A Geospatial Methodology to Identify Locations of Concentrated Runoff from Agricultural Fields1. (19th August 2015)

• Record Type: Journal Article
• Authors: Hancock, Gregory; Hamilton, Stuart E.; Stone, Monica; Kaste, Jim; Lovette, John
• Is Part Of: Journal of the American Water Resources Association. Volume 51:Number 6(2015)
• Page Start: 1613
• Page End: 1625
• Publication Date: 2015-08-19
• Subjects: agricultural runoff -- GIS -- lidar -- Chesapeake Bay -- riparian buffers; Water-supply -- Periodicals; Hydrology -- Periodicals; Water resources development -- Periodicals; Water resources development -- Environmental aspects -- Periodicals; 333.9100973
• DOI: 10.1111/1752-1688.12345
• Languages: English
• ISSNs: 1093-474X

Abstract

Abstract: A geospatial methodology has been developed that utilizes high resolution lidar‐derived DEMs to help track runoff from agricultural fields and identify areas of potential concentrated flow through vegetated riparian areas in the Coastal Plain of Virginia. Points of concentrated flow are identified across 74 agricultural fields within the Virginia portion of the Chesapeake Bay watershed. On average, 70% of the surface area of the agricultural fields analyzed drains through less than 20 m of the field margin, and on average 81% of the field surface area drains through 1% or less of the field margin. Within the riparian buffer, locations that were predicted by the geospatial model to have high levels of concentrated flow were found to exhibit evidence of channelization. Results indicate that flow concentration and channelized flow through vegetated riparian areas may be common along the margin of agricultural fields, resulting in vegetated riparian areas that are less effective at sediment trapping than assumed. Additional results suggest that the regulations governing the location and width of vegetated riparian may not be sufficient to achieve goals for reducing sediment and nutrient runoff from nonpoint agricultural sources. Combined with the increasing availability of lidar‐derived DEMs, the geospatial model presented has the potential to advance management practices aimed at reducing nonpoint source pollution leaving agricultural fields.