Integrating Economic and Biophysical Models to Assess the Impacts of Water Quality TradingEPA Grant Number: R831774
Title: Integrating Economic and Biophysical Models to Assess the Impacts of Water Quality Trading
Investigators: Peterson, Jeffrey M. , Fox, John A. , Leatherman, John C. , Marsh, Thomas L. , Mankin, Kyle R.
Institution: Kansas State University , Washington State University
Current Institution: Kansas State University
EPA Project Officer: Hahn, Intaek
Project Period: January 1, 2005 through December 31, 2008
Project Amount: $392,105
RFA: Market Mechanisms and Incentives for Environmental Management (2003) RFA Text | Recipients Lists
Research Category: Environmental Justice
Many states have recently adopted trading programs to improve water quality. In spite of the potential gains from these programs, a commonly noted feature is their extremely low trading volumes. Consequently, there remains considerable uncertainty regarding the obstacles to trading in water quality markets and the rules and execution that would allow such a program to realize the maximum gains from exchange. Additional research is needed to systematically test alternative program structures and rules in ways that reflect actual trader knowledge, perception and behavior. The overall goal of this project is to obtain a set of general relationships that link the economic and environmental performance of a trading program to a set of causal factors. These factors include the exogenous conditions in a given watershed (e.g., topography), as well as the institutional rules that govern trading (e.g., trading ratios).
Novel approaches will be used to quantify the incentives for trading and to integrate economic and biophysical processes. Micro-level data on the benefits and costs of trading will be gathered from specially designed experimental market sessions of point and nonpoint polluters in two study watersheds. The experiments will be implemented using an existing web-based trading tool known as NutrientNet (http://www.nutrientnet.org Exit ). The experimental data will then be used to estimate a micro-level model of trading behavior based on the method of positive mathematical programming. Using the output of this model, the nutrient credit market will be simulated under alternative trading rules using a variant of the sequential, bilateral trading algorithm pioneered by Atkinson and Tietenberg. The biophysical processes in the study watersheds will be modeled with the Soil and Water Assessment Tool (SWAT). SWAT will be run initially to suggest plausible trading ratios and other rules prior to the simulations in each study watershed, and it will be run a second time at the post-trading equilibrium to identify the effects of alternative programs on water quality. Although data will be gathered for two study watersheds in the state of Kansas, the intent of the analysis is to identify a general set of relationships that are transferable to watersheds in other regions.
The project will lead to an integrated tool that will assess both the economic and water quality impacts of alternative program structures and compare them to alternative policies such as input controls. This tool will be capable of identifying the impact of various institutional rules and other factors on the performance of a trading program in a given watershed. Thus, it will be known what combination of rules would be most appropriate to facilitate trading in certain contexts, as well as the initial conditions under which trading is likely to be most successful.