Ground–Surface Water Assessment for Agricultural Land Prioritization in the Upper Kansai Basin, India: An Integrated SWAT-VIKOR Framework Approach

dc.contributor.authorHalder, Sudiptoen
dc.contributor.authorBanerjee, Santanuen
dc.contributor.authorYoussef, Youssef M.en
dc.contributor.authorChandel, Abhilashen
dc.contributor.authorAlarifi, Nassiren
dc.contributor.authorBhandari, Gupinathen
dc.contributor.authorAbd-Elmaboud, Mahmoud E.en
dc.date.accessioned2025-03-27T13:05:40Zen
dc.date.available2025-03-27T13:05:40Zen
dc.date.issued2025-03-19en
dc.date.updated2025-03-26T15:34:32Zen
dc.description.abstractPrioritizing agricultural land use is a significant challenge for sustainable development in the rapidly urbanizing, semi-arid riverine basins of South Asia, especially under climate variability and water scarcity. This study introduces a systematic framework combining remote sensing and geospatial data with the Soil and Water Assessment Tool (SWAT) model, morphometric analysis, and VIKOR-based Multi-Criteria Decision Analysis (MCDA) to effectively identify Agricultural Land Prioritization (AgLP) areas in the Upper Kansai Basin, India, while reducing the environmental impact, in line with Sustainable Development Goals (SDGs). The SWAT model simulation reveals varied hydrological patterns, with basin water yields from 965.9 to 1012.9 mm and a substantial baseflow (~64% of total flow), emphasizing essential groundwater&ndash;surface water interactions for sustainable agriculture. However, the discrepancy between percolation (47% of precipitation) and deep recharge (2% of precipitation) signals potential long-term groundwater challenges. VIKOR analysis offers a robust prioritization framework, ranking SW4 as the most suitable (Qi = 0.003) for balanced hydrological and morphometric features, in agreement with the SWAT outcomes. SW4 and SW5 display optimal agricultural conditions due to stable terrain, effective water retention, and favorable morphometric traits (drainage density 3.0&ndash;3.15 km/km<sup>2</sup>; ruggedness 0.3&ndash;0.4). Conversely, SW2, with high drainage density (5.33 km/km<sup>2</sup>) and ruggedness (2.0), shows low suitability, indicating risks of erosion and poor water retention. This integrated AgLP framework advances sustainable agricultural development and supports SDGs, including SDG 2 (Zero Hunger), SDG 6 (Clean Water), SDG 13 (Climate Action), and SDG 15 (Life on Land). Incorporating hydrological dynamics, land use, soil properties, and climate variables, this approach offers a precise assessment of agricultural suitability to address global sustainability challenges in vulnerable riverine basins of developing nations.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationHalder, S.; Banerjee, S.; Youssef, Y.M.; Chandel, A.; Alarifi, N.; Bhandari, G.; Abd-Elmaboud, M.E. Ground&ndash;Surface Water Assessment for Agricultural Land Prioritization in the Upper Kansai Basin, India: An Integrated SWAT-VIKOR Framework Approach. Water 2025, 17, 880.en
dc.identifier.doihttps://doi.org/10.3390/w17060880en
dc.identifier.urihttps://hdl.handle.net/10919/125090en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectagricultural land prioritizationen
dc.subjectSWATen
dc.subjectgroundwateren
dc.subjectmorphometric analysisen
dc.subjectVIKOR-MCDMen
dc.subjectsustainable development goalsen
dc.subjectremote sensingen
dc.subjectupper Kansai basinen
dc.titleGround&ndash;Surface Water Assessment for Agricultural Land Prioritization in the Upper Kansai Basin, India: An Integrated SWAT-VIKOR Framework Approachen
dc.title.serialWateren
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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