Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil
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- More information: Publisher Index Page (via DOI)
- Data Release: USGS data release - RSPARROW Model Archive Files for the Grande River Basin TN SPARROW Model
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Abstract
Large-domain hydrological models are increasingly needed to support water-resource assessment and management in large river basins. Here, we describe results for the first Brazilian application of the SPAtially Referenced Regression On Watershed attributes (SPARROW) model using a new open-source modeling and interactive decision support system tool (RSPARROW) to quantify the origin, flux, and fate of total nitrogen (TN) in two sub-basins of the Grande River Basin (GRB; 43,000 km2). Land under cultivation for sugar cane, urban land, and point source inputs from wastewater treatment plants was estimated to each contribute approximately 30% of the TN load at the outlet, with pasture land contributing about 10% of the load. Hypothetical assessments of wastewater treatment plant upgrades and the building of new facilities that could treat currently untreated urban runoff suggest that these management actions could potentially reduce loading at the outlet by as much as 20–25%. This study highlights the ability of SPARROW and the RSPARROW mapping tool to assist with the development and evaluation of management actions aimed at reducing nutrient pollution and eutrophication. The freely available RSPARROW modeling tool provides new opportunities to improve understanding of the sources, delivery, and transport of water-quality contaminants in watersheds throughout the world.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil |
Series title | Water |
DOI | 10.3390/w12102911 |
Volume | 12 |
Issue | 10 |
Year Published | 2020 |
Language | English |
Publisher | MDPI |
Contributing office(s) | WMA - Integrated Modeling and Prediction Division |
Description | 2911, 20 p. |
Country | Brazil |
Other Geospatial | Grande River basin |
Google Analytic Metrics | Metrics page |