Forecasting Future Soil Erosion Risk in Agricultural Landscapes of the Southern United States: Integrating Machine Learning, Environmental Change Scenarios, and Biophysical and Chemical Predictors for Sustainable Land Management
Mahsa Ghorbani1, Christophe J G Darnault2, Shahab Shojaeezadeh3, Malik Al-Wardy4, Mohammad Nikoo5, Steven Campbell6, Marc Parlange7, Henrique Momm8, Daniel C Yoder9 and Giulio Ferruzzi6, (1)Clemson University, School of Civil and Environmental Engineering and Earth Sciences, Clemson, SC, United States, (2)Clemson University, School of Civil and Environmental Engineering and Earth Sciences, Clemson, United States, (3)University of Kassel, Section of Soil Science, Faculty of Organic Agricultural Sciences, Witzenhausen, Germany, (4)Sultan Qaboos University, Department of Soils, Water, and Agricultural Engineering, Muscat, Oman, (5)Sultan Qaboos University, Civil and Architectural Engineering, Muscat, Oman, (6)USDA-NRCS, West National Technology Support Center, Portland, United States, (7)University of Rhode Island, 6Department of Civil and Environmental Engineering, Kingston, United States, (8)Middle Tennessee State University, Department of Geosciences, Murfreesboro, United States, (9)University of Tennessee, Department of Biosystems Engineering and Soil Science, Knoxville, United States
