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Geographic Information Systems Spatial Analysis Laboratory



164A Seaton Hall
920 N. 17th Street
Kansas State University
Manhattan, KS 66506-2904

Phone: 785-532-6727
Fax: 785-532-7310
Email: gissal@k-state.edu

Validating the Kinematic Wave for Rapid Soil Erosion Assessment

estcp_gullyBased on the concept of accumulating overland flow energy, an erosion potential model was developed forFort Riley,Kansas as part of a project funded by the Strategic Enviromental Research and Development Program (SERDP).  By integrating data from digital elevation models (DEMs) and landuse/landcover classifications in a geographic information system (GIS) environment, the model determined where surface water runoff transitions from overland sheet flow to concentrated flow and, as a result, where the potential for soil erosion and gully formation increases.  The first objective of this project, funded by the Environmental Science Technology Certification Program (ESTCP) is to run this erosion potential model for additional military installations selected from regions with different precipitation regimes, landcover conditions, topographic characteristics, and soil types.  A second objective is to operate the model in a predictive mode to better assess the impact of military training activities on future gully formation. 

Determining the overland flowpath of surface water runoff is a key process in erosion modeling because the concentration of overland flow is a primary cause of soil erosion.  However, the ability to classify varying flow regimes is problematic because it is difficult to quantify the energy content of runoff water.  The erosion potential model developed for Fort Riley is capable of determining areas of high erosion potential and, therefore, the optimal locations for siting erosion-preventing BMPs.  Because it requires few inputs, for which easily accessed datasets are available nationwide, data acquisition and preparation times are minimal compared to existing erosion models such as AGNPS and RUSLE.  While the erosion potential model has been shown effective in identifying the location of existing gullies, it can also be operated in a predictive mode to forecast the impact of military training exercises on the formation of new gullies.  By incorporating vehicle tracking data, from field training or simulator-based exercises, anticipated environmental damage such as vegetation loss and vehicle rutting can be simulated and used as the basis to modify representations of current installation terrain.  The validated model can then be run using modified vegetation and topographic input to identify likely sites of gully initiation.    


Military installations will gain the capability to quickly evaluate gully formation potential across their training lands, saving significant time normally spent on ground and air surveys, while making training safer for soldiers and less damaging to equipment.  This modeling approach will assist installation ITAM staff in siting BMPs designed to reduce soil erosion and meet state-enforced TMDLs for streams leaving federal lands.  The ability to predict future erosion potential with the nLS model offers several significant advantages to military installations including providing a sound scientific basis to estimate LRAM costs to repair and prevent gully erosion and the ability to estimate and compare environmental impacts associated with realignment and mission change. 

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