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

Journal Article · 25 June 2019 · Journal of Hydrologic Engineering

DOI: https://doi.org/10.1061/(asce)he.1943-5584.0001805 · OSTI ID:1580919

Quinn, Nigel W. T. ^[1]; Kumar, Saurav ^[2]; La Plante, Rosanna ^[3]; Cubas, Francisco ^[4]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2. Univ. of Texas at El Paso, TX (United States)
3. Baltimore City, Baltimore, MD (United States)
4. Georgia Southern Univ., Statesboro, GA (United States)

We report that 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. Finally, although the MOS is not directly quantified in the current version of the TRS tool, this feature may be incorporated in future updates.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 1580919
• Journal Information: Journal of Hydrologic Engineering, Journal Name: Journal of Hydrologic Engineering Journal Issue: 9 Vol. 24; ISSN 1084-0699
• Publisher: American Society of Civil EngineersCopyright Statement
• Country of Publication: United States
• Language: English