<p>Poorly planned urbanization combined with climate change increases the annual likelihood of flooding in low-lying areas with inadequate storm drainage systems. Therefore, the development of models to predict flood situations in cities is crucial because floods pose significant risks to human lives and infrastructure. This paper utilizes the diffusion model in complex networks to simulate flood scenarios in the specific context of urban hydrology. By adapting the model, this study describes how rainwater spreads through interconnected nodes within the network. These nodes represent different areas of a city, such as buildings, roads, and water bodies. Various properties, including elevation, surface roughness, and permeability, were assigned to nodes that influence the flow of water. The edges between nodes represent pathways for water movement. The model considers factors such as rainfall intensity, network topology, properties, and existing flood mitigation measures. The proposed model was evaluated in two experiments. The first experiment aimed to identify the critical points in the network, whereas the second experiment examined how the number and distribution of storm drains affected flooding. As a case study to test the model, it was tested in a flood-prone section of Guadalajara, Mexico. The experimental results demonstrate that our model is flexible and simple, allowing us to draw interesting conclusions from several flooding scenarios.</p>