Erosion modeling in the Upper Blue Nile Basin: The case for Mizewa Watershed
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Erosion modeling in the Upper Blue Nile Basin: The case for Mizewa Watershed

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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

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 Erosion modeling in the Upper Blue Nile Basin: The case for Mizewa Watershed Presentation Transcript

  • 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 Workshop Addis Ababa, Ethiopia, 9–10 July 2013
  • Contents 1. Introduction 2. Materials and Methods 3. Result and Discussion 4. Conclusion and Recommendation
  • 1. Introduction 1.1. 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, flooding Characterization of erosion rates in a catchment scale especially in the study area is rarely done
  • 1.2. Objectives The 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 Methods 2.1. Study Area Description
  • 3.2. Data collection and Analysis Flow data- was collected from IWMI SS 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 used o 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 field DEM, Soil Map Data
  • 3.3 Modeling- the SWAT Model SWAT- WBE Surface 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 DISCUSSION 4.1. Sediment Rating Curve ,
  • Calibration Result 10 flow & 5 sediment sensitive parameters - calibrated • Flow calibration • Sediment calibration
  • Model Validation Result Flow & 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/nship Relatively 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