Research Of Solute Transport And Contamination Risk In Groundwater Based On Uncertainty Theory

Solute transport and contamination risk assessment in groundwater is one of the important research fields of groundwater resource management. However, there are a wide range of uncertainties affecting the accuracy of the research. And these uncertainties are increasingly becoming an obstacle to the management of groundwater resources.This dissertation first summarized the main features of the groundwater contamination environemntal system, reviewed the research progresses of solute transport, environmental risks, and uncertainty theory and their applications to the groundwater environmental system. Based on that, it was pointed out that there were three types of uncertain theory that used in the disseration. The first type is the basic uncertainty theory, such as stochastic mathsmatic methodology, interval mathsmatic methodolody and fuzzy mathsmatic metholodgy; the second is the heterogenity of the parameters and their stochastic modeling techniques; and the third is the uncertain parameter identification techniques based on Bayesian theory. The main works and novel results include the following elements. (1) Aiming at the heterogenity of the hydraulic conductivity, Gaussian Random Space (RSF) function was used to discribe the distribution of hydraulic conductivity, and aiming at the parameter identification problem, the uncertain parameter identification techniques based on Bayesian theory was applied to infere the posterior distributions of parameters in RSF. The solute transport in the heterogenious aquifer was studied under the two kinds of uncertainties. The results showed that the posterior distributions of parameters were dissymmetrical. When more conditional data were incorporated in the analysis, the standard deviation of parameters was smaller, the centralized trend was more obvious, and the optimal parameters were closer to the hypothetic ones. Hydraulic conductivity had great effects on solute transports in groundwater. Taking the effect of hydraulic conductivity uncertianty into account, the uncertainty for solute transport increased with the increasing of time and decreased with increasing of the number of conditional data. (2) Aiming at uncertainty associatied with solute transport in heterogeneous formations, a coupled inverse modeling metholodgy about optimal solute transport was developed. Conditioning to the measured hydraulic conductivity and observed concentration data, the hydraulic conductivity field and concentration distribution were regenerated at the same time using a new type of algorithm-Mutative Scale Chaos Genetic algorithm (MSCGA). The results showed that the description of hydraulic conductivity and solute concentration filed was improved when both kinds of data were combined in the coupled inverse modeling system. The coupled inverse modeling provided a trade-off between geological setting and solute transport. (3) Aiming at uncertainty associated with different mintoring data, interval number was used to respersent contaminants concentration. Based on the application of interval number theory and fuzzy attributed recognization technique, an intergrated fuzzy model for groundwater environmental health risk assessment was established. The results of case study showed that the hydraulic conductivity was important for the results of parameter identification. The model could resolve the uncertainties in reality to some extent. And compared with groundwater environmental health risk assessment model under certainty, the results of the established model were more comprehensive and reasonable in reflection of the situation of environmental health risks associated with groundwater contamination. (4) Aiming at uncertainties of the parameters in the health risk assessment model developed by the United States Environmental Protection Agency (USEPA), a spatial stochastic risk analysis model was developed. In the model, the concentration of contaminants was simulated with sequential indicator simulation, and the other parameters were sampled from their probability density functions. The results of case study showed that the developed model could basically reflect the human health risk of groundwater pollution. The contaminants concentration was the main factors of uncertainty of the resulted risk. (5) Aiming at the subjects and receptors, the environmental risk was considered to be the"vulnerability"of the aquifer multiplied by"hazard"caused by groundwater contamination logically. Taking the stochastic characteristic of"vulnerability"and fuzzy characteristic of risk into account, an intergrated stochastic-fuzzy modeling approach for risk assessment of groundwater contamination was developed. The results of case study showed that the developed approach offered a unique tool for systematically quantifying various uncertainties and clearly expressing the level of risk.Due to the complexity, unique transport rules and various internal reactions of groundwater environmental system, this disseration analyzed the effects of uncertainties of solute transport in groundwater and developed several models assciated with contaminated risk of groundwater under uncertainties. On one hand, this disseration is helpful to reveal the character of uncertainties in solute transport and contamination risk of groundwater system, and to better understand the uncertainties in groundwater environmental system, which was of theoretical significance in certain degree. On the other hand, the results of typical case studies, such as Chang-Zhu-Tan region for"Resource-saving and Environment-friendly Society"construction and manganese contamiantion in groundwater of Huangxing Town, proved that solute transport in groundwater and contamination risk anlysis under uncertainties could effectively reflect the complex behavior of groundwater system and provide scientific support to the management of groundwater resource and control of groundwater contamiantion.