. K. Ayele, \u0026ldquo;GIS Based Assessment of Hydropower Potential ( A Case Study on Gumara River Basin ),\u0026rdquo; pp. 26\u0026ndash;43, 2020.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Arba Minch University","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":"Irrigation potential, surface water availability, FDC, CROPWAT, Zenti River catchment","lastPublishedDoi":"10.21203/rs.3.rs-4343320/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4343320/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIrrigation potential assessment has enormous use for smallholder farmers, who are largely dependent on subsistence farming systems. Due to rising agricultural production demands and the scarcity of irrigation water resources, assessing irrigation potential is very important for the planning, management, and irrigation development of an area. However, there were very limited studies available in the study area that indicated irrigation water potential, and crop water demand in the area. Therefore, the main objective of this study was to assess the surface water potential and irrigation water requirements for selected crops in the Zenti River catchment, Omo Gibe River Basin, Ethiopia. To achieve the objectives, hydro-meteorological data and physiographic characteristics were used. This was accomplished using the CROPWAT model, FDC2.1 software, and GIS-based tools. The CROPWAT models to estimate the amount of irrigation water needed for major crops growing in the area, as well as FDC 2.1, were used. The FDC 2.1 software result revealed that the overall long-term monthly minimum available stream flow of the Zenti River is 0.11m\u003csup\u003e3\u003c/sup\u003e/s. According to the CROPWAT model result, the seasonal net irrigation requirements for sugarcane, maize, cabbage, and onion (60% field efficiency) were 640.66mm, 260mm, 251.66mm, and 233.17mm, respectively. The result indicated that although the need for irrigation water varies depending on the season, the potential irrigation area of the River catchment is in the order of 0.1% of the watershed. The results from this study could enable decision-makers and smallholder farmers to further use surface water for irrigation purposes with a proper management system.\u003c/p\u003e","manuscriptTitle":"Assessment of surface water potential and irrigation water requirements for selected crops: the case of the Zenti River catchment, Omo Gibe River Basin, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-03 20:50:21","doi":"10.21203/rs.3.rs-4343320/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":"bf9f03c3-2a01-4331-a086-a4e411d2b5ce","owner":[],"postedDate":"May 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":31303436,"name":"Civil Engineering"}],"tags":[],"updatedAt":"2024-05-03T20:50:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-03 20:50:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4343320","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4343320","identity":"rs-4343320","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}