Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.1, 2013 173 Estimating Willingness-To-Pay for Reduction in Uncertainty in Water Quality of Contaminated Aquifers Ashraf A. Shaqadan 1 and Mohammad Al-Rawashdeh 1 1. Civil Engineering Department, Zarqa University, tel:+962-5-3821100, fax: +962-5-3821120, P.O.Box: 132222, Zarqa, Jordan *E-mail of the corresponding author: ashrafshaqadan@yahoo.com Abstract Management of contaminated aquifers is challenged by the limited resources available to monitor and remediate a large number of contaminated sites. Earlier research recognized the negative impacts of spatial data scarcity on the success of aquifer monitoring and remediation plans. Therefore, there exists an important question on how to allocate limited resources to collect additional information to better estimate the risks and remediation priorities versus the willingness to pay by the society. This work introduces one of the early applications of structural benefit transfer to quantify welfare impacts of improving aquifer monitoring in terms of willingness-to-pay (WTP). This work uses health risk assessment methodology and introduces a practical socio-economic framework to estimate individuals’ WTP for a proposed improvement in data gathering. The proposed methodology develops scenarios of uncertainty reductions in subsurface heterogeneity by collecting additional spatial data to reduce health risk to target population and computed the health-economic impact to estimate the aggregate WTP. The variability of characteristics of the target population is represented through probabilistic distributions of income, health state, age, and risk exposure parameters. The proposed methodology produced predictions of WTP that are consistent with the patterns expected in the economic theory and literature. Keywords: Groundwater, contamination, uncertainty reduction, additional data, Willingness-to-Pay 1. Introduction 1.1 Research Needs The accurate monitoring of contaminated aquifers has been a difficult challenge because of the limited resources available, uncertainty arising from complexities of contaminants and media characteristics, and the presence of many large-scale polluted sites (Ward et al., 1986). Water quality problems affect many functions of society including environmental, economical, and ecological functions. Contaminated groundwater has effects on the population that ranges from direct health effects such as morbidity and mortality to indirect economic damages such as restrictions on recreational uses (Maxwell et al., 1998). Assessment of environmental and economic impacts of contaminated groundwater on a population is complicated and there is lack of quantitative research addressing the welfare impacts of the resulting health risks (Zhao and Kaluarachchi, 2002). Therefore, addressing water quality problems calls for a broad view that utilizes several types of data for various variables. There are many contaminated sites on the National Priority List that requires millions of dollars in remediation costs. Stakeholders need a management tool to help guide allocation of limited resources to maximize socio-economic and health benefits. In groundwater contamination, uncertainty translates to tangible outcomes such as under-estimation of health risks due to uncertain input variables. Logically, a decision that reduces uncertainty in aquifer contamination estimation has social benefits including reduction in exposure to unknown health risk and illnesses or even mortality. So, there is a need to evaluate the socio-economic benefits of decisions that reduce uncertainty in estimating groundwater contamination. The quantification of welfare impacts of such decisions in monetary terms is complicated task especially under the time constraints for decision making. In essence, there is a need to fill this gap in groundwater research and to develop a practical methodology to evaluate the population willingness-to-pay (WTP) for improved data collection to reduce unknown health risks. 1.2 Assessment of Welfare Impacts of changes in Health Risk Several studies investigated the valuation of health risk reduction in air and water quality applications. These studies adopt relevant measures of adverse health or environmental effects of expected exposure levels estimated