Applied Water Science最新文献

{"title":"An integrative water quality index and multivariate modeling approach to assess surface water quality, trophic status and nutrient source apportionment in a large tropical reservoir, Hirakud–the longest earthen dam in Asia","authors":"Pranab Gogoi,&nbsp;Basanta Kumar Das,&nbsp;Satish Kumar Koushlesh,&nbsp;Canciyal Johnson,&nbsp;Ramesh Malick,&nbsp;Ajoy Saha,&nbsp;Taniya Kayal,&nbsp;Ratul Chakraborty,&nbsp;Laxmidhar Pradhan,&nbsp;Archan Kanti Das","doi":"10.1007/s13201-025-02517-y","DOIUrl":"10.1007/s13201-025-02517-y","url":null,"abstract":"<div><p>The present study aimed to evaluate the spatio-temporal variations of surface water quality and trophic status of Hirakud reservoir, India based on the study of two annual periods (2022–2024). Nineteen limnological parameters were assessed seasonally at 14 sampling sites throughout the reservoir. Water variables showed significant (<i>p</i> &lt; 0.05) spatial and seasonal variations where seasons had more impact on physicochemical variables. The calculated Arithmetic Weighted WQI value determined the reservoir water to be of <i>‘good’</i> water quality, especially in the pre- and post-monsoon period. However, during monsoon, increased turbidity was found to be a single potent factor for drastic deviation in WQI, rated as <i>‘poor to very poor’</i> water quality. Overall, the entire reservoir was in a mesotrophic state, with Carlson’s Trophic State Index (CTSI) ranging between 40.44 and 50.95. The insignificant (<i>p</i> &gt; 0.05) spatio-temporal variation of CTSI value, which indicates the biological productivity of the reservoir, maintains its homogeneity. The land use land cover map was created for the reservoir with an overall accuracy Kappa index value of 0.85. The present study also evaluated the evolution of eutrophication in relation to Chl <i>a</i> using the Generalized Linear Model (GLM) and BEST Biota––Environmental Matching (BIO–ENV). Our models suggest that water variables (dissolved oxygen, PO₄³⁻, transparency, and electrical conductivity) were the best explained variables for deviating Chl <i>a</i> in reservoir water. Furthermore, the BIO–ENV model suggests that other factors (geographic and climatic) are equally responsible for the local evolution of eutrophication in the reservoir, including allochthonous inputs mainly by feeder river.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02517-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of MRMR algorithm with advanced neural networks for modeling long-term crop water demand in agricultural basins","authors":"Ahmed Elbeltagi,&nbsp;Abdullah A. Alsumaiei,&nbsp;Ali Raza,&nbsp;Mustafa Al-Mukhtar,&nbsp;Salim Heddam","doi":"10.1007/s13201-025-02574-3","DOIUrl":"10.1007/s13201-025-02574-3","url":null,"abstract":"<div><p>Assessing actual evapotranspiration (AET) remains a key challenge in the design of efficient irrigation systems, strategies, and schedules. This complexity arises from the nonlinear nature of AET, which varies with crop type, growth stage, agroclimatic conditions, soil type, and irrigation method. In regions with limited weather data, such as parts of China, a major agricultural nation, precise AET estimation is crucial for optimizing the use of available irrigation water. Therefore, this study aims to achieve more accurate AET predictions through i) evaluating the performance of five artificial neural network (ANN) models optimized with the minimum redundancy maximum relevance (MRMR) algorithm to estimate monthly AET across diverse agroclimatic zones in China and ii) selecting the model with the highest accuracy based on performance metrics and minimal error between estimated and actual AET values. The analysis utilized weather data from Jinzhou, Anshan, Harbin, Shenyang, and Changchun from 1958 to 2021, with 75% of the data allocated for training and 25% for testing. AET was estimated by using five ANN architectures with the MRMR method ranking the AET predictors before modeling. The wide neural network (Wi-ANN) outperformed the other methods in both training and testing, achieving high accuracy across all metrics in the testing stage: <i>R</i>² (0.977), root mean square error 6.423 mm, and mean absolute error 3.371 mm. Overall, these findings underscore the robust capacity of the Wi-ANN model to forecast long-term AET at the studied sites. This approach offers a promising solution for enhancing irrigation practices and boosting agricultural productivity.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02574-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: New core@shell nanogel-based 2-acrylamido-2-methyl-1-propane sulfonic acid for preconcentration of Pb(II) from various water samples","authors":"Kamel Rizq Shoueir,&nbsp;Magda Ali Akl,&nbsp;Ali Ali Sarhan,&nbsp;Ayman Mohamdy Atta","doi":"10.1007/s13201-025-02515-0","DOIUrl":"10.1007/s13201-025-02515-0","url":null,"abstract":"","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02515-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Snowmelt runoff model (SRM) for regulated watersheds with regulation-correction","authors":"Ninad Bhagwat,&nbsp;Xiaobing Zhou,&nbsp;Raja Nagisetty,&nbsp;Liping Jiang,&nbsp;Glenn Shaw,&nbsp;Martha Apple,&nbsp;Jeremy Clotfelter","doi":"10.1007/s13201-025-02579-y","DOIUrl":"10.1007/s13201-025-02579-y","url":null,"abstract":"<div><p>We