Journal of Hydrology-Regional Studies最新文献

{"title":"Groundwater in arid environments: A review of uranium occurrence and impacts","authors":"Laurica Celeste Afrikaner ,&nbsp;Benjamin Mapani ,&nbsp;Hilma Amwele","doi":"10.1016/j.ejrh.2025.102814","DOIUrl":"10.1016/j.ejrh.2025.102814","url":null,"abstract":"<div><h3>Study region</h3><div>This review focuses on major uranium-producing arid regions, including Australia, Chile, Kazakhstan, the USA, Niger, South Africa, and Namibia. These regions are globally significant not only for their uranium deposits but also because communities rely heavily on groundwater as a primary drinking water source.</div></div><div><h3>Study focus</h3><div>The paper synthesises existing knowledge on the occurrence of uranium in groundwater across these arid environments, examining its impacts on water quality and associated health risks. It further evaluates available remediation technologies and considers their applicability under diverse hydrogeological and socio-economic settings. Unlike previous studies limited to individual sites or countries, this review provides a cross-regional comparison that integrates hydrochemical, radiological, and remediation perspectives.</div></div><div><h3>New hydrological insights for the region</h3><div>The analysis reveals recurring hydrogeochemical challenges in arid uranium provinces, particularly the limited application of isotopic tracers, radionuclide monitoring, and advanced groundwater modelling. By comparing case studies across continents, the review identifies consistent knowledge gaps and emphasises that remediation strategies must be tailored to local hydrogeology and cost constraints. This synthesis presents a novel global perspective on understanding uranium-related groundwater risks in arid regions and outlines a roadmap for future research and adaptive water management.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102814"},"PeriodicalIF":5.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantification and classification of supply-flow-demand in the water supply services","authors":"Shi Chen ,&nbsp;Dongjie Guan ,&nbsp;Lilei Zhou ,&nbsp;Jiameng Cao ,&nbsp;Zhifeng Liu","doi":"10.1016/j.ejrh.2025.102794","DOIUrl":"10.1016/j.ejrh.2025.102794","url":null,"abstract":"<div><h3>Study region</h3><div>The Yangtze River Basin (YRB), China.</div></div><div><h3>Study focus</h3><div>The supply-flow-demand process of water supply services (WSSs) directly affects the sustainable development of regional water resources. In this study, a large basin soil and water assessment tool (SWAT) model was constructed to simulate the supply of WSSs. The competitive and non-competitive water demands were evaluated, and the primary factors influencing water demand were identified. On the basis of the service path distribution network (SPAN) model, a new standard for classifying WSSs flows was introduced, five flow types were clearly defined, and the flow characteristics of WSSs were explored.</div></div><div><h3>New hydrological insights</h3><div>The constructed WSSs supply and demand assessment model has good applicability in the YRB. Emphasizing non-competitive demand can help provide a more comprehensive assessment of the water supply and demand status. Both supply and demand clearly exhibit spatiotemporal heterogeneity. The total amounts of supply, competitive demand and non-competitive demand have increased by 36.88 %, 2.11 % and 11.5 % respectively. The flow order of the five flow types was: protection &gt; gain &gt; attenuation &gt; non-loss &gt; jam, and the flow rate of all types increased. The proposed classification and identification method for WSSs flow can be used to analyze the water resource status of a basin effectively and provide a scientific basis for the sustainable development of water resources in the YRB.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102794"},"PeriodicalIF":5.