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Extreme flood events are complex and inherently uncertain phenomenons. Consequently forecasts of floods are inherently uncertain in nature due to various sources of uncertainty including model uncertainty, input uncertainty, and parameter uncertainty. This paper investigates two types of natural and model uncertainties in extreme rainfall-runoff events in a semi-arid region. Natural uncertainty is incorporated in the distribution function of the series of annual maximum daily rainfall, and model uncertainty is an epistemic uncertainty source. The kinematic runoff and erosion model was used for rainfall-runoff simulation. The model calibration scheme is carried out under the generalized likelihood uncertainty estimation framework to quantify uncertainty in the rainfall-runoff modeling process. Uncertainties of the rainfall depths-associated with depth duration frequency curves-were estimated with the bootstrap sampling method and described by a normal probability density function. These uncertainties are presented in the rainfall-runoff modeling for investigation of uncertainty effects on extreme hydrological events discharge and can be embedded into guidelines for risk-based design and management of urban water infrastructure.