FUZZY DECISION MAKING IN GROUND WATER NITRATE RISK MANAGEMENT¹

Abstract

Ground water nitrate contamination is widespread in the United States and especially prevalent in agriculture‐intensive areas such as the Midwest. To reduce human health risks (i.e., methemoglobinemia and cancer risks) from nitrates in ground water supplies, several nitrate risk‐management strategies can be developed based on acceptable levels of human health risks, the reasonableness of the cost required for risk reduction, and the technical feasibility of nitrate‐control methods. However, due to a lack of available information, assessing risk, cost, and technical feasibility contains elements of uncertainty. In this paper, a nitrate risk‐management methodology using fuzzy sets in combination with a multicriterion decision‐making (MCDM) technique is developed to assist decision makers in evaluating, with uncertain information, possible regulatory actions along with the various nitrate risk‐management strategies in order to determine an appropriate strategy. The methodology is illustrated using data from a community with a nitrate water‐quality problem.

An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination

“…For example, Lee et al (1994) proposed a fuzzy-set-based approach to estimate human-health risk from groundwater contamination and evaluate possible regulatory actions; Goodrich and McCord (1995) applied Monte Carlo methods to account for parameter uncertainties in groundwater flow and solute transport processes, and the modeling outputs were then used for exposure assessment; Mills et al (1996) developed a risk-based method to evaluate the allowable levels of soil gasolinecontaining residues in order to protect human health; Hamed and Bedient (1997) applied the first-and secondorder reliability methods in a risk assessment framework to account for uncertainty; Batchelor et al (1998) developed a stochastic risk assessment model for a site by representing relevant parameters as probability distribution functions; Bennett et al (1998) developed an integrated modeling system for risk assessment by using Monte-Carlo-based contaminant transport simulation results; Maxwell et al (1998Maxwell et al ( , 1999 also developed an integrated system of linked groundwater transport modeling and human exposure assessment; Lee et al (2002) applied Monte Carlo simulation to estimate health risk in a groundwatercontaminated community after on-site remediation. More recently, a hybrid method has been proposed to combine probabilistic and fuzzy-set approaches to represent modeling parameter uncertainties involved in the risk assessment process (Li et al, 2003;Liu et al, 2004).…”

Consideration of Trends in Evaluating Inter-basin Water Transfer Alternatives within a Fuzzy Decision Making Framework

“…Development of decision support architectures for water resources planning and management using fuzzy sets theory has been widely studied for different types of decision-making problems (Kung et al 1992;Lee et al 1994;Ravi and Reddy 1999;Yin et al 1999;Chang et al 2001;Prodanovic and Simonovic 2002;Raju and Nagesh Kumar 2005). These studies have limited applications in terms of consideration of the development trends in the decision-making process.…”

Prioritizing groundwater remediation policies: A fuzzy compatibility analysis decision aid

“…Development of decision support architectures for water resources planning and management using fuzzy sets theory has been widely studied for different types of decision-making problems (Kung et al, 1992;Lee et al, 1994;Ravi and Reddy, 1999;Yin et al, 1999;Chang et al, 2001;Prodanovic and Simonovic, 2002). However, these studies have not provided a structure for multi-level decisions and mainly have not considered the interactions between decision criteria while becoming aggregated.…”