Browsing by Author "Sempewo, Jotham Ivan"

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    Assessing willingness to pay for water during the COVID-19 crisis in Ugandan households
    (Social Sciences & Humanities Open, 2021) Sempewo, Jotham Ivan; Kisaakye, Peter; Mushomi, John; Tumutungire, Martin Dahlin; Ekyalimpa, Ronald
    With the emergence of COVID-19, improving hygiene through handwashing with water and detergent is a priority. This behavioural practice requires that households have access to reliable improved water. One measure that can provide an invaluable source of information to measure access to improved water supply is willingness to pay (WTP). However, little is known about WTP for water during a pandemic such as COVID-19. Data from a cross-sectional survey was used to assess potential household determinants of WTP for water during March-June 2020 in 1639 Ugandan households. The focus is on the period March-June 2020 when the government of Uganda implemented a countrywide total lockdown in a bid to curb the spread of the deadly virus. Results indicate that most households were not willing to pay for water during March-June 2020. Sex of the household head, region of residence, water source, number of times hands are washed and whether a household buys or pays for water were significant explanatory household determinants for WTP for water. The results provide a rich understanding of the household factors that determine WTP for water during a pandemic. This evidence is important in guiding government and water utilities in developing sustainable regulations and policy interventions particularly during emergencies. The findings suggest that increasing or maintaining water revenues will be a challenge in emergencies if no attention is placed to addressing the disparity in socio-economic attributes associated with households’ WTP.
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    The Impact of COVID-19 on Households’ Water Use in Uganda
    (Water Supply, 2021) Sempewo, Jotham Ivan; Mushomi, John; Tumutungire, Martin Dahlin; Ekyalimpa, Ronald; Kisaakye, Peter
    The unprecedented outbreak of COVID-19 necessitated the promotion of better hygiene practices to curb the spread of the virus. Better hygiene requires that households have a stable supply of water. However, little is known about the predictors of changes in water use in emergency situations such as COVID-19 in Uganda. This study uses data from a cross-sectional survey to examine the changes in the quantities of water used by 1,639 Ugandan households due to COVID-19. This article also explores the factors that are associated with changes in water use. The month March 2020 is used in this study as a cut-off because this is the month in which the government implemented a lockdown to curb the spread of the virus. Results indicate that most households had an increase in the quantity of water used after March 2020 when compared with the period before March 2020. Household characteristics that were associated with a change in the quantity of water used were age, sex, education, main occupation of household head, household size and region of residence. The results can be used to inform the prediction and demand modelling of household water use for improved water interventions for equitable water supply during emergencies.
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    Logistic Pipe Failure Prediction Models for an Urban Water Distribution Network in the Developing World: a case study of Kampala water, Uganda
    (Water Practice & Technology, 2022) Auma, Rose; Musaazi, Isaac G.; Tumutungire, Martin D.; Sempewo, Jotham Ivan
    Statistical models can be used as proactive approaches to pipe failure management for the satisfactory and efficient functionality of a water distribution network (WDN). The study aimed to develop two logistic regression models using historical data and evaluated them based on prediction accuracy, receiver operator characteristics (ROC), and area under the curve (AUC). Pipe sizes ranging from 150 mm to 350 mm in the WDN were adequate to prevent pipe failure. However, a 250 mm pipe diameter had the lowest failure probability. Old pipes had a lower failure probability than new pipes. Although it was evident that the installation design of water pipes is changing from steel to unplasticized polyvinyl chloride (uPVC), steel pipes had a lower failure probability than uPVC at the same depth from the soil surface. Pipes buried in gravel with a small diameter had a lower failure probability than those in clay of a bigger diameter. With a median pipe age of 8 years in the WDN and greater class weight on pipe failures, the binomial logistic regression model had better performance (accuracy – 96.9%, AUC – 0.996) than the multinomial logistic model (accuracy – 90.9%, AUC – 0.992), representing reliable model predictions. The models can be used to modify data collection protocols to better identify potential water pipes that require maintenance or replacement.
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    Over a Century Evidence of Historical and Recent Dryness/ Wetness in Sub-Humid Areas: A Uganda, East African Case
    (Meteorological Applications, 2021) Byakatonda, Jimmy; Openy, Geoffrey; Sempewo, Jotham Ivan; Mucunguzi, Dominic Banaga
    Many regions globally are grappling with the challenge of recurrent extreme weather events. Whereas attempts are being undertaken to understand their characteristics as a first step to guide targeted mitigation measures, these are focused on dryness and not wetness, which is also a challenge in sub-humid areas. This study investigates dryness and wetness characteristics using the standardized precipitation evaporation index (SPEI) at timescales of 3, 6, 12 and 24 months for a period of 1901–2018 across Uganda's drainage basins. Trends in the dryness and wetness evolutions were conducted using the Mann-Kendall (MK) statistic to establish the effects of global warming on the study area. A step change analysis reveals 1961 as a change point year from cool to warm periods. Results also reveal that warming mainly occurred in the recent period (1962–2018), with a temperature rise of over 2οC being recorded in 2009. Severe dryness events occurred in the recent period as opposed to wetness events that dominated the earlier period (1901–1961). Dryness and wetness varied among drainage basins, with the Aswa basin being more susceptible to severe dryness while the Lake Kyoga basin to severe wetness. Lira and Kitgum were identified as drought hotspots at timescales of 3, 6 and 12 months. SPEI was able to reveal 60% of historical dryness events and 75% of wetness events on record, making it an adequate tool for monitoring humid events as opposed to droughts in sub-humid climates. It is hoped that this evidence can guide targeted mitigation measures towards climatic shocks within the region.
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    Performance Evaluation of CFSR, MERRA-2 and TRMM3B42 Data Sets in Simulating River Discharge of Data-scarce Tropical Catchments: a case study of Manafwa, Uganda
    (Journal of Water and Climate Change, 2022) Nakkazi, Maria Theresa; Sempewo, Jotham Ivan; Tumutungire, Martin Dahlin; Byakatonda, Jimmy
    Data scarcity has been a huge problem in modelling catchments especially in the tropical region. Satellite data and different statistical methods are being used to improve the quality of conventional meteorological data. However, their potential needs to be further investigated. This paper evaluates the performance of three datasets in simulating discharge of River Manafwa, Uganda. Two reanalysis datasets were selected for studying both rainfall and temperature, whereas a satellite algorithm was selected for studying rainfall alone. MERRA-2 data and CFSR were chosen as the reanalysis datasets whereas TRMM3B42 data were used as the satellite product in this study. The SWAT model was used to evaluate the performance of these datasets. The model performance indicators indicated that, at daily time steps, all the three datasets produced values of Nash -Sutcliffe Efficiency (NSE<0.4), coefficient of determination (R2<0.4) and Percent Bias +25%. Despite a general underperformance compared to MERRA-2, CFSR performed better than TRMM. On applying generated bias corrections for precipitation and temperature climate data, overall results showed that the bias-corrected data outperformed the original data. We conclude that, in the absence of gauged hydro-meteorological data, bias-corrected MERRA-2, CFSR and TRMM data could be used for simulating river discharge in data-scarce areas.