From Rainwater Harvesting to Groundwater Exploitation: Understanding theChanging Role of Farm Ponds and their Socio-economic Consequences in Maharashtra's Semi-Arid Region, India.

From Rainwater Harvesting to Groundwater Exploitation: Understanding theChanging Role of Farm Ponds and their Socio-economic Consequences in Maharashtra's Semi-Arid Region, India. | 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 From Rainwater Harvesting to Groundwater Exploitation: Understanding theChanging Role of Farm Ponds and their Socio-economic Consequences in Maharashtra's Semi-Arid Region, India. Taufique Warsi, Sarita Chemburkar, Ankita Yadav, Faraz Rupani, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3933040/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 Groundwater plays a critical role in providing irrigation and drinking water in the drought-prone semi-arid region of Maharashtra, India. To address water scarcity, the government has promoted the construction of Farm Ponds (FPs) as a strategy to secure rural agrarian livelihoods and drought-proof the area. However, FPs, originally designed for rainwater harvesting, have now become commonly used as groundwater storage tanks, leading to overexploitation of groundwater by a few affluent farmers. This creates inequity in access to water by making it private and increases the vulnerability of other user communities. In this study, a systematic hydrogeological assessment was conducted, analysing 68 functional FPs constructed between 2009 and 2016 in six groundwater-vulnerable villages. The assessment focused on using Electrical Conductivity (EC) and Total Dissolved Solids (TDS) as parameters to delineate the zone of influence created by the feeding wells of FPs. Furthermore, the study utilized the Groundwater Survey and Development Agency’s (GSDA) recharge priority zone map to examine the distribution of lined FPs and identify areas where these ponds hinder recharge in high and moderate priority recharge zones and their socio-economic impacts on farmers were evaluated. The findings provide valuable insights into the relationship between the Zone of Influence and its socio-economic impacts on farmers, offering a comprehensive understanding of the distribution, practices, and ill effects of farm ponds. Farm pond Zone of Influence (ZoI) Rainfed Socio-Economics Maharashtra India Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Groundwater, a critical resource, assumes a key role in sustaining livelihoods and meeting water demands in the drought-prone semi-arid region of Maharashtra, India (Foster et al. 2007 ; Khare et al.2020). In this region, erratic rainfall patterns poses water scarcity challenges, where groundwater serves as a lifeline, providing irrigation for agriculture and potable water for rural communities (Kale and Kulkarni 2022 ). The imbalance between water supply and demand in this arid landscape has prompted the government to implement various strategies aimed to address water shortages and ensuring the welfare of agrarian communities (Kerr 2002 ; Kumar et al. 2018 ; Bhadbhade et al. 2019 ). Since 1970, Government of India (GoI) initiated different programs to assure the water security in the drought prone regions of India, the program includes Drought Prone Area Program (DPAP) and the Desert Development Program (DDP) (Kerr 2002 ; Kumar et al. 2018 ). These Government programs invest huge capital (253 million dollar) to support the initiatives of soil water conservation, water resource development, afforestation, and pasture development (MoRD 1994). However, these programs failed to address the water scarcity problem due to improper planning and incomplete implementation (MoRD 1994: 11). The ‘National Water Policy’ that was launched in 1987 was subsequently revised in the year 2002 and 2012. Moreover, it is likely to be revised in near future (Kale et al. 2022 ). Afterwards, various water related schemes on groundwater were launched by state and central government which is being implemented in block/Taluka. The main central schemes are PMKSY, Atal Solar Schemes, and MGNREGA whereas state sponsored schemes are PoCRA, CM-Solar schemes, Dr. Babasaheb Ambedkar Krushi Yojna, Birsa Munda Yojna, and FP on demand (Magel Tyala Shet Tale) brought all the attention in order to cope with the current water crisis (Abhay 2016 ; GSDA 2020). Among all the schemes, the promotion of FPs has emerged as a key element in the government's arsenal to address water scarcity and depicted as a miracle strategy by the Republic and Central authority, which later on popularized by the media (Kale 2017 and Khan 2023 ). However, the accountable body did not notice how the construction of FP is being implemented on the ground during all this running. The requirements for constructing a FPs are-a dug out structure with a definite size and shape which collects rainfall water, one inlet and outlet to arrest the surface runoff from the farm area, and lastly must be built in a low lying area. A FP can be classified into four types depending on its location and water source; 1). Excavated or Dug out ponds 2). Surface ponds 3). Spring or creek fed ponds and 4). Off stream storage ponds (Reddy et al. 2012 ). Initially conceived as tools for rainwater harvesting, FPs have gained widespread adoption and are now commonly used as groundwater storage tanks. These structures, designed to capture rainwater during monsoon seasons, have undergone a significant transformation, taking on new roles as reservoirs for groundwater drawn from the depths of the Earth (Kale 2017 ; Shivakumarappa et al. 2023 ). This shift in purpose, while addressing immediate water needs, has given rise to unintended consequences that reverberate through the social and hydrogeological fabric of the region (Kale et al. 2022 ). One of the most concerning outcomes of this transformation is the overexploitation of groundwater, a situation primarily driven by a selected group of affluent farmers who have harnessed FPs to secure a private source of water. It creates an obvious inequity in water access, as only a privileged few reap the benefits of privately stored groundwater, while other, less fortunate user communities face increased vulnerability due to a dwindling supply of this vital resource. The study delves into this complex issue by conducting a comprehensive assessment in the Ahmednagar district of Maharashtra. Focusing on six groundwater-vulnerable villages in the region, this research scrutinized 68 functional FPs constructed between 2009 and 2016. The investigation embraced a multi-faceted approach, combining systematic household surveys and a hydrogeological assessment, which collectively aimed to shed light on the different dimensions of the issue at hand. In order to understand the subsurface flow and aquifer connectivity, tracer techniques are very potential tool to decipher the subsurface information (Davis et al. 1980 ; Maurice et al. 2011 ; Warsi et al. 2020 ). However, most of the conventional tracers have some limitations and some of them are costly. To trace the extent of influence applied by FP’s pumping well on the surrounding hydrogeological system, the study uses insitu parameters such as Electrical Conductivity (EC) and Total Dissolved Solids (TDS) (Rusydi 2018 ; Jaworska-Szulc 2016 ; Tritschler et al. 2020 ). These indicators were utilized to delineate the "Zone of Influence," an area encompassing the reach of feeding wells associated with FPs. Within this Zone of Influence, the study required to decipher the socio-economic impacts on farmers residing in close proximity to these water storage structures. Additionally, the study took into account the broader implications of FP distribution on groundwater recharge zones. By referencing the Groundwater Survey and Development Agency's (GSDA) recharge priority zone map, we assessed the presence of lined FPs in high and moderate priority recharge zones. This examination aimed to identify areas where farm ponds may inadvertently hinder groundwater recharge, thus intensifying the region's water-related challenges. The findings of this study imparts invaluable insights into the complex relationship between the Zone of Influence created by feeding well of FPs and their socio-economic consequences on local farmers. Moreover, the research will provide a broad understanding of the distribution, operational practices, and detrimental effects associated with the adoption of farm ponds in this region. By considering these aspects, this study contributes to a broader understanding of the evolving dynamics of water resource management in drought-prone regions and recommending important highlights of sustainable and equitable water use to ensure the well-being of rural communities. Study Area The study was conducted in 6 villages of the Sangamner block of Ahmednagar district, which lies between longitudes 74 0 02’ 30’’ and 74 0 16’ 30’’ and between latitudes 19 0 15’ 30’’ and 19 0 26’ 0’’ (Fig. 1 ). It covers a total geographical area of 166530 Ha, which contains 170 Gram Panchayat, 02 towns, and 170 villages. The area experiences uneven rainfall distribution between 484 mm to 879 mm (CGWB 2014). The region's climate is defined by scorching summers and mostly dry weather all year round. These villages were chosen through hydrological investigations based on an assessment of their groundwater vulnerability. Geologically, the region is mostly covered by Simple and Compound Deccan basalt flow, with significant water-bearing formations in the form of Amygdaloidal Basalt, Fractured and Jointed Basalt, and Zeolitic Vesicular Basalt (GSDA 2020). The two main river basins are the Godavari and Pravra subbasins, and black cotton soil is the most common type of soil. The six villages included in the study are Karjule Pathar, Bhojdari, Wankute, Dolasane, Gunjalwadi, and Jawalebaleshwar of the Sangamner block in the Ahmednagar district's "rain shadow zone." Many of the FPs in these villages have been turned into surface storage tanks. Various groundwater sources supplied water to the FPs, three different kinds of water sources exist: surface water, groundwater, and a combination of the two. According to reports, the Sangamner Block's groundwater resources are in a "semi-critical condition" as a result of industrial water demand and agricultural techniques. FPs in communities classified as very vulnerable to groundwater (Sangamner Block) are supplied with water from recently drilled dug wells and boreholes, the quantity of which is expected to rise in the near future. Methodology The data collection process followed a cluster random sampling method in two steps. The entire population was divided into two groups: FP owners and non-farm pond owners, as outlined by Acharya in 2013. For non-farm pond owners, a household-level questionnaire survey was conducted. The study also involved technical analysis of hydrological data, incorporating insights from the FP study by Bendapudi et al. in 2020. To identify the zone of influence, a technical method was employed using INSITU water quality parameters of pumping and surrounding well with having household-level data from 61 farmers who owned 68 FPs as baseline information. The population of non-FP owners was determined based on the ratio with each pumping well used for filling FPs by farm pond owners. For instance, for each source well of a FP, there could be 2 to 3 or even more drawdown wells of neighboring farmers who do not own FPs. In-situ parameter testing: An insitu parameter is a potential tool to understand the local hydrological boundaries and surface water groundwater interaction on the basis of EC, Ph, TDS, and Salinity (Huizar-Alvarez et al. 2004; Rusydi, 2018; Jaworska‐Szulc 2016; Tritschler et al. 2020). In the study area multiple bore wells/dug wells were selected in the surrounding and downstream side of the FP feeding well (Fig. 2). In order to determine the hydrological boundaries, the distance