Barca E, Passarella G
Water Research Institute, IRSA - CNR, National Research Council, via F. De Blasio, 5, 70123 Bari, Italy.
Environ Monit Assess. 2008 Feb;137(1-3):261-73. doi: 10.1007/s10661-007-9758-3. Epub 2007 Jun 13.
In some previous papers a probabilistic methodology was introduced to estimate a spatial index of risk of groundwater quality degradation, defined as the conditional probability of exceeding assigned thresholds of concentration of a generic chemical sampled in the studied water system. A crucial stage of this methodology was the use of geostatistical techniques to provide an estimation of the above-mentioned probability in a number of selected points by crossing spatial and temporal information. In this work, spatial risk values were obtained using alternatively stochastic conditional simulation and disjunctive kriging. A comparison between the resulting two sets of spatial risks, based on global and local statistical tests, showed that they do not come from the same statistical population and, consequently, they cannot be viewed as equivalent in a statistical sense. At a first glance, geostatistical conditional simulation may appear to represent the spatial variability of the phenomenon more effectively, as the latter tends to be smoothed by DK. However, a close examination of real case study results suggests that disjunctive kriging is more effective than simulation in estimating the spatial risk of groundwater quality degradation. In the study case, the potentially 'harmful event' considered, threatening a natural 'vulnerable groundwater system,' is fertilizer and manure application.
在一些先前的论文中，引入了一种概率方法来估计地下水质量退化风险的空间指标，该指标定义为在所研究的水系统中采样的某种通用化学物质浓度超过指定阈值的条件概率。该方法的一个关键阶段是使用地质统计技术，通过交叉空间和时间信息，在多个选定的点上估计上述概率。在这项工作中，通过交替使用随机条件模拟和析取克里金法获得了空间风险值。基于全局和局部统计检验对所得的两组空间风险进行比较，结果表明它们并非来自同一统计总体，因此，从统计学意义上讲，它们不能被视为等效的。乍一看，地质统计条件模拟似乎能更有效地表示该现象的空间变异性，因为后者往往会被析取克里金法平滑处理。然而，对实际案例研究结果的仔细检查表明，在估计地下水质量退化的空间风险方面，析取克里金法比模拟更有效。在该研究案例中，所考虑的潜在“有害事件”，即威胁天然“脆弱地下水系统”的事件，是化肥和粪肥的施用。
