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 1639 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 to 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 under emergencies.

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Data scarcity has been a huge problem in modelling various catchments especially in the tropical region. Satellite data and different statistical methods are being used to improve the quality of conventional meteorological data. However, the potential of using these data needs to be further investigated. This paper evaluates the performance of three reanalysis datasets in hydrological modelling of the Manafwa Catchment, Uganda. Two reanalysis datasets were selected for studying both rainfall and temperature in Manafwa, whereas a satellite algorithm was selected for studying rainfall alone. The Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), which has a horizontal resolution of 50 km and is suitable for investigating rainfall in small precipitation systems, and the Climate Forecast System Reanalysis and Reforecast (CFSR), which has a horizontal resolution of 38 km, were chosen as the reanalysis datasets. The Tropical Rainfall Measuring Mission (TRMM3B42) data were used as the satellite product in this study. The SWAT was set up to compare the performance of reanalysis datasets with that of the observed data. The model performance indicators indicated that, at daily time steps, all the three datasets produced the values of Nash–Sutcliff 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 such as the tropical catchments in Uganda.

Being one of the most important assets of a water utility, urban water distribution pipe systems account highest of the total expenditure involved in water supply systems. However, maintaining water system performance can be challenging due to deterioration. Deterioration, an ongoing process as the system ages is influenced by a number of factors majorly physical, operational, and environmental factors, and is the main cause of pipe failures. Pipe failure has economic, social, and environmental impacts thus increasing operational and maintenance costs. Therefore, the need for proactive approaches for management to ensure the systems operate satisfactorily, and function efficiently and continuously at low costs is highly recommended.