235 citations as recorded by crossref.

1. Estimating the probability of compound floods in estuarine regions W. Wu et al. 10.5194/hess-25-2821-2021
2. Quantifying multidimensional drought propagation risks under climate change: A vine-copula Bayesian factorial analysis method H. Wang et al. 10.1016/j.jhydrol.2024.131396
3. Assessing compound flooding potential with multivariate statistical models in a complex estuarine system under data constraints V. Santos et al. 10.1111/jfr3.12749
4. Coupling Bayesian Network and copula theory for water shortage assessment: A case study in source area of the South-to-North Water Division Project (SNWDP) X. Zha et al. 10.1016/j.jhydrol.2023.129434
5. A new risk probability calculation method for urban ecological risk assessment C. Liu et al. 10.1088/1748-9326/ab6667
6. More meteorological events that drive compound coastal flooding are projected under climate change E. Bevacqua et al. 10.1038/s43247-020-00044-z
7. Spatial-temporal correlation-based analysis of multi-source flood coincidence risks: A case study of the middle and lower Yangtze River basin G. Zhao et al. 10.1016/j.ejrh.2025.102265
8. Flood Risk Evaluation in Ungauged Coastal Areas: The Case Study of Ippocampo (Southern Italy) C. Apollonio et al. 10.3390/w12051466
9. Analyzing solar radiation characteristics using copula and solar power potential in Peninsular Malaysia Z. Yet et al. 10.1007/s12517-022-10878-w
10. Compound Temperature and Precipitation Events in the Czech Republic: Differences of Stratiform versus Convective Precipitation in Station and Reanalysis Data Z. Rulfová et al. 10.3390/atmos12010087
11. A Water Shortage Risk Assessment Model Based on Kernel Density Estimation and Copulas T. Qian et al. 10.3390/w16111465
12. Study on multiscale-multivariate prediction and risk assessment of urban flood Y. Wang et al. 10.1016/j.envsoft.2024.105958
13. Probabilistic Assessment of Global Drought Recovery and Its Response to Precipitation Changes L. Zhang et al. 10.1029/2023GL106067
14. Multivariate Bayesian hierarchical Gaussian copula modeling of the non-stationary traffic conflict extremes for crash estimation C. Fu & T. Sayed 10.1016/j.amar.2020.100154
15. Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts Z. Hao et al. 10.1016/j.earscirev.2022.104241
16. Compound successive dry-hot and wet extremes in China with global warming and urbanization K. He et al. 10.1016/j.jhydrol.2024.131332
17. Sea Level Rise in Europe: Impacts and consequences R. van de Wal et al. 10.5194/sp-3-slre1-5-2024
18. Impact assessment of climate change on compound flooding in a coastal city K. Xu et al. 10.1016/j.jhydrol.2023.129166
19. Compound wind and rainfall extremes: Drivers and future changes over the UK and Ireland C. Manning et al. 10.1016/j.wace.2024.100673
20. Bayesian vine copulas improve agricultural drought prediction for long lead times H. Wu et al. 10.1016/j.agrformet.2023.109326
21. Multivariate statistical modelling of the drivers of compound flood events in south Florida R. Jane et al. 10.5194/nhess-20-2681-2020
22. Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai H. Xu et al. 10.5194/nhess-22-2347-2022
23. Importance of Copula-Based Bivariate Rainfall Intensity-Duration-Frequency Curves for an Urbanized Catchment Incorporating Climate Change A. Suresh & S. Pekkat 10.1061/JHYEFF.HEENG-5577
24. Analyzing the conditional behavior of rainfall deficiency and groundwater level deficiency signatures by using copula functions M. Tahroudi et al. 10.2166/nh.2020.036
25. Larger Spatial Footprint of Wintertime Total Precipitation Extremes in a Warmer Climate E. Bevacqua et al. 10.1029/2020GL091990
26. Precipitation trends determine future occurrences of compound hot–dry events E. Bevacqua et al. 10.1038/s41558-022-01309-5
27. Flood management challenges in transitional environments: Assessing the effects of sea-level rise on compound flooding in the 21st century J. Del-Rosal-Salido et al. 10.1016/j.coastaleng.2021.103872
28. Perspective on uncertainty quantification and reduction in compound flood modeling and forecasting P. Abbaszadeh et al. 10.1016/j.isci.2022.105201
29. History, causes, and trend of floods in the U.S.: a review R. Abegaz et al. 10.1007/s11069-024-06791-y
30. Assessing the compound flood risk in coastal areas: Framework formulation and demonstration M. Mitu et al. 10.1016/j.jhydrol.2023.130278
31. Future climate risk from compound events J. Zscheischler et al. 10.1038/s41558-018-0156-3
32. A monitoring and prediction system for compound dry and hot events Z. Hao et al. 10.1088/1748-9326/ab4df5
33. Changes in compound extremes of rainfall and temperature over West Africa using CMIP5 simulations I. Diba et al. 10.1088/2515-7620/ac9aa7
34. Assessing the Effects of Climate Change on Compound Flooding in Coastal River Areas M. Bermúdez et al. 10.1029/2020WR029321
