Abstract
Abstract. An early warning system for flood prediction based on precipitation forecast is presented. The system uses rainfall forecast provided by MeteoGalicia in combination with a hydrologic (Hydrologic Modeling System, HEC-HMS) and a hydraulic (Iber+) model. The upper reach of the Miño River and the city of Lugo (NW Spain) are used as a study area. Starting from rainfall forecast, HEC-HMS calculates the streamflow and Iber+ is automatically executed for some previously defined risk areas when a certain threshold is exceeded. The analysis based on historical extreme events shows that the system can provide accurate results in less than 1 h for a forecast horizon of 3 d and report an alert situation to decision makers.
Highlights
According to Noji (2000), floods are one of the most dangerous natural hazards in the world. Jonkman (2005) estimated that more than 100 000 deaths in the last century were caused by floods
UNISDR (2009) defines early warning systems as the set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities and organisations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss
The capability of the MeteoGalicia weather forecast system to predict rain events was evaluated by means of the comparison with real precipitation data provided by the rain gauges in the area of study
Summary
According to Noji (2000), floods are one of the most dangerous natural hazards in the world. Jonkman (2005) estimated that more than 100 000 deaths in the last century were caused by floods. Jonkman (2005) estimated that more than 100 000 deaths in the last century were caused by floods. From 1940 to 2018 the number of deaths related to flood events (8138) is only surpassed by lightning fatalities (9386) in the US (https://www.weather.gov/hazstat/, last access: September 2019). The effect of climate change will increase the number of flood events and their negative impact on people and properties (Dankers and Feyen, 2008; Alfieri et al, 2017). The ability to predict these extreme events and prevent their consequences is a challenge for the scientific community worldwide. In this context early warning systems (EWSs) play a key role. UNISDR (2009) defines early warning systems as the set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities and organisations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss
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