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水体状态误分类问题——一种分层方法。

The problem of water body status misclassification-a Hierarchical Approach.

机构信息

Faculty of Building Services, Hydro and Environmental Engineering, Warsaw University of Technology, Nowowiejska 20, 00-653, Warsaw, Poland.

The Polish National Energy Conservation Agency, Al. Jerozolimskie 65/79, 00-697, Warsaw, Poland.

出版信息

Environ Monit Assess. 2018 Apr 3;190(5):264. doi: 10.1007/s10661-018-6603-9.

Abstract

This article addresses the issue of estimating probability of misclassification (PoM), when assessing the status of a water body (w.b.). The standard deviation of a monitoring data is considered a good measure of the uncertainty of the assessed w.b. status. However, when PoM is to be estimated from the biological data, a problem caused by too few monitoring data emerges. The problem is overcome by developing Monte-Carlo models to simulate sufficient synthetic measurements of these elements, thereby accounting for random "disturbances" in the measurements. At each level of a procedure, called the Hierarchical Approach, values of PoM were derived from the Monte-Carlo-simulated data as for the assessment of w.b. status. It is assumed in the Hierarchical Approach that PoMs on each upper level can be estimated by processing PoMs inherited from the lower levels. Data from the river monitoring systems in three Polish regions were used in the study. Values of PoM calculated for biological elements show that 70-80% of cases belong to < 0.0, 0.1 > interval, whereas PoMs for physico-chemical elements in only 20% belong in this interval whereas for 25-40% of cases, PoMs are greater than 0.5. Moreover, when analyzing PoMs for cases when the w.b. status was classified as good, 22-52% of them are characterized by 0.5 or higher probability to be assessed wrongly. These pessimistic results suggest the need for formulation of new directions for future research in determining the PoM (in general, the uncertainty) of the w.b. status estimated from monitoring data.

摘要

本文探讨了在评估水体(w.b.)状况时,估计错误分类概率(PoM)的问题。监测数据的标准差被认为是评估 w.b. 状态不确定性的良好指标。然而,当需要从生物数据中估计 PoM 时,会出现由于监测数据太少而导致的问题。通过开发蒙特卡罗模型来模拟这些元素的足够合成测量值,可以解决这个问题,从而考虑到测量中的随机“干扰”。在称为层次方法的每个程序级别中,都从蒙特卡罗模拟数据中得出 PoM 值,用于评估 w.b. 状态。在层次方法中,假设每个上层的 PoM 可以通过处理从下层继承的 PoM 来估计。研究中使用了波兰三个地区河流监测系统的数据。对于生物元素计算的 PoM 值表明,70-80%的情况属于 <0.0, 0.1> 区间,而物理化学元素的 PoM 只有 20%属于该区间,而对于 25-40%的情况,PoM 大于 0.5。此外,当分析将 w.b. 状态分类为良好的情况下的 PoM 时,22-52%的情况具有 0.5 或更高的错误评估概率。这些悲观的结果表明,需要制定新的方向,以确定从监测数据估计的 w.b. 状态的 PoM(一般来说,不确定性)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feaa/5882631/0886961e4159/10661_2018_6603_Fig1_HTML.jpg

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