Assessment and economic evaluation of delineation of agricultural groundwater potential zones using geo-spatial and multi-influencing factor techniques
{"title":"Assessment and economic evaluation of delineation of agricultural groundwater potential zones using geo-spatial and multi-influencing factor techniques","authors":"Yu Jie, Niamat Ullah, Aqil Tariq, Sanaullah Panezai, M. Abdullah-Al-Wadud, Sajid Ullah","doi":"10.1007/s13201-025-02567-2","DOIUrl":null,"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 km<sup>2</sup> (22.0%); low with an area of 3046.82 km<sup>2</sup> (49.0%); moderate, with an area of 994.88 km<sup>2</sup> (16.0%), and 808.34 km<sup>2</sup> (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":5.7000,"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":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Water Science","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s13201-025-02567-2","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0
Abstract
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.