Can a simple water quality model effectively estimate runoff-driven nutrient loads to estuarine systems? A national-scale comparison of STEPLgrid and SPARROW

This study investigated whether a simple model could scale across watersheds and effectively predict runoff driven nutrient loading as compared to a model with more complex process representation. A lumped model, the Spreadsheet Tool for Estimating Pollutant Load (STEPL), was adapted to use gridded data (STEPLgrid) and applied to 112 coastal watersheds across the Atlantic, Gulf, and Pacific coasts of the contiguous United States (U. S.) to estimate annual runoff-driven total nitrogen (TN) and total phosphorus (TP) loads. STEPLgrid outputs were compared to those of the SPAtially Referenced Regression on Watershed Attributes (SPARROW) model. Relative to SPARROW, STEPLgrid produced comparable estimates of TN and TP loads for most watersheds studied and its predicted loads were more similar to SPARROW for TN than TP. STEPLgrid was particularly effective at rank ordering watersheds by TN and TP loads as compared to SPARROW, indicating that STEPLgrid was useful for relative comparisons across diverse watersheds.

Automated summary

This study investigated the scalability and predictive ability of a simple model compared to a more complex model in terms of runoff-driven nutrient loading across watersheds. The results showed that the STEPLgrid model produced comparable estimates of nitrogen and phosphorus loads to the SPARROW model for most watersheds studied, with its predicted loads being more similar to SPARROW for nitrogen. STEPLgrid was particularly effective at rank ordering watersheds by nitrogen and phosphorus loads, indicating its usefulness for relative comparisons across diverse watersheds.