of downstream wells were measured from the pumping well which feeds the FPs. Subsequently, measured quality parameters were plotted against the borewell distance to understand the zone of influence with the help of a breakthrough curve. Since the pumping well is extracting maximum amount of water with the maximum duration of pumping, so the dilution of solids will be more near the well due to fresh water influx from the surrounding area and as we move away from the pumping well, the rate of dilution will be reduced and a linear pattern will emerge under the same zone of influence. However, a break can be observed when there will be a discontinuity in the aquifer or the extent of pumping influence ends. The selection of well and conceptual design is given in the Fig. 2. Impact of lined farm ponds on recharge: Groundwater Survey and Development Agency (GSDA) has done extensive work in Maharashtra for groundwater exploration and development. GSDA generated groundwater recharge priority map for identifying the artificial recharge zones on the basis of priorities and then the map was categorized into four sections, viz; High priority, moderate priority, low priority, and limited scope recharge zone (GSDA, 2020). The idea behind taking this recharge zone map was to understand the distribution of lined farm ponds and to understand the occupation of each recharge zone map by the FPs. Since the FPs are lined with impervious layers, it blocks the water from infiltration. Which in turn hampers the recharge rate in the respective zones. In order to have a primary understanding of consequences, the total area was calculated which is being blocked by lined FPs. Results and Discussion Physical survey: All 188 farmers who constructed FPs till July 2017 from the six study villages were interviewed using a structured questionnaire. These 188 farmers reported a total of 206 FPs wherein 18 farmers own more than one FP. The information and data set collected from the respondents mainly include the detailed cost of cultivation and production, irrigation using FPs, other sources of irrigation, the dimension of the FPs, investment costs occurred on constructing FP and plastic lining. The information also includes the perceptions of FP owners regarding the use and benefits received. However, 68 working (in use with lining) FPs were identified which belong to 61 owners to proceed with the in-depth hydrogeological analysis which eventually deciphered the subsurface condition by demarcating the zone of influence. All the 68 FP then broadly categorized into three groups on the basis of land holding capacity and the size of FPs (Table 1). Table 1: Classification of Farm pond sizes and Land holding of farm pond owning farmers under study Household category Large land holders Medium land holders Small land holders TOTAL farm ponds (4.1 to 15.4 ha) (2.1 - 4 ha) (0.4 to 2 ha) Large Farm pond >10000 m³ 10 7 6 23 Medium Farm pond 1100 to 10000 m³ 7 9 18 34 Small Farm pond 64 to 1000m³ 0 3 8 11 TOTAL 17 19 32 68 According to the above table, FP owners are classified as per the size of their ponds and their land holdings. Based on the size of a FP, there are three different types: large, medium, and small. The number of large ponds is 23, while the number of medium ponds and small ponds is 23 and 34, respectively. Table 2: Different water source used to fill the farm ponds Farm pond category Farm ponds (No.) Total volume (m³) Dug wells Bore wells Streams Large farm ponds: (10000 - 47572 m³) 23 4,47,935 13 16 3 Medium farm ponds (1000 - 10000 m³) 34 1,35,494 14 15 4 Small farm ponds (64 to 1000 m³) 11 6,148 12 9 1 As shown in the above table, there are three categories: large, medium, and small. It consists of 23 large ponds, 34 medium ponds, and 11 small ponds (Table 2). To fill the FPs, there are 87 water sources, such as dug wells, bore wells, and streams. The Nexus of Water Sources in Current Farm pond practices Scenario1: Using groundwater from dug wells to fill FPs, such as those in Wankute/Jawlebaleshwar, is a common practice. This includes FPs supplied by various groundwater sources like dug wells, bore wells, and horizontal wells (Fig. 3A & 3B). However, the excessive pumping of groundwater has led to a depletion of aquifers. Furthermore, storing pumped water in lined FPs contributes to evaporation losses, particularly during the peak summer months. Concerns arise due to a significant increase in the number of FPs in recent years, with projections indicating a substantial further increase in the near future. This trend exacerbates the challenges associated with groundwater depletion, evaporation losses, and inequitable distribution among farmers. Scenario 2: Utilizing surface water as a resource to replenish the farm pond in Wankute/Jawlebaleshwar involves drawing from rivers, streams, and reservoirs (Fig. 3C). Approximately 13% of the water source for the FP is identified as surface water. This practice has both advantages and disadvantages. When surface water is a shared resource for all water needy, downstream marginal farmers may face negative consequences, while wealthier farmers could further prosper. On the positive side, flood irrigation is practiced in certain areas, contributing to groundwater recharge through irrigation return flow. This practice can have beneficial effects, counteracting the potential drawbacks associated with shared surface water resources. Scenario 3: Using both surface water and groundwater to supply a farm pond (Dolasane) introduces a third and intricate scenario. The complexity arises from the location of the dugwell within a stream, making it challenging to accurately quantify the pumped groundwater and surface water (Fig. 3D). This situation requires a more precise and detailed study. Complications further emerge in cases where multiple wells, owned by a single farmer, are situated within the stream. For instance, in the village of Wankute, a farmer taps water from a stream using 2 dugwells and a borewell to irrigate his 38-acre land. Some streams are seasonal, and excessive pumping poses a risk of depletion. Another frequently observed scenario involves the clustering of FPs, where multiple ponds are constructed in close proximity. To fill these ponds, multiple wells are employed, leading to the creation of multiple cones of depression. The cumulative effect of these cones results in a deeper water table in relation to the adjacent cones. Analysis of INSITU water quality parameter for demarcating Zone of Influence (ZoI) The study aimed to understand the effects of pumping well on the adjacent wells by measuring insitu quality parameter. Several observation wells were geotagged in the vicinity of PW and subsequently the distance of each well was measured. A heavy pumping of a well will cause a greater cone of depression, which will cause the water around the Pumping well to rush towards it. This in turn will be associated with the huge mixing and dilution that will occur, thereby reducing the EC & TDS of the water. As we move away from the PW, the dilution effect will be minimized and reach to the last well falling under the zone of influence. The well which falls immediate to the final well of the ZoI will be marked with the drastic change in the EC and TDS, hence it will define the boundary between the affected and not affected well due to pumping. Due to the extensive number of FPs examined in this study, the graphical representation focuses on illustrating the characteristics of six specific FPs (Fig. 4-6). The INSITU parameter was assessed for Wankute_FP1, revealing an initial electrical conductivity (EC) value of 682 µS/cm at the pumping well. As we move 200 meters away from the pumping well, the EC value increased marginally to 684 µS/cm, indicating a weakening dilution effect. Subsequent measurements at distances of 689 meters and 693.2 meters from the pumping well showed EC values of 680 µS/cm and 705 µS/cm, respectively. The observed trend suggests a discernible zone of influence (ZoI) extending from 689 meters to 693 meters (Fig.4). The findings imply a localized impact on electrical conductivity within this specified range, signifying the influence of the pumping well on the surrounding aquifer. Subsequently, the INSITU parameter was assessed for Wankute_FP4, revealing an electrical conductivity (EC) value of 745 µS/cm at the pumping well. At a distance of 200m from the pumping well, the EC value increased to 771 µS/cm, indicating a diminishing dilution effect. Further moving to 400m from the pumping well resulted in a slight increase in EC value to 790 µS/cm. Especially, at a distance of 425m from the pumping well, the EC value significantly decreased from 790 to 707 µS/cm. Based on these empirical findings, it is inferred that the Zone of Influence (ZoI) extends from 400m to 425m. The INSITU parameter was assessed for the Wankute_FP6, revealing an initial electrical conductivity (EC) value of 602 µS/cm at the pumping well. A systematic spatial analysis indicated a progressive increase in EC with distance from the pumping well. At a distance of 80.9 meters, the EC value rose to 639 µS/cm, indicating a discernible weakening of dilution away from the pumping well. Upon advancing to a distance of 124.5 meters, a slight elevation in EC was observed, reaching 708 µS/cm. However, a subsequent decrease was noted at a distance of 144 meters, where the EC value dropped to 628 µS/cm. intriguingly, at a distance of 207.7 meters from the pumping well, there was a significant surge in EC, escalating from 628 to 696 µS/cm. Upon consideration of the observed values, it was inferred that the Zone of Influence (ZoI) extends from 124 meters to 144 meters (Fig. 5). The quality parameters were systematically evaluated within the context of the Wankute_FP7 study. The Electrical Conductivity (EC) of the pumping well was determined to be 610 µS/cm. Approaching 100 m away from the pumping well resulted in an increase in EC to 722 µS/cm, indicative of weakening dilution effects. Following measurements at distances of 174.5 m, 211.5 m, and 364 m from the pumping well showed EC values of 612 µS/cm, 602 µS/cm, and 801 µS/cm, respectively. The observed data suggests a distinct zone of influence (ZoI) extending up to 100 m from the pumping well, as evidenced by the distinctive EC patterns. The weakening of dilution effects beyond this distance is consistent with the establishment of the ZoI, highlighting the spatial impact of the pumping activity on groundwater electrical conductivity. The subsequent fall and rise of EC after 100m can be attributed the different source which is feeding these wells The INSITU parameter was systematically evaluated for the Wankute_FP9 site, revealing a measured electrical conductivity (EC) value of 550 µS/cm at the pumping well. Notably, at a radial distance of 311.6 m from the pumping well, the EC value exhibited an increment to 584 µS/cm, indicating a discernible attenuation in dilution away from the pumping well. Subsequent assessments at distances of 374 m and 375.8 m demonstrated a gradual rise in EC values to 631 µS/cm and a following significant decrease to 618 µS/cm, respectively. Based on these empirical findings, the delineation of the Zone of Influence (ZoI) is inferred to span from 374 m to 375.8 m (Fig. 6). The case of Jawlebaleshwer_FP2, revealing an initial electrical conductivity (EC) value of 371 µS/cm at the pumping well. Distancing 40 m from the well, the EC value increased to 525 µS/cm, indicative of diminishing dilution effects. Further relocation to 72 m resulted in a significant decrease in EC to 376 µS/cm. surprisingly, at a distance of 81 m from the pumping well, the EC value exhibited a marked escalation from 376 to 700 µS/cm. Based on these observations, it is inferred that the Zone of Influence (ZoI) extends from 40 m to 72 m. These findings contribute valuable insights into the hydrogeological dynamics of the study area. The results