Browsing by Author "Ngailo, Triphonia"
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Item Community views on water demands under a changing climate: The case of River Mpanga Water Catchment, Western Uganda(African Journal of Environmental Science and Technology, 2021) Mugume, Isaac; Semyalo, Ronald; Wasswa, Peter; Ngailo, Triphonia; Inguula Odongo, Ronald; Lunyolo, Joyce; Tao, SulinDifferent sectors globally are experiencing the impacts of changing climate and water resources are among them. This study was conducted with an aim of examining the community views regarding the effect of changing climate on water demand over the River Mpanga Water Catchment. The study employed a cross-sectional survey using 111 household interviews; 14 Focus Group Discussions (FGDs) and 27 key informants interviews (KII). This study considered 14 villages and employed a mixed-methods study design. The analysis was conducted using SPSS software to derive the descriptive statistics. Qualitative information was analyzed using content analysis to conduct an in-depth analysis. The study found that the main source of water is tap water (72.1%) and the main use of water in the study area is domestic water use. This study also found that, breakage in water supply especially during the dry season (10 out of 14 FGDs) and poor quality of water especially the tap water due to chemical treatment (11 out of 14 FDGs) were the major challenges of water the community faced. Additionally, this study observed that 15 out of 27 KII considered drought as a major threat and that the area had experienced decreases in rainfall amounts over the months of January and February. Therefore, this study recommends that the providers of domestic water should invest heavily in technologies for improving water quality and amount; ensure sustainable and equitable rationing of water during scarcity; and promote incentives for water harvesting.Item Examining the Impact of Bias Correction on the Prediction Skill of Regional Climate Projections(Atmospheric and Climate Sciences, 2020) Mugume, Isaac; Ngailo, Triphonia; Semyalo, RonaldRainfall is crucial for many applications e.g. agriculture, health, water resources, energy among many others. However, quantitative rainfall estimation is normally a challenge especially in areas with sparse rain gauge network. This has introduced uncertainties in rainfall projections by climate models. This study evaluates the performance of three representative concentration pathways, RCP i.e. 4.5, 6.0 and 8.5 over Uganda using the Weather Research and Forecasting (WRF) model. It evaluates the model output using observed daily rain gauge data over the period 2006-2018 using Pearson correlation; relative root mean square error; relative mean error and skill scores (accuracy). It also evaluates the potential improvement in the performance of the WRF model with respective RCPs by applying bias correction. The bias correction is carried out using the quantile mapping method. A poor correlation with observed rainfall is generally found (−0.4 to +0.4); error magnitudes in the ranges of 1 to 3.5 times the long-term mean are observed. The RCPs presented different performances over different areas suggesting that no one RCP is universally valid. Application of bias correction did not produce realistic improvement in performance. Largely, the RCPs underestimated rainfall over the study area suggesting that the projected rainfall cases under these RCPs could be seriously underestimated. However, the study found RCP8.5 with slightly better performance and is thus recommended. Due to the general weak performance of the RCPs, the study recommends re-evaluating the assumptions under the RCPs for different regions or attempt to improve them using data assimilation.