Integrating historical storm surge events into flood risk security in the Copenhagen region

被引:0
作者
Su, Jian [1 ]
Poulsen, Bastian [2 ]
Nielsen, Jacob Woge [1 ]
Sorensen, Carlo Sass [2 ]
Larsen, Morten Andreas Dahl [1 ]
机构
[1] Danish Meteorol Inst, Sankt Kjelds Plads 11, DK-2100 Copenhagen, Denmark
[2] Danish Coastal Author, Hojbovej 1, DK-7620 Lemvig, Denmark
来源
WEATHER AND CLIMATE EXTREMES | 2024年 / 45卷
关键词
Storm surge; Flood risk; Climate engineering protection; Extreme value analysis; Historical information; Coastal defence; SEA-LEVEL RISE; CLIMATE-CHANGE IMPACTS; FREQUENCY-ANALYSIS; WATER LEVELS; EXTREME SEA; SCALE; INFORMATION; DECISIONS;
D O I
10.1016/j.wace.2024.100713
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Rapid urbanisation along the coasts of the world in recent decades has increased their vulnerability to storm surges, especially in response to mean sea level rise. The unique geographical and social conditions of Copenhagen, a major European coastal city, have prompted urban expansion along K & oslash;ge Bay to the south of the city. However, this new urbanisation area is confronted with the common obstacle of developing a coastal defence strategy, i.e., the lack of long-term observational data required to determine a reliable storm surge protection level. This study aims to address this issue by developing a framework that integrates historical records of extreme storm surge events into coastal defence strategies, using Copenhagen as a case study. We propose a four-step work framework, including (1) Data collection and analysis: We collected and analysed data from neighbouring cities and used modelling and reanalysis data sets. By combining these sources, we aim to reconstruct historical time series for the study site dating back to 1836. This extended information set enhances our understanding of past storm surge events. (2) Statistical modelling and forecasting: Using Bayesian statistical methods, we fitted the historical storm surge data to appropriate probability distributions. This enabled us to generate probabilistic forecasts of storm surge magnitudes, providing insight into the likelihood of future events and their potential impacts on the coastal area. (3) Sensitivity analyses: We performed sensitivity experiments using Markov chain Monte Carlo (MCMC) methods to identify the most influential parameters, such as thresholds, that affect storm surge levels. This analysis improved our understanding of the key drivers of storm surge events and their uncertainties, further informing coastal defence strategies. (4) Expert judgement and risk management: Expert judgements are implemented to establish the necessary security level to manage flood risks in the city. This helps to ensure that high-impact, low-probability events are adequately considered in risk management efforts. Following this framework, we can develop a comprehensive understanding of storm surge risks in the urbanised region south of Copenhagen and use historical data to inform coastal defence strategies. This study emphasises the importance of incorporating long-term observational data and expert insights to improve the resilience of coastal cities facing the challenges of urbanisation and climate change.
引用
收藏
页数:15
相关论文
共 83 条
  • [1] The role of preconditioning for extreme storm surges in the western Baltic Sea
    Andree, Elin
    Su, Jian
    Dahl Larsen, Morten Andreas
    Drews, Martin
    Stendel, Martin
    Skovgaard Madsen, Kristine
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2023, 23 (05) : 1817 - 1834
  • [2] Simulating wind-driven extreme sea levels: Sensitivity to wind speed and direction
    Andree, Elin
    Drews, Martin
    Su, Jian
    Larsen, Morten Andreas Dahl
    Dronen, Nils
    Madsen, Kristine Skovgaard
    [J]. WEATHER AND CLIMATE EXTREMES, 2022, 36
  • [3] Simulating major storm surge events in a complex coastal region
    Andree, Elin
    Su, Jian
    Larsen, Morten Andreas Dahl
    Madsen, Kristine Skovgaard
    Drews, Martin
    [J]. OCEAN MODELLING, 2021, 162
  • [4] [Anonymous], 2001, INTRO STAT MODELING, DOI [DOI 10.1007/978-1-4471-3675-0, 10.1007/978-1-4471-3675-0]
  • [5] [Anonymous], 2014, Climate Change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of IPCC the intergovernmental panel on climate change, DOI DOI 10.1017/CBO9781107415324
  • [6] Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practise
    Arns, A.
    Wahl, T.
    Haigh, I. D.
    Jensen, J.
    Pattiaratchi, C.
    [J]. COASTAL ENGINEERING, 2013, 81 : 51 - 66
  • [7] Tide-surge historical assessment of extreme water levels for the St. Johns River: 1928-2017
    Bacopoulos, Peter
    [J]. JOURNAL OF HYDROLOGY, 2017, 553 : 624 - 636
  • [8] Ice sheet contributions to future sea-level rise from structured expert judgment
    Bamber, Jonathan L.
    Oppenheimer, Michael
    Kopp, Robert E.
    Aspinall, Willy P.
    Cooke, Roger M.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2019, 116 (23) : 11195 - 11200
  • [9] Benito G, 2004, NAT HAZARDS, V31, P623
  • [10] Berg P., 2012, Technical Report 12-11