76 citations as recorded by crossref.

1. Spatial Footprints of Storm Surges Along the Global Coastlines A. Enríquez et al. https://doi.org/10.1029/2020JC016367
2. A global classification of coastal flood hazard climates associated with large-scale oceanographic forcing A. Rueda et al. https://doi.org/10.1038/s41598-017-05090-w
3. Probabilistic modelling of extreme storms along the Dutch coast F. Li et al. https://doi.org/10.1016/j.coastaleng.2013.12.009
4. Climate‐Based Emulator of Distant Swell Trains and Local Seas Approaching a Pacific Atoll L. Cagigal et al. https://doi.org/10.1029/2020JC016919
5. Swell wave progression in the English Channel: implications for coastal monitoring T. Dhoop & C. Thompson https://doi.org/10.1139/anc-2021-0008
6. Correlation of wind waves and sea level variations on the coast of the seasonally ice-covered Gulf of Finland M. Johansson et al. https://doi.org/10.5194/nhess-22-813-2022
7. Estimating Joint Probabilities for Confluences across CONUS Using Copula A. Ghanghas et al. https://doi.org/10.1061/JHYEFF.HEENG-6284
8. Nonstationary joint probability analysis of extreme marine variables to assess design water levels at the shoreline in a changing climate P. Galiatsatou et al. https://doi.org/10.1007/s11069-019-03645-w
9. Modeling of Future Extreme Storm Surges at the NW Mediterranean Coast (Spain) J. Lin-Ye et al. https://doi.org/10.3390/w12020472
10. A multivariate, stochastic, climate-based wave emulator for shoreline change modelling L. Cagigal et al. https://doi.org/10.1016/j.ocemod.2020.101695
11. Co-occurrence probability of typhoon surges affecting multiple estuaries in the northern coastal region of Taiwan J. Zhai et al. https://doi.org/10.1016/j.rsma.2020.101582
12. Predicting coastal hazards for sandy coasts with a Bayesian Network L. Poelhekke et al. https://doi.org/10.1016/j.coastaleng.2016.08.011
13. Mapping Dependence between Extreme Skew-Surge, Rainfall, and River-Flow S. Stephens & W. Wu https://doi.org/10.3390/jmse10121818
14. Pan-European hydrodynamic models and their ability to identify compound floods D. Paprotny et al. https://doi.org/10.1007/s11069-020-03902-3
15. Effective IoT-Facilitated Storm Surge Flood Modeling Based on Deep Reinforcement Learning Y. Wang et al. https://doi.org/10.1109/JIOT.2020.2969959
16. An Extended Flood Characteristic Simulation Considering Natural Dependency Structures M. Öttl et al. https://doi.org/10.3390/hydrology10120233
17. Coastal flooding: A copula based approach for estimating the joint probability of water levels and waves M. Masina et al. https://doi.org/10.1016/j.coastaleng.2014.12.010
18. Spatial Assessment of Climate Risk for Investigating Climate Adaptation Strategies by Evaluating Spatial-Temporal Variability of Extreme Precipitation B. Jhong et al. https://doi.org/10.1007/s11269-019-02306-8
19. Heat wave Intensity Duration Frequency Curve: A Multivariate Approach for Hazard and Attribution Analysis O. Mazdiyasni et al. https://doi.org/10.1038/s41598-019-50643-w
20. XtremRisK — Integrated Flood Risk Analysis for Extreme Storm Surges at Open Coasts and in Estuaries: Methodology, Key Results and Lessons Learned H. Oumeraci et al. https://doi.org/10.1142/S057856341540001X
21. Assessment and comparison of extreme sea levels and waves during the 2013/14 storm season in two UK coastal regions M. Wadey et al. https://doi.org/10.5194/nhess-15-2209-2015
22. A multivariate design framework for river confluences J. Bender et al. https://doi.org/10.1080/02626667.2015.1052816
23. Coupling infrastructure resilience and flood risk assessment via copulas analyses for a coastal green-grey-blue drainage system under extreme weather events J. Joyce et al. https://doi.org/10.1016/j.envsoft.2017.11.008
24. A Bayesian network approach for coastal risk analysis and decision making W. Jäger et al. https://doi.org/10.1016/j.coastaleng.2017.05.004
25. Integrating a multivariate extreme value method within a system flood risk analysis model D. Wyncoll & B. Gouldby https://doi.org/10.1111/jfr3.12069
26. Coastal Flooding Caused by Extreme Coastal Water Level at the World Heritage Historic Keta City (Ghana, West Africa) E. Brempong et al. https://doi.org/10.3390/jmse11061144
