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TMDLs, or Total Maximum Daily Loads, are a legislated requirement first stipulated in the 1972 Clean Water Act, but 30 years later we are just now trying to implement and make this program work. Progress in the TMDL program and the quality of the work has come under considerable inquiry and diverse criticism. Many have argued that the schedules are too aggressive, leading to poorly developed TMDLs based on insufficient data, poor science, and overly restrictive assumptions. Others argue that progress is too slow and we have enough information to act.

In response to criticisms, there have been several recent efforts to identify issues and recommend improvements related to the TMDL program. In 2001, US EPA contracted with the National Research Council (NRC) to review how scientific data and information should be used in the TMDL program (NRC/NAS, 2001). The Water Environment Research Foundation (WERF) funded three research projects in 2000–2002 that addressed technical tools used in the development of TMDLs (Limno-Tech, et al., 2002a), the listing and delisting process (FTN, et al., 2002), and narrative criteria (Limno-Tech, et al., 2002b). US EPA also recently issued a report on research needs to improve the TMDL Process called “The Twenty Needs Report: How Research Can Improve the TMDL Program (US EPA, 2002b). This paper explores the shortcomings of the TMDL program that have been identified through these and other recent activities, and highlights improvements the authors see that are needed to improve its effectiveness.

In concept the TMDL program is simple: first, identify waters not meeting water quality standards; second, quantify the pollutant source and stressor; then third, allocate load reductions, and then implement them. Unfortunately, problems exist in all areas and improvements are needed. In regards to the first step, establishing standards is a fundamental problem. Standards and related criteria are often mismatched to urban waterways and nearly half of the listed impaired waters involve narrative standards without clear quantitative measures. Improvements are needed for both as well as general methods on how to compare limited data sets to standards. In the second step, quantifying loads and causes, we have major shortcomings in the availability of data and the utility of models to quantify nonpoint sources. Recommendations for a national database and model improvements are provided in these areas. In the third step, establishing necessary load reductions, we have major challenges in selecting and applying appropriate models, and linking them to actual biological impacts. We also have very little experience determining uncertainty and properly incorporating this into the required margin of safety. Various recommendations have been made in each area. Last, in implementing to achieve results we see major shortcomings in using effective regulatory and programmatic tools to control nonpoint sources and often find little progress in implementation as stakeholders debate the analysis and efficacy of the proposed TMDLs.

In response to the above concerns, this paper highlights a series of research guidance and policy needs ranging from research on model uncertainty, to use of adaptive management.
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Document Type: Research Article

Publication date: 2003-01-01

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