expanded the Snowmelt Runoff Model (SRM) to simulate streamflow in regulated watersheds, resulting in a modified framework termed the Expanded SRM (E-SRM) that integrates multi-year automated batch processing, nested iterators, and a seasonal divider algorithm for streamflow simulation. A parsimonious regulation-correction approach was developed that conceptually divides the watershed into a pristine upstream “daughter” subwatershed and a larger, regulated “mother” watershed. Hydrological parameter transferability was assumed between the daughter and mother watersheds. We applied the E-SRM to the Morony watershed in Montana, USA (~ 59,400 km²; elevation range: 860–3418 m). The area was subdivided into the Morony and Canyon Ferry watersheds, with the latter treated as a pristine basin for calibration. Following calibration at Canyon Ferry, regulation-correction was applied using streamflow from the Canyon Ferry, Hauser, and Holter dams. Validation was conducted over the entire Morony watershed. Three methodological scenarios were evaluated: (1) 21-year calibration and 21-year validation; (2) 11-year calibration and 21-year validation; and (3) calibration using odd years with validation on odd and even years. In all scenarios, comparison between observed and regulation-corrected streamflow showed improved performance across multiple model assessment metrics. These included both absolute (e.g. Nash–Sutcliffe Efficiency: from − 0.16 to 0.74, − 0.43 to 0.59, − 0.16 to 0.67; Kling–Gupta Efficiency) and relative (e.g. Root-Mean-Square Error, Normalized Root-Mean-Square Error, Mean Absolute Error, and Volume Difference) indicators, highlighting the significant impact of flow regulation on SRM performance. The E-SRM framework offers new opportunities for research and practical application in water resource management.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02579-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144756279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of reducing long-term groundwater overdraft in uluova micro-basin","authors":"Kürşat Şekerci,&nbsp;M. Cihat Tuna,&nbsp;M. Şahin Doğan","doi":"10.1007/s13201-025-02581-4","DOIUrl":"10.1007/s13201-025-02581-4","url":null,"abstract":"<div><p>Recently, groundwater use has increased significantly in response to limited surface water availability in arid and semi-arid regions. This trend has led to increasing concerns about declining groundwater levels and the risk of overdraft. For the above reasons, a hydroeconomic model was developed in this study to evaluate various management scenarios aimed at mitigating the negative impacts of groundwater overdraft. The Uluhem hydroeconomic model focuses on a total of six different water management operations with different physical constraints. The first scenario is a baseline water operation with groundwater pumping (with overdraft), while the next four scenarios cover four different water management operations where groundwater pumping is restricted at different rates (without overdraft). The sixth and final scenario investigates the installation of a solar-powered system to pump water from a nearby surface water reservoir. This last scenario seeks a potential solution to completely eliminate the agricultural water scarcity and associated scarcity costs arising from the first five scenarios. With the Uluhem model, the water deliveries, water scarcity and economic impacts of these six different management scenarios are analyzed. The findings show that the four different scenarios in which groundwater pumping is restricted contribute positively to the groundwater reservoir but increase water scarcity. The solar power plant installation scenario, on the other hand, offers a promising and sustainable solution that not only effectively addresses water scarcity but also eliminates the associated costs. The study investigates the factors contributing to groundwater overdraft and seeks a sustainable solution to current groundwater utilization. The results emphasize the urgent need for effective and sustainable water management strategies to prevent groundwater overdraft. Overall, the study provides valuable insights into groundwater overdraft problems in the Uluova micro-basin and emphasizes the importance of adopting long-term, sustainable groundwater management practices.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02581-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Projection of hydrological drought based on SSP scenarios using surface water supply index and SWAT model in mountainous watershed","authors":"Omid Babamiri,&nbsp;Yagob Dinpashoh,&nbsp;Alireza Samavati,&nbsp;Faeze Shoja","doi":"10.1007/s13201-025-02582-3","DOIUrl":"10.1007/s13201-025-02582-3","url":null,"abstract":"<div><p>The objective of this research is to explore climate change impact on hydrological drought in mountain watersheds. The Coupled Model Intercomparison Project Phase 6 (CMIP6) models and the Soil and Water Assessment Tool (SWAT) runoff simulation model were utilized to attain the objective of the study. Moreover, the surface water supply index (SWSI) was employed to examine hydrological drought. To correct the bias of the selected CMIP6 models (ACCESS-CM2, CNRM-CM6-1, CNRM-ESM2-1, INM-CM4-8, INM-CM5-0, MIROC6, and MIROC-ES2L), the