This document provides detail of five important recommendations to help predict, prevent and mitigate the scale and impact of flooding.1. A consistent approach to flooding2. Improving flood modelling 3. Improving forecasting and predictions4. Planning, at a national or local level, the response to a flood event5. Identification and protection of critical infrastructure
A CONSISTENT APPROACH TO FLOODINGCreating a Consistent View of the Built and Natural EnvironmentFlooding is a national issue which has the potential to affect many areas of the country through conventional fluvial or tidal flooding, as well as the increasing phenomenon of surface runoff and drainage flooding, which is largely as a result of urbanisation.As demonstrated by the July 2007 floods, areas that were previously thought to be low risk in terms of flooding can in fact be seriously affected.Because of the national scale of this issue and the magnitude of the losses involved, any approach to best predict, prevent and mitigate the potential scale and impact of future flooding must be based on a nationally consistent framework of information.Work on such a framework has been underway for a number of years in the form of the Atlantis programme. The Atlantis programme has been established by a consortium of government organisations with the aim of developing, maintaining and promoting the use of a definitive national geographical data infrastructure with the purpose of enhancing the national capability to understand and manage flood, and other water-related hazards.Current government organisations involved with the Atlantis programme are the British Geological Survey, Centre for Ecology and Hydrology, Environment Agency, Met Office, United Kingdom Hydrographic Office and Ordnance Survey. Each of these organisations maintains a number of definitive datasets which are fundamental to understanding the problem. The explicit aim of the Atlantis programme is to ensure that these critical datasets are engineered to enable them to work together and compliment each other in a consistent manner irrespective of location.These datasets also have the potential to benefit multiple sectors within industry from Local and Central Government, Utility companies and Environmental organisations to Insurance and Land & Property companies. Access to this consistent national framework must therefore be made available to all key stakeholders to quickly and easily to allow rapid response when it is most needed.IMPROVING FLOOD MODELLINGA More Detailed Understanding of the Type and Extent of FloodingFluvial and Coastal Flood Modelling The existing flood zone boundaries are being updated at regular intervals using the latest digital terrain data. New technology enables higher resolution data capture where this is economic. Even then the extent of a predicted event and an actual event can differ significantly and it is the latter that is of operational importance during the management of an event. New technology enables the capture of higher resolution surface data to support better modelling. This surface can be related to the building objects, address and occupancy information ensuring this is interoperable (i.e. using the Digital National Framework protocols). This then provides the potential for a more rigorous environment for site management and evacuation during an emergency and in scenario/contingency planning.Surface Runoff Flood Modelling In addition, standard flood models primarily consider fluvial and tidal flood events. As land becomes more and more built up, surface runoff and drainage-related flooding is becoming more prevalent, as demonstrated by the July 2007 floods. Existing flood models do not consider causes of flooding from other sources, such as rising groundwater, surface permeability and local drainage networks. A village near Kingston-Upon-Hull affected by surface runoff flooding in July 2007 is proposed as example. A clearer understanding provided by enhanced datasets allows the analysis of why this particular area was subject to surface runoff flooding. Due to saturated ground in the surrounding area, runoff water was channelled into the village along routes of easiest flow, namely roads. The village had one main outlet for the water on its eastern edge; however the water was blocked by a roadside cutting which essentially acted as a dam. There is however a lack of understanding as to how areas displaying similar circumstances could be identified throughout Great Britain.It will be necessary to combine surface coverage information with drainage datasets in order to accurately model and predict these scenarios. This will require that utility companies and other data providers work to a common framework to make this information useful and readily available, as provided by the National Underground Assets Group (NUAG).IMPROVING FORECASTS AND PREDICTIONSIntelligent Use of Geographical Information to Predict and Forecast Flood EventsFlooding depends on many factors, and so various datasets are required in order to understand the full picture. These datasets are managed by a number of disparate organisations, each with a specific area of expertise:â¢ The Environment Agency maintains the detailed river networkâ¢ The Met Office records precipitation measurements and predictions â¢ The United Kingdom Hydrographic Office collects detailed information in the marine and coastal environments, such as tidal times and heightsâ¢ The Centre for Ecology and Hydrology deals with flood models and will hold river catchments and depth profilesâ¢ British Geological Survey maps the geology of the landscapeâ¢ Utility companies and local authorities hold information about storm drains, sewers and other drainage featuresâ¢ Ordnance Survey collects detailed height data, surface types and discrete geographical features.Efficient, rapid access to all of this information is needed in order to monitor current conditions and allow accurate forecasting and dynamic modelling of specific flood events. Without bringing the datasets together in a common, nationally consistent information framework this would not be possible. In addition to post-hoc incident response these datasets are essential to improving scenario planning and possible prevention of flood disasters before they occur.PLANNING THE RESPONSE TO FLOODINGUsing available data for detailed scenario planningFor any flood event the most detailed information is required to ensure focused and efficient planning and response.The ability to quickly identify individual buildings, including addresses and their usage & occupation, that have been directly or indirectly affected by the flood, as well as those which are of strategic importance, enables a well prioritised and efficient response.As well as the impact on land and property there is also the capability to assess the potential impact on the transport network, which is equally critical to the safely of life, and aid in the coordination and logistics of a response. It allows the identification of roads which could be rendered impassable or inaccessible due to the flooding, as well as providing the important road routing information critical for the emergency services such as height, weight and width restrictions.The genuine example of Carlisle shown in figure 5 highlights the buildings directly affected by the January 2005 floods, those cut off by the flood, and those which may have had an impact on the response and recovery (such as the Council offices, the fire station, schools and utilities). It also highlights the roads out of action and routing information which could be important for the emergency services.This type of scenario and response planning can potentially be rolled out throughout Great Britain enabled by the national framework on which the Atlantis programme is based. Ultimate responsibility for the coordination of such planning and response strategies should sit with the Local Authority utilising the expert and local knowledge contained within the Authority.IDENTIFYING CRITICAL INFRASTRUCTUREIdentifying Critical Infrastructure on a National ScaleThe identification and protection of critical infrastructure is key to minimising the potential impact of flooding, as highlighted by the Mythe pumping station in Tewksbury which flooded in July 2007 leaving some 150,000 homes without fresh water, and the dam at Ulley reservoir which if breached had the potential to flood thousands of homes.Using the Atlantis datasets to identify areas at risk of flooding on a national scale enables the identification of, and impact assessment on, the vulnerable critical infrastructure features within these high risk areas.For the successful implementation of such a project further information may be required from the utility companies responsible for the critical infrastructure features, such as capacity, who they serve and maintenance history.Further work is required to define exactly what these critical infrastructure features are. There is an element of uncertainty as to what constitutes a feature of critical infrastructure. Different scenarios will require the identification of different features and require different information about these features to properly locate and protect them.CONCLUSIONSWith the advent of new technologies more detailed and higher resolution data is increasingly available to help predict, prevent and mitigate the potential scale and impact of flooding. These datasets allow the identification of individual features impacted by potential flooding and their surrounding environment, enabling more accurate modelling and scenario planning and the potential for a more focused and efficient response.These new and developing datasets must be engineered to provide a consistent view of the built and natural environment with rapid access by key stakeholders when required.
Author: J. Brayshaw, J. Darvill, J. Simmons and K Murray
Bio.: ORDNANCE SURVEY
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