Tool for Searching USEPA’s TMDL Reports Repository to Analyze TMDL Modeling State of the Practice

Abstract

Total maximum daily load (TMDL) reports archived in the USEPA database can provide useful guidance for the development of new TMDLs and watershed management plans by aiding the selection process for the most appropriate modeling tool. The database contains more than 70,000 individual documents; therefore, a rapid screening tool is needed to elicit information about previous modeling studies that might help guide stakeholders and regulators in dealing with the TMDL application at hand, save time, and lead to a more cost-effective regulatory outcome. The paper introduces a smart web-based software tool for TMDL report selection based on different water management criteria. The tool uses an automated search method based on frequency of common water body impairments and models to categorize and select TMDL reports. Additionally, this tool provides better insight on the relationship between the modeling tools used and the impairments they address. This tool has proven useful in reviewing the state of integrated modeling (IM), applications of remote sensing (RS), application of basic versus mechanistic modeling, margin of safety (MOS) assessment, and the state of practice regarding relationships among impairments, models, and regions where TMDLs for various pollutants are being developed. Despite limitations on direct access to all TMDLs developed and reported to the EPA by the user, the tool can be improved over time to derive a better understanding of the relationships between these impairments, data, and the TMDL development process. Although the MOS is not directly quantified in the current version of the TRS tool, this feature may be incorporated in future updates.

Selecting Reliable Models for Total Maximum Daily Load Development: Holistic Protocol

“…The availability of a wide variety of models makes the task of appropriate model selection a challenging one. The more important listings of some TMDL models (Shoemaker et al 1997;Martin and McCutcheon 1999;Bera 2003, 2004;Shoemaker et al 2005;Muñoz-Carpena et al 2006;Moriasi et al 2012Moriasi et al , 2015Martin et al 2015; ASCE TMDL Analysis and Modeling Task Committee 2017; Borah et al 2019a;Camacho et al 2019;Quinn et al 2019;Zhang and Quinn 2019;Yuan et al 2020) are not fully focused on the fundamentals of TMDL model selection. However, no comprehensive model selection protocol exists.…”

“…Very few such studies exist (Neilson and Stevens 2002;Cabrera-Stagno 2007;Benham et al 2008;Clark and Vanrolleghem 2010;Topp et al 2020). We also studied documents describing the modeling and data needs of various commonly used watershed and water quality models (Deas and Lowney 2000;Muñoz-Carpena et al 2006;Keisman and Shenk 2013;Quinn et al 2019;Water Environment Federation 2020). In addition to these documents, we found guidance documents on TMDL model selection (Oregon Department of Environmental Quality, n.d.; Deas and Lowney 2000;Imhoff 2003; USEPA 2018d).…”

“…At the same time, no attempt has been made in the past to review the more than 70,000 USEPA-approved TMDL documents and build a comprehensive catalog of models and analytical procedures (Quinn et al 2019). To the best of our knowledge, our compilation of TMDL reports in Table 1 and derivation of statistics shown in Fig.…”

“…Very few receiving water quality models have been actually peer-reviewed, and in most cases, the stage of model development ranging from research models to fully developed models optimized for the practice of TMDL determination has not been defined (e.g., NCASI 1982;McCutcheon 1983b). More recent evaluations include selections of watershed and receiving water quality models that were heuristically chosen for TMDL determination (Martin and McCutcheon 1999;Bera 2003, 2004;Shoemaker et al 2005;Muñoz-Carpena et al 2006;Moriasi et al 2012Moriasi et al , 2015Martin et al 2015; ASCE TMDL Analysis and Modeling Task Committee 2017; Borah et al 2019a;Camacho et al 2019;Quinn et al 2019;Zhang and Quinn 2019;Yuan et al 2020).…”