Masters Degree Dissertations

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12504/111

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    A time series forecasting model for rainfall in Kasese district, Uganda using the SARIMA approach
    (Kyambogo University (Unpublished work), 2025-06) Kaluya, Joshua
    The study developed a time series forecasting model aimed at predicting monthly rainfall in Kasese district, Uganda. Rainfall patterns play a critical role in agriculture, water management, and disaster preparedness in the region. Using data from January 1960 to December 2023 obtained from the Uganda National Meteorological Authority (UNMA), the study employed a Seasonal Autoregressive Integrated Moving Average (SARIMA) model to analyze and predict rainfall trends. Preliminary analysis revealed that the data was non-stationary, as confirmed by the Augmented Dickey-Fuller (ADF) test (test statistic = -8.56, p-value = 0.01), and showed significant autocorrelation based on the ACF and PACF plots. The analysis showed that the months of March–April–May (MAM) and September–October–November (SON), with a mean monthly rainfall of approximately 118.03 mm (95% confidence interval: 111.32–124.74 mm) receive the highest amount of rainfall. In contrast, the driest months—January, February, June, and July—had a mean monthly rainfall of about 47.53 mm (95% confidence interval: 43.02–52.04 mm). A SARIMA (3, 1, 1) (1, 0, 0) [12] model was selected based on the Akaike Information Criterion (AIC = 7948.98) and the Bayesian Information Criterion (BIC = 7976.55). A 12 – month seasonal model was used to capture monthly rainfall variations throughout the year, despite Uganda’s two main rainy seasons. The model demonstrated good predictive accuracy, achieving a MAE of 42.5962, RMSE of 54.972, and MASE of 0.8376. Residual analysis confirmed that the model adequately captured the seasonal and trend components without significant autocorrelation. The study concluded that the SARIMA model provided reliable short-term forecasts of monthly rainfall in Kasese, supporting agricultural planning and disaster risk reduction. The research recommended adopting of the model by local authorities, for short – term forecasts to improve agricultural planning, and also hold workshops and training sessions to educate the people on how to use and interpret the model forecasts and predict rainfall trends.
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    Community perceptions and practices towards waste management and effects on water quality in landing sites along lake Albert : a case of Kitebere landing site, Kagadi district
    (Kyambogo University, 2021-02) Opio, Stephen
    This study sought to find out Kitebere residents‘ perceptions and practices towards waste management (WM) and investigates the effects of the practices on water quality. To achieve this aim, the study‘s main objective was to assess community perceptions and practices towards waste management and its effects on water quality in Kitebere landing site. The descriptive survey design and cross sectional research design was used with quantitative and qualitative research approaches. These were administered to the households to collect information about perceptions, waste management practices, wastes generated and attitudes, or behaviours. Focus group guides were used to collect data from both women and men. Two gendered FGDs were held among fishermen, fish mongers and boat owners. Information regarding waste collection and disposal practices in the market area and general community were collected. Semi structured questions were administered to key informants including District departments, local councils, health inspectors, traders and area councilors. Key data that were collected included existence of Environment Awareness (EA). Transect walks or guided community walks were conducted with the guide of the area councilor. The purpose of the transect walks was to observe waste management practices and types of wastes generated. Additionally, a handheld camera was used to capture the status of open defecation, waste in the drainage channels, makeshift toilets and urinals draining directly into the lake. The GPS was also used to capture locations of dumpsites, toilets and urinals including their distance from the open water. Secondary data from archival sources, books, articles, reports, internet, newspapers, journals among others were reviewed. The data reviewed was related to environmental health, public health and waste management in communities in regards to their perceptions and practices. A total of 95 participants participated in the study. Systematic and purposive sampling was used to select participants. Interview schedule was used to collect data from 95 residents and the interview guide was used to collect data from the district and sub county representatives. Observation guides and transect walk methods were used to ascertain some responses from participants. Data collected were analysed using Statistical Package for the Social Sciences (SPSS), excel and descriptive statistics were used to analyse the raw data.