Coastal flood risk in Europe and the socio-economic impacts in a changing climate

Project Information

CRISIS

Grant agreement ID: 658025

DOI

10.3030/658025

Project terminated on 7 February 2017

EC signature date 3 March 2015

Start date 1 March 2016

End date 28 February 2018

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 195 454,80

EU contribution

€ 195 454,80

Coordinated by

UNIVERSITY OF SOUTHAMPTON
United Kingdom

Periodic Reporting for period 1 - CRISIS (Coastal flood risk in Europe and the socio-economic impacts in a changing climate)

Reporting period: 2016-03-01 to 2018-02-28

Summary of the context and overall objectives of the project

A large portion of the coastal population worldwide, including Europe, is already vulnerable to extreme high sea level events. In the future it is expected that climate change will increase coastal flood risk making costly adaptation (e.g. raising dikes and barriers, such as the Thames Barrier and Delta Works) inevitable. In order to help develop robust and flexible coastal management strategies, decision makers need to explore how, when, and where future changes in the physical environment will require immediate action. This is aggravated by the existence of large uncertainties in climate projections. Impact assessment models, such as the Dynamic Interactive Vulnerability Assessment (DIVA) model, have been used extensively to assess the socio-economic impacts associated with coastal flooding under climate change and to explore the benefits of mitigation, adaptation, and migration. However, because the DIVA model is applied at broad scales, it is based on a number of significant assumptions. Most notably, present-day return water levels (one of the key forcing parameters in the model) were derived using a simple global approach. In the future, one of the main consequences of mean sea level rise (MSLR) on human settlements and infrastructure will be an increase in the intensity and frequency of extreme sea levels (ESL). Hence, robust information on both MSLR and ESL is necessary for assessing impacts of and adaptation to MSLR. While substantial research efforts are directed towards quantifying projections and uncertainties of future global MSLR, corresponding uncertainties in ESL have not been assessed and projections are limited.
Our results (see below for more details) highlight that uncertainties in present-day ESL are at least as important as uncertainties in future MSLR projections and both types of uncertainties need to be understood and combined to fully assess potential impacts and adaptation needs. Including our new estimates of ESL into broad-scale integrated impact assessment modelling frameworks will improve the overall results and facilitate better informed decisions.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

We quantified, for the first time at global scale, the uncertainties in present-day ESL estimates, which have by default been ignored in broad-scale sea-level rise impact assessments to date. A recently developed database of historical tide gauge observations (GESLA2, http://www.gesla.org/) was used to explore uncertainties in extreme sea level estimates owing to the subjective selection of certain extreme value models. Given the global nature of the database this part of the analysis was also carried out at the global scale. In total we used 20 different extreme value models comprising different sampling techniques to identify extremes and a range of parametric distributions to quantify inter-model uncertainties. The latter can be compared to inter-model uncertainties in future mean sea level projections published by the Intergovernmental Panel on Climate Change (IPCC) in its Fifth Assessment report (AR5). Based on the results, recommendations were provided which model to use and how to analyze extreme sea levels for broad-scale coastal impact and adaptation analyses, namely the Generalized Pareto distribution (GPD) along with high sea level events that exceed the 99% percentile threshold.
We showed that ESL uncertainties exceed those from global MSLR projections and, assuming that we meet the Paris agreement goals, the projected MSLR itself by the end of the century, in particular in high risk regions such as Europe, the U.S. and Southeast Asia. For Europe, as an example, we also compared the uncertainties in present-day ESL estimates to projections of future changes in the storm surge climate under various greenhouse gas emission scenarios. The former were an order of magnitude larger than the projected future changes.
Also for the European coastline, the results from the global tide gauge analysis were used and integrated with an analysis of storm surge water levels that were derived with hydrodynamic numerical models for the entire coast, every few kilometers (not just at the tide gauge locations). As a result, we obtained maps of robust and spatially coherent return water level estimates for the entire coast. Adjustments have been made to the DIVA model source code in order to allow the inclusion of this three-parametric distribution in addition to the simplistic two-parametric Gumbel distribution that was applied in previous assessments. The new model setup will next be used to explore how the improved representation of storm surges affects estimates of present-day and future flood risk and associated adaptation costs.
Another shortcoming in all broad-scale coastal impact models is the omission of what we refer to as “compound flooding”. The latter occurs when freshwater from rivers or rainfall run-off cannot drain as it would usually do because of elevated sea levels due to a storm surge. So far, it has been widely assumed that extreme rainfall (and resulting river discharge) and storm surges are independent processes that only coincide by chance. Recent research has shown, however, that significant correlation exists between the two at many coastline stretches. Including these high impact events into flood risk management and disaster mitigation is essential and has been identified as a priority within the World Climate Research Program’s Grand Challenge on Extremes. Given the innovative nature of the topic and missing guidelines how to incorporate compound events into broad-scale impact models we developed a commentary paper to benchmark current knowledge.
The topics addressed in the project and results obtained have been, and will continue to be, promoted and disseminated in multiple ways. As of now 6 journal papers have been published or are under review, 9 abstracts and presentations have been contributed to national and international conferences and workshop, 4 conferences and conference sessions have been and will be organized, several media articles have been published (http://www.nature.com/articles/sdata2016107/metrics) and a website has been created where results will be published in the future (after acceptance of journal papers; https://thomaswahl.org/crisis/).

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Our work and the results produced during the project will improve the representation of storm surges in broad-scale impact models. The new maps of return water levels have already been implemented into the DIVA data base and the model code has been revised to include more advanced extreme value distributions to model extreme sea levels. The focus was on the European coast, but collaborations with international partners have been established and will continue to facilitate similar improvements for global scale assessments.
A community effort to tackle the complex issue of compound extremes, with a focus on hydrologic events, has been initiated and will continue into the future. Results will feed into the WCRP Grand Challenge on Extremes and are expected to lead to revisions in current risk assessment methodologies and disaster management plans.

Combined uncertainties in extreme sea level estimates and future mean sea level rise projections.