historical period from 1990 to 2014 was used as a baseline. It was found that the MIROC-ES2L model exhibited greater accuracy compared to the other chosen models in the context of the examined mountain basin, namely the Ekbatan watershed in Iran. The calibration and validation of the SWAT model were conducted using the Sequential Uncertainty Fitting version 2 (SUFI-2) algorithm, covering the calibration period from 2004 to 2017 and the validation period from 2018 to 2020. The results indicated that the model effectively simulates runoff in the watershed. The highest percentage error, as measured by the Normalized Root Mean Square Error (NRMSE), was 18.78% during the validation phase. Results from a trend analysis of runoff using the Mann–Kendall test for the projected period (2023–2042) indicate that runoff is not expected to exhibit a significant decreasing or increasing trend during this timeframe. Furthermore, an assessment of runoff uncertainty within the projected period (2023–2042) revealed that the most substantial variability or uncertainty is associated with the month of April, with a range of 0 to 9.55 m³/s. The comparison of future runoff (2023–2042) with past runoff (2000–2020) indicates an increase in runoff during typically dry months (August, September, and October). This increase is particularly pronounced in September, where, under the SSP2-4.5 scenario and the best-performing model (MIROC-ES2L), runoff is projected to be nearly twelve times higher. This phenomenon may be attributed to the potential occurrence of intense rainfall events influenced by climate change during the dry season. Additionally, due to the generally low streamflow in this period, the relative increase appears more significant. When comparing drought conditions between the periods of 2023–2042 and 2000–2020, as assessed by SWSI, the results show that, on a 12-month scale, drought conditions in the typically wet months (February, March, April, and May) are expected to intensify under all scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). In other words, these months are projected to become drier in the future. The most significant increase in drought severity is anticipated in February under the SSP5-8.5 scenario, reaching a magnitude of 86.84%. Overall, results indicated an intensification of hydrological drought during the wet months in the mountainous basin.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02582-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early warning and formation mechanism analysis of groundwater environment in irrigation area, Guanzhong Basin","authors":"Qiying Zhang,&nbsp;Hui Qian,&nbsp;Wenhao Ren,&nbsp;Panpan Xu,&nbsp;Aihui Wei","doi":"10.1007/s13201-025-02576-1","DOIUrl":"10.1007/s13201-025-02576-1","url":null,"abstract":"<div><p>Long-term intensive human activities in irrigation areas seriously threaten their groundwater environment. In this study, the early warning status of the groundwater environment and the possible influencing factors were analyzed based on 63 samples using the BP neural network and gray relational analysis. For groundwater depth, the upper limits of blue and red warnings were set at 5 m and 2 m, respectively. The prediction results show that the maximum value of the water table in the study area exhibits a downward trend, whereas the minimum value exhibits an upward trend. Only blue and yellow warnings occur in 2025, implying that the early warning state of the groundwater level, will improve in the later stage. The early warning grades of groundwater salinity in 2025 were also analyzed and the results show that orange warning is dominant, accounting for 53.97%, with a distribution area of about 552.811 km², followed by yellow warning and blue warning, without any red warning. The early warning grade of salt content in the highest in the hinterland of the study area. This is because the middle area has a shallow groundwater level with strong evaporation. By analyzing the factors affecting groundwater level and salinity, evaporation was found to be the strongest factor influencing groundwater level and salinity, followed by precipitation and irrigation infiltration. Furthermore, on the basis of the aforementioned results, six targeted countermeasures are put forward. The findings will contribute toward the protection of the local livelihood and achieving sustainable development of water resources.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02576-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable water purification through the adsorptive removal of tetracycline via modified clay and regeneration via controlled thermolysis: a reusable and environmentally friendly approach for contaminant mitigation","authors":"Iyad Dawood,&nbsp;Ahed H. Zyoud,&nbsp;Shaher Zyoud,&nbsp;Ameed Amireh,&nbsp;Samer H. Zyoud,&nbsp;Tae Woo Kim","doi":"10.1007/s13201-025-02555-6","DOIUrl":"10.1007/s13201-025-02555-6","url":null,"abstract":"<div><p>Pharmaceutical pollutants such as tetracycline (TC) are environmentally dangerous because of their persistence in aquatic bodies. This work introduces a unique and sustainable treatment approach by combining modified natural clay (MC) adsorption with controlled thermolysis regeneration to eliminate TC from wastewater in a reusable system. Batch adsorption experiments revealed an optimum