A trading ratio is required for water quality trading that involves nonpoint sources to compensate for the difficulty of determining nonpoint loadings, the stochastic characteristics of nonpoint loadings, and the uncertainty inherent in nonpoint source pollution control strategies. Compensating for risk and uncertainty is one of the primary justifications that a trading ratio greater than one is commonly considered. However, the appropriate specific value of a trading ratio remains unclear because of qualitative differences between point and nonpoint sources. This study addresses a growing concern with the analytical underpinnings of point/nonpoint trading ratios in water quality trading programs. This paper considers a basic spatial-temporal optimal control model assuming that the goal of the decision maker is to maximize ecological services from the watershed over a 10-year planning horizon given a predetermined budget each year to treat acid mine drainage problems. The level of pollution is assumed to be known but declining slightly over time as the acid mine drainage sources evolve. Resources are assumed to be spent on remediation projects that produce long term but declining treatment results. The primary goal of the model is to distribute the available resources over the basin by investing in restoration projects for targeted streams each year that will maximize the ecological return on this investment. The model reflects both the spatial reality of variations in flow, in pollution, in treatment, and in the ecological benefits produced and the intertemporal constraints of limited resources and the inability to move remediation programs once the initial investment is made. The resulting optimal temporal and spatial investment strategies are derived from solutions to a mixed integer programming problem obtained using the GAMS/CPLEX mixed integer programming package. The optimal results are then manipulated to evaluate trading ratios. A hypothetical acidity trading scenario is proposed in which a point source (a new coal mine operation subject to TMDL rules) uses credits generated through remediation projects at other sites from treatment of nonpoint sources within the same basin over the 10-year planning horizon. The trading ratio is the ratio of the expected amount of pollutant removed by treating the nonpoint source divided by the amount of additional pollution allowed from the new point source. Our results indcate that point/nonpoint trading ratios in proposed trading scenarios greater than one can be justified. For example, for a point/nonpoint trade between sources in adjacent stream segments, the appropriate trading ratio is 3.66 (or 3.66 to one). We note that current regulations give a lower bound for point/nonpoint trading ratio of 1:1. The upper bound for point/nonpoint trading ratio depends on technical aspects of the relative costs of treating the point source or treating nonpoint sources and reflects the limit of how much one is willing to pay for credits. A variety of factors determine trading ratios. First, to encourage trades with less uncertainty, trades in which the credit seller and buyer are in close proximity, and in which the credit seller is upstream, lower trading ratios are recommended. Second, trading ratios should be adjusted to favor trades that contribute to strategic restoration goals such as the improvement or maintenance of water quality in a particular basin. Reduced ratios provide incentives to promote the generation of credits in priority locations. Finally, trading ratios for same-pollutant trades should be lower than those for cross-pollutant trades. Three separate trading currencies would be used to account for same-pollutant acid mine drainage trades: pounds of iron, aluminum, and manganese. There would be little uncertainty in the outcome of a trade if the credit generator and buyer were affecting the same pollutant. In contrast, cross-pollutant trades that use a common currency such as ecological indices would be measured based on their ecological effect, which is one step removed from the actual changes in pollutant loads. The higher trading ratio required for cross-pollutant trades reflects this greater uncertainty. All potential trades considered in this study are interspatial trades; trades occur in the same basin; trades could be cross-pollutant trades within acid mine draiange and same-pollutant trades as well; and the credit buyer is the new coal mining operation; credit generators could be government agencies or nonprofit organization; and abandned mine lands and bond forfeiture sites can be sites where credits are generated.


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