AAU Institutional Repository (AAU-ETD)
Addis Ababa University Institutional repository is an open access repository that collects,preserves, and disseminates scholarly outputs of the university. AAU-ETD archives' collection of master's theses, doctoral dissertations and preprints showcase the wide range of academic research undertaken by AAU students over the course of the University's long history.
How to Submit Your Work
The repository contains scholarly work, both unpublished and published, by current or former AAU faculty, staff, and students, including Works by AAU students as part of their masters, doctoral, or post-doctoral research
- All AAU faculty, staff, and students are invited to submit their work to the repository. Please contact the library at your college.
You may contact digirep@aau.edu.et.with any questions about the repository
Colleges,Institutes in AAU-ETD
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Recent Submissions
An Economic Menace or Growth Opportunity of Land Speculation: The case of Shashemene City
(Addis Ababa University, 2020-11-01) Bedane Shata Gemeda; Birhanu Girma Abebe (PhD)
Land speculation in urban and periurban area can be extremely strenuous to the upheld intensification of cities, which is critical to economic development. Inaccurately, speculative land investors, worried about benefits from exchanging landed possessions, can influence urban development supporting populace, where the principle is often inadequately controlled and exceptionally bureaucratic. The key troubles of governing land speculation are rapidly deeming hot spot zones of eagerness, naming land jobbers, and directing encouraging and negative spats of property speculation. The research employed the case study, desk review, and survey research stratagem. Also, multiple regressions, Cumulative Sum statistics, and the Principal Component Analysis systems were used to scrutinize facts. The MORRIS and TOPISS models were also used to rate the space-based expansion of the city. Next to the case study folklore, a mix of various facts collection tools, for instance, questionnaires, Focus Group Discussions, key informant interviews, and direct field observation, were exploited to collect study truths as of the case study district. The Shashemene city admin was intentionally chosen while the case study area in the first stage of the case study district choice procedure. Four urban villages, explicitly: Awasho, Alelu, Burka Gudina, and Buclhena, were chosen in the next stage. Further, policy documents were reviewed, and a survey was conducted to get adequate data. The result indicates that the land worth is assenting and expansively allied with the size of property seizing by regional land jobbers. According to influential variable estimate, one birr m2 swell of land price would prompt local speculators to hoard 39.7𝑚2 more land per year. Land conjecture, which raises land worth 13 times its opportunity outlay - raised societal expenditures by 5.6% to 11.3%. Local GDP turn down by 33%, district revenue lifted by 15.1%, and unfair distribution of the middling property increment worth ratio for farmers (1.8%), local governments (19%), and builders (79.2%) correspondingly. The subsequent three tips are recommended to control land speculation: (1) one-personnel-single-plot law, (2) property value tax and (3) land development time limitations.
Keywords: Land speculation, property rights, land rent, opportunity cost, Ethiopia
Analyzing the Impacts of Urbanization and Climate Change on Urban Flood and Planning of Resilience-Based Flood Hazard Management: A Case of Adama City, Ethiopia
(Addis Ababa University, 2021-06-01) Dejene Tesema Bulti; Birhanu Girma (PhD)
Urban flooding, which occurs when rainfall exceeds the capacity of urban drainage systems, has become a major concern in many cities across the world. Due to urbanization-driven increases in impermeable surfaces and climate change-induced increases in extreme precipitation, urban flood is anticipated to rising in frequency and intensity in the future. The majority of Ethiopian cities are susceptible to urban floods, although there is little research on the subject. Understanding of the contributions of main drivers at appropriate spatial and temporal scales, features of potential floods under current and future conditions and various flood frequencies, as well as flood adaptation measures at smaller spatial scales can aid efforts to effectively respond to the current problem of urban flooding, as well as consideration of its potential future increase. This study aims to analyze the impacts of urbanization and climate change on urban flood in Adama City and to devise resilience-based flood hazard management strategies. By mapping LULC of the City at about 5-year interval from 1995 to 2019 and computing the runoff depth at respective years using SCS-CN method, the dynamics of the City’s hydrologic characteristics attributable to urbanization-induced spatio-temporal changes of LULC was analyzed. Statistical downscaling model (SDSM) and extreme precipitation indices were, respectively used for downscaling daily precipitation from the projections of two Global Circulation Models (CanESM2 and HadCM3) and for analyzing the impacts of climate change on the historical and future extreme precipitation events. Further, the potential changes in the relationship between intensity-duration-frequency (IDF) of extreme precipitation in present-day and future periods were compared and contrasted. IDF curves and their functions were deduced using Gumbel Type I probability distribution and power-regression model, respectively. Flood inundation model was developed with coupled 1D-2D flood modeling method using PCSWMM, and used for simulating potential floods for a range of return periods and possible combinations of existing and future LULC and climate scenarios. Flood hazard levels were determined based on flow depth-velocity approach, for each