Spatial Variability in Nutrient Transport by HUC8, State, and Subbasin Based on Mississippi/Atchafalaya River Basin SPARROW Models

• Published in: Journal of the American Water Resources Association 2014-08, Vol.50 (4), p.988-1009
• Main Authors: Robertson, Dale M., Saad, David A., Schwarz, Gregory E.
• Format: Article
• Language: English
• Subjects: Earth sciences; Earth, ocean, space; Exact sciences and technology; Hydrology; Hydrology. Hydrogeology; Hypoxia; loading; Nitrogen; nutrients; Phosphorus; prioritizing; ranking; Regression analysis; River basins; Simulation; SPARROW; Water resources; watershed modeling; Watersheds
• ISSN: 1093-474X; 1752-1688
• DOI: 10.1111/jawr.12153

Nitrogen (N) and phosphorus (P) loading from the Mississippi/Atchafalaya River Basin (MARB) has been linked to hypoxia in the Gulf of Mexico. With geospatial datasets for 2002, including inputs from wastewater treatment plants (WWTPs), and monitored loads throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) watershed models were constructed specifically for the MARB, which reduced simulation errors from previous models. Based on these models, N loads/yields were highest from the central part (centered over Iowa and Indiana) of the MARB (Corn Belt), and the highest P yields were scattered throughout the MARB. Spatial differences in yields from previous studies resulted from different descriptions of the dominant sources (N yields are highest with crop‐oriented agriculture and P yields are highest with crop and animal agriculture and major WWTPs) and different descriptions of downstream transport. Delivered loads/yields from the MARB SPARROW models are used to rank subbasins, states, and eight‐digit Hydrologic Unit Code basins (HUC8s) by N and P contributions and then rankings are compared with those from other studies. Changes in delivered yields result in an average absolute change of 1.3 (N) and 1.9 (P) places in state ranking and 41 (N) and 69 (P) places in HUC8 ranking from those made with previous national‐scale SPARROW models. This information may help managers decide where efforts could have the largest effects (highest ranked areas) and thus reduce hypoxia in the Gulf of Mexico.