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Integrating a GIS-Based Multi-Influence Factors Model with Hydro-Geophysical Exploration for Groundwater Potential and Hydrogeological Assessment: A Case Study in the Karak Watershed, Northern Pakistan
The optimization of groundwater conditioning factors (GCFs), the evaluation of groundwater potential (GWpot), the hydrogeological characterization of aquifer geoelectrical properties and borehole lithological information are of great significance in the complex decision-making processes of groundwat...
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Published in: | Water (Basel) 2021-05, Vol.13 (9), p.1255 |
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description | The optimization of groundwater conditioning factors (GCFs), the evaluation of groundwater potential (GWpot), the hydrogeological characterization of aquifer geoelectrical properties and borehole lithological information are of great significance in the complex decision-making processes of groundwater resource management (GRM). In this study, the regional GWpot of the Karak watershed in Northern Pakistan was first evaluated by means of the multi-influence factors (MIFs) model of optimized GCFs through geoprocessing tools in geographical information system (GIS). The distribution of petrophysical properties indicated by the measured resistivity fluctuations was then generated to locally verify the GWpot, and to analyze the hydrogeological and geoelectrical characteristics of aquifers. According to the weighted overlay analysis of MIFs, GWpot map was zoned into low, medium, high and very high areas, covering 9.7% (72.3 km2), 52.4% (1307.7 km2), 31.3% (913.4 km2), and 6.6% (44.8 km2) of the study area. The GWpot accuracy sequentially depends on the classification criteria, the mean rating score, and the weights assigned to GCFs. The most influential factors are geology, lineament density, and land use/land cover followed by drainage density, slope, soil type, rainfall, elevation, and groundwater level fluctuations. The receiver operating characteristic (ROC) curve, the confusion matrix, and Kappa (K) analysis show satisfactory and consistent results and expected performances (the area under the curve value 68%, confusion matrix 68%, Kappa (K) analysis 65%). The electrical resistivity tomography (ERT) and vertical electrical sounding (VES) data interpretations reveals five regional hydrological layers (i.e., coarse gravel and sand, silty sand mixed lithology, clayey sand/fine sand, fine sand/gravel, and clayey basement). The preliminary interpretation of ERT results highlights the complexity of the hydrogeological strata and reveals that GWpot is structurally and proximately constrained in the clayey sand and silicate aquifers (sandstone), which is of significance for the determination of drilling sites, expansion of drinking water supply and irrigation in the future. Moreover, quantifying the spatial distribution of aquifer hydrogeological characteristics (such as reflection coefficient, isopach, and resistivity mapping) based on Olayinka’s basic standards, indirectly and locally verify the performance of the MIF model and ultimately determine new locations f |
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In this study, the regional GWpot of the Karak watershed in Northern Pakistan was first evaluated by means of the multi-influence factors (MIFs) model of optimized GCFs through geoprocessing tools in geographical information system (GIS). The distribution of petrophysical properties indicated by the measured resistivity fluctuations was then generated to locally verify the GWpot, and to analyze the hydrogeological and geoelectrical characteristics of aquifers. According to the weighted overlay analysis of MIFs, GWpot map was zoned into low, medium, high and very high areas, covering 9.7% (72.3 km2), 52.4% (1307.7 km2), 31.3% (913.4 km2), and 6.6% (44.8 km2) of the study area. The GWpot accuracy sequentially depends on the classification criteria, the mean rating score, and the weights assigned to GCFs. The most influential factors