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This study investigated the propagation of errors in input satellite-based precipitation products (SPPs) on streamflow and water quality indicators simulated by a hydrological model in the Occoquan Watershed, located in the suburban Washington, D.C. area. A dense rain gauge network was used as reference to evaluate three SPPs which are based on different retrieval algorithms. A Hydrologic Simulation Program-FORTRAN (HSPF) hydrology and water quality model was forced with the three SPPs to simulate output of streamflow (Q), total suspended solids (TSS), stream temperature (TW), and dissolved oxygen (DO). Results indicate that the HSPF model may have a dampening effect on the precipitation-to-streamflow error. The bias error propagation of all three SPPs showed a positive dependency on basin scale for streamflow and TSS, but not for TW and DO. On a seasonal basis, bias error propagation varied by product, with larger values generally found in fall and winter. This study demonstrated that the spatiotemporal variability of SPPs, along with their algorithms to estimate precipitation, have an influence on water quality simulations in a hydrologic model.

Investigating the Error Propagation from Satellite-Based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model