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydro-power dam construction and water availability in the Bui Basin of Ghana","authors":"Samuel Nana Safo Kantanka ,&nbsp;Michael Addaney ,&nbsp;Prosper Kpiebaya ,&nbsp;Jonas Ayaribilla Akudugu ,&nbsp;Benjamin Wullobayi Dekongmen","doi":"10.1016/j.ejrh.2025.102813","DOIUrl":"10.1016/j.ejrh.2025.102813","url":null,"abstract":"<div><h3>Study region</h3><div>Bui River Basin, Bono Region, Ghana</div></div><div><h3>Study focus</h3><div>This study evaluates the hydrological impacts of the 400 megawatt hydroelectric Bui Dam built on Ghana’s Black Volta River using remote sensing, GIS, the InVEST water yield model, and IHA analysis. The InVEST model estimated a progressive increase in annual water yield, from 3.25 MCM (2000) to 4.75 MCM (2020), with a net rise of 1.50 MCM over the study period. This trend correlated with land-use changes, including forest decline (81.4–35.8 % coverage) and urban expansion (24,713.48 ha to 95,207 ha).</div></div><div><h3>New hydrologic insights</h3><div>The IHA analysis revealed severe hydrological alterations, including a 92-day extension of dry-season flows and earlier wet-season peaks by 10 days, disrupting ecological and livelihood systems. Model validation showed strong agreement between observed and simulated yields (NSE &gt; 0.8, R² &gt; 0.85). The findings highlight trade-offs between hydropower generation and riverine ecosystem integrity, emphasizing the need for adaptive dam management to sustain water availability.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102813"},"PeriodicalIF":5.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment on the influence of environmental changes on hydrothermal processes in extremely arid inland basins: Evidence from remote sensing data","authors":"Xudong Zhang ,&nbsp;Congjian Sun ,&nbsp;Wei Chen","doi":"10.1016/j.ejrh.2025.102817","DOIUrl":"10.1016/j.ejrh.2025.102817","url":null,"abstract":"<div><h3>Study region</h3><div>the Tarim River Basin (TRB), China.</div></div><div><h3>Study focus</h3><div>We based on surface hydrothermal data, along with LUCC and major environmental factors from three ecosystems in the mountain, oasis, and desert regions of the TRB from 1990 to 2022, and investigated the response of surface hydrothermal processes in different ecosystems to LUCC and climate change.</div></div><div><h3>New insights into the response of surface hydrothermal processes in different ecosystems to LUCC and climate change</h3><div>Significant expansion of cropland and impervious areas occurred in the oasis regions (+15,091.2 km² and +2329.7 km², respectively), primarily through conversion of grasslands and barren lands. Glacier/snow areas of the mountains region reduction (-1192.7 km²), while desert regions showed enhanced land utilization with barren land decrease (-1366.3 km²). (2) Regional land surface temperature (LST) demonstrated an upward trend (<em>P</em> &lt; 0.01). Soil moisture (SM) declined significantly, particularly in the winter of the oases region (-0.0006 m³/m³ yr⁻¹, <em>P</em> &lt; 0.05). Except for the mountain area, the actual evapotranspiration (AET) showed a downward trend. (3) Conversion to forests/grasslands significantly suppressed regional LST increasing, decelerated SM decline, and enhanced AET. Conversely, conversion to impervious areas intensified regional LST rising and SM depletion. (4) Hydrothermal drivers exhibited significant spatiotemporal heterogeneity. Solar radiation (SRAD) dominated regional LST variability (70.7 % summer explanatory power in mountainous regions), PRE governed regional AET variability (exceeding 80 % explanatory power in oasis regions), and regional SM was jointly controlled by regional LST and PRE. The results of this study will provide a crucial scientific basis for regional ecological protection and climate change response.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102817"},"PeriodicalIF":5.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional water supply capacity assessment in different drought scenarios based on Budyko supply and demand framework","authors":"Liyuan Wang,&nbsp;Xuebin Wang,&nbsp;Jianxia Chang,&nbsp;Yimin Wang,&nbsp;Xuejiao Meng,&nbsp;Chengqing Ren,&nbsp;Zhiwen Peng","doi":"10.1016/j.ejrh.2025.102804","DOIUrl":"10.1016/j.ejrh.2025.102804","url":null,"abstract":"<div><h3>Study region</h3><div>Chuxiong Yi Autonomous Prefecture in Yunnan Province, China.</div></div><div><h3>Study focus</h3><div>This study aims to assess water resource availability under extreme drought conditions by developing a Budyko supply-demand framework. This approach integrates hydrological engineering measures and drought scenarios to evaluate monthly-scale water supply capacity (WSC), estimate WSC for low-probability extreme drought events, and identify key factors influencing WSC variations through elasticity analysis.