Delineation of groundwater potential zones and identification of artificial recharge sites in the Kinnerasani Watershed, India, using remote sensing-GIS, AHP, and Fuzzy-AHP techniques

IF 2.1 4区 环境科学与生态学 Q2 ENGINEERING, CIVIL AQUA-Water Infrastructure Ecosystems and Society Pub Date : 2023-07-05 DOI:10.2166/aqua.2023.052
Padala Raja Shekar, Aneesh Mathew
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引用次数: 1

Abstract

The sustainable management of groundwater resources is crucial for ecological diversity, human health, and economic growth. This study employs scientific concepts and advanced techniques, including the analytic hierarchy process (AHP) and Fuzzy-AHP, to identify groundwater potential zones (GWPZs). Thematic maps representing drainage density, elevation, soil, geomorphology, slope, land use and land cover, and rainfall are used to delineate the GWPZs. Both techniques are employed to assign weights to these thematic maps based on their characteristics and water potential. The study revealed that in the investigated area, 17.76 and 18.27% of the final GWPZs (AHP and Fuzzy-AHP) can be classified as having poor potential, while 72.79 and 71.07% are categorized as having moderate potential. Moreover, 9.45 and 10.69% of the final GWPZs are identified as having high potential using the AHP and Fuzzy-AHP models, respectively. Receiver operating characteristics (ROCs) analysis is employed to validate these findings, demonstrating that the Fuzzy-AHP technique achieves an accuracy of 74% in identifying GWPZs in the region. This study utilises the best method derived from both models to identify 26 suitable locations for artificial recharge sites. The reliable findings of this research offer valuable insights into decision-makers and water users in the Kinnerasani Watershed.
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基于遥感gis、AHP和模糊AHP技术的印度Kinnerasani流域地下水潜力区划分和人工补给点识别
地下水资源的可持续管理对生态多样性、人类健康和经济增长至关重要。本研究运用科学的概念和先进的技术,包括层次分析法(AHP)和模糊层次分析法(Fuzzy-AHP),对地下水潜势区进行识别。地图的主题包括排水密度、高程、土壤、地貌、坡度、土地利用和土地覆盖,以及降雨量。这两种技术都是根据这些专题地图的特点和水势来分配权重的。研究表明,调查区最终的gwpz (AHP和Fuzzy-AHP)中,有17.76和18.27%可划分为潜力差,72.79和71.07%可划分为中等潜力。利用AHP和Fuzzy-AHP模型分别确定了9.45%和10.69%的最终gwpz具有高潜力。采用接受者工作特征(roc)分析来验证这些发现,表明模糊层次分析法在该地区识别gwpz的准确率达到74%。本研究利用两种模型得出的最佳方法确定了26个适宜的人工补给点。这项研究的可靠发现为Kinnerasani流域的决策者和用水者提供了有价值的见解。
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来源期刊
CiteScore
4.10
自引率
21.10%
发文量
0
审稿时长
20 weeks
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