Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams
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Abstract
Understanding spatial variability in contaminant fate and transport is critical to efficient regional water-quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km2 Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant (α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km2) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams |
Series title | JAWRA |
DOI | 10.1111/1752-1688.12419 |
Volume | 52 |
Issue | 3 |
Year Published | 2016 |
Language | English |
Publisher | American Water Resources Association |
Contributing office(s) | Maryland Water Science Center |
Description | 20 p. |
First page | 685 |
Last page | 704 |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |