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Spring flood modeling is a major tool used to understand the risks of severe hydrological events in the context of climate change. In Kazakhstan spring of 2024 was a rapid shift from cold to mild temperatures in just a few weeks. While traditional flood forecasting methods have been limited in their ability to consider the interactions of the natural processes that create runoff, this research sets out to address these limitations by modelling the formation of spring floods using a numerical approach. The study discusses the effects of snowmelt and freeze-thaw processes on surface runoff and the flooding that results from it in the northern and western regions of Kazakhstan. A comprehensive model has been developed that considers the heat transfer in soil, infiltration of meltwater, and propagation of runoff. Numerical modelling indicates that in 2024, relative to 2021, there was earlier soil thawing and shallower depths of soil freezing. However, an increase in the intensity of snowmelt leads to the fact that the infiltration capacity of the soil is insufficient, despite the formation of a thawed layer. As a result, a higher surface runoff is formed. Using Saint-Venant’s equations to perform calculations indicates that higher values of current depth and velocity of runoff were observed in 2024 than in 2021, indicating a greater likelihood of flooding. Therefore, it can be concluded that increases in winter temperatures have the potential to create an increased flooding impact due to changes in the proportions of surface runoff and infiltration.