are geology, lineament density, and land use/land cover followed by drainage density, slope, soil type, rainfall, elevation, and groundwater level fluctuations. The receiver operating characteristic (ROC) curve, the confusion matrix, and Kappa (K) analysis show satisfactory and consistent results and expected performances (the area under the curve value 68%, confusion matrix 68%, Kappa (K) analysis 65%). The electrical resistivity tomography (ERT) and vertical electrical sounding (VES) data interpretations reveals five regional hydrological layers (i.e., coarse gravel and sand, silty sand mixed lithology, clayey sand/fine sand, fine sand/gravel, and clayey basement). The preliminary interpretation of ERT results highlights the complexity of the hydrogeological strata and reveals that GWpot is structurally and proximately constrained in the clayey sand and silicate aquifers (sandstone), which is of significance for the determination of drilling sites, expansion of drinking water supply and irrigation in the future. Moreover, quantifying the spatial distribution of aquifer hydrogeological characteristics (such as reflection coefficient, isopach, and resistivity mapping) based on Olayinka’s basic standards, indirectly and locally verify the performance of the MIF model and ultimately determine new locations for groundwater exploitation. The combined methods of regional GWpot mapping and hydrogeological characterization, through the geospatial MIFs model and aquifer geoelectrical interpretation, respectively, facilitate decision-makers for sustainable GRM not only in the Karak watershed but also in other similar areas worldwide.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w13091255</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Aquifers ; Boreholes ; Case studies ; Climatic changes ; Decision making ; Drainage density ; Drilling ; Drinking water ; Electrical resistivity ; Elevation ; Environmental impact ; Feasibility studies ; Fluctuations ; Geoelectricity ; Geographic information systems ; Geology ; Geophysical exploration ; Geophysical methods ; Geospatial data ; Gravel ; Groundwater ; Groundwater levels ; Groundwater management ; Groundwater potential ; Hydrogeology ; Hydrologic data ; Hydrology ; Irrigation water ; Land cover ; Land use ; Lithology ; Management ; Mapping ; Methods ; Optimization ; Precipitation ; Prospecting ; Rainfall ; Reflectance ; Resource management ; Sand ; Sandstone ; Seasons ; Sediments ; Soil density ; Soil erosion ; Spatial distribution ; Stratigraphy ; Surface water ; Water ; Water shortages ; Water supply ; Water, Underground ; Watersheds</subject><ispartof>Water (Basel), 2021-05, Vol.13 (9), p.1255</ispartof><rights>COPYRIGHT 2021 MDPI AG</rights><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-ea66dfc1fca94bb982568b75283d9c6b5630380b6c21cc5dea3d93dd686f78ed3</citedby><cites>FETCH-LOGICAL-c331t-ea66dfc1fca94bb982568b75283d9c6b5630380b6c21cc5dea3d93dd686f78ed3</cites><orcidid>0000-0001-6075-9359 ; 0009-0001-6989-2639 ; 0000-0001-6963-9396</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2530130827/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2530130827?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25752,27923,27924,37011,44589,74997</link.rule.ids></links><search><creatorcontrib>Khan, Umair</creatorcontrib><creatorcontrib>Faheem, Haris</creatorcontrib><creatorcontrib>Jiang, Zhengwen</creatorcontrib><creatorcontrib>Wajid, Muhammad</creatorcontrib><creatorcontrib>Younas, Muhammad</creatorcontrib><creatorcontrib>Zhang, Baoyi</creatorcontrib><title>Integrating a GIS-Based Multi-Influence Factors Model with Hydro-Geophysical Exploration for Groundwater Potential and Hydrogeological Assessment: A Case Study in the Karak Watershed, Northern Pakistan</title><title>Water (Basel)</title><description>The optimization of groundwater conditioning factors (GCFs), the evaluation of groundwater potential (GWpot), the hydrogeological characterization of aquifer geoelectrical properties and borehole lithological information are of great significance in the complex decision-making processes of groundwater