|LI, Z - Northwest Agriculture And Forestry University|
|LIU, W - Northwest Agriculture And Forestry University|
Submitted to: Agro-Environment Symposium
Publication Type: Abstract Only
Publication Acceptance Date: 3/1/2010
Publication Date: 5/22/2010
Citation: Zhang, X.J., Li, Z., Liu, W.Z. 2010. Potential change in soil erosion trend and risk during 2010-2039 in central Oklahoma, USA [abstract]. In: Proceedings of the Agro-Environment Symposium: Environmental Sustainability of Agricultural Management Systems in an Ever Changing World, May 19-22, 2010, Cancun, Mexico. 2010 CDROM.
Interpretive Summary: Abstract only.
Technical Abstract: The potential for global climate changes to increase risk of soil erosion is clear, but quantitative analysis of this risk is limited due to high spatial and temporal variability in projected climate change scenarios. For accurate prediction of soil erosion risk under climate change, climate change scenarios projected by General Circulation Models (GCMs) must be appropriately downscaled to particular locations. The objective of this study was to evaluate the site-specific impacts of climate change on soil erosion and surface hydrology at El Reno, Oklahoma in U.S.A. using the Water Erosion Prediction Project (WEPP) model and tempo-spatially downscaled GCMs projections. Climate change scenarios during 2010-2039 projected by four climate models (CCSR/NIES, CGCM2, CSIRO-Mk2 and HadCM3) under three emission scenarios (A2, B2 and GGa) were used. Univariate transfer functions were derived by matching probability distributions between station-measured and GCM-projected monthly precipitation and temperature for the 1957-2006 period. The derived functions were used to spatially downscale the GCMs monthly projections of 2010-2039 to the El Reno unit watershed. The downscaled monthly data were further disaggregated to daily weather series using a stochastic weather generator (CLIGEN). Potential changes in soil erosion risk or uncertainty at the study location will be evaluated using soil erosion rates predicted for the climate change scenarios projected by the four GCMs. The effectiveness of conservation tillage under future climate change will also be assessed.