The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands
Arid/semi-arid regions face water challenges much like the Arabian Peninsula, which is primarily caused by continuing shortages and growing activities of reclaimed land, as well as industrial and domestic activities. Consequently, identifying groundwater prospective zones (GWPZs) has become essentia...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-02-01
|
| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2022-0666 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823860473292914688 |
|---|---|
| author | Wang Yuxia Han Yanzhong Guo Yujiao Wang Jingwei Wang Nana Abdelkareem Mohamed |
| author_facet | Wang Yuxia Han Yanzhong Guo Yujiao Wang Jingwei Wang Nana Abdelkareem Mohamed |
| author_sort | Wang Yuxia |
| collection | DOAJ |
| description | Arid/semi-arid regions face water challenges much like the Arabian Peninsula, which is primarily caused by continuing shortages and growing activities of reclaimed land, as well as industrial and domestic activities. Consequently, identifying groundwater prospective zones (GWPZs) has become essential for securing water resources. The study aims to delineate and predict the best areas of groundwater prospection and abstraction by implementing the analytical hierarchy process-geographic information system (GIS) techniques in a rough terrain that occupies ∼70% of fractured hard rocks including ∼34% of the basaltic flow sheet of Wadi Marawani, Saudi Arabia. To investigate the combined impact of the model, 13 input thematic maps, including elevation, slope, curvature, depression, drainage density, Topographic Wetness Index, distance to river, Stream Power Index, Terrain Roughness Index, geology, lineaments, Normalized Difference Vegetation Index, and rainfall factors, were created, and employed in the model, which was subsequently merged through GIS techniques to reveal prospective zones. These maps are mainly derived from Shuttle Radar Topography Mission, Sentinel-1, Landsat, and Tropical Rainfall Measuring Mission. The output map is categorized as very low, low, moderate, high, or very high, and excellent occupying ∼7%. This promising zone is the result of the intersection of several criteria that control groundwater occurrences. The results were enhanced by implementing optical and radar remote sensing data, and thus, suitable recharge places for the future governance and abstraction of groundwater have been identified using GIS–AHP–multicriteria decision analysis methods. For validation, large numbers of well/spring locations that reached 415 are used in total. The efficiency of the model is estimated at 79.90% (area under curve) based on the receiver operating characteristic curve. Moreover, the Interferometry Synthetic Aperture Radar coherence change detection image validated the predicted model and revealed areas of no-coherence areas marked in brown matched to vegetated areas and excellent zones of GWPZs. The applied methodologies and findings of this study present significant insights for water resources planning and management to develop groundwater resources in similar regions worldwide. |
| format | Article |
| id | doaj-art-0b8623b9ba2a449aa2b5f6c6eba0b0bf |
| institution | Kabale University |
| issn | 2391-5447 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj-art-0b8623b9ba2a449aa2b5f6c6eba0b0bf2025-02-10T13:24:15ZengDe GruyterOpen Geosciences2391-54472025-02-011711587210.1515/geo-2022-0666The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid landsWang Yuxia0Han Yanzhong1Guo Yujiao2Wang Jingwei3Wang Nana4Abdelkareem Mohamed5Shandong Agriculture and Engineering University, Jinan, Shandong, ChinaShandong Hengyuan Geographic Information Technology Co., Ltd, Jinan, Shandong, ChinaShandong Tianyunhe Information Technology Co., Ltd., Zibo, Shandong, ChinaRizhao Natural Resources and Planning Bureau, Rizhao, Shandong, ChinaShandong Tianyi Real Estate Land Evaluation Co., Ltd, Taian, Shandong, ChinaGeology Department, South Valley University, 83523, Qena, EgyptArid/semi-arid regions face water challenges much like the Arabian Peninsula, which is primarily caused by continuing shortages and growing activities of reclaimed land, as well as industrial and domestic activities. Consequently, identifying groundwater prospective zones (GWPZs) has become essential for securing water resources. The study aims to delineate and predict the best areas of groundwater prospection and abstraction by implementing the analytical hierarchy process-geographic information system (GIS) techniques in a rough terrain that occupies ∼70% of fractured hard rocks including ∼34% of the basaltic flow sheet of Wadi Marawani, Saudi Arabia. To investigate the combined impact of the model, 13 input thematic maps, including elevation, slope, curvature, depression, drainage density, Topographic Wetness Index, distance to river, Stream Power Index, Terrain Roughness Index, geology, lineaments, Normalized Difference Vegetation Index, and rainfall factors, were created, and employed in the model, which was subsequently merged through GIS techniques to reveal prospective zones. These maps are mainly derived from Shuttle Radar Topography Mission, Sentinel-1, Landsat, and Tropical Rainfall Measuring Mission. The output map is categorized as very low, low, moderate, high, or very high, and excellent occupying ∼7%. This promising zone is the result of the intersection of several criteria that control groundwater occurrences. The results were enhanced by implementing optical and radar remote sensing data, and thus, suitable recharge places for the future governance and abstraction of groundwater have been identified using GIS–AHP–multicriteria decision analysis methods. For validation, large numbers of well/spring locations that reached 415 are used in total. The efficiency of the model is estimated at 79.90% (area under curve) based on the receiver operating characteristic curve. Moreover, the Interferometry Synthetic Aperture Radar coherence change detection image validated the predicted model and revealed areas of no-coherence areas marked in brown matched to vegetated areas and excellent zones of GWPZs. The applied methodologies and findings of this study present significant insights for water resources planning and management to develop groundwater resources in similar regions worldwide.https://doi.org/10.1515/geo-2022-0666water resourceshard rocksarid-semi arid conditionsradar images |
| spellingShingle | Wang Yuxia Han Yanzhong Guo Yujiao Wang Jingwei Wang Nana Abdelkareem Mohamed The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands Open Geosciences water resources hard rocks arid-semi arid conditions radar images |
| title | The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands |
| title_full | The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands |
| title_fullStr | The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands |
| title_full_unstemmed | The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands |
| title_short | The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands |
| title_sort | use of radar optical remote sensing data and geographic information system analytical hierarchy process multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid semi arid lands |
| topic | water resources hard rocks arid-semi arid conditions radar images |
| url | https://doi.org/10.1515/geo-2022-0666 |
| work_keys_str_mv | AT wangyuxia theuseofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT hanyanzhong theuseofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT guoyujiao theuseofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT wangjingwei theuseofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT wangnana theuseofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT abdelkareemmohamed theuseofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT wangyuxia useofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT hanyanzhong useofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT guoyujiao useofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT wangjingwei useofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT wangnana useofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands AT abdelkareemmohamed useofradaropticalremotesensingdataandgeographicinformationsystemanalyticalhierarchyprocessmulticriteriadecisionanalysistechniquesforrevealinggroundwaterrechargeprospectivezonesinaridsemiaridlands |