Performance of the National Water Model in Iowa Using Independent Observations. (17th December 2019)

• Record Type: Journal Article
• Authors: Rojas, Marcela; Quintero, Felipe; Krajewski, Witold F.
• Is Part Of: Journal of the American Water Resources Association. Volume 56:Number 4(2020)
• Page Start: 568
• Page End: 585
• Publication Date: 2019-12-17
• Subjects: National Water Model -- evaluation -- performance -- data assimilation; Water-supply -- Periodicals; Hydrology -- Periodicals; Water resources development -- Periodicals; Water resources development -- Environmental aspects -- Periodicals; 333.9100973
• DOI: 10.1111/1752-1688.12820
• Languages: English
• ISSNs: 1093-474X

Abstract

Abstract: This paper explores the performance of the analysis‐and‐assimilation configuration of the National Water Model (NWM) v1.0 in Iowa. The NWM assimilates streamflow observations from the United States Geological Survey (USGS), which increases the performance but also limits the available data for model evaluation. In this study, Iowa Flood Center Bridge Sensors (IFCBS) data provided an independent nonassimilated dataset for evaluation analyses. The authors compared NWM outputs for the period between May 2016 and April 2017, with two datasets: USGS streamflow and velocity observations; Stage and streamflow data from IFCBS. The distribution of Spearman rank correlation ( r s ), Nash–Sutcliffe efficiency ( E ), and Kling–Gupta efficiency (KGE) provided quantification of model performance. We found the performance was linked with the spatial scale of the basins. Analysis at USGS gauges showed the strongest performance in large (>10, 000 km 2 ) basins ( r s = 0.9, E = 0.9, KGE = 0.8), with some decrease at small (<1, 000 km 2 ) basins ( r s = 0.6, E = −0.25, KGE = −0.2). Analysis with independent IFCBS observations was used to report performance at large basins ( r s = 0.6, KGE = 0.1) and small basins ( r s = 0.2, KGE = −0.4). Data assimilation improves simulations at downstream basins. We found differences in the characterization of the model and observed data flow velocity distributions. The authors recommend checking the connection of USGS gauges and NHDPlus reaches for selected locations where performance is weak. Abstract : Research Impact Statement : Streamflow and velocity estimates from the National Water Model (NWM) are evaluated using an independent dataset. NWM predictions are better at larger watersheds and downstream basins in Iowa.