The Sampling Planning for Groundwater Risk Assessment using Fuzzy Theory
Date Issued
2005
Date
2005
Author(s)
Huang, Jen-Wei
DOI
zh-TW
Abstract
Sampling is a method to value the uncertainty in groundwater remediation system. This study presents a method using fuzzy set theory to quantify the uncertainty of parameters and facilitate the subsequent remediation. This method firstly takes the coefficient of variation (CV) of risk as inputs of membership function and then transfers it to linguistic variables, credibility, and finally quantifies the uncertainty by Fuzzy-Based Comprehensive Assessment Theory. Besides, in order to reduce the influences of space variations and uncertainty, we couple random field generation and conditional simulation procedure to obtain several conditional realizations to allocate the optimal sampling positions in the study.
The case study shows that the major parameters affecting cancer risk are hydraulic conductivity, bulk density, effective porosity and longitudinal dispersivity, according to priority. And some fuzzy models would have inappropriate credibility assessment results. Then, when the parameters are considered as “fields” instead of “values”, it suggests that Monte Carlo simulations should be modeled more than 5000 times to make the probability distribution of risk stable.
Based on the reduction of risk uncertainty, the results also show that the optimal sampling positions are better located in the pollution sources and pollution acceptors or the neighborhood. In addition, the number of random fields would not influence the overall sampling configuration but the sequence of sampling positions.
Subjects
不確定性
模糊集理論
條件模擬
地下水污染
Uncertainty
Fuzzy set theory
Conditional simulation
Groundwater contamination
SDGs
Type
thesis
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