35. Vine copula statistical disclosure control for mixed-type data A. Chu et al. 10.1016/j.csda.2022.107561
36. Compound flood hazard at Lake Como, Italy, is driven by temporal clustering of rainfall events F. Banfi & C. De Michele 10.1038/s43247-022-00557-9
37. Multivariate Analysis of Compound Flood Hazard Across Canada's Atlantic, Pacific and Great Lakes Coastal Areas F. Jalili Pirani & M. Najafi 10.1029/2022EF002655
38. Storm Surge and Extreme River Discharge: A Compound Event Analysis Using Ensemble Impact Modeling S. Khanal et al. 10.3389/feart.2019.00224
39. Conditional probability modeling of intensity measures for offshore mainshock-aftershock sequences X. Bai et al. 10.1016/j.soildyn.2022.107408
40. Separating the attributions of anthropogenic activities and climate change to streamflow and multivariate dependence analysis A. Askari et al. 10.1007/s11600-024-01479-0
41. Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation W. Wang et al. 10.1016/j.wse.2023.05.004
42. Probabilistic Projections of Multidimensional Flood Risks at a Convection‐Permitting Scale B. Zhang et al. 10.1029/2020WR028582
43. Modeling the spatial dependence of floods using the Fisher copula M. Brunner et al. 10.5194/hess-23-107-2019
44. Impact of ENSO on dependence between extreme rainfall and storm surge W. Wu & M. Leonard 10.1088/1748-9326/ab59c2
45. What's streamflow got to do with it? A probabilistic simulation of the competing oceanographic and fluvial processes driving extreme along-river water levels K. Serafin et al. 10.5194/nhess-19-1415-2019
46. Compound effects in complex estuary-ocean interaction region under various combination patterns of storm surge and fluvial floods Z. Wang et al. 10.1016/j.uclim.2024.102186
47. Investigating compound flooding in a low elevation coastal karst environment using multivariate statistical and 2D hydrodynamic modeling F. Peña et al. 10.1016/j.wace.2022.100534
48. Satellite features of river plumes over the Lobos–Tuxpan reef system J. de Jesús Salas Pérez et al. 10.1007/s10872-023-00680-x
49. Trivariate Probabilistic Assessments of the Compound Flooding Events Using the 3-D Fully Nested Archimedean (FNA) Copula in the Semiparametric Distribution Setting S. Latif & S. Simonovic 10.1007/s11269-023-03448-6
50. Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA) L. Terlinden-Ruhl et al. 10.5194/nhess-25-1353-2025
51. Multi-hazard dependencies can increase or decrease risk J. Hillier et al. 10.1038/s41558-020-0832-y
52. Image-based 3D characterization and reconstruction of heterogeneous battery electrode microstructure V. Nagda et al. 10.1016/j.commatsci.2023.112139
53. Risk of crop failure due to compound dry and hot extremes estimated with nested copulas A. Ribeiro et al. 10.5194/bg-17-4815-2020
54. Time-frequency spillover and early warning of climate risk in international energy markets and carbon markets: From the perspective of complex network and machine learning C. Xu et al. 10.1016/j.energy.2025.134857
55. Coastal Vulnerability Assessment of Thrace Peninsula: Implications for Climate Change and Sea Level Rise E. Ozsahin et al. 10.3390/rs15235592
56. Dependence structure analysis of multisite river inflow data using vine copula-CEEMDAN based hybrid model H. Nazir et al. 10.7717/peerj.10285
57. Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management T. Nguyen-Huy et al. 10.1016/j.wace.2018.07.002
58. Comparison between canonical vine copulas and a meta-Gaussian model for forecasting agricultural drought over China H. Wu et al. 10.5194/hess-26-3847-2022
59. Weather warning archives reveal spatio-temporal hot spots of compound natural hazards W. Yang et al. 10.1038/s41598-025-96842-6
60. A Vine Copula‐Based Ensemble Projection of Precipitation Intensity–Duration–Frequency Curves at Sub‐Daily to Multi‐Day Time Scales B. Zhang et al. 10.1029/2022WR032658
61. VineCopulas: an open-source Python package for vine copula modelling J. Claassen et al. 10.21105/joss.06728
62. Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards R. Villalobos-Herrera et al. 10.5194/nhess-21-1867-2021
63. 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. 10.1016/j.oceaneng.2022.111159
64. Recent Trends in Individual and Multivariate Compound Flood Drivers in Canada's Coasts F. Jalili Pirani & M. Najafi 10.1029/2020WR027785
65. Time of emergence of compound events: contribution of univariate and dependence properties B. François & M. Vrac 10.5194/nhess-23-21-2023
66. Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. 10.1002/wat2.1520
67. Predicting Hydrological Drought With Bayesian Model Averaging Ensemble Vine Copula (BMAViC) Model H. Wu et al. 10.1029/2022WR033146
68. Modeling compound flood risk and risk reduction using a globally applicable framework: a pilot in the Sofala province of Mozambique D. Eilander et al. 10.5194/nhess-23-2251-2023
