15th HEPEX Webinar: Flood Forecasting in Early Warning Systems
The next HEPEX webinar will be a bit different, since it is hosted not by us, but by CH2M HILL, who developed the ISIS software. The seminar is given by Murray Dale, and you can register for the seminar here.
Date and time: Thursday 1 May at 10:00 BST (09:00 UTC)
Abstract: Natural disasters are increasing in number and severity. Flooding, in particular, is a very damaging natural hazard. In the United States, where flood mitigation and prediction is advanced, floods do about $6 billion worth of damage and kill about 140 people every year; globally, coastal flooding alone does some $3 trillion in damage. Forecasting floods, and the impact they have through early warning systems, can result in reduced loss of life and allow institutions and agencies to be better prepared, enabling a greater response. Components within early warning systems include river models with inputs from meteorological forecasts that can be quickly run to show where flood water is expected to travel and the likely impact of that flood water.
The webinar will focus on:
– The role of river models within flood early warning systems
– The application of ISIS in early warning systems
– Case studies where ISIS has been used to forecast likely flood impact
– Setting thresholds within early warning systems for floods
– Coping with uncertain meteorological forecasts within an early warning system
About the speaker: Murray Dale is a senior hydrometeorologist at CH2M HILL with more than twenty years of experience in water and flood risk management. He has worked on flood forecasting projects throughout the world including the USA, UK, Ireland and Algeria and he regularly delivers training courses to organizations and government agencies.
For the World Bank, Murray was involved in the establishment of suitable rainfall thresholds for flood warning used by the National Meteorological Organisation in Algeria, including communication links between the meteorological agency and emergency responders.