presented above represent a specific scenario within the influence zone of Wankute FP-6, ranging from 124 to 144 meters. In examining the plotted data, we observe a direct proportional relationship between Electrical Conductivity (EC), Total Dissolved Solids (TDS), and Salinity. This means that as one of these parameters increases, the others also tend to increase, with a slight shift in response to changes in temperature (Fig. 7). On the other hand, the pH value exhibits an interesting trend—it is inversely proportional to the remaining parameters. In simpler terms, when EC, TDS, or Salinity increase, the pH tends to decrease, and vice versa. This observation provides valuable insights into the dynamic interactions between pH and the other water quality parameters. Table 3. Zone of Influence of the farm pond water sources and its impact on the sources of neighboring farmers Farm pond (FP) owners Number of FPs Total Volume of water in FPs Non FP household within the Zone of Influence Number of wells of non-FP owners within the Zone of Influence Large FP owner 23 447935 13 21 Medium FP owner 34 135494 21 29 Small FP owner 11 6148 34 34 Total 68 589577 68 84 In this study, we investigated the distribution and impact of FPs on the sources (DW & BW) of neighboring farmers (Table 3). Based on the size of their FPs, the survey classified FP owners into three categories: large, medium, and small. According to the distribution, those who own medium-sized FPs have the most ponds overall, followed by those who own large and small FPs. There are differences in the number of non-FP households in the Zone of Influence between the various types of FP owners. The largest proportion of non-FP households are affected by small FP owners inside their ZOI, suggesting possible effects on nearby household. When the number of non-FP owners' wells inside the ZOI is examined, it is shown that larger and medium-sized FP owners have a greater impact on more wells (50) than small FP owners do, the feeder well of 68 FPs is affecting a total of 84 different wells of non-FP owners. Construction of Farm Ponds on different Recharge priority zones Recharge is a phenomenon of adding water into the aquifer by natural or artificial means, it plays a vital role to replenish the depleted aquifer by water movement from the surface to unsaturated zone which eventually goes to the saturated zone. The water which falls on the surface does not filtrate uniformly into the soil, the rate of infiltration is controlled by rock properties and soil characteristics which drive the rate at which water goes down into the unsaturated zone. In order to understand the suitability of the surface, several methods and techniques are used, which generate the map in terms of groundwater potential recharge zone map (Kumar et al., 2008, Kadam et al., 2012, Ammar et al., 2016). GSDA has done extensive work in Maharashtra for groundwater exploration and development. GSDA generated groundwater recharge priority map for identifying the artificial recharge zones on the basis of priorities and then the map was categorized into four sections, viz; High priority, moderate priority, low priority, and limited scope recharge zone (Fig. 8). High priority zone is defined as the zone where maximum amount of water infiltrates into the unsaturated zone to support the rate of recharge, however, the low priority and limited scope zones have low potential for infiltration. The idea behind taking this recharge zone map was to understand the distribution of lined FPs on the different recharge priority zones and the occupation of each recharge zone map. The location of FPs is identified on the GSDA artificial recharge zone map based on priority zones. In Dolasane village, the majority of FPs fall within a high-priority zone, accounting for 60%. Gunjalwadi village boasts the highest number of FPs within a moderate-priority zone, reaching 94.1%, followed closely by Jawale Baleshwar with 87.5% (Fig. 9). It is important to note that these statistics are specific to the FPs included in the study. However, there are numerous additional FPs in the study villages, and following the observed trend, they are likely to cover more surface areas, emphasizing the need for strategic water management practices in these regions. For example; in the study village (Dolasane), out of 34 farm ponds, there are 16 FPs which are falling on a high Priority recharge zone and simultaneously there are 26 dug wells and borewells which are tapping water to fill the FP from the same zone. In total, it has been observed that 13.54 Ha area is covered by impervious lined FPs falling in high and moderate priority recharge zones. Since the FPs are lined with impervious layers, it blocks the water from infiltration. Which in turn hampers the recharge rate in the respective zones. So the construction of FPs without understanding the above mentioned zones will end up with the consequences, which in long run will affect the recharge rate and the sustainability of aquifer will be in a threat. Economic analysis of the loss posed by farm pond for the studied villages In the six study villages, a total of 178 impervious (lined) FPs (year 2021-22) occupy 13.54 ha of high and moderate priority recharge zones. Moreover, borewells and dug wells tap into the high priority recharge area. The FPs with plastic lining have become essential for protective irrigation. However, the impervious layers that line these ponds obstruct water infiltration, adversely affecting the recharge rate in the respective zones. Furthermore, a substantial amount of stored water is lost to the atmosphere through evaporation. An approximate calculation was done to quantify this water loss in monetary terms. The loss in recharge due to impervious lining is calculated based on the total FP area of 13.54 hectare and an annual rainfall of 490 mm (Sasane 2016). Using GEC method, with 9% infiltration factor, it was determined that 44.1 mm of rainfall does not infiltrate into the aquifer (GEC 2015). This results in a total water retention of 59,68,594 liters. Additionally, evaporation loss is estimated at 25% of the total water volume, amounting to 667,538,000 liters. Therefore, the combined loss is calculated as 67,35,06,594 liters. Considering the literature review's estimation that the lost water could irrigate ~44.6 hectares of sugarcane crop, with a yield of 2 crore liters per hectare (0.5cr through rainfall) (Shrivastava et al. 2011). A potential gross income of Rs 3,11,220 per hetare is projected. Consequently, the total loss incurred on irrigation for sugarcane cultivation due to FP practices amounts to Rs 42,84,000. This analysis underscores the economic impact of water loss through FP systems, emphasizing the need for sustainable water management practices to optimize agricultural productivity and income for farmers in the Maharashtra region. Conclusion The primary objectives of FPs are rainwater harvesting and groundwater recharge. Many farmers utilize these ponds as storage structures, employing plastic lining on the bottom and sides to minimize water loss through percolation. Selecting a suitable FP site should consider local soil conditions, topography, drainage, infiltration capacity, and rainfall patterns. Construction should follow the specified guidelines, including inlets for surface water flow during rains and outlets for overflow. Unfortunately, the absence of science-based guidance in site selection and design has resulted in the inefficient performance of many FPs. The lack of technical support leads to poorly constructed ponds, often situated on fallow land or along slopes where overland flow quickly reaches farmlands. Common practices such as drawing water from bore or dug wells to fill ponds contribute to significant evaporation loss. Many ponds need proper inlets and outlets, to enable them for effective rainwater harvesting. Farmers often line ponds with low-quality materials to reduce costs, disregarding government standards that recommend ISI-mark plastic lining. This choice restricts seepage and recharge and transforms ponds into mere storage structures. Villagers' preference for cheaper materials adversely affects the longevity of FPs, leading to recurring costs and high maintenance efforts. The expense of plastic linings surpasses the cost of digging a FP, rendering many documented ponds non-functional due to owners' inability to bear high lining costs. This, in turn, has detrimental effects on the water table, exacerbating competition for groundwater extraction from the aquifer, a shared resource. Upon looking the combined loss of evaporation and groundwater recharge, it has been estimated that Rs 42,84,000 could have been saved with the proper planning. Overall, addressing these issues is crucial to enhancing the effectiveness of farm ponds in promoting sustainable water management. Recommendations: The FP initiative holds significant potential in addressing drought and boosting farmers' income. The state's commendable efforts to promote this initiative are noteworthy. However, the study emphasizes the urgent necessity for adjustments to the scheme. Implementing effective regulations for FP construction is imperative, ensuring adherence to specified standards and dimensions by farmers. Additionally, a systematic approach must be established to determine the number of FPs in a village or watershed. A rigorous monitoring system is crucial, particularly in drought-prone and overexploited areas, to oversee the practice of groundwater extraction for filling FPs. These changes are crucial for the sustainable management of groundwater resources, preserving their unique status as common pool resources. Recommendations are provided to ensure that FPs serve as well-adapted measures for mitigating drought. Assess the local watershed's carrying capacity by analyzing factors such as regional rainfall data, runoff, and groundwater recharge. Estimate the required number of FPs based on size and depth considerations. Restrict the construction of additional FPs in areas which are falling in a high and moderate priority recharge zones. Promote the construction of FPs without linings that harvest surface runoff, taking into account local hydro-geological settings and soil quality. Revise the design of FPs to effectively address various concerns, such as mitigating evaporation and recharge losses, ensuring convenient accessibility, and optimizing electricity consumption for cost efficiency. Declarations Acknowledgement The authors sincerely thank The Hongkong and Shanghai Banking Corporation (HSBC) Software Development (India) Private Limited for their generous financial support, which significantly contributed to the successful completion of the project. Special thanks are also due to the director of W-CReS for providing valuable insights and guidance. Additionally, the authors express gratitude to their colleagues at W-CReS and the field team whose support was indispensable in making this research work possible. Ethical Approval Ethics approval and consent to participate: Before examinations, all the Farm Pond owners and non-farm pond owners in the study villages are provided written informed consent. The study was performed by Watershed Organization Trust (WOTR) and financially supported by The Hongkong and Shanghai Banking Corporation (HSBC) Software Development (India) Private Limited. The survey commenced in 2016 with the approval of The WOTR Centre for Resilience Studies (W-CReS), Watershed Organisation Trust (WOTR). The authors affirm that there is no conflict of interest associated with the study. Consent to participate ‘Not Applicable’ Consent to Publish I have taken the consent for publishing this research work on the individual and organizational level Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Taufique Warsi, Sarita Chemburkar and Ankita yadav. The Socio-Economic portion was written by Faraz Rupani. The first draft of the manuscript was written by Taufique Warsi and all authors commented on previous versions of the manuscript. Marcella D’Souza reviewed and shaped all the written draft. All authors read and approved the final manuscript. Funding This research study was funded and supported by ‘The Hongkong and Shanghai Banking Corporation (HSBC) Software Development (India) Private Limited’. Competing interest The author declare that there is no Competing interest for this research work References Abhay, N (2016): “How to Get Shettale Subsidy for Farm Pond in 2016,” 27 March, http://indiamicrofinance.com/shettale-subsidy-farm-pond2016.html. Acharya, A. S., Prakash, A., Saxena, P., & Nigam, A. (2013). Sampling: Why and how of it. Indian Journal of Medical Specialties , 4 (2), 330-333. Ammar, A., Riksen, M., Ouessar, M., & Ritsema, C. (2016). Identification of suitable sites for rainwater harvesting structures in arid and semi-arid regions: A review. International Soil and Water Conservation Research , 4 (2), 108-120. https://doi.org/10.1016/j.iswcr.2016.03.001 Bendapudi, R., Yadav, A., Chemburkar, S., & D’Souza, M. (2020). Adaptation Strategy or Maladaptation–The conversion of Farm ponds into surface storage tanks in Semi-Arid regions of Maharashtra. Adaptation at Scale in Semi-Arid Regions (ASSAR) & The Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) . Bhadbhade, N., Bhagat, S., Joy, K. J., Samuel, A., Lohakare, K., & Adagale, R. (2019). Can Jalyukt Shivar Abhiyan prevent drought in Maharashtra. Economic & Political Weekly , 54 (25), 13. Davis, S. N., Thompson, G. M., Bentley, H. W., & Stiles, G. (1980). Ground‐water tracers—A short review. Groundwater, 18(1), 14-23, https://doi.org/10.1111/j.1745-6584. 