Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Spatio-temporal Analysis of Sediment Yield Estimation Using Integrated RUSLE and GIS Technique: Case of Nashe Dam Reservoir, Abay Basin, Ethiopia

Version 1 : Received: 21 February 2021 / Approved: 22 February 2021 / Online: 22 February 2021 (14:57:30 CET)

How to cite: Tamiru, H.; Wagari, M. Spatio-temporal Analysis of Sediment Yield Estimation Using Integrated RUSLE and GIS Technique: Case of Nashe Dam Reservoir, Abay Basin, Ethiopia. Preprints 2021, 2021020480 (doi: 10.20944/preprints202102.0480.v1). Tamiru, H.; Wagari, M. Spatio-temporal Analysis of Sediment Yield Estimation Using Integrated RUSLE and GIS Technique: Case of Nashe Dam Reservoir, Abay Basin, Ethiopia. Preprints 2021, 2021020480 (doi: 10.20944/preprints202102.0480.v1).

Abstract

Sediment accumulation in a dam reservoir is a common happening environmental problem throughout the world. Topographic conditions, land use land cover change, the intensity of rainfall, and the soil characteristics are the major driving factors for sedimentation to occur. The effect of sedimentation in a dam reservoir is very visible in the watershed as a result of hilly topographic conditions, high rainfall intensity, thin land cover, and less soil infiltration capacity. In this paper, an integrated RUSLE and GIS technique was implemented to estimate a mean annual sediment yield based on spatial and temporal variations in Nashe dam reservoir situated in Fincha catchment, Abaya River basin, Ethiopia. Spatial and temporal estimation of mean annual sediment yield was estimated using the Revised Universal Soil Loss Equation (RUSLE) model and GIS. Historical 6-year (2014-2019) rainfall for the temporal variations and other physical factors such as soil erodibility, slope and length steepness, management and land used land cover, and support practice for spatial variations were used as sediment driving factors. The mean annual sediment yield ranges from 0 to 2712.65 t ha-1 year-1 was seen. Spatially, Very high, high, moderate, low, and very low sediment yield severity with total area coverage with 25%, 10%, 30%, 15%, and 20% in 2017, 2015, 2019, 2014, and 2018 respectively. The information about the spatial and temporal variations of the severity of sediment yield in RUSLE model has a paramount role to control the entry of sediment into the dam reservoir in this watershed. The results of the RUSLE model can also be further considered along with the watershed for planning strategies for dam reservoirs in the catchment.

Subject Areas

GIS; RUSLE; Sediment Yield; Spatial Variation; Temporal Variation

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