Modeling Rainfall Erosivity From Daily Rainfall Events, Upper Blue Nile Basin, Ethiopia

Abstract

The upper Blue Nile River basin is one of the most degraded basins in Ethiopia. Soil erosion hazard assessment is of paramount importance in order to reduce soil erosion. Presently, the most commonly used empirical models, in Ethiopia, for annual soil loss assessments are the Universal Soil Loss Equation (USLE) and its revised version, RUSLE. The rainfall erosivity factor (R) is an important factor used in computation of soil erosion by the USLE, the Revised and Modified USLEs. And, therefore, the value of R for the upper Blue Nile River basin was computed using autographical data of 6–10 years from 12 meteorological stations scattered all over the basin based on the method suggested by Wischmeier and Smith (Predicting Rainfall Erosion Losses: A Guide to Conservation Planning,1978) . Accordingly, higher rainfall erosivity values were recorded in the basin, the highest and the lowest being 7,208.91 and 1,737.97 MJ-mm/ha·h·year, respectively. Rainfall erosivity peaks were observed in the months of July and August throughout the basin. Various models were developed to predict rainfall erosivity for areas where self-recording rain gauges are not available. The validity test of the monthly rainfall erosivity equations, developed for the two rainfall zones, revealed model efficiencies of 0.73 and 0.82 for Zone A and Zone B, respectively. Nevertheless, the model efficiency of the monthly rainfall erosivity prediction equation for the entire basin is 0.85. The validity test of the annual erosivity models resulted in model efficiencies of 0.89 for Zone A, 0.65 for Zone B, and 0.80 for the entire basin. Using the developed annual rainfall erosivity prediction model at basin level, annual rainfall erosivity values of 72 stations equipped with non-recording rain gauges were predicted so that it would help all stakeholders to make proper planning and implement effective measures to reduce the problem. However, further research is needed to investigate the variability of erosivity under changing climate by taking different factors into consideration.