Africa Center of Excellence for Water Management

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Browsing Africa Center of Excellence for Water Management by Author "Abebe, Adane (PhD)"

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    Evaluating the Land Use and Land Cover Change Impact on Streamflow Kulfo Catchment
    (Addis Ababa University, 2021-10-27) Anja, Assebe; Abebe, Adane (PhD)
    Streamflow is one of the key components of the hydrological cycle that can be altered and/or modified by a variety of variables. One of the key variables is the change in LULC. In kulfo cathement, in Ethiopia's southern region, suitable LULC detection techniques were not addressed and evaluated yet, and also the changing of the exesting LULC is the main stress in the streamflow of the Kulfo catchment. As a result, the impact of LULC change on streamflow was assessed in this study using the soil and water assessment tool model. Sensitivity, calibration, and validation were also performed using historical streamflow data in SWAT-CUP (Calibration and Uncertainty program) using sequential uncertainty fitting–version 2 (SUFI-2). There were four different algorithms applied to classify the LULC change. The best performing of four distinct algorithms (SVM, CART, RF, and Navia's) available in the Google Earth Engine were compared, and the best performing was chosen to generate the time-series LULC maps of the research area (1986, 2000, 2016, and 2020). GCPs gathered in the field were used to assess the accuracy of these algorithms. To train and evaluate the LULC maps generated from the Google Earth Engine platform, high resolution (30m) Landsat imagery from the thematic mapper (TM), enhanced thematic mapper plus (ETM+), and operational land imager (OLI) were employed, along with historical trends and ground-based data. As a result, the SVM method outperformed the other algorithms in this study when it came to LULC classification. During the study's period, the area covered by vegetation declined from 18.81 % to 3.1 %, while agricultural land increased from 19.44 % to 57.12 % and shrub land decreased from 34.18 % to 14.73 %. As a result, the impact of these LULC variations on streamflow was assessed using the Soil & Water Assessment Tool (SWAT) model, and over the study's period, substantial mean monthly and seasonal streamflow variability was observed. Monthly, these variabilities were raised from 6.72 % to 7.85%. The year has been divided in to three seasons Kiremt, Belg, and Bega. Seasonally, streamflow has dropped for all seasons (Kiremt, Belg, and Bega) from 2016 to 2020, but it has increased from 2000 to 2016. (Kiremt, Belg, and Bega). The calibration results showed an acceptable range between observed and simulated streamflow (0.6, 0.8, 0.75, and 0.75 for NSE and 0.75, 0.76, 0.79, and 0.81 for R2). Validation findings for observed and simulated streamflow were similarly within acceptable limits (0.72, 0.6, 0.74, and 0.75 for NSE and 0.8, 0.75, 0.73, and 0.8 for R2).
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    Hydrological and Hydrodynamic Modelling of Flows to Support Establishment of Flood Adaptation Strategies for River Malaba Sub-Catchment in Uganda
    (Addis Ababa University, 2022-03-22) Mubialiwo, Ambrose; Abebe, Adane (PhD); Onyutha, Charles (PhD)
    Many people tend to live in the floodplains along River Malaba due to fertile soils which support agriculture. However, heavy rains in the highlands of Mount Elgon often lead to floods which end up affecting especially the local population in terms of loss of lives and destruction of infrastructure within the low-lying areas of River Malaba sub-catchment in Uganda. This research aimed at presenting a platform for understanding the impacts of flooding on the socio-economy while investigating perceived effectiveness of establishing flood adaptation strategies for predictive risk-based water resources management in the study area. The study had four specific objectives including; (i) to analyse changes in historical rainfall and potential evapotranspiration (PET), (ii) to perform hydrological modelling of extreme peak flows, (iii) to estimate impacts of flooding given the spatial extents of flooding inundations, and (iv) to analyse community willingness-to-pay (WTP) for flooding adaptation strategies. Changes in terms of trends and variability were analysed using nonparametric approach based on the cumulative sum of the difference between