气候变化领域集成服务门户

Understanding all watershed systems and their interactions is a complex, but critical, undertaking when developing practices designed to reduce topsoil loss and chemical/nutrient transport from agricultural fields. The presence of riparian buffer vegetation in agricultural landscapes can modify the characteristics of overland flow, promoting sediment deposition and nutrient filtering. Watershed simulation tools, such as the USDA-Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model, typically require detailed information for each riparian buffer zone throughout the watershed describing the location, width, vegetation type, topography, and possible presence of concentrated flow paths through the riparian buffer zone. Research was conducted to develop GIS-based technology designed to spatially characterize riparian buffers and to estimate buffer efficiency in reducing sediment loads in a semiautomated fashion at watershed scale. The methodology combines modeling technology at different scales, at individual concentrated flow paths passing through the riparian zone, and at watershed scales. At the concentrated flow path scale, vegetative filter strip models are applied to estimate the sediment-trapping efficiency for each individual flow path, which are aggregated based on the watershed subdivision and used in the determination of the overall impact of the riparian vegetation at the watershed scale. This GIS-based technology is combined with AnnAGNPS to demonstrate the effect of riparian vegetation on sediment loadings from sheet and rill and ephemeral gully sources. The effects of variability in basic input parameters used to characterize riparian buffers, onto generated outputs at field scale (sediment trapping efficiency) and at watershed scale (sediment loadings from different sources) were evaluated and quantified. The AnnAGNPS riparian buffer component represents an important step in understanding and accounting for the effect of riparian vegetation, existing and/or managed, in reducing sediment loads at the watershed scale.