Climate change has become one of the greatest challenges facing the world in recent years and affects many aspects of life, including transportation and communications infrastructure systems. For this reason, it is essential to develop intelligent adaptation strategies to handle risk assessments related to extreme rainfall, which affects mobility and safety within cities and especially in crowded urban areas. The system proposed in this paper supports decision making for rainfall-related risk assessment and early warning system planning, and contributes to providing an efficient road plan for risk mitigation. It consists of three modules: a data collection module, a risk analysis module, and a decision-making module. The data collection module works in an interactive manner, and can collect data from many sources; this includes real data entered by users, sensor data, and Global Navigation Satellite Systems (GNSSs) or other data generated by forecasting applications. The risk analysis module evaluates data, accounts for other factors related to Earth's topography and uses GIS-based processes to assess geographic data. The decision making module helps users make appropriate decisions about movement and avoid dangerous roads. End users may include workers from civil protection services, management entities, and non-professional users. This proposed system will be subject to case studies related to rainfall in Saudi Arabia. It is likely to be useful for informing more detailed infrastructure risk assessments.