Addis Ababa university
Ethiopian Institute of Water Resources
Understanding Runoff Generation Processes and Rainfall Runof...
Introduction
Background
Watershed based planning and management requires thorough
understanding of the hydrological proce...
Materials and Methodology
Materials used
Rain gauges , Water level measuring stage boards ,Current
meter , Ground water l...
Data Analysis
rainfall, runoff, soil moisture and groundwater data screening
was done by visual inspection of daily data....
Data Analysis (continued)
Relationship of rainfall with runoff, soil moisture, groundwater
level,etc was conducted using ...
Results and Discussion
Analysis of rainfall data indicated weak daily correlation of
areal rainfall between Galessa, Seri...
Results and Discussion (continued)
There is strong relationship of runoff with ground water level
and soil moisture but t...
Results and Discussion(continued)
Results and Discussion (continued)
HBV model in Kolu during calibration and verification period
was performed satisfactor...
Conclusion and recommendation
Conclusion
Analysis of rainfall data indicated weak daily correlation of
areal rainfall bet...
Conclusion (continued)
There is moderate relationship of rainfall and ground water
level.
There is spatial variability o...
Conclusion (continued)
The general relationship between runoff and monthly average
soil moisture at different layers in M...
Recommendation
In order to know more on hydrological processes study on the
aquifer behavior and soil texture sample test...
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Understanding runoff generation processes and rainfall runoff modeling: The case of Meja Watershed in the Upper Blue Nile Basin Ethiopia

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Presented by Solomon Berhane at the Nile Basin Development Challenge (NBDC) Science Workshop–2013, Addis Ababa, Ethiopia, 9 – 10 July 2013

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Understanding runoff generation processes and rainfall runoff modeling: The case of Meja Watershed in the Upper Blue Nile Basin Ethiopia

  1. 1. Addis Ababa university Ethiopian Institute of Water Resources Understanding Runoff Generation Processes and Rainfall Runoff Modeling. The case of Meja Watershed in the Upper Blue Nile Basin Ethiopia Solomon Berhane (Msc) Major adviser Dr.Brhanu Zemadim Co adviser Dr.Dereje Hailu Co adviser Dr.Assefa Melese Nile Basin Development Challenge (NBDC) Science Workshop Addis Ababa, Ethiopia, 9–10 July 2013
  2. 2. Introduction Background Watershed based planning and management requires thorough understanding of the hydrological processes and accurate estimation of runoff. This study utilized the already available hydrological and meteorological monitoring stations in Jeldu district. The purpose of the study was to understand runoff generation processes and model rainfall runoff relationship
  3. 3. Materials and Methodology Materials used Rain gauges , Water level measuring stage boards ,Current meter , Ground water level measuring instruments( SEBA Electric Contact Meter type KLL ) and Soil moisture profile propes (Profile Probe type PR2 ) Data Collection Primary data collection Rainfall, runoff ,soil moisture, Ground water level ,and other weather parameters such as wind speed, sun shine hours,etc were collected from July 15 2011 up to September 30 2012.
  4. 4. Data Analysis rainfall, runoff, soil moisture and groundwater data screening was done by visual inspection of daily data. Areal rainfall was determined using thiessen polygons Evapotranspiration was calculated using FAO Penman- Monteith equation.
  5. 5. Data Analysis (continued) Relationship of rainfall with runoff, soil moisture, groundwater level,etc was conducted using excel sheet of statistical analysis techniques such as regression analysis, Linear correlation coefficient and coefficient of determination. Plot of each parameters are analyzed in order to understand hydrological processes in the watershed. For the part of modelling, HBV and RRL SMAR models have been used. The available data set was split into two. The data range from 15 July 2011 to 5 May 2012 was used for calibration and the rest of the range between 6 May 2012 and 30 September 2012 was used to validate the model.
  6. 6. Results and Discussion Analysis of rainfall data indicated weak daily correlation of areal rainfall between Galessa, Serity and Kolu and similar annual total and average rainfall of the three sites of Meja watershed. There is moderate relationship between rainfall and runoff in daily analysis. In monthly basis the relationship between rainfall and runoff is strong.
  7. 7. Results and Discussion (continued) There is strong relationship of runoff with ground water level and soil moisture but there is moderate relationship of GW and rainfall, so that there is higher horizontal permeability than vertical hydraulic permeability, and also there is high contribution of sub surface and ground water flow to the stream.  When the depth from the ground surface increases, volumetric monthly soil moisture also increases but the relationship between rainfall and soil moisture decreases.
  8. 8. Results and Discussion(continued)
  9. 9. Results and Discussion (continued) HBV model in Kolu during calibration and verification period was performed satisfactory and in Meja the model performed very Good. SMAR model in Kolu and in Meja indicates satisfactory performance during calibration and verification period. So that HBV model performed better than RRL SMAR in Meja and in Kolu.
  10. 10. Conclusion and recommendation Conclusion Analysis of rainfall data indicated weak daily correlation of areal rainfall between Galessa, Serity and Kolu and similar annual total and average rainfall of the three sites of Meja watershed. There is no strong rainfall and runoff relationship in daily basis (r2 <0.5). Ground water level and runoff has strong relationship (r2 > 0.65) in monthly basis .
  11. 11. Conclusion (continued) There is moderate relationship of rainfall and ground water level. There is spatial variability of soil moisture content in Meja watershed. In 600 mm layer soil moisture has strong relationship with ground water than rainfall but unlike this in 100 mm layer soil moisture has strong relationship with rainfall than ground water level.
  12. 12. Conclusion (continued) The general relationship between runoff and monthly average soil moisture at different layers in Meja watershed and Kolu is strong. HBV and RRL SMAR models perform well in Meja. SMAR model couldn’t capture low flow in Meja and Kolu And doesn’t perform well in Kolu.
  13. 13. Recommendation In order to know more on hydrological processes study on the aquifer behavior and soil texture sample test is required. In order to know or confirm whether there is, blockage or capillary barriers dye tracer experiment must be done. There must be high temporal resolution of data, measurement specially soil moisture and groundwater. In order to get accurate result on runoff generation mechanism or occurrence of surface runoff source areas it is good to conduct study using sub surface and surface runoff sensors. SMAR and HBV model can be applied in Meja watershed but in the nested catchments such as Kolu HBV model is recommended. The models must be tested using long period of data.

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