Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Streamflow and Sediment Yield Prediction for Watershed Prioritization in the Upper Blue Nile River Basin, Ethiopia

Domain:

environment and energyagriculturegeospatial

Record type:

paper
Creator:
GebEngBofIan
Publisher:
MDP
Host:
Inappropriate use of land and poor ecosystem management have accelerated land degradation and reduced the storage capacity of reservoirs. To mitigate the effect of the increased sediment yield, it is important to identify erosion-prone areas in a 287 km2 catchment in Ethiopia. The objectives of this study were to: (1) assess the spatial variability of sediment yield; (2) quantify the amount of sediment delivered into the reservoir; and (3) prioritize sub-catchments for watershed management using the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated and validated using SUFI-2, GLUE, ParaSol, and PSO SWAT-CUP optimization algorithms. For most of the SWAT-CUP simulations, the observed and simulated river discharge were not significantly different at the 95% level of confidence (95PPU), and sources of uncertainties were captured by bracketing more than 70% of the observed data. This catchment prioritization study indicated that more than 85% of the sediment was sourced from lowland areas (slope range: 0–8%) and the variation in sediment yield was more sensitive to the land use and soil type prevailing in the area regardless of the terrain slope. Contrary to the perception of the upland as an important source of sediment, the lowland in fact was the most important source of sediment and should be the focus area for improved land management practice to reduce sediment delivery into storage reservoirs. The research also showed that lowland erosion-prone areas are typified by extensive agriculture, which causes significant modification of the landscape. Tillage practice changes the infiltration and runoff characteristics of the land surface and interaction of shallow groundwater table and saturation excess runoff, which in turn affects the delivery of water and sediment to the reservoir and catchment evapotranspiration.

Visit

doi.org

Licenses

https://creativecommons.org/licenses/by/4.0/

Similar

Seasonal forecast of streamflow and suspended sediment in the Blue Nile Basin, EthiopiaPrioritization of watershed management scenarios under climate change in the Jemma sub-basin of the Upper Blue Nile Basin, EthiopiaMachine Learning-Based Sedigraph Reconstruction for Enhanced Sediment Yield Estimation in the Upper Blue Nile BasinTeleconnection, Modeling, Climate Anomalies Impact and Forecasting of Rainfall and Streamflow of the Upper Blue Nile River Basin TELECONNECT BLUE NILE BASIN RAINFALL & RUNOFFData Supporting "Assessing Soil Erosion Risk Using RUSLE and GIS in Mitike Watershed, Upper Blue Nile River Basin, Ethiopia"Combining Machine Learning and Process-Based Modelling for Sediment Load Estimation in the Data-Scarce Kessie Watershed, Upper Blue Nile Basin

Seasonal forecast of streamflow and suspended sediment in the Blue Nile Basin, Ethiopia

The demand for seasonal hydrologic forecasts is significant and various applications for water resou

Prioritization of watershed management scenarios under climate change in the Jemma sub-basin of the Upper Blue Nile Basin, Ethiopia

Machine Learning-Based Sedigraph Reconstruction for Enhanced Sediment Yield Estimation in the Upper Blue Nile Basin

Sediment-laden runoff in Ethiopia’s Upper Blue Nile Basin (UBNB) threatens the ecological balance of

Teleconnection, Modeling, Climate Anomalies Impact and Forecasting of Rainfall and Streamflow of the Upper Blue Nile River Basin TELECONNECT BLUE NILE BASIN RAINFALL & RUNOFF

The Nile River, the primary water resource and the life artery for the downstream countries, Egypt a

Data Supporting "Assessing Soil Erosion Risk Using RUSLE and GIS in Mitike Watershed, Upper Blue Nile River Basin, Ethiopia"

This dataset contains the input data, derived RUSLE factors, and outputs used to assess soil erosion

Combining Machine Learning and Process-Based Modelling for Sediment Load Estimation in the Data-Scarce Kessie Watershed, Upper Blue Nile Basin

The Upper Blue Nile Basin contributes about 60% of the Nile River’s annual streamflow but faces seve