Mapping erosion risk for saline rangelands of the Mancos Shale using the rangeland hydrology erosion model

Authors: MCGWIRE, KENNETH - Desert Research Institute; Weltz, Mark; Nouwakpo, Sayjro; SPAETH, KENNETH - Natural Resources Conservation Service (NRCS, USDA); FOUNDS, MICHAEL - Desert Research Institute; CADARET, ERIK - Desert Research Institute

Submitted to: Land Degradation and Development
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/3/2020
Publication Date: 4/23/2020
Citation: Mcgwire, K., Weltz, M.A., Nouwakpo, S.K., Spaeth, K., Founds, M., Cadaret, E. 2020. Mapping erosion risk for saline rangelands of the Mancos Shale using the rangeland hydrology erosion model. Land Degradation and Development. 2020. 31:2552-2564. https://doi.org/10.1002/ldr.3620.
DOI: https://doi.org/10.1002/ldr.3620

Interpretive Summary: This research used the rangeland hydrology and erosion model (RHEM) to map erosion risks affecting water quality of the Colorado River that originate from the Mancos Shale formation in Utah, Colorado,New Mexico, and Arizona. The Mancos Shale formation is a significant source of salinity, and a portion of that salt load derives from erosion of rangeland soils. Here we demonstrate that the hillslope-scale RHEM model can effectively characterize erosion risk across this large, discontinuous region. Inputs to RHEM included digital elevation data, soil properties, vegetation attributes, Landsat and MODIS satellite imagery, field data from the USDA Natural Resources Conservation Service (NRCS) Rangeland National Resource Inventory program, and rainfall data from Atlas 14 of the U.S. National Atmospheric and Oceanographic Administration. RHEM predicted sediment yield for 30 and 60-minute durations storms with a return frequency of 10-year and 25-year. Results corresponded reasonably with prior field experiments that used the Walnut Gulch Rainfall Simulator (WGRS), with a Spearman’s rank-order correlation of 0.76 for cumulative sediment yield after 20 minutes of rainfall. Issues of input map accuracy were identified for rainfall intensity and estimates for sodium adsorption ratio (SAR) of soils using NRCS web soil survey inputs. Correction of erroneous SAR at WGRS sites in one location improved rank-order correlation to 0.93, indicating very good model performance where map inputs are accurate. The high-resolution map of erosion risk developed from RHEM can help to prioritize specific areas suitable for development of conservation plans to reduce risks of salt loading to the Colorado River.

Technical Abstract: This research used the rangeland hydrology and erosion model (RHEM) to map erosion risks affecting water quality of the Colorado River that originate on the Mancos Shale formation in Utah, Colorado, New Mexico, and Arizona. The Mancos Shale is a significant source of salinity, and a portion of that salt load derives from erosion of rangeland soils. Here we demonstrate that the hillslope-scale RHEM model can effectively characterize erosion risk across this large, discontinuous region. Inputs to RHEM included digital elevation data, statistically modeled maps of soil properties, the LANDFIRE vegetation map,Landsat and MODIS satellite imagery, field data from the Rangeland National Resource Inventory program of the U.S. Natural Resources Conservation Service, and rainfall data from Atlas 14 of the U.S. National Atmospheric and Oceanographic Administration. RHEM predicted sediment yield at a 30 m spatial resolution for storms with 30 and 60-minute durations whose intensities corresponded to 10-year and 25-year return frequencies. Results corresponded reasonably with prior field experiments that used the Walnut Gulch Rainfall Simulator (WGRS), with a Spearman’s rank-order correlation of 0.76 for cumulative sediment yield after 20 minutes of rainfall. Issues of input map accuracy were identified for rainfall intensity and estimates for sodium adsorption ratio (SAR) of soils. Correction of erroneous SAR at WGRS sites in one location improved rank-order correlation to 0.93, indicating very good model performance where map inputs are accurate. The high-resolution map of erosion risk developed from RHEM can help to prioritize specific areas for more intensive study and action.