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A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region

机译:干旱地区地下水位图的熵指标与突变理论方法的比较

摘要

In this study, index of entropy and catastrophe theory methods were used for demarcating groundwater potential in an arid region using weighted linear combination techniques in geographical information system (GIS) environment. A case study from Badra area in the eastern part of central of Iraq was analyzed and discussed. Six factors believed to have influence on groundwater occurrence namely elevation, slope, aquifer transmissivity and storativity, soil, and distance to fault were prepared as raster thematic layers to facility integration into GIS environment. The factors were chosen based on the availability of data and local conditions of the study area. Both techniques were used for computing weights and assigning ranks vital for applying weighted linear combination approach. The results of application of both modes indicated that the most influential groundwater occurrence factors were slope and elevation. The other factors have relatively smaller values of weights implying that these factors have a minor role in groundwater occurrence conditions. The groundwater potential index (GPI) values for both models were classified using natural break classification scheme into five categories: very low, low, moderate, high, and very high. For validation of generated GPI, the relative operating characteristic (ROC) curves were used. According to the obtained area under the curve, the catastrophe model with 78 % prediction accuracy was found to perform better than entropy model with 77 % prediction accuracy. The overall results indicated that both models have good capability for predicting groundwater potential zones.
机译:在这项研究中,使用熵指数和突变理论方法在地理信息系统(GIS)环境中使用加权线性组合技术在干旱地区划分地下水潜力。对伊拉克中部东部巴德拉地区的一个案例进行了分析和讨论。作为栅格专题层,准备了六个被认为会影响地下水发生的因素,即海拔,坡度,含水层的透射率和储能度,土壤以及到断层的距离,以方便将其集成到GIS环境中。根据数据的可用性和研究区域的当地条件选择因素。两种技术都用于计算权重,并且分配等级对于应用加权线性组合方法至关重要。两种模式的应用结果表明,影响最大的地下水发生因素是坡度和海拔。其他因素的权重值相对较小,这意味着这些因素在地下水发生条件中的作用较小。两种模型的地下水潜力指数(GPI)值均使用自然中断分类方案分为五类:极低,极低,中,高和极高。为了验证生成的GPI,使用了相对工作特性(ROC)曲线。根据获得的曲线下面积,发现具有78%预测精度的突变模型的性能优于具有77%预测精度的熵模型。总体结果表明,这两种模型都具有良好的预测地下水潜在地带的能力。

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