Impacts of the SWOT mission’s unique space-time sampling in the context of hydrologic model calibration

Abstract:

Expected to launch in 2022, the Surface Water and Ocean Topography (SWOT) satellite mission will observe surface water extents and elevations for rivers greater than 50-100 m wide, enabling river discharge estimation at an unprecedented scale. SWOT orbit specifications yield non-uniform space-time measurements globally, however, so resulting river discharge timeseries will be irregular. Previous studies have found that SWOT’s unique spatiotemporal sampling will not have a significant impact on various hydrologic applications including calculating storm return periods, analyzing discharge frequency distributions, identifying river baseflow conditions, and capturing flood dynamics. Here, we extend the analysis of the potential value of SWOT products in the context of hydrologic model calibration. Using previously derived synthetic SWOT discharges, we calibrate a hydrologic model across 39 gauges in the Ohio River basin. Three separate discharge timeseries are used for calibration: daily gauge, temporal SWOT sampling, and temporal SWOT sampling with added uncertainty. Parameter values are changed systematically to create 10,000 model iterations and calibrating the outputs with each discharge timeseries results in similar optimal parameters and overall model performance. Calibration using SWOT temporal sampling alone in fact tends to increase Kling-Gupta Efficiency (KGE) values on average by 0.01. The combined effects of SWOT temporal sampling and potential uncertainty decrease KGE values on average by only 0.09. Our findings suggest that model performance is not significantly impacted when calibrating with a synthetic SWOT discharge timeseries.