exceedance and nonexceedance counts of data points. The second specific objective consisted of determining which hydrological model could best reproduce observed extreme peak flows. Hydrodynamic modelling was performed using a two-dimensional Hydraulic Engineering Center’s River Analysis System model. Double-bound dichotomous choice contingent valuation method was applied to assess the local population’s WTP for flooding adaptation measures. The number of days with rainfall intensity > 5 mm/day and 10 mm/day had insignificant (p>0.05) decreasing trend. The sum of rainfall with intensities > 5 mm/day exhibited a significant (p<0.05) decreasing trend. However, annual maxima rainfall increased (p>0.05), indicating less frequent rains but some events having very high intensity. Variability of rainfall sub-trends was insignificant (p>0.05) and had a common pattern. PET had an insignificant (p>0.05) positive trend. The amplitudes in PET variability were insignificant (p>0.05) and though of generally common pattern. The Australian Water Balance Model exhibited the best performance in reproducing extreme peak flows and it had Nash–Sutcliffe efficiency (NSE) of 0.837. Land-use change had insignificant (p>0.05) influence on determining flood inundation extents. Inundation of rice gardens by the most severe 100-year flood was found to lead to an economic loss of about US$ 39 million. Amongst the infrastructure, churches showed the highest economic losses of US$ 1,623,832 due to flooding of 100-year return period. In general, the local community was aware of the flood citing rainfall variability and longer rainfall durations as main cause of flooding. Post- flood strategies were more efficient than those practiced before- and during-floods. Among the suggested structural and non-structural strategies, “river training structures” and “flood forecasting and early warning” were highly preferred, respectively. 55% of the households expressed WTP an individual amount between Uganda shillings (UGX) 5,000 (US$ 1.35) to UGX 500,000 (US$ 135.14). Several demographic, social and institutional factors had significant (p<0.01) positive impact on community WTP. This study findings are relevant in supporting policy makers regarding predictive planning and development of flood risk adaptation pathways given the established destructions within the sub-catchment due to flooding.
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    Reservoir Operation for Optimal Water Use: A Case Study of Kabalega Reservoir in Uganda
    (Addis Ababa University, 2020-07-03) Cyrus, Chelangat; Abebe, Adane (PhD)
    Wambabya River catchment over the past years (since 2013) has been experiencing alterations in its upstream (forests cleared for agriculture) which may have resulted in seasonal variability in rainfall pattern. Temperatures have increased and thus high-water loss through evapotranspiration. River inflows into the reservoir have decreased thus affecting the power generation from Kabalega dam as evidenced by the operation below its capacity in most of the first quarter months of the year and thus being unable to meet the power demand and downstream ecological requirement. The study developed reservoir operation policies for optimal water use of Kabalega reservoir in order to meet the target demands. Australian Water Balance Model (AWBM) was used to simulate Wambabya River inflow into Kabalega reservoir. The model was calibrated with observed flow from 1990-2009 and validated with flow from 2010-2019. Nash & Sutcliff efficiency for calibration and validation is 0.758 and 0.67 respectively. HEC-ResSim model was used to optimize and develop new reservoir operating rules by calibrating and validating the model for 5 and 3 years which yielded Nash Sutcliff coefficient and correlation coefficient of 0.85 and 0.82 respectively. respectively. The reservoir system performance was further investigated by using statistical performance indices which are; reliability, vulnerability, resilience and sustainability index. Simulated releases were compared to the actual releases and generated/ simulated power compared to power demand and it was found that the system exhibits fewer deficits in terms of power supply, with minimal spill flows over the spillway found to occur compared to the original operation policy. The derived operation policies are thus recommended to serve as decision-making tools for operation of Kabalega reservoir to maximize the benefits.
