An efficient semi-distributed hillslope erosion model for the subhumid Ethiopian Highlands
- 1Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, USA
- 2School of Civil and Water Resources Engineering, Bahir Dar University, Bahir Dar, Ethiopia
- 3Integrated Watershed Management and Hydrology Program, Cornell University, Bahir Dar, Ethiopia
- 4Adet Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia
- 5Israel Oceanographic and Limnological Research, The Yigal Allon Kinneret Limnological Laboratory, Migdal, Israel
Abstract. Erosion modeling has been generally scaling up from plot scale but not based on landscape topographic position, which is a main variable in saturation excess runoff. In addition, predicting sediment loss in Africa has been hampered by using models developed in western countries and do not perform as well in the monsoon climate prevailing in most of the continent. The objective of this paper is to develop a simple erosion model that can be used in the Ethiopian Highlands in Africa. We base our sediment prediction on a simple distributed saturated excess hydrology model that predicts surface runoff from severely degraded lands and from bottom lands that become saturated during the rainy season and estimates interflow and baseflow from the remaining portions of the landscape. By developing an equation that relates surface runoff to sediment concentration generated from runoff source areas, assuming that baseflow and interflow are sediment-free, we were able to predict daily sediment concentrations from the Anjeni watershed with a Nash–Sutcliffe efficiency ranging from 0.64 to 0.78 using only two calibrated sediment parameters. Anjeni is a 113 ha watershed in the 17.4 million ha Blue Nile Basin in the Ethiopian Highlands. The discharge of the two watersheds was predicted with Nash–Sutcliffe efficiency values ranging from 0.80 to 0.93. The calibrated values in Anjeni for degraded (14%) and saturated (2%) runoff source area were in agreement with field evidence. The analysis suggests that identifying the runoff source areas and predicting the surface runoff correctly is an important step in predicting the sediment concentration.