1980.tb03366.x Foster, Stephen, Héctor Garduño, and Albert Tuinhof. "Confronting the groundwater management. Challenge in the Deccan Traps Country of Maharashtra–India." World Bank, Washington DC (2007). Groundwater Surveys and Development Agency (GSDA), Atal Bhujal Yojna (AtalJal) Maharashtra, Hydrogeological Report (2020) Huizar-Alvarez, R., Carrillo-Rivera, J. J., Angeles-Serrano, G., Hergt, T., & Cardona, A. (2004). Chemical response to groundwater extraction southeast of Mexico City. Hydrogeology Journal , 12 , 436-450. https://doi.org/10.1007/s10040-004-0343-3 Jaworska‐Szulc, B. (2016). Role of the lakes in groundwater recharge and discharge in the Young Glacial Area, northern Poland. Groundwater , 54 (4), 603-611. https://doi.org/10.1111/gwat.12385 Kadam, A. K., Kale, S. S., Pande, N. N., Pawar, N. J., & Sankhua, R. N. (2012). Identifying potential rainwater harvesting sites of a semi-arid, basaltic region of Western India, using SCS-CN method. Water resources management , 26 (9), 2537-2554. https://doi.org/10.1007/s11269-012-0031-3 Kale, E. (2017). Problematic uses and practices of farm ponds in Maharashtra. Economic and Political Weekly , 20-22. Kale, E. & Kulkarni, P. (2022). Challenging Today’s Water Threats for Tenable Tomorrow: A Review of Policies and Programs in the Water sector of Maharashtra, research report, Watershed Organisation Trust, Pune, India Kale, E., D'Souza, M., & Chemburkar, S. (2022). Making the invisible, visible: 3D aquifer models as an effective tool for building water stewardship in Maharashtra, India. Water Policy , 24 (5), 718-728. https://doi.org/10.2166/wp.2022.210 Kerr, J. 2002. Watershed development, environmental services, and poverty alleviation in India. World Development 30(8): 1387-1400. https://doi.org/10.1016/S0305-750X(02)00042-6 Khan, P. M. K. A. (2023). Critical Study of Governments Financial Assistance for Farm Pond and their Impact on Socio Economic Development of Farmers in Marathwada Region of Maharashtra. Khare, Y. D., Varade, A. M., Lamsoge, B. R., & Deshmukh, S. (2020). Challenges in Sustainable Development of Groundwater Resources in Maharashtra: An Integrated Approach. Journal of Geosciences Research , 5 (1), 17-25. Kumar, M. G., Agarwal, A. K., & Bali, R. (2008). Delineation of potential sites for water harvesting structures using remote sensing and GIS. Journal of the Indian Society of Remote Sensing , 36 (4), 323-334. Mall, R K et al. 2006. “Jun06-Water-Cc-Cgc-India-Cursci.” 90(12). https://doi.org/10.1007/s12524-008-0033-z Kumar, M.D.; Reddy, V.R.; Narayanamoorthy, A.; Bassi, N. and James, A.J. 2018. Rainfed areas: Poor definition and flawed solutions. International Journal of Water Resources Development 34(2): 278-291. https://doi.org/10.1080/07900627.2017.1278680 Maurice, L., Barker, J. A., Atkinson, T. C., Williams, A. T., & Smart, P. L. (2011). A tracer methodology for identifying ambient flows in boreholes. Groundwater, 49(2), 227-238, https://doi.org/10.1111/j.1745-6584.2010.00708.x. MoRD (Ministry of Rural Development). 1994. Report of the Technical Committee on Drought Prone Areas Programme and Desert Development Programme. New Delhi: Government of India. Reddy, K. S., Manoranjan Kumar, K. V. Rao, V. Maruthi, B. M. K. Reddy, B. Umesh, R. Ganesh Babu, and K. Srinivasa Reddy (2012). "FARM PONDS: A Climate Resilient Technology for Rainfed Agriculture Planning, Design and Construction". Report on the Ground Water Resources Estimation Committee (GEC, 2015) of Central Ground Water Board (CGWB), MOWR, RD & GR, New Delhi. Rusydi, A. F. (2018, February). Correlation between conductivity and total dissolved solid in various type of water: A review. In IOP conference series: earth and environmental science (Vol. 118, p. 012019). IOP Publishing. 10.1088/1755-1315/118/1/012019 Sasane, M. S. (2016). RAINFALL SPATIAL DISTRIBUTION IN AHMEDNAGAR DISTRICT (MS). In Proceeding of. Shivakumarappa, G., Kumbhare, N. V., Padaria, R. N., Burman, R. R., Kumar, P., Bhoumik, A., & Prasad, S. (2023). Constraints in the Adoption of Farm Pond in Drought Regions of Maharashtra. Indian Journal of Extension Education , 59 (1), 142-145. https://doi.org/10.48165/IJEE.2023.59130 Shrivastava, A. K., Srivastava, A. K., & Solomon, S. (2011). Sustaining sugarcane productivity under depleting water resources. Current Science, 748-754. Tritschler, F., Binder, M., Händel, F., Burghardt, D., Dietrich, P., & Liedl, R. (2020). Collected Rain Water as Cost‐Efficient Source for Aquifer Tracer Testing. Groundwater , 58 (1), 125-131. https://doi.org/10.1111/gwat.12898 Warsi, T., Bhattacharjee, L., Thangamani, S., Jat, S. K., Mohanta, K., Bhattacharjee, R. R., ... & Rao, T. V. (2020). Emergence of robust carbon quantum dots as nano-tracer for groundwater studies☆. Diamond and Related Materials, 103, 107701, https://doi.org/10.1016/j.diamond.2020.107701 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-3933040","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280794870,"identity":"c8b9b8e5-7ef8-4df5-a7ea-5c0a5305bb58","order_by":0,"name":"Taufique Warsi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYJCCDwkwVkIFkGBmbsCrnIeBgXEGQssZkBZGIrTAeYxtYBK/Fnv2M4YND8oOyxkcP/v4w8N5tdH87UAtPyq24baFJ8ewIeHcYWODM+lmEonbjufOOMzYwNhz5jYeh+WYP0hsO5y47UAaG0PitmO5DUAtzIxteLTwvzFsAGqp33b+GfOHxDnHcucT1CKRA9aSYHYjjUEisaEmdwNBLTeeFQL9km64/8YzNomEYwdyNwK1HMTnF/b+5I2NP8qs5SX705g//qipy513/vDBBz8qcGuBADY46zCYPEBAPYqWOsKKR8EoGAWjYMQBAG6+YBBshzhyAAAAAElFTkSuQmCC","orcid":"","institution":"Watershed Organisation Trust","correspondingAuthor":true,"prefix":"","firstName":"Taufique","middleName":"","lastName":"Warsi","suffix":""},{"id":280794871,"identity":"4dad31be-437e-4537-af6c-fa074b50d25b","order_by":1,"name":"Sarita Chemburkar","email":"","orcid":"","institution":"WOTR: Watershed Organisation Trust","correspondingAuthor":false,"prefix":"","firstName":"Sarita","middleName":"","lastName":"Chemburkar","suffix":""},{"id":280794872,"identity":"75a9b6e2-1d33-4adc-aa23-e2638dc4f59d","order_by":2,"name":"Ankita Yadav","email":"","orcid":"","institution":"WOTR: Watershed Organisation Trust","correspondingAuthor":false,"prefix":"","firstName":"Ankita","middleName":"","lastName":"Yadav","suffix":""},{"id":280794873,"identity":"0578da95-4386-4fda-a63f-762f599cc15e","order_by":3,"name":"Faraz Rupani","email":"","orcid":"","institution":"WOTR: Watershed Organisation Trust","correspondingAuthor":false,"prefix":"","firstName":"Faraz","middleName":"","lastName":"Rupani","suffix":""},{"id":280794874,"identity":"f08a34d5-111e-4bab-b1b4-54d8dc240018","order_by":4,"name":"Marcella D'Souza","email":"","orcid":"","institution":"WOTR: Watershed Organisation Trust","correspondingAuthor":false,"prefix":"","firstName":"Marcella","middleName":"","lastName":"D'Souza","suffix":""}],"badges":[],"createdAt":"2024-02-06 06:40:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3933040/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3933040/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53049838,"identity":"c92a1560-1ad6-4234-bbae-5873b958287b","added_by":"auto","created_at":"2024-03-20 04:26:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":202677,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of study villages, ochre yellow filled 6 villages are taken under study and the pinned location is represented as Farm Pond\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/837d2da522e114ca01f2f195.png"},{"id":53049840,"identity":"f8c15e3e-ba80-40f3-ab61-6db65d6b3f48","added_by":"auto","created_at":"2024-03-20 04:26:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":113643,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual design of methodology adopted for insitu analysis\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/d7456e9b2cc05349e37a73b8.png"},{"id":53049841,"identity":"3dbb3a40-4913-4b8a-8066-a6ed428cd7ce","added_by":"auto","created_at":"2024-03-20 04:26:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1868450,"visible":true,"origin":"","legend":"\u003cp\u003eScenarios of farm ponds with respect of its feeding source\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/81311c1027d32569d96fcc4a.png"},{"id":53049837,"identity":"d3dfaf6f-d500-4bfd-b169-99e2737c7f47","added_by":"auto","created_at":"2024-03-20 04:26:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":60597,"visible":true,"origin":"","legend":"\u003cp\u003eBreakthrough curve of Electrical Conductivity VS lateral distance from the source well. (L) Feeding dugwell of Wankute FP-1 showing the Zone of Influence (ZoI) ranges from 689m to 693m. (R) Feeding dugwell of FP-4 showing the zone of influence ranges from 400m to 415m.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/c8eab79d538edd0fafbdc21e.png"},{"id":53049843,"identity":"503cfe2f-32fd-4901-9af1-e4886f21524d","added_by":"auto","created_at":"2024-03-20 04:26:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":65169,"visible":true,"origin":"","legend":"\u003cp\u003eBreakthrough curve of Electrical Conductivity VS lateral distance from the source well. (L) Feeding dugwell of Wankute FP-6 showing the Zone of Influence (ZoI) ranges from 125m to 140m. (R) Feeding dugwell of Wankute FP-7 showing the zone of influence ranges from 100m to ~150m.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/8e9d1b1784fa7f3102893f74.png"},{"id":53049839,"identity":"2c745e16-a014-4de8-aa90-60ee7c301b43","added_by":"auto","created_at":"2024-03-20 04:26:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":63011,"visible":true,"origin":"","legend":"\u003cp\u003eBreakthrough curve of Electrical Conductivity VS lateral distance from the source well. (L) Feeding dugwell of Wankute FP-9 showing the Zone of Influence (ZoI) ranges from 375m to 380m. (R) Feeding dugwell of Jawlebaleshwer FP-2 showing the zone of influence ranges from 72m to 78m.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/db953bf39a44a9359ae85842.png"},{"id":53049844,"identity":"4a4b1bfb-13b1-4fe5-8d16-063c8baad321","added_by":"auto","created_at":"2024-03-20 04:26:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":133861,"visible":true,"origin":"","legend":"\u003cp\u003ePlotting of Wankute FP-6 case example for all the insitu parameters (EC, pH, Salinity, TDS, and temperature) to understand the correlation among all the given parameters.