http://repository.pauwes-cop.net/handle/1/167 2026-07-26T17:35:16Z 2026-07-26T17:35:16Z NAMWANJE, Roset http://repository.pauwes-cop.net/handle/1/492 2022-06-02T02:00:40Z 2021-11-15T00:00:00Z

A COMPARATIVE ANALYSIS ON GIS BASED METHODS AND MACHINE LEARNING ALGORITHM IN LANDSLIDE SUSCEPTIBILITY MODELING, A case study of Bududa, Uganda NAMWANJE, Roset Landslide susceptibility modeling is of critical importance to landslide risk management, urban planning, understanding landscape evolution, and identifying landslide spatial and temporal signatures. In this study, the GIS-based weight of evidence model and the Support Vector Machine learning algorithms were compared in landslide susceptibility assessments using a case study of Bududa located in the eastern part of Uganda. The inventory of landslides applied in the study was created using satellite imagery and historical maps of the region. The causative factors were derived from the STRM DEM of 30m resolution and the Geological characteristics of the region were obtained from the Ministry of Geological Survey and Mines. The Weight of Evidence model revealed 5 factors with a positive spatial association to landslide occurrences and these were the Slope Angle, Profile Curvature, Plan Curvature, Geology and Distance to Rivers. The SVM model identified Slope Angle, Profile Curvature, Stream Power Index and Elevation as triggering factors. The comparative analysis between the two methods was conducted using the Confusion Matrix, the Receiver Operating Curves (ROC) and the developed susceptibility maps. The ROC curves gave an accuracy of 87% of the Area under Curve (AUC) for the Optimizable Support Vector Machines and a 79% (AUC) for Weight of Evidence in performance. The field validation data placed ten landslide points in the mapped susceptibility zones for both models which indicated a good overall performance for both methodologies, however the study evinced potential of more efficient and accurate results with the integration of both approaches in landslide susceptibility modeling.

2021-11-15T00:00:00Z Yimer, Sadame Mohammed http://repository.pauwes-cop.net/handle/1/106 2020-01-28T13:13:15Z 2016-01-01T00:00:00Z

Effects of Land Use Changes on Sediment Yield and Its Potential Contribution to Greenhouse Gases Emissions from Reservoirs Yimer, Sadame Mohammed Sedimentation is becoming a big challenge worldwide to water resources development in general and to the reservoirs in particular by reducing the storage capacity and then useful lifetime of the dam. Tekeze dam is the recently constructed hydropower dam in Ethiopia which is threatened by siltation problem. The rugged topographic nature, land use changes and poor watershed management in general, are the main driving factors for high sediment yield to the Tekeze dam reservoir. Despite the perception hydropower dam as a clean energy source, recent researchers have reported that hydropower plants located particularly in tropical region emit a significant amount of greenhouse gases to the atmosphere due to flooding of huge biomass during impoundment and the presence of high tempreture. The continuously flushed nutrients and organic matter with sediment also contributed to reservoirs organic carbon bugdet. The general objective of this research was to assess the effect of land use changes on sediment yield and its potential contribution to the greenhouse gas emission from Tekeze dam reservoir. In particular, it was aimed to estimate the sediment yield with two land use change scenarios, the useful life of the reservoir, estimate the gross GHGs emission level from Tekeze dam, and trends of greenhouse gases emission amount from the reservoir due change in sediment yield which resulted from land use changes. The research was carried out using secondary data from open sources. Universal soil loss equation (USLE) has been used to estimate soil erosion rate with change in land use scenarios. The two past land use conditions that have been actually on the ground in 2001 and 2010 were used as scenarios. Results indicate that soil erosion rate increases from 104.5 ton/ha/year to 129.2 ton/ha/year with 2001 and 2010 land use scenarios respectively. This change in sediment yield will shorten the expected reservoir lifetime from 29 years to 22 years starting from now. The Greenhouse gas risk assessment tool (beta version) developed by UNESCO/IHA has been used to estimate the gross emission level of CO2 and CH4. The results show that the level of emission for both CO2 and CH4 is high in the first 20 to 30 years from impoundment and gradually decline with time. The approaches that used to see the trends of GHGs emission amount due to sediment yield change were by looking at how the organic carbon budget of the reservoir and retention time of the inflow water in the reservoir will be. Thus, empirical equation given by (Gert Verstraeten and Poesen 2002) was adapted to estimate the organic carbon yield in the reservoir sediment. And from the general definition of retention time, the storage capacity divide by outflow rate has been used to estimate the retention time. The analysis showed that the change in land use from 2001 to 2010 scenario is expected to increase the greenhouse gas emission level due to the organic carbon content coming with sediment. On the other hand, the deposited sediment can bury the inundated biomass permanently and may make it inactive from decomposition and involvement in the greenhouse gas production. Regarding the retention time, Greenhouse gases emission is expected to be high in 2001 land use scenario due to more residence time than 2010 land use condition. Particularly CH4 emission is expected to increase by a greater proportion than CO2 in 2001 scenario due to the significance of retention time in methane production than CO2. Therefore, it is concluded that the change of land use in the catchment has a significant impact in the reservoir useful lifetime due to downstream sedimentation problem. Whereas the effect of sediment yield changes to greenhouse gas emission amount from reservoirs have seen in two contrary directions. Then, it was found that in one side it increases the GHGs emission potential due to more organic carbon addition and on the other side decrease the potential emission due to less retention time in the long term of the dam life. Hence, in order to identify the most significant or overweighed emission tendency due to sediment yield change needs further detail research in this area.

2016-01-01T00:00:00Z Musyoka, Francis Kilundi http://repository.pauwes-cop.net/handle/1/103 2020-01-28T13:13:15Z 2016-01-01T00:00:00Z

Assessing The Impact Of Climate Change On Hydropower Generation In Kenya A Case Study Of Upper Tana River Basin Musyoka, Francis Kilundi Hydropower is currently Kenya’s second most dominant source of renewable electrical energy accounting for close to 49 per cent of power supply. The main source of hydropower in Kenya is the seven forks dams located in the Upper Tana river basin. Among the hydropower dams, Masinga Dam serves as a storage reservoir, controlling hydrology through a series of downstream hydroelectric reservoirs. The operation of Masinga dam is therefore crucial in meeting the power demands for the country, thus contributing significantly to the country’s economy. The main resource for hydropower generation is runoff which hugely depends on precipitation. Temperature and precipitation effects from global climate change could alter future hydrologic conditions in the upper Tana River basin and, as a result, hydropower generation. This research thesis is therefore a study that aims to assess the changes in hydropower generation in Kenya as a result of the changing climate, with a focus on the seven forks hydropower project. A simple approach assumes that hydropower systems will reduce generation if water supply reduces, and vice versa. The study uses a 30-year climate data to establish the precipitation trend and runoff variations of the study area. Based on the runoff changes, hydropower generation is estimated by relating the runoff changes to hydropower generation potential. The ArcSWAT model has been used for runoff analysis and simulation. ArcSWAT ArcGIS extension is a graphical user interface for the SWAT model developed to predict the impact of land management practices on water, sediment, and agricultural chemical yields in large, complex watersheds with varying soils, land use, and management conditions over long periods of time. The model is physically based and computationally efficient, uses readily available inputs and enables users to study long-term impacts. The results show that climate change is affecting the stream flow of the Upper Tana basin and hence leading to reduction in hydropower generation due to reduced or increased reservoir storage.

2016-01-01T00:00:00Z