Suitability of Watershed Models to Predict Distributed Hydrologic Response in the Awramba Watershed in Lake Tana Basin

2016 ◽  
Vol 28 (4) ◽  
pp. 1386-1397 ◽  
Author(s):  
Mamaru A. Moges ◽  
Petra Schmitter ◽  
Seifu A. Tilahun ◽  
Simon Langan ◽  
Dessalegn C. Dagnew ◽  
...  
Keyword(s):  
Hydrologic Response ◽  
Lake Tana ◽  
Watershed Models ◽  
Lake Tana Basin

scholarly journals Application of HEC-HMS Model for Flow Simulation in the Lake Tana Basin: The Case of Gilgel Abay Catchment, Upper Blue Nile Basin, Ethiopia

Hydrology ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 21 ◽  
Author(s):  
Bitew G. Tassew ◽  
Mulugeta A. Belete ◽  
K. Miegel
Keyword(s):  
Sensitivity Analysis ◽  
Relative Error ◽  
Soil Conservation ◽  
Curve Number ◽  
Soil Conservation Service ◽  
Nile Basin ◽  
Lake Tana ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Lake Tana Basin

Understanding the complex relationships between rainfall and runoff processes is necessary for the proper estimation of the quantity of runoff generated in a watershed. The surface runoff was simulated using the Hydrologic Modelling System (HEC-HMS) for the Gilgel Abay Catchment (1609 km2), Upper Blue Nile Basin, Ethiopia. The catchment was delineated and its properties were extracted from a 30 m × 30 m Digital Elevation Model (DEM) of the Lake Tana Basin. The meteorological model was developed within HEC-HMS from rainfall data and the control specifications defined the period and time step of the simulation run. To account for the loss, runoff estimation, and flow routing, Soil Conservation Service Curve Number (SCS-CN), Soil Conservation Service Unit Hydrograph (SCS-UH) and Muskingum methods were used respectively. The rainfall-runoff simulation was conducted using six extreme daily time series events. Initial results showed that there is a clear difference between the observed and simulated peak flows and the total volume. Thereafter, a model calibration with an optimization method and sensitivity analysis was carried out. The result of the sensitivity analysis showed that the curve number is the sensitive parameter. In addition, the model validation results showed a reasonable difference in peak flow (Relative Error in peak, REP = 1.49%) and total volume (Relative Error in volume, REV = 2.38%). The comparison of the observed and simulated hydrographs and the model performance (NSE = 0.884) and their correlation (R2 = 0.925) showed that the model is appropriate for hydrological simulations in the Gilgel Abay Catchment.

Climate-induced flood inundation in Fogera-Dera Floodplain, Lake Tana basin, Ethiopia

2019 ◽  
pp. 407-418
Author(s):  
Temeselew Yeshitila ◽  
Mamaru A. Moges ◽  
Tesfaye A. Dessalegn ◽  
Assefa M. Melesse
Keyword(s):  
Floodplain Lake ◽  
Flood Inundation ◽  
Lake Tana ◽  
Lake Tana Basin

scholarly journals Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

Heliyon ◽  
2019 ◽  
Vol 5 (9) ◽  
pp. e02469 ◽  
Author(s):  
Achenafi Teklay ◽  
Yihun T. Dile ◽  
Dereje H. Asfaw ◽  
Haimanote K. Bayabil ◽  
Kibruyesfa Sisay
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Lake Tana ◽  
Model Simulations ◽  
Lake Tana Basin

scholarly journals Identifying erosion hotspots in Lake Tana Basin from a multisite Soil and Water Assessment Tool validation: Opportunity for land managers

2019 ◽  
Vol 30 (12) ◽  
pp. 1449-1467 ◽  
Author(s):  
Hanibal Lemma ◽  
Amaury Frankl ◽  
Ann Griensven ◽  
Jean Poesen ◽  
Enyew Adgo ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Lake Tana ◽  
Erosion Hotspots ◽  
Water Assessment ◽  
Soil And Water ◽  
Lake Tana Basin
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