Department of Civil Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, Uttar Pradesh, India.
Banerjee Centre of Atmospheric & Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Prayagraj, 11002, Uttar Pradesh, India.
Environ Sci Pollut Res Int. 2022 Jul;29(31):47740-47758. doi: 10.1007/s11356-022-19211-0. Epub 2022 Feb 19.
The present study illustrates the delineation of the groundwater potential zones in one of the most critical and drought-affected areas under Bundelkhand region of Uttar Pradesh (India). Hydrological evaluations were carried out using GIS tools and remote sensing data which ultimately yielded several thematic maps, such as lineament density, land use/land cover, drainage density, lithology, slope, geomorphology, topographic wetness index (TWI), DEM, and soil. Thematic layers were assigned relative weightages as per their groundwater potential prospects under multi-criteria decision making (MCDM) method through analytical hierarchy process (AHP). To recognize the groundwater potential zone, weighted overlay analysis was also performed. Additionally, for testing of the Dempster-Shafer model, 16 wells in the study area have been selected. Based on the probability of the groundwater occurrence, the belief factor was equated to delineate groundwater potential zones which illustrate five different potential zones. According to the AHP model, the northwest side of the study area is characterized with very high potential zones whereas the northeast and southeast regions constitute medium and low groundwater potential zones respectively. According to the DS model, very high groundwater potential zones constitute 17% and the remaining area falls under low potential. Overall accuracy of the DS model is higher than AHP model.
本研究描绘了印度北方邦邦德尔汗德地区最关键和受干旱影响最严重的地区之一的地下水潜力区的划分。使用 GIS 工具和遥感数据进行了水文评估，最终生成了几个专题地图，如线性密度、土地利用/土地覆盖、排水密度、岩性、坡度、地貌、地形湿度指数 (TWI)、DEM 和土壤。根据多准则决策 (MCDM) 方法中的层次分析法 (AHP)，根据地下水潜力前景为专题层分配相对权重。为了识别地下水潜力区，还进行了加权叠加分析。此外，为了测试 Dempster-Shafer 模型，在研究区域内选择了 16 口井。根据地下水发生的概率，置信因子被用来划定地下水潜力区，说明了五个不同的潜力区。根据 AHP 模型，研究区的西北侧具有很高的潜力区，而东北和东南地区分别构成中低地下水潜力区。根据 DS 模型，极高的地下水潜力区占 17%，其余区域属于低潜力区。DS 模型的整体准确性高于 AHP 模型。
