The development of TMDLs typically involves quantitative water quality and watershed modeling. For agencies/stakeholders faced with the task of developing TMDLs, the selection of an appropriate modeling framework can be a daunting task. This paper presents an approach to selecting
appropriate watershed modeling tools, identifies important considerations and potential pitfalls pertaining to model selection, and presents a case study of the proposed approach on the Steamboat Creek watershed, NV. The Steamboat Creek watershed case study was conducted as part of the watershed
model selection process for the region. The case study involved a detailed comparison of the Watershed Analysis Risk Management Framework (WARMF) model to an industry standard model for TMDL projects, Hydrologic Simulation Program – Fortran (HSPF), in order to provide confidence in the
application of the WARMF model in the region. The case study was conducted to assess the use of the Watershed Analysis Risk Management Framework (WARMF) model for TMDL studies in the region. This detailed comparison was undertaken to: 1) compare the applicability of WARMF and HSPF for watershed
modeling; and 2) compare non-point source loading estimates and water quality calibration results for dissolve oxygen, nitrogen, phosphorous and total dissolved solids. Flows and constituent concentrations were calibrated in both models to match observed values at three locations: Galena Gage,
Rhodes Road and Kimlick Lane. The target accuracy was ±10 percent for periods with accurate data and ±20 percent for periods with marginal data quality. The HSPF model simulated hydrology relatively well with deviations, generally over-estimated flows, occurring due to snowmelt
or irrigation diversions. WARMF simulated hydrology fairly well and captured the peaks and recessions due to snow melt fairly well, but generally, over-estimated flows during the irrigation months. HSPF water quality calibration results followed the year to year and seasonal trends reasonably
well for all constituents but over-estimated TN, TP, TDS and TSS during the winter periods. Calibration results for WARMF followed the year to year and seasonal trends reasonably well for all constituents but under-estimated TN, TP, TDS and TSS during storm events. In addition to water quality,
pollutant loads were evaluated on a monthly and yearly basis for TN, TP, TDS and TSS.
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