Uncertainty Assessments of Flood Inundation Impacts: Using spatial climate change scenarios to drive ensembles of distributed models for extremes

Lead Research Organisation: King's College London
Department Name: Geography

Abstract

Exploratory climate change studies for the UK indicate that an increase in the frequency of extreme events and associated flood risk is likely. Given that floods cause damage of over £1bn per year under present climatic conditions, climate change bears significant consequences for flood risk management. In order to evaluate these consequences, hydrological and flood inundation models are forced with projections of precipitation from atmospheric models for a range of Greenhouse gas emission scenarios to produce future flood predictions. However the validity and uncertainty of these model-based input precipitation fields are of key concern, as they potentially constitute a major source of ambiguity for hydrological and hydraulic modelling. Additionally, uncertainty is associated with the hydrological and inundation models themselves, such as for example the models ability to represent the dominating physical processes and to uniquely identify effective model factors (parameters and any other model variables) that will shape future forecasts. As the non-linear interaction of all model components will influence the total uncertainty associated with hydrological impact assessments these need to be comprehensively assessed. Therefore, a key and exciting challenge is to describe and quantify the origin and propagation of uncertainty from climate to hydrological to flood inundation models. This project aims to develop a novel holistic modelling approach for doing this. Our region of focus will be the River Severn catchment because of concerns about current and future flood risk. Specifically we will: (1) Quantify the 'top-end' uncertainties associated with climate change hydrological impact assessments by analyzing precipitation fields produced by two contrasting methods and assess how these affect the nature of flood and inundation predictions (2) Evaluate all uncertainties between and within a cascade modeling framework for flood inundation predictions in a fully coupled and dynamic way (3) Use novel techniques of uncertainty analysis including global sensitivity analysis and a new efficient functional similarity sampling approach to enable an effective evaluation of the uncertainties in the modeling cascade. (4) Assess the likely flood hazard change for the River Severn catchment over the next 100 years for various climate, landuse and soil moisture scenarios This project will deliver an insightful scientific methodology which can be used in future research assessments and catapult UK science to the forefront of an exciting, socially, and politically important international research area.

Publications

10 25 50
 
Description A full assessment of the uncertainty in using RCM climate projections for use in flood impact modelling studies has been presented. Using these projections is not straightforward, as the spread in the uncertainty is very large and this is inflated through the modelling chain, leading to very uncertain flood projections.
The research also provided the first evidence of the potential for improvements in flood forecasting through using ensemble forecasting and decision making techniques. The research included the first setup of a coupled atmospheric-hydrologic-hydraulic model cascade system which used a grand ensemble of weather forecasts to produce probabilistic flood inundation forecasts. By tracking the uncertainty through the model cascade, the dominating influence of the uncertainties from the rainfall could be understood, and the promise of such a tool for forecasting flood inundation demonstrated.
Exploitation Route Operational flood forecasters can use these new techniques to improve forecast skill and make better decisions.
Methodologies for robustly understanding climate change impact on water resources including flooding and low flow at the catchment scale are of use to water resource modellers.
Sectors Environment

 
Description Since 2012 an operational EFAS now provides flood forecasting information two days or more before a flood event to the national authorities around Europe as well as the Emergency Response Coordination Centre of the European Commission. The skill of EFAS forecasts and warnings has been continuously improving (https://www.efas.eu/download/efasBulletins/2014/bulletin_dec-jan_14.pdf) and the system has demonstrated its early warning capabilities in several recent events (e.g. the Balkan floods in 2014 and the central European Floods in 2013), assisting with early flood preparedness for the ERCC, European national authorities and thus all European Citizens. Although citizen protection is of paramount importance in flood warning provision, floods are also harbingers of substantial damage costs, particularly in urban areas and although the exact cost-benefit ratio of EFAS flood warnings are currently being researched the system is very likely to have net economic value (Pappenberger et al, The Economic Value of Early Flood Warnings in Europe. Manuscript in Preparation.) The research provided scientific innovation, technical system developments and practical focus on enduser understanding which has contributed directly to these benefits, and costly and potentially contentious decisions are now made in a more consistent, risk-informed way. These knowledge transfer activities, supported by the strong scientific evidence from the research work and demonstrations of the value in systems such as EFAS, have led to a wider move in the UK (and beyond) towards ensemble flood forecasting. The Flood Forecasting Centre and the EA national forecasting centres have (or some cases very soon will have) implemented ensemble flood forecasting systems. Such an ensemble approach is likely to have improved the preparedness for the winter 2013/2014 flooding in the UK (Stephens & Cloke, 2014). In China, forecasts have been improved with the implementation of ensemble systems.
First Year Of Impact 2010
Sector Environment
Impact Types Societal,Economic,Policy & public services