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/a233eac71914681bd33fe5f1.png"},{"id":53049845,"identity":"b91ee9fb-1c13-4ce9-a3b4-ee0c59d0ae1c","added_by":"auto","created_at":"2024-03-20 04:26:33","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":393522,"visible":true,"origin":"","legend":"\u003cp\u003eGroundwater artificial recharge priority zone map (Modified after GSDA)\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/9208fa4feeb85c08b127e053.png"},{"id":53049842,"identity":"f17b0a06-dc46-4e9c-bf3c-c20d36fba625","added_by":"auto","created_at":"2024-03-20 04:26:33","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":162095,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage (%) of farm ponds falling over the different recharge priority zones\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/a3bfdf95f70c00c635bccf57.png"},{"id":84946093,"identity":"e09a3d5a-22bb-4c29-9bc5-6aecc9bb7c71","added_by":"auto","created_at":"2025-06-19 06:13:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3594049,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3933040/v1/ab3084a2-8954-42de-a28f-07f42e667142.pdf"}],"financialInterests":"","formattedTitle":"From Rainwater Harvesting to Groundwater Exploitation: Understanding theChanging Role of Farm Ponds and their Socio-economic Consequences in Maharashtra's Semi-Arid Region, India.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGroundwater, a critical resource, assumes a key role in sustaining livelihoods and meeting water demands in the drought-prone semi-arid region of Maharashtra, India (Foster et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Khare et al.2020). In this region, erratic rainfall patterns poses water scarcity challenges, where groundwater serves as a lifeline, providing irrigation for agriculture and potable water for rural communities (Kale and Kulkarni \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The imbalance between water supply and demand in this arid landscape has prompted the government to implement various strategies aimed to address water shortages and ensuring the welfare of agrarian communities (Kerr \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Kumar et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bhadbhade et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Since 1970, Government of India (GoI) initiated different programs to assure the water security in the drought prone regions of India, the program includes Drought Prone Area Program (DPAP) and the Desert Development Program (DDP) (Kerr \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Kumar et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These Government programs invest huge capital (253\u0026nbsp;million dollar) to support the initiatives of soil water conservation, water resource development, afforestation, and pasture development (MoRD 1994). However, these programs failed to address the water scarcity problem due to improper planning and incomplete implementation (MoRD 1994: 11). The \u0026lsquo;National Water Policy\u0026rsquo; that was launched in 1987 was subsequently revised in the year 2002 and 2012. Moreover, it is likely to be revised in near future (Kale et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Afterwards, various water related schemes on groundwater were launched by state and central government which is being implemented in block/Taluka. The main central schemes are PMKSY, Atal Solar Schemes, and MGNREGA whereas state sponsored schemes are PoCRA, CM-Solar schemes, Dr. Babasaheb Ambedkar Krushi Yojna, Birsa Munda Yojna, and FP on demand (Magel Tyala Shet Tale) brought all the attention in order to cope with the current water crisis (Abhay \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; GSDA 2020). Among all the schemes, the promotion of FPs has emerged as a key element in the government's arsenal to address water scarcity and depicted as a miracle strategy by the Republic and Central authority, which later on popularized by the media (Kale \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e and Khan \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the accountable body did not notice how the construction of FP is being implemented on the ground during all this running. The requirements for constructing a FPs are-a dug out structure with a definite size and shape which collects rainfall water, one inlet and outlet to arrest the surface runoff from the farm area, and lastly must be built in a low lying area. A FP can be classified into four types depending on its location and water source; 1). Excavated or Dug out ponds 2). Surface ponds 3). Spring or creek fed ponds and 4). Off stream storage ponds (Reddy et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInitially conceived as tools for rainwater harvesting, FPs have gained widespread adoption and are now commonly used as groundwater storage tanks. These structures, designed to capture rainwater during monsoon seasons, have undergone a significant transformation, taking on new roles as reservoirs for groundwater drawn from the depths of the Earth (Kale \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Shivakumarappa et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This shift in purpose, while addressing immediate water needs, has given rise to unintended consequences that reverberate through the social and hydrogeological fabric of the region (Kale et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). One of the most concerning outcomes of this transformation is the overexploitation of groundwater, a situation primarily driven by a selected group of affluent farmers who have harnessed FPs to secure a private source of water. It creates an obvious inequity in water access, as only a privileged few reap the benefits of privately stored groundwater, while other, less fortunate user communities face increased vulnerability due to a dwindling supply of this vital resource. The study delves into this complex issue by conducting a comprehensive assessment in the Ahmednagar district of Maharashtra. Focusing on six groundwater-vulnerable villages in the region, this research scrutinized 68 functional FPs constructed between 2009 and 2016. The investigation embraced a multi-faceted approach, combining systematic household surveys and a hydrogeological assessment, which collectively aimed to shed light on the different dimensions of the issue at hand. In order to understand the subsurface flow and aquifer connectivity, tracer techniques are very potential tool to decipher the subsurface information (Davis et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Maurice et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Warsi et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, most of the conventional tracers have some limitations and some of them are costly. To trace the extent of influence applied by FP\u0026rsquo;s pumping well on the surrounding hydrogeological system, the study uses insitu parameters such as Electrical Conductivity (EC) and Total Dissolved Solids (TDS) (Rusydi \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jaworska-Szulc \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Tritschler et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These indicators were utilized to delineate the \"Zone of Influence,\" an area encompassing the reach of feeding wells associated with FPs. Within this Zone of Influence, the study required to decipher the socio-economic impacts on farmers residing in close proximity to these water storage structures. Additionally, the study took into account the broader implications of FP distribution on groundwater recharge zones. By referencing the Groundwater Survey and Development Agency's (GSDA) recharge priority zone map, we assessed the presence of lined FPs in high and moderate priority recharge zones. This examination aimed to identify areas where farm ponds may inadvertently hinder groundwater recharge, thus intensifying the region's water-related challenges.\u003c/p\u003e \u003cp\u003eThe findings of this study imparts invaluable insights into the complex relationship between the Zone of Influence created by feeding well of FPs and their socio-economic consequences on local farmers. Moreover, the research will provide a broad understanding of the distribution, operational practices, and detrimental effects associated with the adoption of farm ponds in this region. By considering these aspects, this study contributes to a broader understanding of the evolving dynamics of water resource management in drought-prone regions and recommending important highlights of sustainable and equitable water use to ensure the well-being of rural communities.\u003c/p\u003e\n\u003ch3\u003eStudy Area\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in 6 villages of the Sangamner block of Ahmednagar district, which lies between longitudes 74\u003csup\u003e0\u003c/sup\u003e 02\u0026rsquo; 30\u0026rsquo;\u0026rsquo; and 74\u003csup\u003e0\u003c/sup\u003e 16\u0026rsquo; 30\u0026rsquo;\u0026rsquo; and between latitudes 19\u003csup\u003e0\u003c/sup\u003e 15\u0026rsquo; 30\u0026rsquo;\u0026rsquo; and 19\u003csup\u003e0\u003c/sup\u003e 26\u0026rsquo; 0\u0026rsquo;\u0026rsquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It covers a total geographical area of 166530 Ha, which contains 170 Gram Panchayat, 02 towns, and 170 villages. The area experiences uneven rainfall distribution between 484 mm to 879 mm (CGWB 2014). The region's climate is defined by scorching summers and mostly dry weather all year round. These villages were chosen through hydrological investigations based on an assessment of their groundwater vulnerability. Geologically, the region is mostly covered by Simple and Compound Deccan basalt flow, with significant water-bearing formations in the form of Amygdaloidal Basalt, Fractured and Jointed Basalt, and Zeolitic Vesicular Basalt (GSDA 2020). The two main river basins are the Godavari and Pravra subbasins, and black cotton soil is the most common type of soil. The six villages included in the study are Karjule Pathar, Bhojdari, Wankute, Dolasane, Gunjalwadi, and Jawalebaleshwar of the Sangamner block in the Ahmednagar district's \"rain shadow zone.\" Many of the FPs in these villages have been turned into surface storage tanks. Various groundwater sources supplied water to the FPs, three different kinds of water sources exist: surface water, groundwater, and a combination of the two. According to reports, the Sangamner Block's groundwater resources are in a \"semi-critical condition\" as a result of industrial water demand and agricultural techniques. FPs in communities classified as very vulnerable to groundwater (Sangamner Block) are supplied with water from recently drilled dug wells and boreholes, the quantity of which is expected to rise in the near future.