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Total Maximum Daily Loads (TMDLs), as established by section 303(d) of the Clean Water Act, have been the metric utilized for the assessment and monitoring of the water quality within watersheds. However, with limited gauge stations on the majority of water bodies throughout the United States, determining waterbody impairment has come to rely on hydrological models. This research analyzes the limitations of the TMDL framework and the limitations of the current state-of-the-science models in the context of the use of adequate datasets as well as the appropriateness of both the models and the imposed regulations to capture the proper processes propagating NPS pollution in the context of the reemergence of Lake Erie algal blooms. The Maumee River basin has been documented as the number one contributing source of nutrients responsible for algal blooms in Lake Erie’s Western Basin. This relationship has seen higher discharge values being correlated to increased algal bloom severity. Three analyses were completed. The first of these was an assessment of potential variability among datasets in order to look at the appropriateness of certain frequencies and lengths and to identify where potential sources of error may exist. Secondly, the impacts of chronic and acute loading were examined in order to solidify the understanding of the impacts of spring storm events and establish a context for a process-based evaluation of loading. Finally, a ratio analysis was performed on the chronic and acute loading components of discharge and loads from the Maumee River to evaluate the effectiveness of the SWAT model to capture the appropriate transport processes the watershed exhibits. The spring events were reaffirmed as the primary indicator of the strength of late summer algal blooms in Lake Erie’s Western Basin, establishing the importance of acute transport events and surface transport mechanisms in this region. Here, March flows correlated with blooms at an R2 of 0.72 with the late summer blooms. Evaluated against SWAT model output, SWAT data showed a shift towards chronic with a March ratio shift from 0.62 base/storm for the observed data to 0.95 for the SWAT modeled data. This shift towards baseflow transport processes indicate issues associated with appropriate parameterization in during the calibration and validation process.