Water Resource Engineering

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Browsing Water Resource Engineering by Author "Birhanu, Zemadim (PhD)"

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    Runoff Estimation and Water Management for Holetta River, Awash Subbasin, Ethiopia
    (Addis Ababa University, 2013-06) Mahtsente, Tibebe; Assefa, Melesse (PhD); Dereje, Hailu (PhD); Birhanu, Zemadim (PhD)
    The hydrology of Holetta River and its seasonal variability is not fully studied. In addition to this, due to scarcity of the available surface water and increase in water demand for irrigation, the major users of the river are facing a challenge to allocate the available water. Therefore, the aim of this research was to investigate the water availability of Holetta River and to study the water management in the catchment using Geographical Information Systems (GIS) tool, statistical methods, and hydrological model. The rainfall runoff process of the catchment was modeled by Soil and Water Assessment Tool (SWAT). According to SWAT classification, the watershed was divided in to 6 subbasins and 33 hydrological response units (HRUs). The only gauged subbasin in the catchment was subbasin one that is found in the upper part of the area. Therefore, sensitivity analysis, calibration, and validation of the model was performed at subbasin one and then the calibrated model was used to estimate runoff at the ungauged part of the catchment. The performance of SWAT model was evaluated by using statistical (coefficient of determination [R2], Nash-Sutcliffe Efficiency Coefficient [NSE] and Index of Volumetric Fit [IVF]) and graphical methods. The result showed that R2, NSE, and IVF were 0.85, 0.84 and 102.8 respectively for monthly calibration and 0.73, 0.67 and 108.9 respectively for monthly validation. These indicated that SWAT model performed well for simulation of the hydrology of the watershed. After modeling the rainfall runoff relation and studying the availability of water at the Holetta River, the water demand of the area was assessed. The survey form was used to identify information, which includes the number of Holetta River consumers, major crops grown by irrigation and the total area coverage. CropWat model was used to calculate the irrigation water requirement for major crops. Based on the result of CropWat model and survey analysis, the irrigation water demand for the three major users of Holetta River was calculated. The total water demand of all three major users was 0.313, 0.583, 1.004, 0.873 and 0.341 MCM from January to May respectively. The available river flow from January to May was taken from the result of SWAT simulation at subbasins 2,3,4 and 5. The average flow was 0.749, 0.419, 0.829, 0.623 and 0.471 MCM from January to May respectively. From the five months, the demand and the supply showed a gap during February, March and April. This indicated that there is shortage of supply during these months with 0.59 MCM. Therefore, in order to solve this problem alternative source of water supply should be studied and integrated water management system should be implemented.
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    Understanding Runoff Generation Processes and Rainfall Runoff Modeling in Meja Watershed
    (Addis Ababa University, 2013-06) Solomon, Berhane; Birhanu, Zemadim (PhD); Dereje, Hailu (PhD); Assefa, Melesse (PhD)
    Understanding the basic relationships between rainfall, runoff, soil moisture and ground water level are vital for an effective and sustainable water resources planning and management activities. But so far there are no hydrological studies in Meja watershed that aims to understand the watershed characteristics and runoff generation processes. This study was conducted to understand runoff generation processes and model rainfall runoff relationship in Meja watershed having a drainage area of 96.6 km2.The watershed is one of the three research sites of International Water Management Institute (IWMI) developed in early 2010 in the upper Blue Nile Basin Ethiopia. In the study, primary data of soil moisture, shallow ground water level, rainfall and runoff were collected from the hydrological monitoring network in the watershed. Two nested sub- watersheds namely Galessa and Kolu were defined in the watershed for detail analysis of hydrologic variables. Galessa has drainage area of 1.6 km2 and Kolu has a drainage area of 2.5 km2. Hydrological models like HBV and RRL SMAR were configured to understand the relationship between rainfall and runoff in the watershed. Relationships between rainfall, soil moisture, shallow ground water level and runoff were developed to understand runoff generation processes in the watershed. Analysis of rainfall data indicated weak daily correlation (r2<0.35) of areal rainfall between Galessa, Serity and Kolu and similar annual total and average rainfall of the three sites of Meja watershed. However monthly correlation of areal rainfall between the three sites was better than daily correlation (r2>0.8). According to one year and three months data, there is no strong daily rainfall and runoff relationship (r2<0.5) in Meja and Kolu which is nested sub - watershed; this may be due to abstractions such as irrigation and human interventions in the watershed. Ground water level and runoff has strong relationship (r2>0.65) in monthly basis of Kolu nested sub watershed but there is moderate relationship of rainfall and ground water level. There is spatial variability of soil moisture content in Meja watershed, this variation occurs due to heterogeneity of the soil, which means the places are different in soil texture and also the variation is due to vegetation cover and change of slope. There is strong linear relationship of rainfall and monthly averaged volumetric soil moisture in most soil moisture layers of Meja and its nested sub-watersheds. The general relationship between runoff and monthly averaged soil moisture at different layers in Meja watershed and Kolu is strong. Analysis of rainfall runoff models indicated that relationships of rainfall with observed and simulated runoff was similar.HBV model performs better than RRL SMAR model in Meja and Kolu. RRL SMAR model couldn’t capture low flow in Meja and Kolu. This inaccurate result of SMAR model in Kolu sub-watershed may be due to inability of the model to simulate runoff in very small catchments like Kolu.