| With the rapid growing of economic development,groundwater environment is getting steadily worse and the environmental problem of groundwater pollution has become the focus of attention.Therefore,it is necessary to actively carry out the management of polluted sites,determine the remediation technology of groundwater pollution,effectively control and reduce pollutant emission.For decades,a large number of groundwater remediation technology has been improved and innovated.In the actual remediation process,different contaminated sites and various remediation technologies would be faced.Before the repair operation at a great expense,decision makers need to measure the site environmental conditions,technical feasibility,remediation effect,duration of treatment,national environmental standards and health risk standards in order to identify the most desirable management strategy.Based on the concept of sustainable development of groundwater,this dissertation focuses on the simulation of contaminant transport in groundwater,health risk assessment and multi-attribute decision making method.Decision models for remediation of contaminated groundwater were developed and a set of alternatives under different management periods were analyzed,which could provide theoretical basis and decision support for the selection of remediation strategies for groundwater contaminated sites.The main contents are summarized as follows:(1)The remediation of groundwater pollution is a complex process of physical,chemical and biological synthesis with many uncertainties.Compared with the fuzzy membership function or the exact probability distribution function,it is relatively easy to obtain the uncertain value range(i.e.,upper and lower bounds)for decision makers.Thus,two multi-attribute decision making methods of groundwater management strategies for dealing with interval attribute values were proposed,i.e.,interval-based multi-attribute decision analysis(IMADM)and Monte Carlo-based interval transformation multi-attribute decision making(MCITA-MADM).In IMADM,interval theory was introduced into the traditional MADM decision analysis.MCITA-MADM is combined with Monte Carlo method,Interval transformation analysis and MADM.A coal-fired power plant in Anhui province where groundwater has been contaminated was used to demonstrate the performance of the proposed approach.Based on the pump and treat method,finite set of alternatives and multi-attributes were evaluated.Combined with analytic hierarchy process,the ranking order of the alternatives were calculated and then the most desirable groundwater management strategies were selected.The results indicated the two methods could effectively deal with the interval attributes with the upper and lower bounds,and provide the ranking result for decision makers under different durations.(2)In dealing with multi-attribute decision making problems,fuzzy theory has become an effective tool to deal with uncertain information.However,due to the existence of multiple uncertainties during the process of remediation,the attribute information in the form of regular triangular fuzzy numbers were too subjective and a large amount of objective information would be lost.Moreover,it is difficult to determine the precise values for lower and upper bounds of triangular fuzzy number.Instead,defining the lower and upper bounds values as an interval seems to be more accurate for expressing the uncertainty information.Thus,an inexact interval-valued triangular fuzzy based multiattribute decision making(IVTF-MADM)method was developed for evaluating the selection of remediation strategies of groundwater remediation under uncertainty.The level of health risk that was determined as one of the decision attributes was introduced into the framework of groundwater remediation decision-making system.Interval triangular fuzzy numbers were used to represent the uncertainty of the contaminant concentration and the level of health risk simulated under different porosities.The interval theory and analytic hierarchy process were combined to determine the importance of different evaluation attributes in terms of experts.By combining the algorithm of the possible degree of interval numbers,the IVTF-MADM decision model was used in the management of chlorhydrocarbons-contaminated groundwater.The results showed that the proposed method could effectively analyze the decision information which were input with interval triangular fuzzy number,and provide the ranking order of different remediation alternatives for decision makers.The traditional determination numbers and triangular fuzzy numbers were only special cases of interval triangular fuzzy numbers,thus the ranking results obtained by IVTF-MADM were more convincing.(3)Health risk assessment of groundwater pollution was closely connected with groundwater pollution and human health.By assessing groundwater pollution,the potential impact of pollutants on human health could be quantified.There were many uncertainties in the evaluation process.Thus,a rough-interval-based multi-attribute decision making method(RI-MAMD)was developed to balance the interaction and operation effect of each alternative in the attributes of daily total pumping rate,total cost and rough-interval risk.The uncertainty of slope factors was considered in excess lifetime cancer risk assessment,and the slope factor was treated as a random variable in the health risk assessment model.Rough interval decision matrixes were generated through pair-wise combining the values under three confidence levels(i.e.68.3%,95.4% and 99.7%).Fifty remediation alternatives under four duration options(i.e.5,10,15,and 20 years)and ten attributes were taken into consideration to in the decision model.The results showed that the most desirable groundwater remediation strategies were different under different remediation periods.Compared with the traditional MADM,the RI-MADM proposed in this study can solve the interaction of the double interval parameters and the interaction between the decision results,which could consider the uncertainty and reduce the subjectivity as much as possible.(4)The traditional uncertain MADM methods could only be used for solving complex problems on existence of the parameters with fuzziness or randomness,leading to the decision results unreliable due to fuzziness and randomness were existed simultaneously during the decision-making process for site remediation.Thus,a cloud model based multiattribute decision making framework(CM-MADM)with Monte Carlo were for the contaminated-groundwater remediation strategies selection.The cloud model was used to handle imprecise numerical quantities.The cloud model based contaminated concentrations and carcinogenic risk level were aggregated via the backward cloud generator.The weights of attributes were calculated by employing the weight cloud model.The preference degree between alternatives under one attribute and all attributes were analyzed under uncertainty.The Monte Carlo method was used to simulate the cloud drop score of the cloud model based net outranking flow.The optimal extraction scheme under different durations were evaluated by comparing the expected value or median value.In the evaluation process,evaluation attributes that were related to technology,economic and environmental impact were involved.The results indicated that the method could describe the ambiguity and randomness of decision information more accurately,and providing decision support for identifying the best suitable groundwater restoration management. |
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