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Application of geospatial technology for delineating groundwater potential zones in the Gandheswari watershed, West Bengal

机译:地理空间技术在西孟加拉邦甘德斯瓦里流域划定地下水潜力区中的应用

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摘要

Identification of groundwater potential zones needs an understanding of different hydro-geological parameters of the concerned region. This present study done on Gandheswari watershed of West Bengal is mainly based on RS and GS techniques. Seven important parameters are taken into consideration namely geology, lineament, slope, drainage, soil, rainfall, and land use and land cover which are mutually interdependent to each other in the groundwater development process. Satellite image of Landsat-8, SRTM-DEM of USGS, rainfall data of IMD, topographical sheets of SOI, geological map of GSI, soil map of NBSS&LUP are collected and processed as per requirements in the ArcGIS, Erdas Imagine and PCI Geometica software to create or extract layers for all the parameters. The MIF technique is applied to assign weight to each parameter based on its level of influence to other parameters. All the layers are now integrated together adopting weighted overlay method in ArcGIS software. The prepared final map shows the groundwater potential zones of the Gandheswari watershed. An accuracy assessment is done based on groundwater fluctuation data of last 10 years (2018-2009) from CGWB calculating Kappa co-efficient to validate the study. The study reveals that an area of 275.9 km~2 (69.86%) is found to be good prospect of groundwater. The overall accuracy level of the study is calculated to be 84.62%, while the result of the Kappa co-efficient is 88% for the same.
机译:确定地下水潜在区需要了解有关地区的不同水文地质参数。本研究主要在RS和GS技术的基础上对西孟加拉邦的Gandheswari流域进行。考虑了七个重要参数,即地质,地貌,坡度,排水,土壤,降雨以及土地利用和土地覆盖,它们在地下水开发过程中相互关联。根据ArcGIS,Erdas Imagine和PCI Geometica软件的要求,收集并处理Landsat-8的卫星图像,USGS的SRTM-DEM,IMD的降雨数据,SOI的地形图,GSI的地质图,NBSS&LUP的土壤图。为所有参数创建或提取图层。 MIF技术用于根据每个参数对其他参数的影响程度为每个参数分配权重。现在,所有层都通过ArcGIS软件中的加权叠加方法集成在一起。准备好的最终地图显示了Gandheswari流域的地下水潜在区域。基于CGWB计算Kappa系数的最近十年(2018-2009年)的地下水波动数据进行了准确性评估,以验证研究结果。研究表明,发现275.9 km〜2(69.86%)的面积是地下水的良好前景。研究的整体准确性水平经计算为84.62%,而相同的Kappa系数结果为88%。

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