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThe data collection process followed a cluster random sampling method in two steps. The entire population was divided into two groups: FP owners and non-farm pond owners, as outlined by Acharya in 2013. For non-farm pond owners, a household-level questionnaire survey was conducted. The study also involved technical analysis of hydrological data, incorporating insights from the FP study by Bendapudi et al. in 2020. To identify the zone of influence, a technical method was employed using INSITU water quality parameters of pumping and surrounding well with having household-level data from 61 farmers who owned 68 FPs as baseline information. The population of non-FP owners was determined based on the ratio with each pumping well used for filling FPs by farm pond owners. For instance, for each source well of a FP, there could be 2 to 3 or even more drawdown wells of neighboring farmers who do not own FPs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn-situ parameter testing:\u003c/strong\u003e An insitu parameter is a potential tool to understand the local hydrological boundaries and surface water groundwater interaction on the basis of EC, Ph, TDS, and Salinity (Huizar-Alvarez et al. 2004; Rusydi, 2018; Jaworska‐Szulc 2016; Tritschler et al. 2020). In the study area multiple bore wells/dug wells were selected in the surrounding and downstream side of the FP feeding well (Fig. 2). In order to determine the hydrological boundaries, the distance of downstream wells were measured from the pumping well which feeds the FPs. Subsequently, measured quality parameters were plotted against the borewell distance to understand the zone of influence with the help of a breakthrough curve. Since the pumping well is extracting maximum amount of water with the maximum duration of pumping, so the dilution of solids will be more near the well due to fresh water influx from the surrounding area and as we move away from the pumping well, the rate of dilution will be reduced and a linear pattern will emerge under the same zone of influence. However, a break can be observed when there will be a discontinuity in the aquifer or the extent of pumping influence ends. The selection of well and conceptual design is given in the Fig. 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of lined farm ponds on recharge:\u0026nbsp;\u003c/strong\u003eGroundwater Survey and Development Agency (GSDA) has done extensive work in Maharashtra for groundwater exploration and development. GSDA generated groundwater recharge priority map for identifying the artificial recharge zones on the basis of priorities and then the map was categorized into four sections, viz; High priority, moderate priority, low priority, and limited scope recharge zone (GSDA, 2020). The idea behind taking this recharge zone map was to understand the distribution of lined farm ponds and to understand the occupation of each recharge zone map by the FPs. Since the FPs are lined with impervious layers, it blocks the water from infiltration. Which in turn hampers the recharge rate in the respective zones. In order to have a primary understanding of consequences, the total area was calculated which is being blocked by lined FPs.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e\u003cstrong\u003ePhysical survey:\u0026nbsp;\u003c/strong\u003eAll 188 farmers who constructed FPs till July 2017 from the six study villages were interviewed using a structured questionnaire. These 188 farmers reported a total of 206 FPs wherein 18 farmers own more than one FP. The information and data set collected from the respondents mainly include the detailed cost of cultivation and production, irrigation using FPs, other sources of irrigation, the dimension of the FPs, investment costs occurred on constructing FP and plastic lining. The information also includes the perceptions of FP owners regarding the use and benefits received. However, 68 working (in use with lining) FPs were identified which belong to 61 owners to proceed with the in-depth hydrogeological analysis which eventually deciphered the subsurface condition by demarcating the zone of influence. All the 68 FP then broadly categorized into three groups on the basis of land holding capacity and the size of FPs (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eClassification of Farm pond sizes and Land holding of farm pond owning farmers under study\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"603\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.867549668874172%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.211920529801326%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLarge land holders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedium land holders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.887417218543046%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmall land holders\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.496688741721854%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTAL farm ponds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e(4.1 to 15.4 ha)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.75757575757576%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e(2.1 - 4 ha)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.90909090909091%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e(0.4 to 2 ha)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.867549668874172%\" valign=\"top\"\u003e\n \u003cp\u003eLarge Farm pond \u0026gt;10000 \u0026nbsp;m\u0026sup3;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.211920529801326%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.887417218543046%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.496688741721854%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.867549668874172%\" valign=\"top\"\u003e\n \u003cp\u003eMedium Farm pond 1100 to 10000 m\u0026sup3;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.211920529801326%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.887417218543046%\" valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.496688741721854%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.867549668874172%\" valign=\"top\"\u003e\n \u003cp\u003eSmall Farm pond 64 to 1000m\u0026sup3;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.211920529801326%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.887417218543046%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.496688741721854%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.867549668874172%\" valign=\"top\"\u003e\n \u003cp\u003eTOTAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.211920529801326%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5364238410596%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.887417218543046%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.496688741721854%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to the above table, FP owners are classified as per the size of their ponds and their land holdings. Based on the size of a FP, there are three different types: large, medium, and small. The number of large ponds is 23, while the number of medium ponds and small ponds is 23 and 34, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eDifferent water source used to fill the farm ponds\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"622\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.186495176848876%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFarm pond category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.469453376205788%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFarm ponds (No.)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.363344051446944%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal volume (m\u0026sup3;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.308681672025724%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDug wells\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.434083601286174%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBore wells\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.237942122186496%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStreams\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.186495176848876%\" valign=\"bottom\"\u003e\n \u003cp\u003eLarge farm ponds: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;(10000 - 47572 \u0026nbsp;m\u0026sup3;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.469453376205788%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.363344051446944%\" valign=\"bottom\"\u003e\n \u003cp\u003e4,47,935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.308681672025724%\" valign=\"bottom\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.434083601286174%\" valign=\"bottom\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.237942122186496%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.186495176848876%\" valign=\"bottom\"\u003e\n \u003cp\u003eMedium farm ponds \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;(1000 - 10000 m\u0026sup3;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.469453376205788%\" valign=\"bottom\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.363344051446944%\" valign=\"bottom\"\u003e\n \u003cp\u003e1,35,494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.308681672025724%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.434083601286174%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.237942122186496%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.186495176848876%\" valign=\"bottom\"\u003e\n \u003cp\u003eSmall farm ponds \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (64 to 1000 m\u0026sup3;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.469453376205788%\" valign=\"bottom\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.363344051446944%\" valign=\"bottom\"\u003e\n \u003cp\u003e6,148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.308681672025724%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.434083601286174%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.237942122186496%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs shown in the above table, there are three categories: large, medium, and small. It consists of 23 large ponds, 34 medium ponds, and 11 small ponds (Table 2). To fill the FPs, there are 87 water sources, such as dug wells, bore wells, and streams.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Nexus of Water Sources in Current Farm pond practices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScenario1:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing groundwater from dug wells to fill FPs, such as those in Wankute/Jawlebaleshwar, is a common practice. This includes FPs supplied by various groundwater sources like dug wells, bore wells, and horizontal wells (Fig. 3A \u0026amp; 3B). However, the excessive pumping of groundwater has led to a depletion of aquifers. Furthermore, storing pumped water in lined FPs contributes to evaporation losses, particularly during the peak summer months. Concerns arise due to a significant increase in the number of FPs in recent years, with projections indicating a substantial further increase in the near future. This trend exacerbates the challenges associated with groundwater depletion, evaporation losses, and inequitable distribution among farmers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScenario 2:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUtilizing surface water as a resource to replenish the farm pond in Wankute/Jawlebaleshwar involves drawing from rivers, streams, and reservoirs\u0026nbsp;(Fig. 3C). Approximately 13% of the water source for the FP is identified as surface water. This practice has both advantages and disadvantages. When surface water is a shared resource for all water needy, downstream marginal farmers may face negative consequences, while wealthier farmers could further prosper. On the positive side, flood irrigation is practiced in certain areas, contributing to groundwater recharge through irrigation return flow. This practice can have beneficial effects, counteracting the potential drawbacks associated with shared surface water resources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScenario 3:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing both surface water and groundwater to supply a farm pond (Dolasane) introduces a third and intricate scenario. The complexity arises from the location of the dugwell within a stream, making it challenging to accurately quantify the pumped groundwater and surface water\u0026nbsp;(Fig. 3D). This situation requires a more precise and detailed study. Complications further emerge in cases where multiple wells, owned by a single farmer, are situated within the stream. For instance, in the village of Wankute, a farmer taps water from a stream using 2 dugwells and a borewell to irrigate his 38-acre land. Some streams are seasonal, and excessive pumping poses a risk of depletion. Another frequently observed scenario involves the clustering of FPs, where multiple ponds are constructed in close proximity. To fill these ponds, multiple wells are employed, leading to the creation of multiple cones of depression. The cumulative effect of these cones results in a deeper water table in relation to the adjacent cones.