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Calibration of groundwater vulnerability mapping using the generalized reduced gradient method

机译:使用广义简化梯度法校准地下水脆弱性图

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Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods.
机译:地下水脆弱性评估研究对水资源管理至关重要。诸如DRASTIC之类的覆盖索引方法广泛用于绘制地下水脆弱性,但是这些方法主要受模型参数的主观选择之苦。这项研究的目的是引入一种校准程序,以更准确地评估地下水脆弱性。使用目标函数将评估的改进公式化为参数优化问题,该目标函数基于实际地下水污染与脆弱性指标值之间的相关性。非线性优化问题通过广义降阶法(GRG)解决,这是一种基于数值算法的优化方法。为了证明该程序的适用性,使用硝酸盐浓度数据对Tahtali流域的脆弱性图进行了校准。校准程序易于实施,其目标是使观察到的污染物浓度与地下水脆弱性指数值之间的相关性最大化。通过执行单参数敏感性分析,可以评估每个漏洞参数在漏洞指数计算中的影响。敏感性分析的结果表明,所有因素对最终脆弱性指数均有效。易损性图的校准可将指标值与测量的硝酸盐浓度之间的相关性提高19%。回归系数从0.280增加到0.485。显然,随着校准过程的发生,脆弱性类别区域的空间分布和比例将发生显着变化。尽管在DRASTIC模型上证明了校准方法的适用性,但是该方法的适用性并不特定于某个模型,并且还可以轻松地应用于其他叠加索引方法。

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