Water Risk Assessment in the Hindon Catchment, India: Challenges and Opportunities for Resilience Building

Water Risk Assessment in the Hindon Catchment, India: Challenges and Opportunities for Resilience Building | 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 Water Risk Assessment in the Hindon Catchment, India: Challenges and Opportunities for Resilience Building LALIT MOHAN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7210895/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 India's rapidly expanding population and industrial base have resulted in escalating water demand, increasingly outpacing available supply and degrading water quality. The Hindon River, a tributary of the Yamuna, exemplifies these challenges across 6,232 km2 catchment, encompassing diverse land-use zones from agricultural plains to urban centres like Ghaziabad and Gautam Budh Nagar. This study applies a water balance methodology using open -sources datasets, QGIS, and python -based analytics to assess hydrological trends, groundwater dynamics, evapotranspiration, and land-use impacts in the Hindon catchment. Results reveal a critical water deficit of -342.8 mm/year, driven by overextraction of groundwater, water intensive crops, and high evapotranspiration losses. The paper outlines sectoral vulnerabilities across agriculture, industry, and domestic supply, and proposes a multi-pronged strategy encompassing crop diversification, real-time monitoring, urban water body restoration, and nature – based solutions for building long-term water resilience. Hydrology Geographic Information Systems Urban Studies Hindon River groundwater depletion water balance catchment management evapotranspiration agricultural risk GIS-based assessment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction India faces mounting pressures to reconcile rapid development with sustainable water management. With over 20 major river basins and numerous smaller tributaries, understanding water dynamics at sub – basin levels is essential. The Hindon River catchment, part of the Yamuna basin, originates from Saharanpur district of Uttar Pradesh, flows 350km, draining into the Yamuna River. It traverses mixed land -use zones including high- density urban areas and water – water intensive agricultural zones. The catchment also touches or very small portion of Delhi. The Kali and Krishni rivers are the main tributary of the Hindon river. The location of the Hindon catchment given in Figure 1. Once supporting domestic water needs, the Hindon River is now severely polluted and primarily serves non-potable uses such as livestock washing (Lewis, 2007). With erratic precipitation patterns, intense agricultural pressure, and unregulated groundwater withdrawal assessing water risk in this basin is urgent. 2. Objectives The study pursues the following objectives: 1. Assess systematic water risks in the Hindon catchment 2. Identify region specific vulnerabilities in agriculture, domestic, and industrial sectors. 3. Propose actionable frameworks to enhance long-term water resilience. 3. Methodology The following method adopted to do this assignment given in Figure 2. A simple method used to conduct this study. The details of data sources and framework provided in the following sections. This integrated methodological approach enables a comprehensive understanding of water risks in the Hindon catchment while providing a foundation for identifying targeted interventions to build water resilience in the region. 3.1 Data Collection and Sources This study relies on multiple open sources datasets provided in Table 1. Table 1: data sources used for the study Category Data Sources Hydrological data Rainfall from IMD (10 years), Format- NetCDF Indian Meteorological Department (IMD) Evapotranspiration, Format-GeoTiff USGS -MODIS Groundwater Fomat- Excel/PDF Central Groundwater Board Spatial datasets SRTM 30m DEM, Format -GeoTiff USGS Land use land cover, Resolution -10m, Format- GeoTiff Sentinel-2 Soil, Format-Shapefile FAO Government reports and assessments CGWB groundwater reports Pollution Control Borad water quality monitoring data District agricultural contingency plans, Format- PDF, Text 2.1 Analytical Framework The methodology integrates spatial analysis, water balance modelling, and sensitivity analyses: · Watershed delineation in QGIS using SRTM DEM · Run off estimates via land use and soil -based coefficient methods · Water quality and groundwater status assessment using CGWB datasets · Water balance: Water Availability = P – Q - ET Where P = Precipitation, Q = Runoff, ET = Evapotranspiration 2.2 Tools Used · QGIS for spatial analysis and watershed modelling · Python scripting for data cleaning, time series analyses, and model integration 4. Catchment Profile 4.1 Administrative Coverage The Hindon catchment spans across 11 districts, predominantly in Uttar Pradesh, and includes key urban-industrial hubs and agriculture belts. The largest shares lie within Saharanpur (1,808 km 2 ) and Muzaffarnagar (1,550 km 2 ) districts. The district wise area distribution provided in Table 2 and shown in Figure 3. Table 2: District comes under the Hindon catchment DISTRICT STATE AREA (Km 2 ) Haridwar Uttarakhand 318.9 Saharanpur Uttar Pradesh 1808.45 Muzaffarnagar Uttar Pradesh 1557.91 Shamli Uttar Pradesh 541.73 Meerut Uttar Pradesh 361.76 Bagpat Uttar Pradesh 721.32 Ghaziabad Uttar Pradesh 524.29 Gautam Budh Nagar Uttar Pradesh 340.45 East Delhi 16.06 Northeast Delhi 8.24 Shahdara Delhi 28.69 4.2 Climate The climate ranges from tropical to temperate with temperature variation up to 3 °C in winter and up to 43 °C in summer and mean annual rainfall of 702 mm subjected to spatial variations (Mayuri Chabukdhara, 2012). The weather averages for the month of October, temperature averages around 33°c and at night it feels like 22°c. In October, Ghaziabad gets on an average 28.11mm of rain[1] and approximately 2 rainy days in the month. The rainfall pattern shown in Figure 4. Humidity is close to 40%. The highest average rainfall occurs during the month of June–September (monsoon period). 