Multi-scale Comparison of Stage IV Nexrad (MPE) and Gauge Precipitation Data for Watershed Modeling

Abstract

Watershed hydrologic and fate-and transport models are widely used to forecast water quantity and quality responses to alternative land use and climate change scenarios. The ability of such tools to forecast changes in ecosystem services with reasonable accuracy depends on calibrating reliable simulations of streamflow, which in turn require accurate climatic forcing data. Precipitation is widely acknowledged to be the largest source of uncertainty in watershed modeling. Most watershed models are designed to easily incorporate publicly available precipitation data from rain gauges (e.g., data provided by the National Climatic Data Center), but several additional data products from ground-based radar and satellite-based sensors are now available and can potentially be used to generate more precise, spatially-explicit precipitation estimates. Here, we investigate whether the use of higher-resolution Multisensor Precipitation Estimator (MPE, also known as Stage IV NEXRAD) data can improve the accuracy of daily streamflow simulations using the Soil and Water Assessment Tool (SWAT) watershed hydrology model. Simulated vs. observed streamflow and model calibrations are compared for two Piedmont sub-basins of the Neuse River in North Carolina (21 and 203 km2 watershed area) for an 8 year simulation period (January 1, 2002 to August 31, 2010). MPE simulations led to more accurate simulations of daily streamflow magnitude and frequency measures than gauge data, and differences were more pronounced in the smaller watershed. Compared with USGS-observed flows, MPE simulations produced R2 values of 0.64 and 0.54 for the larger and smaller watershed, respectively, while gauge data produced R2 values of 0.19 in both watersheds. Nash- Sutcliffe Efficiency and other goodness-of-fit indices also showed much better simulations associated with MPE data. Additionally, the temporal structure of MPE simulated streamflows more closely approximated that of the observed streamflows. These results are likely extendable to the Piedmont of the broader southeastern U.S. Ongoing research on this topic investigates additional spatial and temporal scales, as well as additional precipitation data types.