Application of analytical hierarchical process, multi-influencing factor, and geospatial techniques for groundwater potential zonation in a semi-arid region of western India
- Authors
- Yadav, Brijesh; Malav, Lal Chand; Jangir, Abhishek; Kharia, Sushil Kumar; Singh, Shruti V.; Yeasin, Md; Nogiya, Mahaveer; Meena, Roshan Lal; Meena, Ram Swaroop; Tailor, Bhagwati Lal; Mina, Banshi Lal; Alhar, Munirah Sulaiman Othman; Jeon, Byong-Hun; Cabral-Pinto, Marina M.S.; Yadav, Krishna Kumar
- Issue Date
- Feb-2023
- Publisher
- Elsevier B.V.
- Keywords
- Analytical hierarchy process; Geographic information system; Groundwater potential zonation; Jaipur; Multi influence factor; Receiver operating characteristics
- Citation
- Journal of Contaminant Hydrology, v.253, pp.1 - 15
- Indexed
- SCOPUS
- Journal Title
- Journal of Contaminant Hydrology
- Volume
- 253
- Start Page
- 1
- End Page
- 15
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/182166
- DOI
- 10.1016/j.jconhyd.2022.104122
- ISSN
- 0169-7722
- Abstract
- Groundwater resources are alarmingly depleting due to over-exploitation and significant climate changes over time. Therefore, demarcation of groundwater potential zones is essential for addressing the needs of various industries in semi-arid area. Depleting groundwater resources, topography, aquifer features and climatic factors make it necessary to demarcate ground water potential zones in semiarid region of Rajasthan. The Analytical Hierarchy Process (AHP), Geographic Information System (GIS), and Multi Influence Factor (MIF) were used to determine the groundwater potential zones (GWPZs) in the semi-arid region of Jaipur, located in western Rajasthan. In present study, ten influential factors were employed i.e., geomorphology, land use/land cover (LULC), drainage density, rainfall, topographic wetness index (TWI), soil texture, slope, roughness, topographic position index (TPI) and curvature. In AHP technique, the pairwise comparison matrix was generated, and weightages were given to each thematic layer while for MIF, a proposed score for each layer was computed from the aggregate weight of major and minor effects. The GWPZ map generated by AHP technique was categorised into three parts: high, moderate and poor potential zones, covering 13%, 50.7% and 36.3% of the district. While, the GWPZ map produced with the MIF technique was also divided into the same poor, moderate, and high categories, encompassing 35.3, 44.1, and 20.6% of the district, respectively. The results of AHP and MIF techniques were then cross-validated with well depth data obtained from CGWB report, 2019–20. The receiver operating characteristics (ROC) were plotted and the findings shows that the Area under the Curve (AUC) was 79% and 76% for AHP and MIF, respectively which is considered as moderate to high in predictive precision. The study would be helpful in locating drilling sites for groundwater exploration and developing sustainable groundwater and land use policies.
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