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of INSITU water quality parameter for demarcating Zone of Influence (ZoI)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study aimed to understand the effects of pumping well on the adjacent wells by measuring insitu quality parameter. Several observation wells were geotagged in the vicinity of PW and subsequently the distance of each well was measured. A heavy pumping of a well will cause a greater cone of depression, which will cause the water around the Pumping well to rush towards it. This in turn will be associated with the huge mixing and dilution that will occur, thereby reducing the EC \u0026amp; TDS of the water. As we move away from the PW, the dilution effect will be minimized and reach to the last well falling under the zone of influence. The well which falls immediate to the final well of the ZoI will be marked with the drastic change in the EC and TDS, hence it will define the boundary between the affected and not affected well due to pumping.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDue to the extensive number of FPs examined in this study, the graphical representation focuses on illustrating the characteristics of six specific FPs (Fig. 4-6).\u003c/p\u003e\n\u003cp\u003eThe INSITU parameter was assessed for Wankute_FP1, revealing an initial electrical conductivity (EC) value of 682 \u0026micro;S/cm at the pumping well. As we move 200 meters away from the pumping well, the EC value increased marginally to 684 \u0026micro;S/cm, indicating a weakening dilution effect. Subsequent measurements at distances of 689 meters and 693.2 meters from the pumping well showed EC values of 680 \u0026micro;S/cm and 705 \u0026micro;S/cm, respectively. The observed trend suggests a discernible zone of influence (ZoI) extending from 689 meters to 693 meters (Fig.4). The findings imply a localized impact on electrical conductivity within this specified range, signifying the influence of the pumping well on the surrounding aquifer. Subsequently, the INSITU parameter was assessed for Wankute_FP4, revealing an electrical conductivity (EC) value of 745 \u0026micro;S/cm at the pumping well. At a distance of 200m from the pumping well, the EC value increased to 771 \u0026micro;S/cm, indicating a diminishing dilution effect. Further moving to 400m from the pumping well resulted in a slight increase in EC value to 790 \u0026micro;S/cm. Especially, at a distance of 425m from the pumping well, the EC value significantly decreased from 790 to 707 \u0026micro;S/cm. Based on these empirical findings, it is inferred that the Zone of Influence (ZoI) extends from 400m to 425m.\u003c/p\u003e\n\u003cp\u003eThe INSITU parameter was assessed for the Wankute_FP6, revealing an initial electrical conductivity (EC) value of 602 \u0026micro;S/cm at the pumping well. A systematic spatial analysis indicated a progressive increase in EC with distance from the pumping well. At a distance of 80.9 meters, the EC value rose to 639 \u0026micro;S/cm, indicating a discernible weakening of dilution away from the pumping well. Upon advancing to a distance of 124.5 meters, a slight elevation in EC was observed, reaching 708 \u0026micro;S/cm. However, a subsequent decrease was noted at a distance of 144 meters, where the EC value dropped to 628 \u0026micro;S/cm. intriguingly, at a distance of 207.7 meters from the pumping well, there was a significant surge in EC, escalating from 628 to 696 \u0026micro;S/cm. Upon consideration of the observed values, it was inferred that the Zone of Influence (ZoI) extends from 124 meters to 144 meters (Fig. 5). The quality parameters were systematically evaluated within the context of the Wankute_FP7 study. The Electrical Conductivity (EC) of the pumping well was determined to be 610 \u0026micro;S/cm. Approaching 100 m away from the pumping well resulted in an increase in EC to 722 \u0026micro;S/cm, indicative of weakening dilution effects. Following measurements at distances of 174.5 m, 211.5 m, and 364 m from the pumping well showed EC values of 612 \u0026micro;S/cm, 602 \u0026micro;S/cm, and 801 \u0026micro;S/cm, respectively. The observed data suggests a distinct zone of influence (ZoI) extending up to 100 m from the pumping well, as evidenced by the distinctive EC patterns. The weakening of dilution effects beyond this distance is consistent with the establishment of the ZoI, highlighting the spatial impact of the pumping activity on groundwater electrical conductivity. The subsequent fall and rise of EC after 100m can be attributed the different source which is feeding these wells\u003c/p\u003e\n\u003cp\u003eThe INSITU parameter was systematically evaluated for the Wankute_FP9 site, revealing a measured electrical conductivity (EC) value of 550 \u0026micro;S/cm at the pumping well. Notably, at a radial distance of 311.6 m from the pumping well, the EC value exhibited an increment to 584 \u0026micro;S/cm, indicating a discernible attenuation in dilution away from the pumping well. Subsequent assessments at distances of 374 m and 375.8 m demonstrated a gradual rise in EC values to 631 \u0026micro;S/cm and a following significant decrease to 618 \u0026micro;S/cm, respectively. Based on these empirical findings, the delineation of the Zone of Influence (ZoI) is inferred to span from 374 m to 375.8 m (Fig. 6). The case of Jawlebaleshwer_FP2, revealing an initial electrical conductivity (EC) value of 371 \u0026micro;S/cm at the pumping well. Distancing 40 m from the well, the EC value increased to 525 \u0026micro;S/cm, indicative of diminishing dilution effects. Further relocation to 72 m resulted in a significant decrease in EC to 376 \u0026micro;S/cm. surprisingly, at a distance of 81 m from the pumping well, the EC value exhibited a marked escalation from 376 to 700 \u0026micro;S/cm. Based on these observations, it is inferred that the Zone of Influence (ZoI) extends from 40 m to 72 m. These findings contribute valuable insights into the hydrogeological dynamics of the study area.\u003c/p\u003e\n\u003cp\u003eThe results presented above represent a specific scenario within the influence zone of Wankute FP-6, ranging from 124 to 144 meters. In examining the plotted data, we observe a direct proportional relationship between Electrical Conductivity (EC), Total Dissolved Solids (TDS), and Salinity. This means that as one of these parameters increases, the others also tend to increase, with a slight shift in response to changes in temperature (Fig. 7). On the other hand, the pH value exhibits an interesting trend\u0026mdash;it is inversely proportional to the remaining parameters. In simpler terms, when EC, TDS, or Salinity increase, the pH tends to decrease, and vice versa. This observation provides valuable insights into the dynamic interactions between pH and the other water quality parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Zone of Influence of the farm pond water sources and its impact on the sources of neighboring farmers\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFarm pond (FP) owners\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of FPs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Volume of water in FPs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon FP household within the Zone of Influence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of wells of non-FP owners within the Zone of Influence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eLarge FP owner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e447935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eMedium FP owner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e135494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eSmall FP owner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e6148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e589577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn this study, we investigated the distribution and impact of FPs on the sources (DW \u0026amp; BW) of neighboring farmers (Table 3). Based on the size of their FPs, the survey classified FP owners into three categories: large, medium, and small. According to the distribution, those who own medium-sized FPs have the most ponds overall, followed by those who own large and small FPs. There are differences in the number of non-FP households in the Zone of Influence between the various types of FP owners. The largest proportion of non-FP households are affected by small FP owners inside their ZOI, suggesting possible effects on nearby household. When the number of non-FP owners\u0026apos; wells inside the ZOI is examined, it is shown that larger and medium-sized FP owners have a greater impact on more wells (50) than small FP owners do, the feeder well of 68 FPs is affecting a total of 84 different wells of non-FP owners.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction of Farm Ponds on different Recharge priority zones\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecharge is a phenomenon of adding water into the aquifer by natural or artificial means, it plays a vital role to replenish the depleted aquifer by water movement from the surface to unsaturated zone which eventually goes to the saturated zone. The water which falls on the surface does not filtrate uniformly into the soil, the rate of infiltration is controlled by rock properties and soil characteristics which drive the rate at which water goes down into the unsaturated zone. In order to understand the suitability of the surface, several methods and techniques are used, which generate the map in terms of groundwater potential recharge zone map (Kumar et al., 2008, Kadam et al., 2012, Ammar et al., 2016). GSDA has done extensive work in Maharashtra for groundwater exploration and development. GSDA generated groundwater recharge priority map for identifying the artificial recharge zones on the basis of priorities and then the map was categorized into four sections, viz; High priority, moderate priority, low priority, and limited scope recharge zone (Fig. 8). High priority zone is defined as the zone where maximum amount of water infiltrates into the unsaturated zone to support the rate of recharge, however, the low priority and limited scope zones have low potential for infiltration. The idea behind taking this recharge zone map was to understand the distribution of lined FPs on the different recharge priority zones and the occupation of each recharge zone map.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe location of FPs is identified on the GSDA artificial recharge zone map based on priority zones. In Dolasane village, the majority of FPs fall within a high-priority zone, accounting for 60%. Gunjalwadi village boasts the highest number of FPs within a moderate-priority zone, reaching 94.1%, followed closely by Jawale Baleshwar with 87.5% (Fig. 9). It is important to note that these statistics are specific to the FPs included in the study. However, there are numerous additional FPs in the study villages, and following the observed trend, they are likely to cover more surface areas, emphasizing the need for strategic water management practices in these regions. For example; in the study village (Dolasane), out of 34 farm ponds, there are 16 FPs which are falling on a high Priority recharge zone and simultaneously there are 26 dug wells and borewells which are tapping water to fill the FP from the same zone. In total, it has been observed that 13.54 Ha area is covered by impervious lined FPs falling in high and moderate priority recharge zones. Since the FPs are lined with impervious layers, it blocks the water from infiltration. Which in turn hampers the recharge rate in the respective zones. So the construction of FPs without understanding the above mentioned zones will end up with the consequences, which in long run will affect the recharge rate and the sustainability of aquifer will be in a threat.