resource management (GRM). In this study, the regional GWpot of the Karak watershed in Northern Pakistan was first evaluated by means of the multi-influence factors (MIFs) model of optimized GCFs through geoprocessing tools in geographical information system (GIS). The distribution of petrophysical properties indicated by the measured resistivity fluctuations was then generated to locally verify the GWpot, and to analyze the hydrogeological and geoelectrical characteristics of aquifers. According to the weighted overlay analysis of MIFs, GWpot map was zoned into low, medium, high and very high areas, covering 9.7% (72.3 km2), 52.4% (1307.7 km2), 31.3% (913.4 km2), and 6.6% (44.8 km2) of the study area. The GWpot accuracy sequentially depends on the classification criteria, the mean rating score, and the weights assigned to GCFs. The most influential factors are geology, lineament density, and land use/land cover followed by drainage density, slope, soil type, rainfall, elevation, and groundwater level fluctuations. The receiver operating characteristic (ROC) curve, the confusion matrix, and Kappa (K) analysis show satisfactory and consistent results and expected performances (the area under the curve value 68%, confusion matrix 68%, Kappa (K) analysis 65%). The electrical resistivity tomography (ERT) and vertical electrical sounding (VES) data interpretations reveals five regional hydrological layers (i.e., coarse gravel and sand, silty sand mixed lithology, clayey sand/fine sand, fine sand/gravel, and clayey basement). The preliminary interpretation of ERT results highlights the complexity of the hydrogeological strata and reveals that GWpot is structurally and proximately constrained in the clayey sand and silicate aquifers (sandstone), which is of significance for the determination of drilling sites, expansion of drinking water supply and irrigation in the future. Moreover, quantifying the spatial distribution of aquifer hydrogeological characteristics (such as reflection coefficient, isopach, and resistivity mapping) based on Olayinka’s basic standards, indirectly and locally verify the performance of the MIF model and ultimately determine new locations for groundwater exploitation. The combined methods of regional GWpot mapping and hydrogeological characterization, through the geospatial MIFs model and aquifer geoelectrical interpretation, respectively, facilitate decision-makers for sustainable GRM not only in the Karak watershed but also in other similar areas worldwide.</description><subject>Aquifers</subject><subject>Boreholes</subject><subject>Case studies</subject><subject>Climatic changes</subject><subject>Decision making</subject><subject>Drainage density</subject><subject>Drilling</subject><subject>Drinking water</subject><subject>Electrical resistivity</subject><subject>Elevation</subject><subject>Environmental impact</subject><subject>Feasibility studies</subject><subject>Fluctuations</subject><subject>Geoelectricity</subject><subject>Geographic information systems</subject><subject>Geology</subject><subject>Geophysical exploration</subject><subject>Geophysical methods</subject><subject>Geospatial data</subject><subject>Gravel</subject><subject>Groundwater</subject><subject>Groundwater levels</subject><subject>Groundwater management</subject><subject>Groundwater potential</subject><subject>Hydrogeology</subject><subject>Hydrologic data</subject><subject>Hydrology</subject><subject>Irrigation water</subject><subject>Land cover</subject><subject>Land use</subject><subject>Lithology</subject><subject>Management</subject><subject>Mapping</subject><subject>Methods</subject><subject>Optimization</subject><subject>Precipitation</subject><subject>Prospecting</subject><subject>Rainfall</subject><subject>Reflectance</subject><subject>Resource management</subject><subject>Sand</subject><subject>Sandstone</subject><subject>Seasons</subject><subject>Sediments</subject><subject>Soil density</subject><subject>Soil erosion</subject><subject>Spatial distribution</subject><subject>Stratigraphy</subject><subject>Surface water</subject><subject>Water</subject><subject>Water