4.3 Topography The elevation range of the Hindon catchment range is 180 m to 880m. SRTM 90m digital elevation model (DEM) used for elevation profile and the slope (Figure 5). 4.4 Land-Use The predominant land-use in the Hindon catchment area is primarily agricultural, with a notable presence of built-up urban areas. Specifically, there has been substantial urban development, particularly in the Ghaziabad and Gautam Budh Nagar districts. The land use taken from the Sentinel-2 of the year 2022 (Karra, 2021). The land use classification given in Table 3 and shown in Figure 6. Table 3: Land use classification Classification Area (km 2 ) Water Bodies 14 Forest 278 Agriculture Land 4826 Built up 1079 Bare Ground 31 4.5 Soil The soil[2] in the Hindon catchment mainly loamy in texture and depth of soil is between 100-150cm. The type of soil given in Figure 7. 4.6 Groundwater Groundwater status is the key indicator of water risk of any area. There are 46 administrative blocks are coming where groundwater status assessed. 18 blocks in the catchment are over exploited and 5 are in critical stage. The status of groundwater status shown in Figure 8. The data have been taken from the CGWB groundwater assessment report 2022 and 2024. This shows the water shortage in the future and can impact the local business. 4.7 Evapotranspiration The average evapotranspiration[3] of Hindon catchment is 900mm/year shown in Figure 9. The figure also depicts that evapotranspiration is high in the agriculture areas (green in colour) and evapotranspiration is low in the built-up areas (red colour). 4.8 Water uses India’s water use[4] is heavily dominated by agriculture (85%) due to water intensive crops. Urban and rural water benchmarks are 135 and 55 lpcd respectively, but the actual per capita water footprint is far higher due to water use in food, energy, and goods production. Growing demands, especially in cities and industries, risks severe water scarcity by 2030. This also applicable for Hindon catchment where more than 70% are is agriculture and followed by built up (Ghaziabad, Noida and Saharanpur are major cities etc.,).The district wise annual groundwater extraction ( (Region, 2021) in the Hindon catchment provided in Table 4. Table 4: Annual groundwater extraction (MCM) of the main districts in the Hindon catchment District Irrigation Industrial Domestic Haridwar (UK) -- -- -- Saharanpur (UP) 125786.56 -- 6976.31 Muzaffarnagar (UP) 71932.20 -- 6555.94 Shamli (UP) 41319.36 -- 3009.89 Meerut (UP) 52687.00 -- 8766.22 Bagpat (UP) 35149.16 -- 2.45 Ghaziabad (UP) 37002.24 -- 8060.3 Gautam Budh Nagar (UP) 60634.0 -- 1530.81 5. Water Availability To understand the water risk in the Hindon catchment water availability needs to calculate After the detailed understanding of catchment profile water balance approach have been used to calculate the water balance. It will also help us to understand to connect this with local economy, business and health impacts. This analysis supports decision-makers in planning and implementing timely interventions to mitigate the effects of climate change. 5.1 Water Balance in Hindon Catchment The primary use of water is agriculture which around 70% and sugarcane is main crop. Sugarcane is a water intensive crop. Here water balance approach used to estimate water availability and common factors used to do so. These factors are: soil type, land use, and vegetation cover. For the runoff coefficient, soil and land use parameter used and in the case of Hindon catchment soil is loamy and agriculture is the main land use and this case the runoff coefficient[5] is 0.30. The annual runoff = = Average annual rainfall(mm) X Runoff coefficient =796 X 0.30 =238.8mm The key components of the water balance: Component Value Average Annual Rainfall (mm) 796 Runoff (mm) 238.8 Evapotranspiration (ET) 900 Groundwater Recharge (mm) 200 The water availability is calculated using the formula: Water balance = Precipitation (mm) - Runoff – Evapotranspiration (mm) Water balance = 796 – 238.8 - 900 = -342.8 mm/year The water availability in the Hindon catchment is negative means water deficit that translate annual shortage of approximately 2,136 MCM (342.8 mm/year × 6,232 km²) necessitating continued reliance on groundwater or external supply (e.g., Ganga canal) or indicating that there is not enough water to meet the demands of the catchment. 6. Sectoral Risk Analysis 6.1 Agricultural Risk Crop like sugarcane and paddy demand 1500-2500mm/year and water stress may reduce sugarcane yields by 20-30%. The estimated economic loss is ₹150-200 million annually for sugarcane alone and 70% of the local population is dependent on agriculture. 6.2 Industrial Risk · Industrial zones (e.g. Noida, Ghaziabad) extract large volumes of groundwater · Regulatory restrictions on extraction pose operational risks. · Water scarcity may cause supply disruptions and financial instability. 6.3 Domestic Water Supply · Urban centres increasingly rely in groundwater withdrawn from overexploited blocks. · Public health threats and potential drinking water shortages · Rapidly urbanization nodes like Ghaziabad face growing per capita demand 6.4 Environmental and Ecological Risks · Low lean season baseflow due to groundwater decline · Degradation of riparian ecosystems, loss of urban green spaces. 