By any metric—from financial ruin to human toll—floods rank alongside earthquakes, hurricanes, and tsunamis. Flash floods are serious weather emergencies and are becoming more frequent with extreme weather events. Here, we present a systematic framework that considers a variety of features explaining different components of risk (i.e. floods (including flash floods) natural hazards with highest frequency of occurrence (43.4% of total) floods and flash floods affect most people (about 2 billion over last 20 years; 48% of total affected by all hazards) Earlier studies: more than 5,000 people die from flash floods annually worldwide in mm/12h) for high percentiles, e.g. Studies suggest that being able to predict extreme rainfall over a small area would be sufficient. Flash floods are costly natural hazards, primarily due to their rapid onset.
The additional data gives forecasters a much better picture of when and where flash floods may occur. Predicting flash floods. Meteorologists and hydrologists struggle to predict such floods because they are caused by a combination of intense rainfall and ground conditions that promote heavy runoff. Predicting the amount of rainfall is different from weather forecasting. These data have proven to be very valuable with regard to predicting flash floods. How are floods predicted? Flash floods, walls of water that quickly sweeps across an area, are the floods that result in the most loss of life and property. Predicting floods is notoriously tricky. Flood predictions require several types of data: The amount of rainfall occurring on a real-time basis.

For example, a user may be interested in identifying the wettest places in the world in two days’ time in order to anticipate which areas are vulnerable to flash floods. Predicting flash floods is arguably somewhat less involved than predicting broader-scale flooding events associated with large rivers, because one does not necessarily need to use detailed hydrological models.
They could plot point rainfall (e.g. On the surface, flash floods seem pretty self-explanatory. Therefore, predicting property damage of flash floods is imperative for proactive disaster management. However it has proven extremely difficult to do even that. Instead of only one or two reporting sites in a county, usually at a local air port, there may be dozens with the addition of these volunteers. In some cases the ground can be too dry to soak up rain, in others too wet. The rate of change in river stage on a real-time basis, which can help indicate the severity and immediacy of the threat. Predicting Floods. In the pantheon of natural disasters, floods are among the worst. In fact, the most deadly disaster of the 20 th century was the China floods of 1931, which may have resulted in more than a million deaths. According to the IPPC report (Intergovernmental Panel on Climate Change), 2018, increasing temperatures will increase the amount of rainfall and hence the intensity of flooding on land [13].