shortages</subject><subject>Water supply</subject><subject>Water, Underground</subject><subject>Watersheds</subject><issn>2073-4441</issn><issn>2073-4441</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNpNUdtuEzEQXSGQqEof-IOReEJiiy978fIWojaNaKFSQTyuvPZ443ZjB9urkE_kr3AIQsw8zOjonDMjnaJ4Tckl5x15v6ecdJTV9bPijJGWl1VV0ef_7S-LixgfSa6qE6ImZ8WvtUs4BpmsG0HCav1QfpQRNdzNU7Ll2plpRqcQrqVKPkS48xon2Nu0gZuDDr5cod9tDtEqOcHVz93kj2begfEBVsHPTu9lwgD3PqFLNrOk0yftiH7y4x_lIkaMcZsZH2ABy_wCPKRZH8A6SBuETzLIJ_h-dIob1O_gsw8ZDw7u5ZONSbpXxQsjp4gXf-d58e366uvyprz9slovF7el4pymEmXTaKOoUbKrhqETrG7E0NZMcN2pZqgbTrggQ6MYVarWKDPOtW5EY1qBmp8Xb06-u-B_zBhT_-jn4PLJntWc5AgEazPr8sQa5YS9dcanIFVujVurvENjM75oO8pZx1qaBW9PAhV8jAFNvwt2K8Ohp6Q_ptv_S5f_BmlVmik</recordid><startdate>20210501</startdate><enddate>20210501</enddate><creator>Khan, Umair</creator><creator>Faheem, Haris</creator><creator>Jiang, Zhengwen</creator><creator>Wajid, Muhammad</creator><creator>Younas, Muhammad</creator><creator>Zhang, Baoyi</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0001-6075-9359</orcidid><orcidid>https://orcid.org/0009-0001-6989-2639</orcidid><orcidid>https://orcid.org/0000-0001-6963-9396</orcidid></search><sort><creationdate>20210501</creationdate><title>Integrating a GIS-Based Multi-Influence Factors Model with Hydro-Geophysical Exploration for Groundwater Potential and Hydrogeological Assessment: A Case Study in the Karak Watershed, Northern Pakistan</title><author>Khan, Umair ; Faheem, Haris ; Jiang, Zhengwen ; Wajid, Muhammad ; Younas, Muhammad ; Zhang, Baoyi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-ea66dfc1fca94bb982568b75283d9c6b5630380b6c21cc5dea3d93dd686f78ed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aquifers</topic><topic>Boreholes</topic><topic>Case studies</topic><topic>Climatic changes</topic><topic>Decision making</topic><topic>Drainage density</topic><topic>Drilling</topic><topic>Drinking water</topic><topic>Electrical resistivity</topic><topic>Elevation</topic><topic>Environmental impact</topic><topic>Feasibility studies</topic><topic>Fluctuations</topic><topic>Geoelectricity</topic><topic>Geographic information systems</topic><topic>Geology</topic><topic>Geophysical exploration</topic><topic>Geophysical methods</topic><topic>Geospatial data</topic><topic>Gravel</topic><topic>Groundwater</topic><topic>Groundwater levels</topic><topic>Groundwater management</topic><topic>Groundwater potential</topic><topic>Hydrogeology</topic><topic>Hydrologic data</topic><topic>Hydrology</topic><topic>Irrigation water</topic><topic>Land cover</topic><topic>Land use</topic><topic>Lithology</topic><topic>Management</topic><topic>Mapping</topic><topic>Methods</topic><topic>Optimization</topic><topic>Precipitation</topic><topic>Prospecting</topic><topic>Rainfall</topic><topic>Reflectance</topic><topic>Resource management</topic><topic>Sand</topic><topic>Sandstone</topic><topic>Seasons</topic><topic>Sediments</topic><topic>Soil density</topic><topic>Soil erosion</topic><topic>Spatial distribution</topic><topic>Stratigraphy</topic><topic>Surface water</topic><topic>Water</topic><topic>Water shortages</topic><topic>Water supply</topic><topic>Water, Underground</topic><topic>Watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Khan, Umair</creatorcontrib><creatorcontrib>Faheem, Haris</creatorcontrib><creatorcontrib>Jiang, Zhengwen</creatorcontrib><creatorcontrib>Wajid, Muhammad</creatorcontrib><creatorcontrib>Younas, Muhammad</creatorcontrib><creatorcontrib>Zhang, Baoyi</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Khan, Umair</au><au>Faheem, Haris</au><au>Jiang, Zhengwen</au><au>Wajid, Muhammad</au><au>Younas, Muhammad</au><au>Zhang, Baoyi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrating a GIS-Based Multi-Influence Factors Model with Hydro-Geophysical Exploration for Groundwater Potential and Hydrogeological Assessment: A Case Study in the Karak Watershed, Northern Pakistan</atitle><jtitle>Water (Basel)</jtitle><date>2021-05-01</date><risdate>2021</risdate><volume>13</volume><issue>9</issue><spage>1255</spage><pages>1255-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>The