6.5 Socioeconomic Risks · Risk of out-migration from rural areas to crop failure and employment loss · Water-Related conflicts among competing user sectors (agriculture vs. urban/industrial) 7. Sensitivity Analysis To understand how variations in key parameters affect water availability, a sensitivity analysis (Table 5) was performed by adjusting each parameter while holding others constant: Table 5: Sensitivity analysis Parameter Value Water Balance (mm/year) Change from Base (mm) Change from Base (%) Precipitation (mm) 700 -410 -67.2 -19.60 Precipitation (mm) 750 -375 -32.2 -9.39 Precipitation (mm) 800 -340 2.8 0.82 Precipitation (mm) 850 -305 37.8 11.03 Precipitation (mm) 900 -270 72.8 21.24 Precipitation (mm) 950 -235 107.8 31.45 Precipitation (mm) 1000 -200 142.8 41.66 Runoff Coefficient 0.2 -263.2 79.6 23.22 Runoff Coefficient 0.25 -303 39.8 11.61 Runoff Coefficient 0.3 -342.8 0 0.00 Runoff Coefficient 0.35 -382.6 -39.8 -11.61 Runoff Coefficient 0.4 -422.4 -79.6 -23.22 Evapotranspiration (mm) 800 -242.8 100 29.17 Evapotranspiration (mm) 850 -292.8 50 14.59 Evapotranspiration (mm) 900 -342.8 0 0.00 Evapotranspiration (mm) 950 -392.8 -50 -14.59 Evapotranspiration (mm) 1000 -442.8 -100 -29.17 Based on the sensitivity analysis the key findings are tabulated in Table 6. Table 6: Key findings from sensitivity analysis Precipitation Impact A 19% increase in annual rainfall (to 950 mm) would improve the water balance by 31.4%, but would still leave a significant deficit of -235 mm/year. Evapotranspiration Dominance Changes in evapotranspiration have the most direct impact on water balance. An 11% reduction in ET (to 800 mm) would improve the water balance by 29.2%. Runoff Management Reducing the runoff coefficient from 0.30 to 0.20 through better water harvesting and infiltration would improve the water balance by 11.7%. Breaking Even Point To achieve water balance equilibrium (zero deficit) with current evapotranspiration and runoff coefficient values, the catchment would require annual precipitation of approximately 1,285 mm—a 61% increase from current levels, which is climatologically improbable. Combined Approach Even with optimistic improvements to individual parameters, the catchment would still face a water deficit. This underscores the need for comprehensive interventions targeting multiple aspects of the water cycle. 8. Recommendations · Hydrological monitoring: Real time assessment of river flows and quality · Crop diversification: Switch from water intensive sugarcane to less water demanding crops · STP/ETP Optimization: prevent untreated discharge into the river · Nature based solutions: Wetlands and recharge zone for aquifer recovery · Decision Support Systems: Integrate spatial and temporal data for water management planning. 9. Conclusion The Hindon river basin embodies the broader challenge of water scarcity in India’s rapidly urbanizing and agrarian contexts. The study establishes that business- as-usual practices are unsustainable against a background of declining water availability, overexploited groundwater blocks, and insufficient sectoral use. To enable long-term water resilience, a cross – sectoral, data driven approach forcing on ecological restoration, demand management, and policy integration is critical. increasing demand for water and the impacts of climate change necessitates timely planning and interventions. Restoration and rejuvenation of existing water resources, such as the Hindon River, are essential. The Hindon River holds significant potential to supplement the Ganga water in certain areas. A holistic approach to managing water resources, particularly the Hindon River, is crucial. Declarations Authors Contributions: There is no other author involved in this research. I am the only who conceptualize, design, analysis and interpretation of data. Competing Interest Declaration: I declare that there are no competing interests related to the research, authorships, or publication of this research. Funding: This is my independent work and my interest. This work did not receive any funding. References Board, U. P. (n.d.). Action Plan for restoration of polluted stretch of river Hindon from district Saharanpur to district Ghaziabad. Uttar Pradesh Pollution Control Board . Idrisi, B. &. (2020). Guide to Preparing River Basin Management Plans for Medium and Minor Rivers [Making Rivers Flow]. New Delhi: Natural Heritage Division, INTACH. Karra, K. e. (2021). Global land use/land cover with Sentinel-2 and deep learning. IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE . Lewis, H. (2007). Hindon River: Gasping for Breath. New Delhi: Janhit Foundation. Mayuri Chabukdhara, A. K. (2012). Assessment of heavy metal contamination in Hindon River sediments: A chemometric and geochemical approach. Science Direct . Region, G. W. (2021). DYNAMIC GROUND WATER RESOURCES. Lucknow: Government of Uttar Pradesh. Welfare, D. o. (2019). Agriculture Contingency Plan for District: Muzaffarnagar . https://agriwelfare.gov.in/en/AgricultureContigencyPlan/UTTAR%20PRADESH?page=3. Welfare, D. o. (2019). Agriculture Contingency Plan for District: Saharanpur . Department of Agriculture and Family Welfare (https://agriwelfare.gov.in/en/AgricultureContigencyPlan/UTTAR%20PRADESH?page=4). Footnotes [1] Ghaziabad Annual Weather Averages - Uttar Pradesh, IN (worldweatheronline.com) [2] Bhuvan Store (nrsc.gov.in) [3] https://earlywarning.usgs.gov/fews/product/458/ [4] https://www.teriin.org/sites/default/files/2021-06/water-factsheet.pdf [5] Potential runoff coefficient for different land use, soil type and slope. | Download Table (researchgate.net) Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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catchment\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7210895/v1/a42686743f42c59dd136e96a.png"},{"id":87692168,"identity":"e56b0e27-1aca-4398-b4bb-d3f41741e238","added_by":"auto","created_at":"2025-07-28 04:56:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":114554,"visible":true,"origin":"","legend":"\u003cp\u003eLand use classification of Hindon Catchment\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7210895/v1/fa9a329837920119265a0e20.png"},{"id":87692177,"identity":"9f1b913e-1c49-4edf-b2dd-9196090e6c0e","added_by":"auto","created_at":"2025-07-28 04:56:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":31060,"visible":true,"origin":"","legend":"\u003cp\u003eSoil type in the Hindon catchment\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7210895/v1/15d0675918c1d2b66e4fbe0d.png"},{"id":87692162,"identity":"e61daa4c-0790-4b1d-a66c-29d5e17354e5","added_by":"auto","created_at":"2025-07-28 04:56:02","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":89241,"visible":true,"origin":"","legend":"\u003cp\u003eGroundwater status of Hindon Catchment\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7210895/v1/517055b8ed609873508fa9ce.png"},{"id":87692181,"identity":"ef47842d-cc68-4073-9794-23fd3885513c","added_by":"auto","created_at":"2025-07-28 04:56:03","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":56498,"visible":true,"origin":"","legend":"\u003cp\u003eEvapotranspiration(mm/yr) of Hindon catchment\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7210895/v1/ee50c0b3b4ba583e6e8d7271.png"},{"id":88505159,"identity":"57c1a9dd-0256-473f-abf1-b408adcc4375","added_by":"auto","created_at":"2025-08-07 07:19:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1997062,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7210895/v1/e7170fba-300f-4747-85bf-ce65972614fd.