27. An event-based approach for extreme joint probabilities of waves and sea levels F. Mazas & L. Hamm https://doi.org/10.1016/j.coastaleng.2017.02.003
28. Probabilistic assessment of port operation downtimes under climate change P. Camus et al. https://doi.org/10.1016/j.coastaleng.2019.01.007
29. A multivariate extreme wave and storm surge climate emulator based on weather patterns A. Rueda et al. https://doi.org/10.1016/j.ocemod.2016.06.008
30. Sea‐level rise impacts on the temporal and spatial variability of extreme water levels: A case study for St. Peter‐Ording, Germany S. Santamaria‐Aguilar et al. https://doi.org/10.1002/2016JC012579
31. Statistical Assessment of Storm Surge Scenarios Within Integrated Risk Analyses T. Wahl et al. https://doi.org/10.1142/S0578563415400033
32. Combining probability distributions of sea level variations and wave run-up to evaluate coastal flooding risks U. Leijala et al. https://doi.org/10.5194/nhess-18-2785-2018
33. An extreme value model for maximum wave heights based on weather types A. Rueda et al. https://doi.org/10.1002/2015JC010952
34. Combining Surge and Wind Risk from Hurricanes Using a Copula Model: An Example from Galveston, Texas J. Trepanier et al. https://doi.org/10.1080/00330124.2013.866437
35. Stochastic modeling of long-term wave climate based on weather patterns for coastal structures applications D. Lucio et al. https://doi.org/10.1016/j.coastaleng.2020.103771
36. Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico T. Wahl et al. https://doi.org/10.1002/2015JC011482
37. Joint probability analysis of storm surges and waves caused by tropical cyclones for the estimation of protection standard: a case study on the eastern coast of the Leizhou Peninsula and the island of Hainan in China Z. Haixia et al. https://doi.org/10.5194/nhess-23-2697-2023
38. Copula-based joint impact assessment of rainfall and tidal level on flood risk in tidal-influenced plain river network areas, Taihu Lake Basin H. Zhou et al. https://doi.org/10.1016/j.jhydrol.2025.132785
39. Extreme Statistics of Storm Surges in the Baltic Sea E. Kulikov & I. Medvedev https://doi.org/10.1134/S0001437017060078
40. The performance of the copulas in estimating the joint probability of extreme waves and surges along east coasts of the mainland China J. Li et al. https://doi.org/10.1016/j.oceaneng.2021.109581
41. Joint probability analysis of extreme wave heights and surges along China's coasts Y. Chen et al. https://doi.org/10.1016/j.oceaneng.2018.12.010
42. Applying a Bayesian network based on Gaussian copulas to model the hydraulic boundary conditions for hurricane flood risk analysis in a coastal watershed A. Sebastian et al. https://doi.org/10.1016/j.coastaleng.2017.03.008
43. Enabling dynamic modelling of coastal flooding by defining storm tide hydrographs J. Dullaart et al. https://doi.org/10.5194/nhess-23-1847-2023
44. Projecting compound wave and sea-level events at a coastal structure site under climate change D. Lucio et al. https://doi.org/10.1016/j.coastaleng.2024.104490
45. Influence of storm type on compound flood drivers of a mid-latitude coastal urban environment Z. Chen et al. https://doi.org/10.5194/hess-29-3101-2025
46. Compounding Effects of Fluvial Flooding and Storm Tides on Coastal Flooding Risk in the Coastal-Estuarine Region of Southeastern China W. Lu et al. https://doi.org/10.3390/atmos13020238
47. Probability Analysis and Control of River Runoff–sediment Characteristics based on Pair-Copula Functions: The Case of the Weihe River and Jinghe River Q. You et al. https://doi.org/10.3390/w11030510
48. A Copula-Based Simulation of Wave-Induced Pore Water Pressure Gradient and Local Acceleration Within Surf Zone for Natural and Laboratory Barred Beach Profiles M. Tabasi et al. https://doi.org/10.3389/fbuil.2022.816020
49. Assessing storm surge compound disasters risk: A case study of the coastal area of Qingdao S. Tian et al. https://doi.org/10.1016/j.ocecoaman.2025.107593
50. The Importance of Marine Research Infrastructures in Capturing Processes and Impacts of Extreme Events N. Lo Bue et al. https://doi.org/10.3389/fmars.2021.626668
51. Increased Extreme Coastal Water Levels Due to the Combined Action of Storm Surges and Wind Waves M. Marcos et al. https://doi.org/10.1029/2019GL082599
52. Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential D. Anderson et al. https://doi.org/10.1029/2019JC015312
53. Combined effects of climatic factors on extreme sea level changes in the Northwest Pacific Ocean L. Fan & L. Du https://doi.org/10.1007/s10236-023-01543-1
54. The impact of climate change on the storm surges of the Mediterranean Sea: Coastal sea level responses to deep depression atmospheric systems C. Makris et al. https://doi.org/10.1016/j.ocemod.2022.102149
55. Coastal flooding in the Maldives: an assessment of historic events and their implications M. Wadey et al. https://doi.org/10.1007/s11069-017-2957-5
56. Characterizing multivariate coastal flooding events in a semi-arid region: the implications of copula choice, sampling, and infrastructure J. Lucey & T. Gallien https://doi.org/10.5194/nhess-22-2145-2022
57. Generating Boundary Conditions for Compound Flood Modeling in a Probabilistic Framework P. Maduwantha et al. https://doi.org/10.5194/hess-30-401-2026
58. Assessing Flood Risk Under Sea Level Rise and Extreme Sea Levels Scenarios: Application to the Ebro Delta (Spain) J. Sayol & M. Marcos https://doi.org/10.1002/2017JC013355
59. Deriving the 100-Year Total Water Level around the Coast of Corsica by Combining Trivariate Extreme Value Analysis and Coastal Hydrodynamic Models J. Louisor et al. https://doi.org/10.3390/jmse9121347
60. Multivariate joint distribution of five-dimensional wind and wave parameters in the sea-crossing bridge region using Hierarchical Archimedean Copulas Y. Yang et al. https://doi.org/10.1016/j.jweia.2024.105684
61. River Levee Overtopping: A Bivariate Methodology for Hydrological Characterization of Overtopping Failure M. Isola et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001929
62. A Vine-Copula Model for Time Series of Significant Wave Heights and Mean Zero-Crossing Periods in the North Sea W. Jäger & O. Nápoles https://doi.org/10.1061/AJRUA6.0000917
63. Estimating storm surge intensity with Poisson bivariate maximum entropy distributions based on copulas S. Tao et al. https://doi.org/10.1007/s11069-013-0654-6
64. Risk-driven statistical modeling for hurricane-induced compound events: Design event implementation for industrial areas subjected to coastal floods and winds M. Lan et al. https://doi.org/10.1016/j.oceaneng.2022.111159
65. Optimization of Bathymetry Estimates for Nearshore Hydrodynamic Models Using Bayesian Methods S. Ardani & J. Kaihatu https://doi.org/10.1061/(ASCE)WW.1943-5460.0000472
66. Assessment of the joint impact of extreme rainfall and storm surge on the risk of flooding in a coastal area B. Zellou & H. Rahali https://doi.org/10.1016/j.jhydrol.2018.12.028
67. Temperature magnitude duration frequency curves to unravel temperature extremes incorporating climate change across India A. Rahman & S. Pekkat https://doi.org/10.1016/j.uclim.2025.102494
68. Multivariate Hybrid Modelling of Future Wave-Storms at the Northwestern Black Sea J. Lin-Ye et al. https://doi.org/10.3390/w10020221
69. A joint probability approach using a 1-D hydrodynamic model for estimating high water level frequencies in the Lower Rhine Delta H. Zhong et al. https://doi.org/10.5194/nhess-13-1841-2013
70. A multivariate statistical model of extreme events: An application to the Catalan coast J. Lin-Ye et al. https://doi.org/10.1016/j.coastaleng.2016.08.002
71. Multivariate design in the presence of non-stationarity J. Bender et al. https://doi.org/10.1016/j.jhydrol.2014.04.017
72. Probabilistic assessment of climate-related impacts and risks in ports D. Lucio et al. https://doi.org/10.1016/j.ress.2024.110333
73. Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge H. Wang et al. https://doi.org/10.1016/j.coastaleng.2023.104330
74. Quantifying compound flood event uncertainties in a wave and tidally dominated coastal region: The impacts of copula selection, sampling, record length, and precipitation gauge selection J. Lucey & T. Gallien https://doi.org/10.1111/jfr3.12984
75. A methodology for deriving extreme nearshore sea conditions for structural design and flood risk analysis B. Gouldby et al. https://doi.org/10.1016/j.coastaleng.2014.01.012
76. Statistical modelling of extreme storms using copulas: A comparison study F. Li et al. https://doi.org/10.1016/j.coastaleng.2018.09.007