 
Description Training in interpretation of Ensemble Flood Forecast products
Geographic Reach Asia 
Policy Influence Type Influenced training of practitioners or researchers
Impact Flood forecasters more confident to implement and use ensemble flood forecasts in their operational products
 
Description Applying probabilistic flood forecasting in Flood Incident Management.
Amount £200,000 (GBP)
Funding ID Science Project SC090032 
Organisation Environment Agency 
Sector Public
Country United Kingdom
Start 01/2009 
End 05/2011
 
Description DEFRA Catchment Modelling call
Amount £50,452 (GBP)
Organisation Department For Environment, Food And Rural Affairs (DEFRA) 
Sector Public
Country United Kingdom
Start 08/2014 
End 09/2015
 
Description Industrial CASE PhD: Uncertainty in future flood risk for insurance markets
Amount £78,000 (GBP)
Funding ID NE/H017836/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 09/2010 
End 08/2014
 
Description Interdisciplinary PhD studentship: Developing a Risk-Based and Participatory Approach to Reducing the Uncertainty in Modelling Climate Impact on Flood Inundation
Amount £78,000 (GBP)
Funding ID 1014118 
Organisation Economic and Social Research Council 
Sector Public
Country United Kingdom
Start 09/2010 
End 08/2015
 
Description Partnership Grant: Novel early flood warning system.
Amount £50,721 (GBP)
Organisation Queen Mary University of London 
Department Innovation China UK
Sector Private
Country United Kingdom
Start 01/2009 
End 12/2009
 
Title Ensemble Flood Forecasting 
Description A modelling methodology for representing uncertainty by implementing probabilistic ensembles in flood forecasts, particularly in the medium range. 
Type Of Material Computer model/algorithm 
Year Produced 2009 
Provided To Others? Yes  
Impact The method is now integrated into the European Flood Awareness System and has been emulated in other operational systems, including those int the UK. 
 
Description Environment Agency 
Organisation Environment Agency
Country United Kingdom 
Sector Public 
PI Contribution Working on understanding flood risk in flood susceptible catchments and improving flood forecasting.
Collaborator Contribution Provision of data, expertise, forecast systems. The context of the flood risk framework.
Impact EA/DEFRA technical report
Start Year 2007
 
Description European Flood Awareness System 
Organisation European Commission
Department European Flood Awareness System (EFAS)
Country European Union (EU) 
Sector Public 
PI Contribution Scientific innovation, technical system developments and practical focus on enduser understanding for the EFAS: e.g. The research provided the first evidence of the potential for improvements in flood forecasting through using ensemble forecasting and decision making techniques.
Collaborator Contribution Provision of expert advice, computing resources and expertise, data, methods, stakeholder network. Research secondments. Willingness to co-test new ideas within the operational system.
Impact The EFAS now provides flood forecasting information two days or more before a flood event to the national authorities around Europe as well as the Emergency Response Coordination Centre of the European Commission, and has been operational since 2012. The skill of EFAS forecasts and warnings has been continuously improving (https://www.efas.eu/download/efasBulletins/2014/bulletin_dec-jan_14.pdf) and the system has demonstrated its early warning capabilities in several recent events (e.g. the Balkan floods in 2014 and the central European Floods in 2013). This has provided an earlier flood preparedness, days earlier than conventional flood forecasting systems, and thus greatly improving flood preparedness for the ERCC, European national authorities and all European Citizens. Hannah's scientific innovation and technical system developments has provided an evidence base for implementing early warning from ensembles and contributed directly to the improved flood warning from EFAS. Hannah's work with social scientists on improving communication of EFAS flood alerts has allowed EFAS forecasters to change their practice both in the way alerts are given and the way that they engage with forecast recipients, allowing costly and potentially contentious decisions to be made in a more consistent, risk-informed way. In addition, the EFAS system with an estimated development cost over 10 years of 20 million Euros, is now estimated to provide net economic benefit.
 
Description Joint Research Centre 
Organisation European Commission
Department Joint Research Centre (JRC)
Country European Union (EU) 
Sector Public 
PI Contribution Working on using ensemble forecasts and uncertainty analysis in their operational modelling systems.
Collaborator Contribution Expertise, access to computers, research visits, access to data, models and stakeholders.
Impact Development of EFAS
 
Description Met Office 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Academic/University 
PI Contribution Improving flood forecasting, land surface hydrology for seasonal forecasting, interpretation of climate projections for water resource impacts
Collaborator Contribution Provision of data, expertise, models. Co-producing methods.
Impact Several research articles
Start Year 2007