Uncertainty Analysis of an Aquivalence-based Fate and Transport Model using a Hybrid Fuzzy-Probabilistic Approach

摘要

Fate and transport models have extensively been used to predict distribution of toxic substances in the multi-media environment. In mining industry, predictive models are commonly used to evaluate performance of mitigation measures and estimate remediation costs during different phases of a mine lifecycle. These models are often used in deterministic form; however the probabilistic analysis through Monte Carlo analysis simulations is also popular to describe parameter uncertainties. In pre-mine phase, where data and information that characterize a mine site are scarce, some parameters of fate and transport models can be best described as random and can subjectively be defined as fuzzy variable. This paper presents a fuzzy-probabilistic approach to propagate parameters uncertainties throughout the modeling process. An aquivalence-based fate and transport model was developed for a mine site. This model was integrated with fuzzy-probabilistic algorithm to predict the distribution of copper concentrations in soil and groundwater. The prediction results showed the distribution of copper concentrations in groundwater, the associated prediction uncertainties and sources of uncertainty.