TC removal of 93% at pH 3.5, 25 °C, and 40 mg/L TC, with an equilibrium time of 45 min. Adsorption followed the Langmuir isotherm (<i>R</i>² = 0.9713), indicating monolayer adsorption with a capacity of 85.54 mg/g, whereas kinetic modeling was pseudo-second order, suggesting chemisorption. The integration of thermolysis at 550 °C for 120 min not only decomposed TC into CO₂ and H₂O but also preserved the structural integrity of the MC for reuse over five cycles. Continuous-flow column trials corroborated the effectiveness of the approach under real conditions in practical applications. Structural characterization techniques (XRD, SEM, TGA, and FT-IR) were used to validate the thermal stability, porous structure, and high adsorption capacity of MC. This adsorption‒thermolysis approach with combined adsorption presents an economically viable and environmentally friendly alternative to traditional water treatment processes, which effectively destroys secondary waste and facilitates sustainable pollutant removal. This closed-loop, eco-friendly method not only eliminates secondary waste but also demonstrates scalable potential for industrial wastewater treatment.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02555-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manganese-coated granular oyster shells: a novel approach for heavy metal removal from urban stormwater runoff","authors":"Quynh Thi Phuong Tran,&nbsp;Trung Thanh Nguyen,&nbsp;Oanh Nguyen Song Dao,&nbsp;Chia-Yu Lin,&nbsp;Po-Hsun Lin","doi":"10.1007/s13201-025-02568-1","DOIUrl":"10.1007/s13201-025-02568-1","url":null,"abstract":"<p>This study introduces manganese oxide (MnO_x)-coated granular oyster shells (MnO_x@GOS) as an advanced adsorbent for heavy metal removal from urban stormwater runoff. The MnO_x coating increased the surface area of ​​granular oyster shell (GOS) by 132% (from 1.0534 to 2.4420 m²/g), enhancing the adsorption capacity. Selective adsorption followed the order of Pb(II) &gt; Cu(II) &gt; Zn(II) &gt; Ni(II), influenced by ionic radius compatibility, hydration energy, and MnO_x redox interactions. Kinetic studies showed that the adsorption process was fit to the pseudo-second-order (<i>R</i>^<i>2</i> = 0.9590–0.9931), confirming chemisorption as the dominant mechanism. The highest kinetic rate constant (<i>K</i>_<i>2</i> = 0.0766 g/mg·min) was observed for Ni(II), whereas Pb(II) exhibited the strongest affinity. The Freundlich model provided a better fit (<i>R</i>^<i>2</i> = 0.9900–0.9969) than the Langmuir model (<i>R</i>^<i>2</i> = 0.9433–0.9826), confirming that adsorption primarily occurred through a multilayer process on a heterogeneous surface. Fixed-bed column studies demonstrated over 90% removal efficiency for Pb(II) and Cu(II) over eight days, confirming MnO_x@GOS as an effective adsorbent. With abundant oyster shell waste and a simple synthesis process, MnO_x@GOS has great potential for cost-effective, large-scale use in low impact development (LID) systems such as bioretention cells and permeable pavements. However, ensuring long-term stability, efficient regeneration, and consistent performance under a wide range of environmental conditions remains a key challenge for real-world deployment.</p>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02568-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment and economic evaluation of delineation of agricultural groundwater potential zones using geo-spatial and multi-influencing factor techniques","authors":"Yu Jie,&nbsp;Niamat Ullah,&nbsp;Aqil Tariq,&nbsp;Sanaullah Panezai,&nbsp;M. Abdullah-Al-Wadud,&nbsp;Sajid Ullah","doi":"10.1007/s13201-025-02567-2","DOIUrl":"10.1007/s13201-025-02567-2","url":null,"abstract":"<div><p>Climate change has affected groundwater resources worldwide. Consequently, Pakistan is ranked in the world’s top ten climate change-affected countries and is experiencing a water stress situation. Remote sensing and geographic information systems (RS and GIS) play important roles in preserving water resources. This study was carried out in one of the most climate-affected provinces of Pakistan to delineate potential groundwater resources. This study has integrated RS, GIS, and multi-influencing factor (MIF) techniques for delineating groundwater potential zones (GWPZs). Various groundwater influencing thematic layers, including geology, soil, land use, land cover, slope, etc., were employed in the GIS domain. All these thematic layers were assigned weights and ranks using the MIF technique through weight overlay analysis in ArcGIS 10.8.2. The study area was classified into four groundwater potential zones (GWPZs) very low, covering an area of 1367.96 km² (22.0%); low with an area of 3046.82 km² (49.0%); moderate, with an area of 994.88 km² (16.0%), and 808.34 km² (13.0%) of the study area fall under ‘high’ GWPZs. Lastly, the model produced through RS, GIS, and MIF techniques was validated using water table depth data from the existing tube wells in the study area. However, in the present study, the overall accuracy of the produced model is more than 90%. The produced model is helpful for water management authorities for the future sustainable use of groundwater resources in the study area.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02567-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}