Flood disasters have increased in frequency, magnitude, time and space. Climate change and variability have been considered as the main cause. However, population increases have also increased pressure on land resources for settlement and food production. This is apparent in many river basins in Malawi, forcing people to invest in fringe and flood-prone areas. However, not much has been documented to inform decision-making. Therefore, the aim of this study was to examine the rainfall-runoff relationship for predicting flood peaks in the North Rukuru River basin in Northern Malawi. This is a heavily committed river basin sustaining the socio-economic livelihoods of the riparian communities. The study calibrated and validated the HEC-HMS model using historical observed data for the river at station from 2000 to 2023. The model was then applied to simulate the peak discharge response to rainfall. The model performance during the calibration and validation was acceptable, with the determination coefficient (DC) value above 0.85, suggesting a strong relationship between rainfall and discharge in the North Rukuru River Basin. Such a relationship is helpful for the prediction of peak discharge and can be used for decision-making in flood alerts in prone areas. The peak flow and flood frequency analysis was done using annual maximum series. The probability of maximum flood level was α = 0.35 of the Log-Gumbel type III, which shows an increase in distribution. The study concludes that the model was suitable and efficient in determining the likelihood of peak discharge with increasing rainfall, and the flood level events have been increasing recently.
Keywords: Flood disasters, HEC-HMS model, North Rukuru, Malawi, Peak discharge Rainfall-runoff relationship, Regression analysis
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