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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Publications at this Location » Publication #327642

Research Project: AGRICULTURAL LAND MANAGEMENT TO OPTIMIZE PRODUCTIVITY AND NATURAL RESOURCE CONSERVATION AT FARM AND WATERSHED SCALES

Location: Agroclimate and Natural Resources Research

Title: Riparian Erosion Suitability Model Based on Environmental Features

Author
item Botero, A - University Of Illinois
item Chu, M - University Of Illinois
item Guzman, J - Waterborne Environmental
item Starks, Patrick - Pat
item Moriasi, Daniel

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/17/2017
Publication Date: 3/17/2017
Citation: Botero, A., Chu, M.L., Guzman, J.A., Starks, P.J., Moriasi, D.N. 2017. Riparian Erosion Suitability Model Based on Environmental Features. Journal of Hydrology. 1-11.

Interpretive Summary: Riparian erosion is a major cause of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and loss of land. Land and soil management practices are implemented as conservation and restoration measures in order to mitigate environmental problems brought about by riparian erosion. This, however, requires the identification of vulnerable areas to soil erosion. Because of the complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes, assessing erosion vulnerability at the watershed scale is challenging. The main objective of this study was to develop a methodology to identify areas along riparian zones that are potentially susceptible to erosion. The methodology was developed by integrating a watershed model and a habitat suitability model to quantify the probability of presences of elevation changes (a proxy for erosion) across the watershed. The presences of elevation changes were estimated from two LIDAR-based elevation datasets, one taken in 2009 and one in 2012. The changes in elevation were grouped into four erosion categories: low (0.5 - 0.67 m), medium (0.67 - 0.91 m), high (0.91 - 1.34 m) and very high (1.38 - 4.27 m). The categories and their locations were then used to create a thematic map in MaxEnt. Land cover type, soil type, degree of slope, depth of overland flow, lateral inflow to streams, and discharge were used as environmental features in the models as limits on the erosion processes. The modeling methodology was tested in the Fort Cobb Reservoir Experimental watershed (FCREW), located in southcentral Oklahoma. Results showed that the most vulnerable areas for very high erosion were located in the upper riparian zones of the Cobb and Lake Creek sub-watersheds. The main waterways of these sub-watersheds were also found to be prone to stream bank erosion. Approximatively 80% of the riparian zone (stream bank included) was found to have a 30% or less probability to experience very high erosion, while the remaining 20% of the riparian zone had up to a 70% probability of experiencing very high erosion. Furthermore, the results revealed that soil type and slope were the most important predictors of riparian zone erosion in the FCREW. Soils found to be the most prone to very high erosion belonged to soil types having high (> 50%) sand or silt composition. The methodology developed in this study can be used to identify areas most vulnerable to stream and riparian sediment mobilization, enabling targeting of conservation and management practices in areas needing the most attention and resources.

Technical Abstract: Riparian erosion is a major cause of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and loss of land. Land and soil management practices are implemented as conservation and restoration measures in order to mitigate environmental problems brought about by riparian erosion. This, however, requires the identification of vulnerable areas to soil erosion. Because of the complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes, assessing erosion vulnerability at the watershed scale is challenging. The main objective of this study was to develop a methodology to identify areas along riparian zones that are potentially susceptible to erosion. The methodology was developed by integrating the physically-based watershed model MIKE-SHE, which simulates water movement over the landscape, and the habitat suitability model, MaxEnt, which was used to quantify the probability of presences of elevation changes (a proxy for erosion) across the watershed. The presences of elevation changes were estimated from two LIDAR-based elevation datasets, one taken in 2009 and one in 2012. The changes in elevation were grouped into four erosion categories: low (0.5 - 0.67 m), medium (0.67 - 0.91 m), high (0.91 - 1.34 m) and very high (1.38 - 4.27 m). The categories and their locations were then used to create a thematic map in MaxEnt. Environmental features used as constraints to the presence of erosion were land cover, soil, slope, depth of overland flow, lateral inflow to streams, and discharge. The modeling framework was tested in the Fort Cobb Reservoir Experimental watershed (FCREW), located in southcentral Oklahoma. Results showed that the most vulnerable areas for very high erosion (1.38 m to 4.27 m) were located in the upper riparian zones of the Cobb and Lake Creek sub-watersheds. The main waterways of these sub-watersheds were also found to be prone to streambank erosion. Approximatively 80% of the riparian zone (streambank included) was found to have a 30% or less probability to experience very high erosion, while the remaining 20% had a probability of up to 70% to experience very high erosion. Furthermore, the results revealed that soil type and slope were the most important predictors of riparian zone erosion in the FCREW. Soils found to be the most prone to very high erosion belonged to hydrologic groups B and C having high (> 50%) sand or silt composition. The methodology developed in this study can be used to identify areas most vulnerable to stream and riparian sediment mobilization, enabling targeting of conservation and management practices in areas needing the most attention and resources.