</div></div><div><h3>New hydrological insights</h3><div>The study highlights substantial regional variations in water supply capacity across Chuxiong, with severe deficits noted in areas like Yuanmou County, particularly during drought years. Sensitivity analysis shows that water demand exerts a stronger influence on water supply reliability than water availability, especially in regions with high demand elasticity such as Yuanmou and Wuding This underscores the critical role of demand management in addressing water shortages. Moreover, while the region’s water supply is constrained by existing infrastructure, improvements in distribution networks and efficient management practices can significantly mitigate the effects of fluctuating demand. By successfully reconstructing long-term water supply processes and capturing the impacts of extreme drought events, the research provides valuable insights into the hydrological dynamics of the region. These findings are essential for developing strategies to enhance water resource resilience, support sustainable development, and address global water security challenges amid climate variability and human-induced changes.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102804"},"PeriodicalIF":5.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal variation of actual evapotranspiration in a transboundary river basin based on MGWR downscaling","authors":"Boyang Li ,&nbsp;Hangnan Yu ,&nbsp;Jing Zhao ,&nbsp;Jiangtao Yu ,&nbsp;Xinyue Gao ,&nbsp;Weihong Zhu","doi":"10.1016/j.ejrh.2025.102803","DOIUrl":"10.1016/j.ejrh.2025.102803","url":null,"abstract":"<div><h3>Study region</h3><div>Tumen River Basin.</div></div><div><h3>Study focus</h3><div>Achieving high spatial resolution of actual evapotranspiration (ETa) is crucial for effective management of regional soil and water resources. However, current satellite technology limits the simultaneous acquisition of high temporal and spatial resolution data. Thus, downscaling ETa from lower to higher resolution is a practical solution. In this paper, the multi-scale geographically weighted regression (MGWR) model is used to downscale ETa data in the Tumen River Basin (TRB) from 1 km to 30 m resolution, using normalized difference vegetation index (NDVI), land surface temperature (LST), and digital elevation model (DEM) as independent variables. Furthermore, this study analyzed the spatiotemporal evolution of ETa in the TRB from 1990 to 2020 using high-resolution ETa data obtained from downscaling across seven periods.</div></div><div><h3>New hydrological insights for the region</h3><div>The results show the MGWR model's effectiveness, achieving an R² of 0.912, and accurately capturing the spatially heterogeneous relationships between ETa and the independent variables. The downscaled ETa data enhances spatial detail while preserving the original low-resolution patterns. From 1990–2020, ETa in the TRB showed a generally non-significant decreasing trend, with the basin-wide average decreasing from 102.37 mm to 101.06 mm. On the Chinese side, it declined from 107.12 mm to 105.93 mm, and on the side of the Democratic People's Republic of Korea (DPRK), from 91.78 mm to 90.22 mm.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102803"},"PeriodicalIF":5.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal dynamic characteristics and influencing factors of propagation time from meteorological drought to agricultural drought","authors":"Zhengguang Xu ,&nbsp;Xiao Guo ,&nbsp;Zhiyong Wu ,&nbsp;Guicai Li","doi":"10.1016/j.ejrh.2025.102806","DOIUrl":"10.1016/j.ejrh.2025.102806","url":null,"abstract":"<div><h3>Study region</h3><div>Yangtze River Basin (YRB), China</div></div><div><h3>Study focus</h3><div>Understanding the propagation from meteorological to agricultural drought is essential for effective agricultural drought risk management. However, the spatiotemporal dynamics and factors influencing this propagation remain poorly understood. This study characterized meteorological and agricultural droughts using the Standardized Precipitation Index and Improved Soil Moisture Anomaly Percentage Index. A correlation analysis combined with a moving window approach was employed to determine the dynamic drought propagation time. Additionally, the eXtreme Gradient Boosting (XGBoost) algorithm was applied to identify the primary factors associated with these variations.