AI Revolutionizes Rainfall Forecasting in the Netherlands
Utrecht, Tuesday, 28 October 2025.
Ruben Imhoff is advancing rainfall forecasting using AI to tackle urban flooding exacerbated by climate change, aiming for enhanced prediction accuracy and disaster response in the Netherlands.
The Role of AI in Modern Meteorology
Ruben Imhoff, a researcher at Deltares, is pioneering the integration of artificial intelligence into rainfall forecasting to address urban flooding issues exacerbated by climate change. Deltares, a research institute in the Netherlands, collaborates with various scientific disciplines to enhance the accuracy of weather predictions. Imhoff’s work primarily focuses on short-term rainfall forecasting, also known as nowcasting, which aims to predict rainfall within the next few hours [1].
Challenges and Innovations in Forecasting
Traditional weather models often struggle to predict extreme rainfall events accurately. This gap in forecasting is where AI comes into play, as it can detect subtle patterns and correlations in vast datasets that conventional models might overlook. Deltares is developing hybrid models that combine AI with physics-based models to improve forecast accuracy without losing insights into underlying processes [1][2]. This innovation is crucial as urban areas in the Netherlands and globally face increasing risks from climate change-induced weather patterns [3].
Collaborative Efforts and Global Applications
Deltares is not working in isolation. The institute collaborates with organizations such as Rijkswaterstaat, Innovatieplatform DigiShape, and KNMI under the AI Impulsprogramma to enhance water movement models. This collaboration aims to make these models more responsive to modern challenges like extreme weather and climate change [2]. Internationally, Deltares is involved in projects in countries like Ghana and Ethiopia, integrating AI techniques into existing software tools to respond more effectively to extreme rainfall [1].
Future Directions and Implementation
Looking ahead, the implementation of AI in rainfall forecasting is expected to be evaluated in practical applications starting in early 2026. This timeline underscores the urgency of developing reliable forecasting systems that can significantly mitigate the impact of urban flooding. Imhoff emphasizes the importance of explainable AI, ensuring that AI remains a tool to enhance human understanding and response capabilities rather than an end goal in itself [1][3].