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Presented by Maru Alem Assegahegn and Birhanu Zemadim at the Nile Basin Development Challenge (NBDC) Science Workshop–2013, Addis Ababa, Ethiopia, 9 – 10 July 2013
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Erosion modeling in the Upper Blue Nile Basin: the Case for Mizewa Watershed
Maru Alem Assegahegn Birhanu Zemadim(PhD)
Nile Basin Development Challenge (NBDC) Science WorkshopAddis Ababa, Ethiopia, 9–10 July 2013
Contents
1. Introduction2. Materials and Methods3. Result and Discussion4. Conclusion and Recommendation
1. Introduction1.1. Background and Problem statement Erosion is a universally accepted environmental
problem that threat man’s dev’t (Hudson, 1981)Ethiopia is described as the most soil erosion affected country in the world (Beyene, 2011)Annual soil loss ranges from16 to 300 t/ha Lake Tana Basin-experiences severe erosion-soil fertility & water quality degr’n, siltation, floodingCharacterization of erosion rates in a catchment
scale especially in the study area is rarely done
1.2. ObjectivesThe overall objective of the research is studying soil
erosion and its impact on water productivity in the study area.
Specific Objectives• To investigate hydrological processes and r/nships
between water budget and soil loss in Mizewa watershed
• To estimate magnitude of erosion spatially and temporally
• To identify erosion sensitive areas in the study area
2. Material and Methods2.1. Study Area Description
3.2. Data collection and AnalysisFlow data- was collected from IWMISS data-sampled from July 1 to Aug 31/2012 at the outlet and upstream on site 2 (2 times/day)o Simple grabbing technique was usedo Suspended sediment conc.(g/L) was analyzed o Sediment rating curve
Climatic Data-collected from NMSA and IWMI Landuse/land cover data - collected in the fieldDEM, Soil Map Data
3.3 Modeling- the SWAT ModelSWAT- WBESurface Runoff Volume- Peak Runoff rate or
PET- Penman Monteith Soil Water and Groundwater were simulated by SWAT Sediment- MUSLE- Sensitivity Analysis, Calibration & Validation- were done Model Performance test-
3.4 SWAT Model Setup- Watershed delineation, Landuse map, soil map, slope class, HRU
4. RESULT AND DISCUSSION4.1. Sediment Rating Curve
,
Calibration Result 10 flow & 5 sediment sensitive parameters - calibrated • Flow calibration
• Sediment calibration
Model Validation ResultFlow & sediment Validation
Simulated Results Flow simulation- the model captured both dry &
wet periods flow - the dry period slightly deviates negatively and wet period slightly deviates positively with 15% annual deviation
Simulated rate of average annual soil loss of the watershed is 40.91 ton/ha (high)
Simulated average annual sediment yield at the outlet is 12.78 t/ha & measured 11.45 ton/ha
The highest measured and simulated soil loss was recorded in July followed by August
Subbasin erosion simulation-temporal/spatial
Water budget and erosion r/nshipRelatively high average annual rainfall (1385mm
measured & 1374 mm simulated) responsible for high erosion in the watershed
From SWAT water balance simulation, surface runoff component, 335.70 mm (24%) of Rainfall is responsible for soil loss in the catchment (high erosion potential)
High soil water storage characterizes high runoff in turn high erosion
5. Conclusion and Recommendation Modeling was conducted with one year primary data Model calibration & validation were done with data of the
same time series but with varied spatial location The R2 and NSE
values (>0.5) (good model performance) and with fair agreement of observed Vs simulated result
High SSC(g/L) and soil loss recorded in July and Soil loss in subbasin 3> subbasin 2 > subbasin 1
Long duration time series primary data of the watershed is vital to minimize uncertainty in modeling
Catchment scale controlled modeling should be encouraged Continuous studies should be conducted to recommend
appropriate erosion control remedies at the watershed