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首页> 外文期刊>Journal of the Indian Society of Remote Sensing >An Integrated GIS Based Statistical Model to Compute Groundwater Vulnerability Index for Decision Maker in Agricultural Area
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An Integrated GIS Based Statistical Model to Compute Groundwater Vulnerability Index for Decision Maker in Agricultural Area

机译:基于集成GIS的农业地区决策者地下水脆弱性指数的统计模型

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The conservation areas in a plain are affected by the groundwater contamination from intense application of the fertilizers. The vulnerability of groundwater can be tested by using the DRASTIC model for the pollutants. The groundwater susceptibility to pollution in the various areas is mapped through DRASTIC model. However, the effects of pollution types and its characteristics are not considered, as this model is used without any modifications. This technique must be standardized for usage in the various aquifers and specific pollution types. The rates of DRASTIC parameters are corrected to obtain the potential for a more accurate analysis of the vulnerability pollution. The relationships between the parameters are identified with respect to the nitrate concentration in the groundwater by calculating the new rates. The methodology was applied to the selected area situated in the south eastern region of Iran at Kerman plain. Twenty-seven different locations were selected to test and analyse the nitrate concentration in the water from underground wells. The pollution in the aquifer was associated and correlated with the DRASTIC index by using the measured nitrate concentrations. The relationship between the index and the measured pollution in the Kerman plain was determined by applying the Wilcoxon ranksum nonparametric statistical tests and the rates were calculated. It was found specifically in the agricultural areas that the modified DRASTIC model performed more efficiently than the traditional method for nonpoint source pollution, as indicated by the results. After modifications, the regression coefficients revealed that the relationship between the vulnerability index and the nitrate concentration was 77%, while it was 37% before the modifications were used. These statistics show that the modified DRASTIC performed far more efficiently than the original version.
机译:平原上的保护区受到大量施肥对地下水污染的影响。可以使用DRASTIC模型测试污染物的地下水脆弱性。通过DRASTIC模型绘制了各个地区的地下水对污染的敏感性。但是,未考虑污染类型及其特性的影响,因为使用了该模型而未做任何修改。必须对该技术进行标准化,以用于各种含水层和特定的污染类型。校正DRASTIC参数的速率,以获得对漏洞污染进行更准确分析的潜力。通过计算新的速率,可以确定参数之间相对于地下水中硝酸盐浓度的关系。该方法已应用于位于伊朗东南部克尔曼平原的选定区域。选择了27个不同的位置来测试和分析地下井水中水中的硝酸盐浓度。通过使用测得的硝酸盐浓度,含水层中的污染与DRASTIC指数相关并相关。通过应用Wilcoxon ranksum非参数统计检验确定了指数与克尔曼平原测得的污染之间的关系,并计算了比率。结果表明,特别是在农业地区,改进的DRASTIC模型比传统的非点源污染方法更有效。修改后,回归系数显示脆弱性指数与硝酸盐浓度之间的关系为77%,而修改前为37%。这些统计数据表明,修改后的DRASTIC的执行效率远高于原始版本。

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