</div></div><div><h3>New hydrological insights</h3><div>The western YRB experienced the most significant fluctuations in propagation time. The propagation times in spring and winter were more sensitive to changing environments. The dominant factor influencing these variations at the grid scale was mean annual temperature (Tem). The factors influencing the spatial variability of the propagation time vary by region and season. Although the mean annual precipitation (Pre) was the most important factor influencing the spatial variation in propagation time in the YRB, the coupling relationship between soil moisture and precipitation (SM_Pre), along with soil moisture memory, dominated this variation in the middle-lower YRB. Seasonally, Pre was the dominant factor influencing the spatial variation in the propagation time in spring, SM_Pre primarily affected this variation in summer and autumn, and Tem was the dominant factor in winter.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102806"},"PeriodicalIF":5.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating the agent-based approach with hydraulic analysis of the water distribution network to a realistic micro-scale simulation of end-users in GAZ City, Iran","authors":"Zohre Fakhari ,&nbsp;Azadeh Ahmadi","doi":"10.1016/j.ejrh.2025.102805","DOIUrl":"10.1016/j.ejrh.2025.102805","url":null,"abstract":"<div><h3>Study region</h3><div>GAZ City water distribution network in Isfahan province, Iran</div></div><div><h3>Study focus</h3><div>In conventional water distribution network models, consumer water demand and water use behaviors are often oversimplified. These models are typically one-directional, simulating how water distribution networks' performance affects nodal demand estimation, neglecting complexity behind mutual interactions between household and water distribution network behaviors. This study proposes a novel framework, integrating an agent-based model with a hydraulic simulator, to simulate realistic consumer water use, which can capture reciprocal dynamics between end-user behaviors and the hydraulic performance of water distribution networks. These dynamics simulate how network pressure influences individual water use and how consumer water use feeds back hydraulic performance. The primary objective is to simulate these two-way interactions under abnormal conditions, thereby strengthening hydraulic analysis and supporting the assessment of social satisfaction.</div></div><div><h3>New hydrological insights for the region</h3><div>In the proposed framework, individual water-use behaviors across different activities are simulated under varying pressure conditions, accounting for both individual characteristics and social interactions. Results showed that consumer dissatisfaction was concentrated during peak demand periods under low-pressure conditions, while water use exceeded demand during off-peak times. Furthermore, modifying consumer attitudes toward water conservation improved network performance by 13 % without altering hydraulic parameters. By simulating realistic consumer responses, the framework provides a tool for evaluating the outcomes of water management policies under abnormal conditions.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102805"},"PeriodicalIF":5.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective intelligent flood control operation rules extraction for reservoirs-lake system based on long and short-term memory neural networks coupled with physical constraints","authors":"Bin Xu ,&nbsp;Xinman Qin ,&nbsp;Huili Wang ,&nbsp;Xuesong Yang ,&nbsp;Jianyun Zhang ,&nbsp;Fubao Yang ,&nbsp;Jiaying Tan ,&nbsp;Jiayi Jiang ,&nbsp;Pengwei Jiang ,&nbsp;Yutong Chen ,&nbsp;Wei Zhi ,&nbsp;Shanshui Yuan","doi":"10.1016/j.ejrh.2025.102808","DOIUrl":"10.1016/j.ejrh.2025.102808","url":null,"abstract":"<div><h3>Study region</h3><div>Chaohu Basin, lower Yangtze River region, China.