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eWater Risk Assessment in the Hindon Catchment, India: Challenges and Opportunities for Resilience Building\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIndia faces mounting pressures to reconcile rapid development with sustainable water management. With over 20 major river basins and numerous smaller tributaries, understanding water dynamics at sub \u0026ndash; basin levels is essential.\u003c/p\u003e\n\u003cp\u003eThe Hindon River catchment, part of the Yamuna basin, originates from Saharanpur district of Uttar Pradesh, flows 350km, draining into the Yamuna River. It traverses mixed land -use zones including high- density urban areas and water \u0026ndash; water intensive agricultural zones. The catchment also touches or very small portion of Delhi. The Kali and Krishni rivers are the main tributary of the Hindon river. The location of the Hindon catchment given in Figure 1.\u003c/p\u003e\n\u003cp\u003eOnce supporting domestic water needs, the Hindon River is now severely polluted and primarily serves non-potable uses such as livestock washing (Lewis, 2007). With erratic precipitation patterns, intense agricultural pressure, and unregulated groundwater withdrawal assessing water risk in this basin is urgent.\u003c/p\u003e"},{"header":"2. Objectives","content":"\u003cp\u003eThe study pursues the following objectives:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.\u0026nbsp; \u0026nbsp;Assess systematic water risks in the Hindon catchment\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp;Identify region specific vulnerabilities in agriculture, domestic, and industrial sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3. \u0026nbsp; Propose actionable frameworks to enhance long-term water resilience.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThe following method adopted to do this assignment given in Figure 2. A simple method used to conduct this study. The details of data sources and framework provided in the following sections.\u003c/p\u003e\n\u003cp\u003eThis integrated methodological approach enables a comprehensive understanding of water risks in the Hindon catchment while providing a foundation for identifying targeted interventions to build water resilience in the region.\u003c/p\u003e\n\u003ch2\u003e3.1 Data Collection and Sources\u003c/h2\u003e\n\u003cp\u003eThis study relies on multiple open sources datasets provided in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1: data sources used for the study\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"306\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eData\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSources\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHydrological data\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eRainfall from IMD (10 years),\u003c/p\u003e\n \u003cp\u003eFormat- NetCDF\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eIndian Meteorological Department (IMD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eEvapotranspiration,\u003c/p\u003e\n \u003cp\u003eFormat-GeoTiff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eUSGS -MODIS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eGroundwater\u003c/p\u003e\n \u003cp\u003eFomat- Excel/PDF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCentral Groundwater Board\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpatial datasets\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSRTM 30m DEM,\u003c/p\u003e\n \u003cp\u003eFormat -GeoTiff\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eUSGS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eLand use land cover,\u003c/p\u003e\n \u003cp\u003eResolution -10m,\u003c/p\u003e\n \u003cp\u003eFormat- GeoTiff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eSentinel-2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSoil,\u003c/p\u003e\n \u003cp\u003eFormat-Shapefile\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eFAO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment reports and assessments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eCGWB groundwater reports\u003c/p\u003e\n \u003cp\u003ePollution Control Borad water quality monitoring data\u003c/p\u003e\n \u003cp\u003eDistrict agricultural contingency plans,\u003c/p\u003e\n \u003cp\u003eFormat- PDF, Text\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.1\u0026nbsp;Analytical Framework\u003c/h2\u003e\n\u003cp\u003eThe methodology integrates spatial analysis, water balance modelling, and sensitivity analyses:\u003c/p\u003e\n\u003cp\u003e\u0026middot; Watershed delineation in QGIS using SRTM DEM\u003c/p\u003e\n\u003cp\u003e\u0026middot; Run off estimates via land use and soil -based coefficient methods\u003c/p\u003e\n\u003cp\u003e\u0026middot; Water quality and groundwater status assessment using CGWB datasets\u003c/p\u003e\n\u003cp\u003e\u0026middot; Water balance:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWater Availability = P \u0026ndash; Q - ET\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWhere P = Precipitation, Q = Runoff, ET = Evapotranspiration\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp;Tools Used\u003c/h2\u003e\n\u003cp\u003e\u0026middot; QGIS for spatial analysis and watershed modelling\u003c/p\u003e\n\u003cp\u003e\u0026middot; Python scripting for data cleaning, time series analyses, and model integration\u003c/p\u003e"},{"header":"4.