Linking Uncertainty Analysis with Trading Ratio Determination from TMDL Allocation Process

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ABSTRACT
TMDL allocation is central to the overall TMDL process because it creates a technically feasible and reasonably fair division of the allowable load among sources. An innovative approach for TMDL allocation and implementation is the watershed-based pollutant trading. Given the inherent scientific uncertainty for the tradeoffs between point and nonpoint sources, setting of trading ratios can be a contentious issue and was already listed as an obstacle by several pollutant trading programs. One of the fundamental reasons that a trading ratio is often set higher (e.g. greater than 2) is to allow for uncertainty in the level of control needed to attain water quality standards, and to provide a buffer in case traded reductions are less effective than expected. Another reason is to account for differences in the impact of a pollutant in different locations. However, most of available studies did not provide an approach to explicitly address the determination of trading ratio. Instead, subjective selection based on project need and previous literature is often employed in selecting trading ratio within a pre-specified range. Furthermore, uncertainty analysis has rarely been linked to determination of trading ratio.

This paper presents a practical methodology in estimating “equivalent trading ratio” and links uncertainty analysis with trading ratio determination from TMDL allocation process. Determination of ETR can provide a preliminary evaluation of “tradeoffs” between various combination of point and nonpoint source control strategies on ambient water quality improvement. Furthermore, there may be many combinations of point and nonpoint source load allocations that can meet the water quality standard. Greater portion of NPS load reduction in overall TMDL load reduction generally correlates with greater uncertainty and thus requires greater trading ratio. By further incorporating economic consideration (e.g. marginal cost for treatment), it will enhance the scientific basis and thus public perception with the determination of trading ratio for more informed decision in overall TMDL-based pollutant trading program.

INTRODUCTION
Total Maximum Daily Load (TMDL) determinations are critical to the attainment of water quality goals in watershed management. TMDL allocation is central to the overall TMDL process because it creates a technically feasible and reasonably fair division of the allowable load among sources. Watershed-based pollutant trading has gained more and more popularity as an innovative approach for TMDL allocation and implementation over the past several years.

Given the scientific uncertainty for the tradeoffs between point and nonpoint sources, setting trading ratios can be a contentious issue. A trading ratio is often set higher (e.g., greater than 2) to provide a buffer in case traded reductions are less effective than expected. For example, the effect of a reduction in discharge or the application of a best management practice (BMP) cannot always be predicted precisely. Also, because natural physical, chemical, and biological processes remove a pollutant as it is transported, pollutants discharged from different sources, at different locations, do not have the same impact. Therefore, it is difficult to determine the correct trading ratio. Unfortunately, most available pollutant trading studies are not much help, so states often use a subjective selection method based on project needs and literature case studies. Furthermore, uncertainty analysis has rarely been linked to determination of trading ratio. Therefore, the objectives of this paper are to present a practical methodology for quantifying trading
ratio and link uncertainty analysis with trading ratio determination from TMDL allocation process.

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