TRAFFIC SPEED MODELLING TO IMPROVE TRAVEL TIME ESTIMATION IN OPENROUTESERVICE

We develop novel probabilistic models to estimate flash flood losses of companies and households in Germany. Using multiple flash flood events, we identify key drivers of flash floods loss. FLEMO flash model reveals that for companies, the effectiveness of emergency measures is crucial in mitigating losses. In contrast, household benefit more from knowledge about emergency response, suggesting that enhancing preparedness can effectively reduce flash flood losses.

Many households in Vietnam depend on revenues from microbusinesses (shop-houses). However, losses caused by regular flooding to the microbusinesses are not modelled. Business turnover, building age and water depth are found to be the main drivers of flood losses to microbusinesses. We built and validated probabilistic models (Non-parametric Bayesian Networks) that estimate flood losses to microbusinesses. The results help in flood risk management and adaption decision making for microbusinesses.