\tCatchment Profile ","content":"\u003ch2\u003e4.1\u0026nbsp;Administrative Coverage\u003c/h2\u003e\n\u003cp\u003eThe Hindon catchment spans across 11 districts, predominantly in Uttar Pradesh, and includes key urban-industrial hubs and agriculture belts. The largest shares lie within Saharanpur (1,808 km\u003csup\u003e2\u003c/sup\u003e) and Muzaffarnagar (1,550 km\u003csup\u003e2\u003c/sup\u003e) districts. The district wise area distribution provided in Table 2 and shown in Figure 3.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2: District comes under the Hindon catchment\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"284\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDISTRICT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSTATE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAREA (Km\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eHaridwar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttarakhand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e318.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eSaharanpur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1808.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eMuzaffarnagar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1557.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eShamli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e541.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eMeerut\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e361.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eBagpat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e721.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eGhaziabad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e524.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eGautam Budh Nagar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUttar Pradesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e340.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eEast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDelhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e16.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDelhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e8.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eShahdara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDelhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e28.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch2\u003e4.2 Climate\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe climate ranges from tropical to temperate with temperature variation up to 3 \u0026deg;C in winter and up to 43 \u0026deg;C in summer and mean annual rainfall of 702 mm subjected to spatial variations (Mayuri Chabukdhara, 2012). The weather averages for the month of October, temperature averages around 33\u0026deg;c and at night it feels like 22\u0026deg;c. In October, Ghaziabad gets on an average 28.11mm of rain[1] and approximately 2 rainy days in the month. The rainfall pattern shown in Figure 4. Humidity is close to 40%. The highest average rainfall occurs during the month of June\u0026ndash;September (monsoon period).\u003c/p\u003e\n\u003ch2\u003e4.3\u0026nbsp;Topography\u003c/h2\u003e\n\u003cp\u003eThe elevation range of the Hindon catchment range is 180 m to 880m. SRTM 90m digital elevation model (DEM) used for elevation profile and the slope (Figure 5).\u003c/p\u003e\n\u003ch2\u003e4.4\u0026nbsp;Land-Use\u003c/h2\u003e\n\u003cp\u003eThe predominant land-use in the Hindon catchment area is primarily agricultural, with a notable presence of built-up urban areas. Specifically, there has been substantial urban development, particularly in the Ghaziabad and Gautam Budh Nagar districts. The land use taken from the Sentinel-2 of the year 2022 (Karra, 2021). The land use classification given in Table 3 and shown in Figure 6.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;3: Land use classification\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"293\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClassification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea (km\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 161px;\"\u003e\n \u003cp\u003eWater Bodies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 161px;\"\u003e\n \u003cp\u003eForest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 161px;\"\u003e\n \u003cp\u003eAgriculture Land\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 161px;\"\u003e\n \u003cp\u003eBuilt up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 161px;\"\u003e\n \u003cp\u003eBare Ground\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e4.5\u0026nbsp;Soil\u003c/h2\u003e\n\u003cp\u003eThe soil[2] in the Hindon catchment mainly loamy in texture and depth of soil is between 100-150cm. The type of soil given in Figure 7.\u003c/p\u003e\n\u003ch2\u003e4.6\u0026nbsp;Groundwater\u003c/h2\u003e\n\u003cp\u003eGroundwater status is the key indicator of water risk of any area. There are 46 administrative blocks are coming where groundwater status assessed. 18 blocks in the catchment are over exploited and 5 are in critical stage. The status of groundwater status shown in Figure 8. The data have been taken from the CGWB groundwater assessment report 2022 and 2024. This shows the water shortage in the future and can impact the local business.\u003c/p\u003e\n\u003ch2\u003e4.7\u0026nbsp;Evapotranspiration\u003c/h2\u003e\n\u003cp\u003eThe average evapotranspiration[3] of Hindon catchment is 900mm/year shown in Figure 9. The figure also depicts that evapotranspiration is high in the agriculture areas (green in colour) and evapotranspiration is low in the built-up areas (red colour).\u003c/p\u003e\n\u003ch2\u003e4.8\u0026nbsp;Water uses\u003c/h2\u003e\n\u003cp\u003eIndia\u0026rsquo;s water use[4] is heavily dominated by agriculture (85%) due to water intensive crops. Urban and rural water benchmarks are 135 and 55 lpcd respectively, but the actual per capita water footprint is far higher due to water use in food, energy, and goods production. Growing demands, especially in cities and industries, risks severe water scarcity by 2030. This also applicable for Hindon catchment where more than 70% are is agriculture and followed by built up (Ghaziabad, Noida and Saharanpur are major cities etc.,).The district wise annual groundwater extraction ( (Region, 2021) in the Hindon catchment provided in \u0026nbsp;Table 4.