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利用多元指示克里金方法评估灌溉地下水污染范围。

Use of multivariate indicator kriging methods for assessing groundwater contamination extents for irrigation.

机构信息

Department of Leisure and Recreation Management, Kainan University, Luzhu, Taoyuan 33857, Taiwan.

出版信息

Environ Monit Assess. 2013 May;185(5):4049-61. doi: 10.1007/s10661-012-2848-x. Epub 2012 Sep 5.

Abstract

Multivariate geostatistical approaches have been applied extensively in characterizing risks and uncertainty of pollutant concentrations exceeding anthropogenic regulatory limits. Spatially delineating an extent of contamination potential is considerably critical for regional groundwater resources protection and utilization. This study used multivariate indicator kriging (MVIK) to determine spatial patterns of contamination extents in groundwater for irrigation and made a predicted comparison between two types of MVIK, including MVIK of multiplying indicator variables (MVIK-M) and of averaging indicator variables (MVIK-A). A cross-validation procedure was adopted to examine the performance of predicted errors, and various probability thresholds used to calculate ratios of declared pollution area to total area were explored for the two MVIK methods. The assessed results reveal that the northern and central aquifers have excellent groundwater quality for irrigation use. Results obtained through a cross-validation procedure indicate that MVIK-M is more robust than MVIK-A. Furthermore, a low ratio of declared pollution area to total area in MVIK-A may result in an unrealistic and unreliable probability used to determine extents of pollutants. Therefore, this study suggests using MVIK-M to probabilistically determine extents of pollutants in groundwater.

摘要

多元地质统计学方法已广泛应用于描述污染物浓度超过人为监管限值的风险和不确定性。在区域地下水资源保护和利用方面,对污染潜在范围进行空间划定具有重要意义。本研究采用多元指示克里金(MVIK)来确定地下水灌溉的污染范围的空间模式,并对两种 MVIK 类型进行了预测比较,包括指示变量相乘的 MVIK(MVIK-M)和指示变量平均的 MVIK(MVIK-A)。采用交叉验证程序来检验预测误差的性能,并探索了两种 MVIK 方法中不同的概率阈值用于计算污染面积与总面积之比。评估结果表明,北部和中部含水层的地下水具有极好的灌溉用水质量。交叉验证程序的结果表明,MVIK-M 比 MVIK-A 更稳健。此外,MVIK-A 中污染面积与总面积之比较低可能导致用于确定污染物范围的概率不切实际和不可靠。因此,本研究建议使用 MVIK-M 来概率性地确定地下水污染物的范围。

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