scenario. The theory of urban resilience to floods was adopted for assessing the flood resilience level of the study area and for planning resilience-based flood hazard management. Flood-prone area was selected from the 100-yr flood scenarios and under the combined future LULC and climate. Localized flood adaption strategies were identified and their suitability for the selected prone area was assessed.The findings show that the built-up area undergone 7.9% expansion rate from 1995 to 2019. Likewise, the runoff depth is increased by 9.5 % in the City administration and 12.9 % and 6.9 % within the two sub-watersheds. At all spatial scales, the temporal change of runoff depth is linearly associated with the rise of imperviousness ratio. Moreover, statistically significant trends were obtained for the majority of extreme precipitation indices computed for historical daily rainfall records of 1967-2016, indicating that climate change has had an impact on historical precipitation. Moreover, extreme precipitation is expected to rise in the future up to 2080. The findings also reveal that extreme precipitation intensity over the years 2021-2070 in Adama City would increase up to 49.5% or decrease up to 106.2%, depending on GCM, storm duration and return period considered. Furthermore, the study area is flooded under both existing and future land cover and climate conditions, with increasing in the water depth, flow velocity and inundation extent as the return period increases. Under historical climate and existing land-use scenario, 123.7 (5-yr)-204.3 ha (100-yr) is prone to flood whereas the extent varies from 178.2 to 396.8 ha, under the combined effect of future land use and climate changes. Moreover, the study area is associated with lower level flood resilience. Finally, elevated configuration, dry-proofing, wet-proofing, temporary measures and site and landscape interventions are proposed as effective strategies for building flood resilience of the prone community. In line with sustainable flood risk management in the City, it is suggested that the stakeholders recognize the level of potential associated risk and improve the awareness of the prone community. Future developments should be guided with impervious surface based land-use regulation in order to better control the hydrological effects of urbanization. Further, the standards and guidelines presently employed by the City for the planning and design of stormwater management infrastructure should be revised in such a way that they reflect global climate change impacts at local level. Designing and updating local development plans on flood-prone areas should also aim to ingrate localized flood adoption strategies to build flood resilience of the prone community. Finally, urban planning policies should aim to promote urban flood modeling as a base for urban flood hazard management operations, and personal responsibility in flood safety.
Keywords: urban flood, climate change, flood modeling, flood hazard, statistical downscaling, flood resilience, extreme precipitation, IDF
Clinical pattern and Management Outcome of Ocular Adnexal Injuries in Menelik II Comprehensive Specialized Hospital
(Addis Ababa University, 2024-01-19) Getu Jufar; Meseret Ejigu
To study the pattern and management outcome of ocular adnexal injuries at
Menelik-II Comprehensive Specialized Hospital
Refractive outcome of Manual Small Incision Cataract Surgery in tertiary teaching Hospital
(Addis Ababa University, 2024-05) Fisiha Ademe; Abeba Teklegiorgis
Cataract remains a leading cause of blindness globally, particularly in developing countries. Manual Small Incision Cataract Surgery (MSICS) has emerged as an effective and cost-efficient technique for cataract removal. However, concerns regarding postoperative refractive outcomes persist.
Rainfall Prediction using Combined Satellite and Station Data: Adeep Learning Approach
(Addis Ababa University, 2023-07-01) Mubarek Jemal; Melkamu Beyene (PhD)
Currently, Ethiopia has high rainfall variance, which is a result of global climate change that has an influence on the environment, property values, and human lives. Accurate rainfall prediction is highly important to smart agriculture practices for developing countries. For rainfall prediction, using station data alone often lacks the required accuracy and spatial coverage, and satellite data has spatial coverage but cannot predict rainfall as accurately as station data. The objective of this research is to develop a model for rainfall prediction using deep learning approaches by combining weather station and satellite data. A design science research methodology was used to develop a rainfall prediction model with 30 years (1990 - 2020) of daily weather station data from the National Meteorological Agency Ethiopian and satellite data from TAMSAT v3.1 and JRA-55 climate models. In data engineering, missing values were handled using mean imputation by dividing the dataset based on the three seasons of Ethiopia. Deep learning approach that includes multi-layer perceptron (MLP), Convolutional Neural Network (CNN), Long Short Term Memory (LSTM), and Bidirectional Long Short Term Memory (BiLSTM) were experimentally evaluated to predict rainfall for selected areas. Lastly, we proposed a model using Bidirectional Long Short Term Memory (BiLSTM) architecture that capable of forecasting daily rainfall for Ethiopia. The performance of the model is evaluated using the state of the art performance evaluation metrics such as; Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE), and the results were 0.0472, 0.0025, and 0.021 respectively. We also compared the proposed model with other deep learning approaches like MLP, CNN, and LSTM. The proposed BiLSTM model outperformed LSTM with an RMSE of 0.0015; CNN with RMSE of 0.0023, and MLP with RMSE of 0.0025. The experimental results show that the Bidirectional Long Short Term Memory (BiLSTM) model has a lower RMSE, MSE, and MAE.