Neglect of Potential Seasonal Streamflow Forecasting Skill in the United States National Water Model

Abstract

Abstract Using data from the NASA Soil Moisture Active/Passive mission, Koster et al. (2023, https://doi.org/10.1038/s41467‐023‐39318‐3) conclude that, for medium‐scale basins in the contiguous United States, a quarter of interannual variability in springtime streamflow is explained by interannual anomalies in late‐fall soil moisture. This lagged relationship can be leveraged for seasonal hydrologic forecasting, but only if effectively captured by existing prediction models. Here, we extend the analysis in Koster et al. (2023, https://doi.org/10.1038/s41467‐023‐39318‐3) to diagnose systematic errors present in the United States National Water Model (NWM). Results demonstrate that the NWM tends to underestimate both the trans‐winter temporal memory of 0–1 m soil moisture as well as the correlation between 0 and 1 m soil moisture and streamflow—thereby reducing the NWM's ability to leverage vertically averaged soil moisture as a source of hydrologic predictability.

Keywords

• soil moisture
• stream flow forecasting
• remote sensing