Economics of aquifer protection in a stochastic environment

Efficient policies to control nonpoint source pollution should recognize the probability distribution of pollutant loadings given the inherent uncertainties. This dissertation develops an economic model of aquifer protection from nitrate contamination in a stochastic environment. First, a stochastic optimal control model is developed, introducing randomness in groundwater quality into economic analysis of public policy alternatives. The model derives optimal combinations of abatement practices necessary to reduce nitrate contamination. If society is risk averse, the optimal abatement levels will be greater, and nitrate concentrations lower, than those corresponding to the deterministic model. The model also demonstrates that increased variability in pollutant accumulation leads to increases in the shadow rent of water quality, which may increase public concern over pollution control. An application of the model to a hypothetical watershed illustrates the impacts of uncertainty on groundwater protection strategies, and examines various policy questions. As empirical data on nitrate leaching are not widely available, the applied economic model is integrated with a nitrogen fate model. The Rhode Island Geographic Information System provides necessary data on geological and land use aspects of the watershed. Using these data, the physical model estimates a probability distribution on nitrate concentrations using the LEACHA model in conjunction with Monte Carlo simulations. The economic model then identifies least cost-means of achieving probabilistic constraints on aquifer pollutant concentrations, where policies are based on setting maximum allowable probabilities of violating standards. The model illustrates substantial discrepancies between conventional approaches based on mean estimates of nitrate leaching, and a probabilistic approach to nonpoint source pollution modeling. When leaching estimates are adjusted for uncertainty, a completely different set of policy recommendations is generated. In particular, results of the stochastic model suggest that variability resulting from agricultural management practices, such as poorly calibrated spreaders and banding, requires extra measures to control nonpoint source pollution. This imposes additional costs on society. Finally, the model is used to explore policy issues, including the impacts of zoning regulation on water quality, efficiencies of environmental policies targeting protection of well sites (versus aquifer protection as a whole), and distributive aspects of water resource management