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地下水脆弱性模型——模糊DRASTIC与模糊DRASTIC-L的比较分析

A comparative analysis on groundwater vulnerability models-fuzzy DRASTIC and fuzzy DRASTIC-L.

作者信息

Saranya Thiyagarajan, Saravanan Subbarayan

机构信息

Department of Civil Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India.

Department of Civil Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.

出版信息

Environ Sci Pollut Res Int. 2022 Dec;29(57):86005-86019. doi: 10.1007/s11356-021-16195-1. Epub 2021 Sep 5.

Abstract

Groundwater vulnerability assessment using the fuzzy logic technique is attempted in this study. A hierarchical fuzzy inference system is created to serve the selected objective. The parameters considered in this study are similar to the seven parameters used in conventional DRASTIC methods; however, the effect of land use and land cover is studied by including it as an additional parameter in a model. A hierarchy is created by comparing two input parameters, say (D and R), and the output of the same is paired as an input with the third parameter (A) and so on using the fuzzy toolbox in MATLAB. Thus, the final output of fuzzy inference systems six and seven (FI6 and FI7) is defuzzified and mapped using ArcGIS to obtain the groundwater vulnerability zones by fuzzy DRASTIC and fuzzy DRASTIC-L. Each map is grouped into five vulnerability classes: very high, high, moderate, low, and very low. Further, the results were validated using the observed nitrate concentration from 51 groundwater sampling points. The receiver operating curve (ROC) technique is adopted to determine the best suitable model for the selected study. From this, area under the curve is estimated and found to be 0.83 for fuzzy DRASTIC and 0.90 for fuzzy DRASTIC-L; the study concludes that fuzzy DRASTIC-L has a better value of AUC suits best for assessing the groundwater vulnerability in Thoothukudi District.

摘要

本研究尝试运用模糊逻辑技术进行地下水脆弱性评估。创建了一个分层模糊推理系统以实现选定目标。本研究中考虑的参数与传统DRASTIC方法中使用的七个参数相似;然而,通过将土地利用和土地覆盖作为模型中的一个附加参数来研究其影响。通过比较两个输入参数(如D和R)创建一个层次结构,并将其输出与第三个参数(A)配对作为输入,以此类推,使用MATLAB中的模糊工具箱。因此,对模糊推理系统六和七(FI6和FI7)的最终输出进行去模糊化处理,并使用ArcGIS进行映射,以通过模糊DRASTIC和模糊DRASTIC-L获得地下水脆弱性区域。每张地图分为五个脆弱性等级:极高、高、中、低和极低。此外,使用从51个地下水采样点观测到的硝酸盐浓度对结果进行验证。采用接收器操作曲线(ROC)技术来确定所选研究的最佳适用模型。据此,估计曲线下面积,发现模糊DRASTIC为0.83,模糊DRASTIC-L为0.90;研究得出结论,模糊DRASTIC-L的AUC值更好,最适合评估杜蒂戈林地区的地下水脆弱性。

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