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEconomic analysis of the loss posed by farm pond for the studied villages\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the six study villages, a total of 178 impervious (lined) FPs (year 2021-22) occupy 13.54 ha of high and moderate priority recharge zones. Moreover, borewells and dug wells tap into the high priority recharge area. The FPs with plastic lining have become essential for protective irrigation. However, the impervious layers that line these ponds obstruct water infiltration, adversely affecting the recharge rate in the respective zones. Furthermore, a substantial amount of stored water is lost to the atmosphere through evaporation. An approximate calculation was done to quantify this water loss in monetary terms. The loss in recharge due to impervious lining is calculated based on the total FP area of 13.54 hectare and an annual rainfall of 490 mm (Sasane 2016). Using GEC method, with 9% infiltration factor, it was determined that 44.1 mm of rainfall does not infiltrate into the aquifer (GEC 2015). This results in a total water retention of 59,68,594 liters. Additionally, evaporation loss is estimated at 25% of the total water volume, amounting to 667,538,000 liters. Therefore, the combined loss is calculated as 67,35,06,594 liters. Considering the literature review\u0026apos;s estimation that the lost water could irrigate ~44.6 hectares of sugarcane crop, with a yield of 2 crore liters per hectare (0.5cr through rainfall) (Shrivastava et al. 2011). \u0026nbsp;A potential gross income of Rs 3,11,220 per hetare is projected. Consequently, the total loss incurred on irrigation for sugarcane cultivation due to FP practices amounts to Rs 42,84,000. This analysis underscores the economic impact of water loss through FP systems, emphasizing the need for sustainable water management practices to optimize agricultural productivity and income for farmers in the Maharashtra region.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe primary objectives of FPs are rainwater harvesting and groundwater recharge. Many farmers utilize these ponds as storage structures, employing plastic lining on the bottom and sides to minimize water loss through percolation. Selecting a suitable FP site should consider local soil conditions, topography, drainage, infiltration capacity, and rainfall patterns. Construction should follow the specified guidelines, including inlets for surface water flow during rains and outlets for overflow. Unfortunately, the absence of science-based guidance in site selection and design has resulted in the inefficient performance of many FPs. The lack of technical support leads to poorly constructed ponds, often situated on fallow land or along slopes where overland flow quickly reaches farmlands. Common practices such as drawing water from bore or dug wells to fill ponds contribute to significant evaporation loss. Many ponds need proper inlets and outlets, to enable them for effective rainwater harvesting. Farmers often line ponds with low-quality materials to reduce costs, disregarding government standards that recommend ISI-mark plastic lining. This choice restricts seepage and recharge and transforms ponds into mere storage structures. Villagers' preference for cheaper materials adversely affects the longevity of FPs, leading to recurring costs and high maintenance efforts. The expense of plastic linings surpasses the cost of digging a FP, rendering many documented ponds non-functional due to owners' inability to bear high lining costs. This, in turn, has detrimental effects on the water table, exacerbating competition for groundwater extraction from the aquifer, a shared resource. Upon looking the combined loss of evaporation and groundwater recharge, it has been estimated that Rs 42,84,000 could have been saved with the proper planning. Overall, addressing these issues is crucial to enhancing the effectiveness of farm ponds in promoting sustainable water management.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations:\u003c/h2\u003e \u003cp\u003eThe FP initiative holds significant potential in addressing drought and boosting farmers' income. The state's commendable efforts to promote this initiative are noteworthy. However, the study emphasizes the urgent necessity for adjustments to the scheme. Implementing effective regulations for FP construction is imperative, ensuring adherence to specified standards and dimensions by farmers. Additionally, a systematic approach must be established to determine the number of FPs in a village or watershed. A rigorous monitoring system is crucial, particularly in drought-prone and overexploited areas, to oversee the practice of groundwater extraction for filling FPs. These changes are crucial for the sustainable management of groundwater resources, preserving their unique status as common pool resources. Recommendations are provided to ensure that FPs serve as well-adapted measures for mitigating drought.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAssess the local watershed's carrying capacity by analyzing factors such as regional rainfall data, runoff, and groundwater recharge. Estimate the required number of FPs based on size and depth considerations.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRestrict the construction of additional FPs in areas which are falling in a high and moderate priority recharge zones.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePromote the construction of FPs without linings that harvest surface runoff, taking into account local hydro-geological settings and soil quality.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRevise the design of FPs to effectively address various concerns, such as mitigating evaporation and recharge losses, ensuring convenient accessibility, and optimizing electricity consumption for cost efficiency.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank The Hongkong and Shanghai Banking Corporation (HSBC) Software Development (India) Private Limited for their generous financial support, which significantly contributed to the successful completion of the project. Special thanks are also due to the director of W-CReS for providing valuable insights and guidance. Additionally, the authors express gratitude to their colleagues at W-CReS and the field team whose support was indispensable in making this research work possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate: \u0026nbsp;Before examinations, all the Farm Pond owners and non-farm pond owners in the study villages are provided written informed consent. The study was performed by Watershed Organization Trust (WOTR) and financially supported by The Hongkong and Shanghai Banking Corporation (HSBC) Software Development (India) Private Limited. The survey commenced in 2016 with the approval of The WOTR Centre for Resilience Studies (W-CReS), Watershed Organisation Trust (WOTR). The authors affirm that there is no conflict of interest associated with the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lsquo;Not Applicable\u0026rsquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI have taken the consent for publishing this research work on the individual and organizational level\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Taufique Warsi, Sarita Chemburkar and Ankita yadav. The Socio-Economic portion was written by Faraz Rupani. The first draft of the manuscript was written by Taufique Warsi and all authors commented on previous versions of the manuscript. Marcella D\u0026rsquo;Souza reviewed and shaped all the written draft.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research study was funded and supported by \u0026lsquo;The Hongkong and Shanghai Banking Corporation (HSBC) Software Development (India) Private Limited\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declare that there is no Competing interest for this research work\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbhay, N (2016): \u0026ldquo;How to Get Shettale Subsidy for Farm Pond in 2016,\u0026rdquo; 27 March, http://indiamicrofinance.com/shettale-subsidy-farm-pond2016.html. \u003c/li\u003e\n\u003cli\u003eAcharya, A. S., Prakash, A., Saxena, P., \u0026amp; Nigam, A. (2013). 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Current Science, 748-754.\u003c/li\u003e\n\u003cli\u003eTritschler, F., Binder, M., H\u0026auml;ndel, F., Burghardt, D., Dietrich, P., \u0026amp; Liedl, R. (2020). Collected Rain Water as Cost‐Efficient Source for Aquifer Tracer Testing. \u003cem\u003eGroundwater\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e(1), 125-131. https://doi.org/10.1111/gwat.12898\u003c/li\u003e\n\u003cli\u003eWarsi, T., Bhattacharjee, L., Thangamani, S., Jat, S. K., Mohanta, K., Bhattacharjee, R. R., ... \u0026amp; Rao, T. V. (2020). Emergence of robust carbon quantum dots as nano-tracer for groundwater studies☆. Diamond and Related Materials, 103, 107701, https://doi.org/10.1016/j.diamond.2020.107701\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"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":"Farm pond, Zone of Influence (ZoI), Rainfed, Socio-Economics, Maharashtra, India","lastPublishedDoi":"10.21203/rs.3.rs-3933040/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3933040/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGroundwater plays a critical role in providing irrigation and drinking water in the drought-prone semi-arid region of Maharashtra, India. To address water scarcity, the government has promoted the construction of Farm Ponds (FPs) as a strategy to secure rural agrarian livelihoods and drought-proof the area. However, FPs, originally designed for rainwater harvesting, have now become commonly used as groundwater storage tanks, leading to overexploitation of groundwater by a few affluent farmers. This creates inequity in access to water by making it private and increases the vulnerability of other user communities. In this study, a systematic hydrogeological assessment was conducted, analysing 68 functional FPs constructed between 2009 and 2016 in six groundwater-vulnerable villages. The assessment focused on using Electrical Conductivity (EC) and Total Dissolved Solids (TDS) as parameters to delineate the zone of influence created by the feeding wells of FPs. Furthermore, the study utilized the Groundwater Survey and Development Agency\u0026rsquo;s (GSDA) recharge priority zone map to examine the distribution of lined FPs and identify areas where these ponds hinder recharge in high and moderate priority recharge zones and their socio-economic impacts on farmers were evaluated. The findings provide valuable insights into the relationship between the Zone of Influence and its socio-economic impacts on farmers, offering a comprehensive understanding of the distribution, practices, and ill effects of farm ponds.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"From Rainwater Harvesting to Groundwater Exploitation: Understanding theChanging Role of Farm Ponds and their Socio-economic Consequences in Maharashtra's Semi-Arid Region, India.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-20 04:26:27","doi":"10.21203/rs.3.rs-3933040/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":"918462d0-25dd-48d4-84c9-0298b1d98de7","owner":[],"postedDate":"March 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-19T06:05:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-20 04:26:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3933040","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3933040","identity":"rs-3933040","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}