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;4: Annual groundwater extraction (MCM) of the main districts in the Hindon catchment\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistrict\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIrrigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndustrial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDomestic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eHaridwar (UK)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eSaharanpur (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e125786.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e6976.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eMuzaffarnagar (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e71932.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e6555.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eShamli (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e41319.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e3009.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eMeerut (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e52687.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e8766.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eBagpat (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e35149.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eGhaziabad (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e37002.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e8060.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eGautam Budh Nagar (UP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e60634.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1530.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"5.\tWater Availability","content":"\u003cp\u003eTo understand the water risk in the Hindon catchment water availability needs to calculate After the detailed understanding of catchment profile water balance approach have been used to calculate the water balance. It will also help us to understand to connect this with local economy, business and health impacts.\u003c/p\u003e\n\u003cp\u003eThis analysis supports decision-makers in planning and implementing timely interventions to mitigate the effects of climate change.\u003c/p\u003e\n\u003ch2\u003e5.1\u0026nbsp;Water Balance in Hindon Catchment\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe primary use of water is agriculture which around 70% and sugarcane is main crop. Sugarcane is a water intensive crop. Here water balance approach used to estimate water availability and common factors used to do so. These factors are: soil type, land use, and vegetation cover.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the runoff coefficient, soil and land use parameter used and in the case of Hindon catchment soil is loamy and agriculture is the main land use and this case the runoff coefficient[5] is 0.30.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe annual runoff =\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;= Average annual rainfall(mm) X Runoff coefficient\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;=796 X 0.30\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e=238.8mm\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe key components of the water balance:\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"293\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComponent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAverage Annual Rainfall (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e796\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eRunoff (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e238.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eEvapotranspiration (ET)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eGroundwater Recharge (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe water availability is calculated using the formula:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWater balance = Precipitation (mm) - Runoff \u0026ndash; Evapotranspiration (mm)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWater balance = 796 \u0026ndash; 238.8 - 900 = -342.8 mm/year\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe water availability in the Hindon catchment is negative means water deficit that translate annual shortage of approximately 2,136 MCM (342.8 mm/year \u0026times; 6,232 km\u0026sup2;) necessitating continued reliance on groundwater or external supply (e.g., Ganga canal) or indicating that there is not enough water to meet the demands of the catchment.\u0026nbsp;\u003c/p\u003e"},{"header":"6.\tSectoral Risk Analysis","content":"\u003ch2\u003e6.1\u0026nbsp;Agricultural Risk\u003c/h2\u003e\n\u003cp\u003eCrop like sugarcane and paddy demand 1500-2500mm/year and water stress may reduce sugarcane yields by 20-30%. The estimated economic loss is ₹150-200 million annually for sugarcane alone and 70% of the local population is dependent on agriculture.\u003c/p\u003e\n\u003ch2\u003e6.2\u0026nbsp;Industrial Risk\u003c/h2\u003e\n\u003cp\u003e\u0026middot; Industrial zones (e.g. Noida, Ghaziabad) extract large volumes of groundwater\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Regulatory restrictions on extraction pose operational risks.\u003c/p\u003e\n\u003cp\u003e\u0026middot; Water scarcity may cause supply disruptions and financial instability.\u003c/p\u003e\n\u003ch2\u003e6.3\u0026nbsp;Domestic Water Supply\u003c/h2\u003e\n\u003cp\u003e\u0026middot; Urban centres increasingly rely in groundwater withdrawn from overexploited blocks.\u003c/p\u003e\n\u003cp\u003e\u0026middot; Public health threats and potential drinking water shortages\u003c/p\u003e\n\u003cp\u003e\u0026middot; Rapidly urbanization nodes like Ghaziabad face growing per capita demand\u003c/p\u003e\n\u003ch2\u003e6.4\u0026nbsp;Environmental and Ecological Risks\u003c/h2\u003e\n\u003cp\u003e\u0026middot; Low lean season baseflow due to groundwater decline\u003c/p\u003e\n\u003cp\u003e\u0026middot; Degradation of riparian ecosystems, loss of urban green spaces.