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Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process

机译:运用层次分析法模拟印度南部波纳亚尔河流域地下水概率指数

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摘要

In the present study, an effort has been made to investigate the analytical hierarchy process has been applied to delineate groundwater potential based on integrated geographic information system (GIS) and remote sensing (RS) techniques in Ponnaiyar River basin, Tamil Nadu, India. At first, the climatic factor, topographic factors, water related factors, geological factors, hydrogeo-logical factors and other ecological factors such as land use/land cover and soil depth were derived from the spatial geo-database. Secondly, the 74 groundwater data with high potential yield values of >40 m3/h were collected and mapped in GIS. Out these, 44 (60 %) cases were randomly selected for models training, and the remaining 31 (40 %) cases were used for the validation purposes. Then, the assigned weights of thematic layers based on expert knowledge were normalized by eigenvector technique of AHP. To prepare the groundwater potential index, the weighted linear combination (WLC) method was applied in GIS. Finally,the receiver operating characteristic (ROC) curve was drawn for groundwater potential map, and the area under curve (AUC) was computed. Results indicated that the rainfall and slope percent factors have taken the highest and lowest weights, respectively. Validation of results showed that the AHP method (AUC = 76.90 %) performed fairly good predication accuracy. Results of this study could be helpful for better management ofgroundwater resources in the study area and give planners and decision makers an opportunity to prepare appropriate groundwater investment plans for sustainable environment.
机译:在本研究中,已努力研究基于印度的泰米尔纳德邦邦纳尔河流域的综合地理信息系统(GIS)和遥感(RS)技术的层次分析法用于描述地下水潜力。首先,从空间地理数据库中得出气候因子,地形因子,与水有关的因子,地质因子,水文地质因子以及其他生态因子,如土地利用/土地覆盖和土壤深度。其次,收集了74个潜在产量> 40 m3 / h的地下水数据,并将其绘制在GIS中。其中,随机选择了44(60%)个案例进行模型训练,其余31(40%)个案例用于验证目的。然后,使用层次分析法的特征向量技术对基于专家知识的主题层分配权重进行归一化。为了编制地下水潜力指数,在GIS中应用了加权线性组合(WLC)方法。最后,绘制了地下水位图的接收器工作特性曲线,并计算了曲线下面积。结果表明,降雨和坡度百分比因子分别具有最高权重和最低权重。结果验证表明,AHP方法(AUC = 76.90%)表现出相当好的预测准确性。这项研究的结果可能有助于更好地管理研究区域的地下水资源,并使计划者和决策者有机会为可持续环境制定适当的地下水投资计划。

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