E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||13|
|Section||Performance and behaviour of flood defences|
|Published online||20 October 2016|
Interpreting the impact of flood forecasts by combining policy analysis studies and flood defence
1 Rijkswaterstaat, Ministry of Infrastructure and the Environment, PObox 2232 3500 GE, Utrecht, the Netherlands
2 HKV Lijn in Water, Botter 1129, 8232 JN Lelystad, The Netherlands
a Corresponding author: Robert.email@example.com
Flood forecasting is necessary to save lives and reduce damages. Reducing damages is important to save livelihoods and to reduce the recovery time. Flood alerts should contain expected time of the event, location and extent of the event. A flood alert is not only one message but part of a rehearsed flow of information using multiple canals. First people have to accept the fact that there might be a threat and what the threat is about. People need a reference to understand the situation and be aware of possible measures they can take to assure their own safety and reduce damages. Information to the general public has to be consistent with the information used by emergency services and has to be very clear about consequences and context of possible measures (as shelter in place or preventive evacuation). Emergency services should monitor how the public is responding to adapt their communication en operation during a crisis. Flood warnings and emergency services are often coordinated by different government organisations. This is an extra handicap for having consistent information out on time for people to use. In an information based society, where everyone has twitter, email and a camera, public organisations may have to trust the public more and send out the correct information as it comes in. In the Netherlands Rijkswaterstaat, the National Water Authority and the National Public Works Department, is responsible for or involved in forecasting in case of floods, policy studies on flood risk, policy studies on maintenance, assessment and design of flood defences, elaborating rules and regulations for flood defences, advice on crisis management to the national government and for maintaining the main infrastructure in the Netherlands (high ways and water ways). The Water Management Center in the Netherlands (WMCN) has developed a number of models to provide flood forecasts. WMCN is run for and by all managers of flood defences and is hosted by Rijkswaterstaat. Other organisations use these forecasts to define the consequences of the forecast, to take measures (as the evacuation of camping places on rivers banks or lake shores) or to estimate the conditional probability of failure of a flood defence. Increasing the resilience of the population by disseminating information from both policy studies (flood scenarios) and flood forecasts has been the project goal of the MEGO project “Module Evacuatie Grote Overstromingen”, an information tool for large scale evacuation due to floods. This information is available on a national website. The MEGO project has focussed on making the information from two major policy studies on flood risk available, the first sturdy determined new risk-based standards for flood defences (WV21). The second study determined the current flood risk (VNK-2). The MEGO database contains a selection of verified flood scenario’s. For each scenario the hydraulic loads which will cause a flood are known as are the probabilities of flooding and predicted casualties and damages. Overland flow maps are available. MEGO combines this data with the flood forecast, open data of the “Cadastre” (national Registry), the national digital terrain model (AHN) and the main infrastructure (local, regional and national). The site offers prepared and real time maps for professionals during a crisis, and tools to increase risk awareness for citizens. The software was recently renamed national water and flood information system, “Landelijk Informatiesysteem Water en Overstromingen (LIWO) ’ when it went live in 2016. In LIWO the second goal of MEGO was realized, by adding the information from flood forecasts. It is an open source model.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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