Bedload transport measurements in the Gilgel Abay River, Lake Tana Basin, Ethiopia

Little is known about the contribution of bedload flux to the total sediment load exported from tropical sand-bed rivers. Yet, predicting bedload transport rates contributes to better river management, more appropriate river engineering works design, accurate knowledge of sediment delivery rates, which greatly benefits sediment related water resources management. Therefore, bedload, suspended load and runoff discharge were measured at the lower Gilgel Abay River in the Blue Nile catchment of Ethiopia. Catchment area is 3887 km(2), average stream discharge in the rainy season 315 (+/- 164) m(3) s(-1), and the stream surface gradient at the sampling station 0.0007 m m(-1). A standard Helley-Smith (U.S. BL-84) cable-suspended sampler was used to take 315 samples to measure bedload fluxes for the 2017 rainy season. The bedload predominantly comprises well to moderately well sorted, medium-sized sand (250-500 mu m) with a symmetric and leptokurtic distribution. The mean daily observed bedload discharge varies from 0.7 to 427.5 Mg d(-1) with an average rate of 175.1 Mg d(-1). Field observations also show that the bedload dynamics become larger near the river banks and decrease towards the middle of the river section due to the presence of a central bridge pier. The average suspended sediment load ranges from 247 to 220,028 Mg d(-1) and dominates the total sediment yield ( > 94.6%). The bedload accounts for only 0.1 to 5.4% of the total sediment load. The area-specific bedload and suspended load are also 0.6 and 22 Mg ha(-1) yr(-1) respectively. The elongated planform growth of the Gilgel Abay River delta in Lake Tana is also in line with the predominance of very fine, suspended load in the sediment transport of this river, in addition to limited alongshore drifting given the low waves of Tana lake. Among the tested bedload prediction criteria, the stream-power based equations of Martin and modified Bagnold performed better. Yet, the bedload prediction performance of simple power regression equations based on runoff discharge and excess unit stream power parameters provided the best agreement with the observed bedload data (Adj. R-2 0.82-0.87). Finally, this study provides plausible estimates of bedload fluxes that are within predicted ranges reported for sand-bed rivers in Africa and other tropical regions.