optimization of groundwater conditioning factors (GCFs), the evaluation of groundwater potential (GWpot), the hydrogeological characterization of aquifer geoelectrical properties and borehole lithological information are of great significance in the complex decision-making processes of groundwater resource management (GRM). In this study, the regional GWpot of the Karak watershed in Northern Pakistan was first evaluated by means of the multi-influence factors (MIFs) model of optimized GCFs through geoprocessing tools in geographical information system (GIS). The distribution of petrophysical properties indicated by the measured resistivity fluctuations was then generated to locally verify the GWpot, and to analyze the hydrogeological and geoelectrical characteristics of aquifers. According to the weighted overlay analysis of MIFs, GWpot map was zoned into low, medium, high and very high areas, covering 9.7% (72.3 km2), 52.4% (1307.7 km2), 31.3% (913.4 km2), and 6.6% (44.8 km2) of the study area. The GWpot accuracy sequentially depends on the classification criteria, the mean rating score, and the weights assigned to GCFs. The most influential factors are geology, lineament density, and land use/land cover followed by drainage density, slope, soil type, rainfall, elevation, and groundwater level fluctuations. The receiver operating characteristic (ROC) curve, the confusion matrix, and Kappa (K) analysis show satisfactory and consistent results and expected performances (the area under the curve value 68%, confusion matrix 68%, Kappa (K) analysis 65%). The electrical resistivity tomography (ERT) and vertical electrical sounding (VES) data interpretations reveals five regional hydrological layers (i.e., coarse gravel and sand, silty sand mixed lithology, clayey sand/fine sand, fine sand/gravel, and clayey basement). The preliminary interpretation of ERT results highlights the complexity of the hydrogeological strata and reveals that GWpot is structurally and proximately constrained in the clayey sand and silicate aquifers (sandstone), which is of significance for the determination of drilling sites, expansion of drinking water supply and irrigation in the future. Moreover, quantifying the spatial distribution of aquifer hydrogeological characteristics (such as reflection coefficient, isopach, and resistivity mapping) based on Olayinka’s basic standards, indirectly and locally verify the performance of the MIF model and ultimately determine new locations for groundwater exploitation. The combined methods of regional GWpot mapping and hydrogeological characterization, through the geospatial MIFs model and aquifer geoelectrical interpretation, respectively, facilitate decision-makers for sustainable GRM not only in the Karak watershed but also in other similar areas worldwide.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w13091255</doi><orcidid>https://orcid.org/0000-0001-6075-9359</orcidid><orcidid>https://orcid.org/0009-0001-6989-2639</orcidid><orcidid>https://orcid.org/0000-0001-6963-9396</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aquifers Boreholes Case studies Climatic changes Decision making Drainage density Drilling Drinking water Electrical resistivity Elevation Environmental impact Feasibility studies Fluctuations Geoelectricity Geographic information systems Geology Geophysical exploration Geophysical methods Geospatial data Gravel Groundwater Groundwater levels Groundwater management Groundwater potential Hydrogeology Hydrologic data Hydrology Irrigation water Land cover Land use Lithology Management Mapping Methods Optimization Precipitation Prospecting Rainfall Reflectance Resource management Sand Sandstone Seasons Sediments Soil density Soil erosion Spatial distribution Stratigraphy Surface water Water Water shortages Water supply Water, Underground Watersheds |
title | Integrating a GIS-Based Multi-Influence Factors Model with Hydro-Geophysical Exploration for Groundwater Potential and Hydrogeological Assessment: A Case Study in the Karak Watershed, Northern Pakistan |
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