Estimating Willingness-To-Pay for Reduction in Uncertainty in Water Quality of Contaminated Aquifers

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