</div></div><div><h3>Study focus</h3><div>This study proposes a multi-objective intelligent operation rules extraction method for flood control in reservoirs-lake system, which integrates Long Short-Term Memory (LSTM) networks with physical constraints. The method extends the input factors of the model to realize the prediction of multi-objective non-inferior solutions set and incorporates hydrological physical constraints into the model’s loss function. This coupling method improves both the model’s physical interpretability and the predictive ability in yielding multi-objective non-inferior solutions over reservoirs-lake system, which minimizes flood indices on reservoirs, lake and flood control point.</div></div><div><h3>New hydrological insights for the region</h3><div>The results show that compared to the conventional LSTM, the CP-LSTM (Physical Constrained Long Short-Term Memory) model demonstrates the following advantages: (1) The CP-LSTM reduces Root Mean Square Error by 0.33 % and increases Nash-Sutcliffe efficiency by 1.12 %, indicating improved accuracy in prediction modeling decision variables. Moreover, it significantly enhances peak flow prediction accuracy, improving the limitation of low peak flow prediction accuracy in the LSTM model; (2) In terms of objective space prediction, the maximum reduction in Objective Values Error reaches 8.00 %, while the Area Overlap Ratio of the predicted objective space to the true objective space improves by 21.50 %. By integrating hydrological physical constraints into the deep learning framework and extending it to multi-objective decision-making problems, this study provides a novel and effective approach for Artificial Intelligence -based flood control rules extraction and its application in multi-objective flood operation strategies.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102808"},"PeriodicalIF":5.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating genetic algorithms and machine learning for spatiotemporal groundwater potential zoning in fractured aquifers","authors":"Prashant Parasar ,&nbsp;Poonam Moral ,&nbsp;Aman Srivastava ,&nbsp;Akhouri Pramod Krishna ,&nbsp;Sayantan Majumdar ,&nbsp;Rajarshi Bhattacharjee ,&nbsp;Arun Partap Mishra ,&nbsp;Debjani Mustafi ,&nbsp;Virendra Singh Rathore ,&nbsp;Richa Sharma ,&nbsp;Abhijit Mustafi","doi":"10.1016/j.ejrh.2025.102800","DOIUrl":"10.1016/j.ejrh.2025.102800","url":null,"abstract":"<div><h3>Study region</h3><div>Groundwater overexploitation in Jharkhand’s fractured hard-rock aquifers threatens sustainability amid rising domestic, agricultural, and urban demands.</div></div><div><h3>Study focus</h3><div>This study develops an integrated framework that combines Genetic Algorithm (GA)-optimized clustering, Random Forest (RF) regression, and Gradient Boosting (GB) classification to map Groundwater Potential Zones (GWPZs) in the Jharkhand state of India (2013–2023) using 103 monitoring wells and multiple hydrogeological, topographic, and remote-sensing variables. GA was applied to optimize hydrostratigraphic clustering. The Mann-Kendall (MK) test assessed temporal groundwater trends, the RF regression predicted groundwater depth at unmonitored sites, and the GB classification was implemented for spatial mapping. Model interpretability was boosted using Local Interpretable Model-Agnostic Explanations (LIME).</div></div><div><h3>New hydrological insights for the region</h3><div>The framework identified three GWPZs (high, medium, and low), validated by strong clustering indices (Silhouette = 0.90, Dunn = 0.94). MK analysis revealed significant groundwater depletion across all clusters (Z = -2.66 to −1.47, p &lt; 0.05). RF regression achieved high predictive accuracy (R² ≈ 0.91, WI = 0.89, PBIAS = 0.25), highlighting curvature and lineament proximity as dominant factors. GB classification yielded an F1-score of 95.56 %. Spatially, high-potential zones were concentrated in West Singhbhum, East Singhbhum, and Gumla, while Giridih, Pakur, and Garhwa exhibited low potential with aquifer depletion. These findings provide scientific support for Jharkhand’s 2025 Groundwater Act and demonstrate the transferability of the framework to other hard-rock and data-scarce aquifers like the Brazilian Shield and African cratons.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"62 ","pages":"Article 102800"},"PeriodicalIF":5.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}