\u003c/p\u003e\n\u003ch2\u003e6.5\u0026nbsp;Socioeconomic Risks\u003c/h2\u003e\n\u003cp\u003e\u0026middot; Risk of out-migration from rural areas to crop failure and employment loss\u003c/p\u003e\n\u003cp\u003e\u0026middot; Water-Related conflicts among competing user sectors (agriculture vs. urban/industrial)\u003c/p\u003e"},{"header":"7.\tSensitivity Analysis","content":"\u003cp\u003eTo understand how variations in key parameters affect water availability, a sensitivity analysis (Table 5) was performed by adjusting each parameter while holding others constant:\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;5: Sensitivity analysis\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"292\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWater Balance (mm/year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange from Base (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange from Base (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-67.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-19.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-9.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e11.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e72.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e21.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e107.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e31.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003ePrecipitation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e142.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e41.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eRunoff Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-263.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e79.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e23.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eRunoff Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e39.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e11.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eRunoff Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-342.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eRunoff Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-382.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-39.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-11.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eRunoff Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-422.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-79.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-23.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eEvapotranspiration (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-242.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e29.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eEvapotranspiration (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-292.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e14.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eEvapotranspiration (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-342.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eEvapotranspiration (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-392.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-14.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eEvapotranspiration (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 41px;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-442.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-29.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eBased on the sensitivity analysis the key findings are tabulated in Table 6.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;6: Key findings from sensitivity analysis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"296\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003ePrecipitation Impact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003eA 19% increase in annual rainfall (to 950 mm) would improve the water balance by 31.4%, but would still leave a significant deficit of -235 mm/year.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eEvapotranspiration\u003c/p\u003e\n \u003cp\u003eDominance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003eChanges in evapotranspiration have the most direct impact on water balance. An 11% reduction in ET (to 800 mm) would improve the water balance by 29.2%.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRunoff Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003eReducing the runoff coefficient from 0.30 to 0.20 through better water harvesting and infiltration would improve the water balance by 11.7%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBreaking Even Point\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003eTo achieve water balance equilibrium (zero deficit) with current evapotranspiration and runoff coefficient values, the catchment would require annual precipitation of approximately 1,285 mm\u0026mdash;a 61% increase from current levels, which is climatologically improbable.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eCombined Approach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003eEven with optimistic improvements to individual parameters, the catchment would still face a water deficit. This underscores the need for comprehensive interventions targeting multiple aspects of the water cycle.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"8.\tRecommendations ","content":"\u003cp\u003e\u0026middot; \u003cstrong\u003eHydrological monitoring:\u003c/strong\u003e Real time assessment of river flows and quality\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u003cstrong\u003eCrop diversification:\u003c/strong\u003e Switch from water intensive sugarcane to less water demanding crops\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u003cstrong\u003eSTP/ETP Optimization:\u003c/strong\u003e prevent untreated discharge into the river\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u003cstrong\u003eNature based solutions:\u003c/strong\u003e Wetlands and recharge zone for aquifer recovery\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u003cstrong\u003eDecision Support Systems:\u003c/strong\u003e Integrate spatial and temporal data for water management planning.