Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

• Published in: Journal of the American Water Resources Association 2020-02, Vol.56 (1), p.16-29
• Main Authors: Driscoll, Jessica M., Hay, Lauren E., Vanderhoof, Melanie K., Viger, Roland J.
• Format: Article
• Language: English
• Subjects: Annual; Annual runoff; Computation; Computer simulation; Correlation; Correlation analysis; Daily; Depression storage; Geographical distribution; Geologic depressions; Geological surveys; Hydrologic models; Hydrology; modeling; Monthly; MWBM; Potholes; PRMS; Runoff; Surface runoff; surface‐depression storage; Surveying; Temporal resolution; Time; Viability; Water balance; Watersheds
• ISSN: 1093-474X; 1752-1688
• DOI: 10.1111/1752-1688.12826

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida). Research Impact Statement: Correlation between simulated runoff and surface depression storage using continental‐extent models to improve understanding and representation of surface‐depression storage processes.