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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

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. HIGHLIGHTS About 2.1 billion people worldwide lack access to clean water for household use.; The outbreak of COVID-19 emphasises the need to improve hygiene as a behavioural strategy.; Households changed behaviour due to COVID-19 which increased water use after March 2020 when compared with the period before March 2020.; There is need to design interventions to cope with the challenges for increased demand for water during emergencies.;

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.