\u003c/p\u003e"},{"header":"9. Conclusion","content":"\u003cp\u003eThe Hindon river basin embodies the broader challenge of water scarcity in India\u0026rsquo;s rapidly urbanizing and agrarian contexts. The study establishes that business- as-usual practices are unsustainable against a background of declining water availability, overexploited groundwater blocks, and insufficient sectoral use. To enable long-term water resilience, a cross \u0026ndash; sectoral, data driven approach forcing on ecological restoration, demand management, and policy integration is critical.\u003c/p\u003e\n\u003cp\u003eincreasing demand for water and the impacts of climate change necessitates timely planning and interventions. Restoration and rejuvenation of existing water resources, such as the Hindon River, are essential. The Hindon River holds significant potential to supplement the Ganga water in certain areas. A holistic approach to managing water resources, particularly the Hindon River, is crucial.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no other author involved in this research. I am the only who conceptualize, design, analysis and interpretation of data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest Declaration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI declare that there are no competing interests related to the research, authorships, or publication of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is my independent work and my interest. This work did not receive any funding.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBoard, U. P. (n.d.). \u003cem\u003eAction Plan for restoration of polluted stretch of river Hindon from district Saharanpur to district Ghaziabad.\u003c/em\u003e Uttar Pradesh Pollution Control Board .\u003c/li\u003e\n \u003cli\u003eIdrisi, B. \u0026amp;. (2020). \u003cem\u003eGuide to Preparing River Basin Management Plans for Medium and Minor Rivers [Making Rivers Flow].\u003c/em\u003e New Delhi: Natural Heritage Division, INTACH.\u003c/li\u003e\n \u003cli\u003eKarra, K. e. (2021). Global land use/land cover with Sentinel-2 and deep learning. \u003cem\u003eIGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eLewis, H. (2007). \u003cem\u003eHindon River: Gasping for Breath.\u003c/em\u003e New Delhi: Janhit Foundation.\u003c/li\u003e\n \u003cli\u003eMayuri Chabukdhara, A. K. (2012). Assessment of heavy metal contamination in Hindon River sediments: A chemometric and geochemical approach. \u003cem\u003eScience Direct\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eRegion, G. W. (2021). DYNAMIC GROUND WATER RESOURCES. Lucknow: Government of Uttar Pradesh.\u003c/li\u003e\n \u003cli\u003eWelfare, D. o. (2019). \u003cem\u003eAgriculture Contingency Plan for District: Muzaffarnagar .\u003c/em\u003e https://agriwelfare.gov.in/en/AgricultureContigencyPlan/UTTAR%20PRADESH?page=3.\u003c/li\u003e\n \u003cli\u003eWelfare, D. o. (2019). \u003cem\u003eAgriculture Contingency Plan for District: Saharanpur .\u003c/em\u003e Department of Agriculture and Family Welfare (https://agriwelfare.gov.in/en/AgricultureContigencyPlan/UTTAR%20PRADESH?page=4).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\n\u003cp\u003e[1] Ghaziabad Annual Weather Averages - Uttar Pradesh, IN (worldweatheronline.com)\u003c/p\u003e\n\u003cp\u003e[2] Bhuvan Store (nrsc.gov.in)\u003c/p\u003e\n\u003cp\u003e[3] https://earlywarning.usgs.gov/fews/product/458/\u003c/p\u003e\n\u003cp\u003e[4] https://www.teriin.org/sites/default/files/2021-06/water-factsheet.pdf\u003c/p\u003e\n\u003cp\u003e[5] Potential runoff coefficient for different land use, soil type and slope. | Download Table (researchgate.net)\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"No","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hindon River, groundwater depletion, water balance, catchment management, evapotranspiration, agricultural risk, GIS-based assessment","lastPublishedDoi":"10.21203/rs.3.rs-7210895/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7210895/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIndia's rapidly expanding population and industrial base have resulted in escalating water demand, increasingly outpacing available supply and degrading water quality. The Hindon River, a tributary of the Yamuna, exemplifies these challenges across 6,232 km2 catchment, encompassing diverse land-use zones from agricultural plains to urban centres like Ghaziabad and Gautam Budh Nagar. This study applies a water balance methodology using open -sources datasets, QGIS, and python -based analytics to assess hydrological trends, groundwater dynamics, evapotranspiration, and land-use impacts in the Hindon catchment. Results reveal a critical water deficit of -342.8 mm/year, driven by overextraction of groundwater, water intensive crops, and high evapotranspiration losses. The paper outlines sectoral vulnerabilities across agriculture, industry, and domestic supply, and proposes a multi-pronged strategy encompassing crop diversification, real-time monitoring, urban water body restoration, and nature – based solutions for building long-term water resilience.\u003c/p\u003e","manuscriptTitle":"Water Risk Assessment in the Hindon Catchment, India: Challenges and Opportunities for Resilience Building","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 04:55:58","doi":"10.21203/rs.3.rs-7210895/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":"b5a40628-5480-47e0-a094-6d501036f0e6","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52099813,"name":"Hydrology"},{"id":52099814,"name":"Geographic Information Systems"},{"id":52099815,"name":"Urban Studies"}],"tags":[],"updatedAt":"2025-07-28T04:55:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 04:55:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7210895","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7210895","identity":"rs-7210895","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}