Compound Continental Risk of Multiple Extreme Floods in the United States

被引:2
作者
Najibi, Nasser [1 ]
Devineni, Naresh [2 ]
Lall, Upmanu [3 ]
机构
[1] Cornell Univ, Dept Biol & Environm Engn, Ithaca, NY 14850 USA
[2] CUNY City Coll, Dept Civil Engn, New York, NY 10031 USA
[3] Columbia Univ, Dept Earth & Environm Engn, Columbia Water Ctr, New York, NY USA
关键词
continental compound flood hazard; portfolio risk; extreme events; stochastic spatial simulator; ocean-atmosphere teleconnections; aggregate flood losses; SEA-SURFACE TEMPERATURE; SPATIAL DEPENDENCE; ENSO INFLUENCE; NORTH-AMERICA; CLIMATE; RIVER; VARIABILITY; PRECIPITATION; OSCILLATION; HAZARD;
D O I
10.1029/2023GL105297
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Understanding spatially correlated floods and modeling joint hazard associated with threshold exceedances across multiple locations is crucial for accurate estimation of continental-scale portfolio risk. This work uses a non-parametric copula-based spatial simulator to analyze peak floods across the United States to derive the first-of-its-kind continental portfolio risk estimates at the 10- and 100-year return levels. We find significant interdependence in floods across the nation, revealing the recurring pattern of extreme events affecting the Northeast, Central, West, and Northwest United States in the same year. The stochastic simulator effectively manages high-dimensional data and offers reliable uncertainty estimates for both spatially dependent floods and the aggregated flood losses at the continental level. El Nino-Southern Oscillation and Atlantic Multidecadal Oscillation are identified as statistically significant tele-connectors of aggregate loss. This research aims to advance the understanding of compound continental flood hazard and the potential large-scale climate teleconnections that lead to such compound floods. It is important to know why past floods occurred in different parts of the United States in the same year and how they were connected to each other. This knowledge helps determine how likely it is for major annual floods to occur all across the country in the future. Consequently, an understanding of what drives such total annual flood losses each year and their relation to climate conditions is of strategic importance. Large-scale climate patterns can influence where, how much, and how often it floods in a given year. The coincidence of many such events in a year across the country is an example of a compound flood hazard, whose aggregate loss is of interest. This study uses a stochastic model for simulating multiple floods across the United States while preserving information as to their co-occurrence. The model also calculates the likelihood of combined flood losses, along with its uncertainty. The key patterns in the ocean and the atmosphere that lead to these widespread losses are then identified. The broader impact of this study is to establish a foundation that any country or region can use to evaluate potential consequences of compound risk from joint extreme events. A non-parametric copula-based stochastic framework is forwarded to assess the risk of multiple peak floods across a regionPeak floods in the US exhibit significant co-occurrence of extreme events, leading to compound flood hazard with high aggregate lossesThe joint occurrence of extreme flood events across the country is a signature of large-scale climate teleconnections
引用
收藏
页数:14
相关论文
共 110 条
  • [31] Tropical Cyclone Compound Flood Hazard Assessment: From Investigating Drivers to Quantifying Extreme Water Levels
    Gori, Avantika
    Lin, Ning
    Xi, Dazhi
    [J]. EARTHS FUTURE, 2020, 8 (12)
  • [32] Assessing Compound Flooding From Landfalling Tropical Cyclones on the North Carolina Coast
    Gori, Avantika
    Lin, Ning
    Smith, James
    [J]. WATER RESOURCES RESEARCH, 2020, 56 (04)
  • [33] Hartigan JA., 1975, CLUSTERING ALGORITHM
  • [34] A conditional approach for multivariate extreme values
    Heffernan, JE
    Tawn, JA
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2004, 66 : 497 - 530
  • [35] Storm Surge Propagation and Flooding in Small Tidal Rivers during Events of Mixed Coastal and Fluvial Influence
    Herdman, Liv
    Erikson, Li
    Barnard, Patrick
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2018, 6 (04):
  • [36] Climate-driven variability in the occurrence of major floods across North America and Europe
    Hodgkins, Glenn A.
    Whitfield, Paul H.
    Burn, Donald H.
    Hannaford, Jamie
    Renard, Benjamin
    Stahl, Kerstin
    Fleig, Anne K.
    Madsen, Henrik
    Mediero, Luis
    Korhonen, Johanna
    Murphy, Conor
    Wilson, Donna
    [J]. JOURNAL OF HYDROLOGY, 2017, 552 : 704 - 717
  • [37] Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons
    Huang, Boyin
    Thorne, Peter W.
    Banzon, Viva F.
    Boyer, Tim
    Chepurin, Gennady
    Lawrimore, Jay H.
    Menne, Matthew J.
    Smith, Thomas M.
    Vose, Russell S.
    Zhang, Huai-Min
    [J]. JOURNAL OF CLIMATE, 2017, 30 (20) : 8179 - 8205
  • [38] Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model: Model development and its application to 2007 Cyclone Sidr in Bangladesh
    Ikeuchi, Hiroaki
    Hirabayashi, Yukiko
    Yamazaki, Dai
    Muis, Sanne
    Ward, Philip J.
    Winsemius, Hessel C.
    Verlaan, Martin
    Kanae, Shinjiro
    [J]. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2017, 9 (04) : 1847 - 1862
  • [39] Floods in a changing climate: Does the past represent the future?
    Jain, S
    Lall, U
    [J]. WATER RESOURCES RESEARCH, 2001, 37 (12) : 3193 - 3205
  • [40] Magnitude and timing of annual maximum floods: Trends and large-scale climatic associations for the Blacksmith Fork River, Utah
    Jain, S
    Lall, U
    [J]. WATER RESOURCES RESEARCH, 2000, 36 (12) : 3641 - 3651