Spatial riverine loads of nitrogen derived from gauge observations and river network across the Conterminous United States

Authors: WANG, Y - Oak Ridge Institute For Science And Education (ORISE); ZHAO, K - The Ohio State University; Zhang, Xuesong

Submitted to: Scientific Data
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/19/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Riverine nitrogen is an important water quality parameter in the U.S. and across the globe. The lack of spatially-explicit riverine nitrogen yield maps represent a knowledge gap in identifying critical source areas of nitrogen pollution. In this study, we calculated riverine nitrogen loads at over 1,800 hydrological stations across the Conterminous United States (CONUS), and derived the spatial distribution of riverine nitrogen yield by combining the riverine nitrogen loads and the catchment topology information from the National Hydrography Dataset. We also estimated that over 64% of the riverine nitrogen yield is contributed from non-point sources by excluding nitrogen inputs from point sources. The newly derived spatial distribution of riverine nitrogen yield can provide useful information for identification of critical source areas for nitrogen pollution and verification of water quality models to ensure credible model simulations.

Technical Abstract: Riverine nitrogen loads are a pivotal determinant influencing water quality in inland and coastal waters. While a multitude of studies have underscored the significance of riverine nitrogen loads on a local scale, the absence of a database encompassing spatial nitrogen loads manifests a discernible gap in our capacity to quantify the net gain or loss of riverine nitrogen burdens. This, in turn, hinders our ability to comprehend the principal contributors to the riverine nitrogen loads. Here, we (1) compiled 294,996 riverine total nitrogen concentrations and concurrent streamflow data across the Conterminous United States (CONUS), (2) estimated the riverine loads of total nitrogen (TN) for over 1,800 hydrological stations, (3) derived the spatial distribution of riverine nitrogen loads by leveraging river and catchment connectivity information contained in the National Hydrography Dataset plus (NHD-plus), and (4) characterized nonpoint-source TN loads by excluding point-source loads. This newly assembled spatial riverine nitrogen load dataset helps enhance the quantification of the spatial sources of nitrogen load and can be used to conduct spatially explicit verification of distributed water quality models. As such, this new dataset represents a valuable resource for both research and management of water quality.