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    Validating Satellite Based Rainfall Product and Hydrological Modeling in Blue Nile Jemma Sub-Basin
    (Addis Ababa University, 2021-09-16) Endayilalu, Getaw; Abebe, Adane (PhD)
    Water resource management absolutely depends on water resource data like rainfall and stream flow. Better quality of such data are obtained by direct measurement via interconnected gauging instruments. Due to limited resource, gauging instruments’ distribution are not dense enough, in turn causes water resource data scarcity. Currently, Satellite rainfall estimates are available with good spatial and temporal resolutions. However, they are estimates rather than direct measurements. Thus, as the study was begun to evaluate the performance of satellite based rainfall product, TRMM_3B42; it was validated in Jemma sub-basin, and its raw and combined version was evaluated as input of distributed type of HEC-HMS model in Gumerrow catchment. For the achievement of the objectives, collected hydro-meteorological, satellite remote sensing and Arc-Info data were processed with appropriate tools like R-programing language, Arc-GIS model builder, HEC-HMS and others. Results also were presented using graphical techniques, categorical and continuous statistics, and model evaluation statistics. The Satellite based rainfall product and Ground rain-gage data were comparable except some important variations. In categorical rainfall values, the overall accuracy of Satellite rainfall estimate was greater than 78.7%, which was observed in Light rain type of daily timescale. However, the stated algorism has faced special difficulty in daily timescale with more false alarms. In continuous rainfall values, Positive linear association was detected in daily, monthly and seasonal timescales with correlation coefficient values of 0.52, 0.915 and 0.926 respectively. And an average underestimation of Satellite rainfall estimate was discovered in all timescales. Among seven HEC-HMS model parameters, Potential max retention factor (S) was obtained as the most sensitive parameter in Gumerrow catchment. Raw Satellite rainfall estimate showed poor performance in calibration period of (2003-2006) with NSE, PBIAS, RSR and R2 values of 0.406, 24.26%, 0.771 and 0.417 respectively. However, the performance had improved significantly to good enough with NSE, PBIAS, RSR and R2 values of 0.532, 14.83%, 0.684 and 0.554 respectively when combined version was used as input of HEC-HMS model. Relative to calibration period, improved performance was discovered in validation period of (2007-2008) with NSE, RSR and R2 values of 0.452, 0.74 and 0.477 respectively for raw Satellite rainfall estimate, and 0.56, 0.663 and 0.618 respectively for combined version.
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    Watershed Regionalization for Regional Flood Frequency Analysis in the Rift Valley Lake Basin Ethiopia
    (Addis Ababa University, 2021-03-17) Sime, Abdisa; Abebe, Adane (PhD)
    The use of regional information to predict magnitude of flow both at site and ungauged catchments are useful for planning and management of water resources. The main objective of this study was to regionalize watersheds in the Rift Valley Lake Basin (RVLB) and flood frequency analysis for the delineated homogeneous regions. In regionalization of the watersheds; Physiographic, drainage, meteorological, soil cover, land-use pattern characteristics and geographical location attributes have been used. Cluster analysis was done by Hierarchical clustering to obtain number of clusters, and final clustering by K-mean method. Accordingly four regions have been identified and checked using homogeneity tests. Using goodness of fit tests (Chi-square test, Kolmogorov–Smirnov, and Anderson–Darling), the best fit distribution models have been selected. Generalized extreme value distribution is the best fit for region I, Log-normal (2P) is selected for region II, Wakeby distribution is found to be the best for region III, and Generalized pareto is chosen for region IV. For the selected distributions efficient parameter estimation technique was selected by performing standard error analysis. Thus, method of moment (MOM) is the one with the lowest error so, selected for region I, and maximum likelihood (ML) method is found the most efficient method for the regions II to IV. For each region unique regional frequency curve is developed with standardized annual maximum flow series (AM), which is a crucial to estimate flood quantile in ungauged areas of the basin. Regional regression model was developed for all region except for region I which consists only one gauged catchment based on their R2 values. Accordingly 0.82, 0.83, and 0.79 of R2 values respectively for all the three regions. For checking performance of the model, validation of regional model was carried out by computing the relative errors, over five gauged watersheds that is representative for each region considering as pseudo ungauged. The relative errors between observed and estimated mean annual maximum flows resulted all regional model performs good having maximum of 10.6% of relative error. So, for any current and future water resources developments in the area, the developed regional model can be applied.