Estimating sediment yield risk of reservoirs in northern Ethiopia using expert knowledge and semi quantitative approaches
MetadataShow full item record
Tamene, L. Abegaz, A. Aynekulu, E. Woldearegay, K. & Vlek, P.L.G. 2011. Estimating sediment yield risk of reservoirs in northern Ethiopia using expert knowledge and semi quantitative approaches. Lakes and Reservoirs: Research and Management, 16:293-305.
Permanent link to cite or share this item: https://hdl.handle.net/10568/34524
External link to download this item: http://onlinelibrary.wiley.com/doi/10.1111/j.1440-1770.2011.00489.x/abstract
Reservoir siltation is a serious problem that threatens the productivity and sustainability of water-harvesting schemes. Quantification of sediment deposition in reservoirs and understanding of its major drivers are needed to apply targeted management interventions. Most of the techniques used to estimate sediment deposition in reservoirs require extensive measurements on a frequent time basis, as well as being costly and time-consuming. Thus, a rapid and relatively economical means of assessing the erosion susceptibility of catchments and predicting their sediment yield potential is necessary. In this study, expert-based rankings and semi-quantitative factorial scoring approaches were applied to assess the siltation severity of 25 reservoirs in the Tigray region of northern Ethiopia. The results were then correlated with quantitative sediment yield estimates acquired for representative sites, and a sediment yield predication model was developed for the region. The calibrated model has an efficiency and relative root mean square error (RRMSE) of 79 and 36%, respectively, which is considered adequate to assess erosion susceptibility and siltation risk of reservoirs in similar environments. The study demonstrates that expert knowledge and rapid characterization of catchments, in terms of susceptibility to erosion, are viable options for assessing siltation risks and for analysing controlling factors at a larger number of sites, with minimum costs and acceptable accuracy.