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State-of-the-Art Modeling Could Help Improve Gulfs Water QualityBy Jennifer Arnold
September 27, 2001
State-of-the-art techniques--combining remote sensing and environmental modeling--can help Mississippi Delta farmers choose the best management practices (BMPs) to reduce the amount of eroded sediments that enter oxbow lakes and rivers in the 7,000-square-mile, cotton-producing Delta.
Oxbow lakes are formed when a river cuts a new path across a large bend, usually during flooding, isolating a U-shaped section of the river. Because of the large amount of agricultural farmland in the Mississippi Delta, BMPs have a great impact on sediment reaching the numerous oxbow lakes and rivers of the Delta and ultimately the Gulf of Mexico.
Agricultural Research Service agricultural engineer Ron Bingner and ARS agronomist Seth Dabney with the National Sedimentation Laboratory, Oxford, Miss., conducted a watershed modeling analysis of a Delta farm.
Bingner also worked with ARS hydraulic engineer Jurgen Garbrecht using TOPAZ--topographic parameterization. TOPAZ uses Geographic Information Systems data and computer technologies to define and analyze land surface, watershed configuration and drainage features. The tool correctly identifies the remotely sensed land characteristics.
TOPAZ-derived information is needed to ensure that accurate data is available to run AGNPS 2001, the Agricultural Non-Point Source Pollution Modeling System. AGNPS predicts soil erosion and nutrient transport/loadings from agricultural watersheds for real or hypothetical storms.
This analysis showed that combining cover crops with no-tillage systems can reduce by up to 65 percent the amount of sediment leaving farms. Adding holding ponds can decrease sediment losses by as much as 90 percent. This modeling technology can help U.S. Department of Agriculture's Natural Resources Conservation Service and Extension personnel in Mississippi aid farmers in evaluating and selecting BMPs that are economically feasible as well as beneficial.
ARS is the U.S. Department of Agricultures chief scientific research agency.