69. Probabilistic Characterization of Extreme Storm Surges Induced by Tropical Cyclones B. Zhang & S. Wang 10.1029/2020JD033557
70. Characterization and impact of fiber size variability on the mechanical properties of fiber networks with an application to paper materials A. Brandberg et al. 10.1016/j.ijsolstr.2022.111438
71. Climate change effects on hydrometeorological compound events over southern Norway B. Poschlod et al. 10.1016/j.wace.2020.100253
72. Focused information criteria for copulas V. Ko et al. 10.1111/sjos.12387
73. Compound Events under Global Warming: A Dependence Perspective Z. Hao & V. Singh 10.1061/(ASCE)HE.1943-5584.0001991
74. Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns P. Camus et al. 10.5194/nhess-21-2021-2021
75. Flood risk analysis and mapping under compound hazards: A copula approach for tropical coastal district of Alappuzha, India S. Binoy et al. 10.1016/j.jher.2022.11.004
76. Estimating the grade of storm surge disaster loss in coastal areas of China via machine learning algorithms S. Zhang et al. 10.1016/j.ecolind.2022.108533
77. A Vine Copula‐Based Polynomial Chaos Framework for Improving Multi‐Model Hydroclimatic Projections at a Multi‐Decadal Convection‐Permitting Scale B. Zhang et al. 10.1029/2022WR031954
78. Projected changes in the frequency of compound hot and dry events over Tropical Brazil in CORDEX-CORE simulations L. Alves et al. 10.1007/s00382-024-07446-1
79. Integrating broad and deep multiple-stressor research: A framework for translating across scales and disciplines A. Santos et al. 10.1016/j.oneear.2024.09.006
80. Compound hazard mapping for tropical cyclone-induced concurrent wind and rainfall extremes over India R. Ranjan & S. Karmakar 10.1038/s44304-024-00013-y
81. Association of climate variability modes with concurrent droughts and heatwaves in India R. Tabbussum et al. 10.1016/j.hydroa.2024.100196
82. Stability of spatial dependence structure of extreme precipitation and the concurrent risk over a nested basin Z. Liu et al. 10.1016/j.jhydrol.2021.126766
83. Applying non-parametric Bayesian networks to estimate maximum daily river discharge: potential and challenges E. Ragno et al. 10.5194/hess-26-1695-2022
84. Disentangling increasing compound extremes at regional scale during Indian summer monsoon R. Guntu & A. Agarwal 10.1038/s41598-021-95775-0
85. Future multivariate weather generation by combining Bartlett-Lewis and vine copula models J. Van de Velde et al. 10.1080/02626667.2022.2144322
86. Synoptic and Dynamical Characteristics of High-Impact Storms Affecting the Iberian Peninsula during the 2018–2021 Extended Winters A. Gonçalves et al. 10.3390/atmos14091353
87. Drought, Heat, and the Carbon Cycle: a Review S. Sippel et al. 10.1007/s40641-018-0103-4
88. Global compound floods from precipitation and storm surge: Hazards and the roles of cyclones Y. Lai et al. 10.1175/JCLI-D-21-0050.1
89. The Precautionary Principles of the Potential Risks of Compound Events in Danish Municipalities L. Modrakowski et al. 10.3389/fclim.2021.772629
90. Future sea level rise exacerbates compound floods induced by rainstorm and storm tide during super typhoon events: A case study from Zhuhai, China Z. Zeng et al. 10.1016/j.scitotenv.2023.168799
91. Compound flood models in coastal areas: a review of methods and uncertainty analysis K. Xu et al. 10.1007/s11069-022-05683-3
92. A composite index framework for compound flood risk assessment J. Del-Rosal-Salido et al. 10.1038/s43247-025-02331-z
93. Sea Level Rise Impact on Compound Coastal River Flood Risk in Klaipėda City (Baltic Coast, Lithuania) E. Čepienė et al. 10.3390/w14030414
94. Compound Flooding in Halmstad: Common Causes, Interannual Variability and the Effects of Climate Change M. Hieronymus et al. 10.16993/tellusa.4068
95. Dynamic vulnerability assessment of maize under low temperature and drought concurrent stress in Songliao Plain Y. Zhao et al. 10.1016/j.agwat.2023.108400
96. Mapping Dependence Between Extreme Rainfall and Storm Surge W. Wu et al. 10.1002/2017JC013472
97. The Australian wildfires from a systems dependency perspective J. Handmer et al. 10.1088/1748-9326/abc0bc
98. Contrasting biosphere responses to hydrometeorological extremes: revisiting the 2010 western Russian heatwave M. Flach et al. 10.5194/bg-15-6067-2018
99. Copulas modelling of maize yield losses – drought compound events using the multiple remote sensing indices over the Danube River Basin V. Potopová et al. 10.1016/j.agwat.2023.108217
100. Nonstationary Hydrological Distribution Estimation Using Hierarchical Model with Stochastic Covariates C. Jiang et al. 10.1061/JHYEFF.HEENG-5809
101. Causes of dependence between extreme floods C. Deidda et al. 10.1088/1748-9326/ac07d5
102. Development of a physics-informed data-driven model for gaining insights into hydrological processes in irrigated watersheds K. Li et al. 10.1016/j.jhydrol.2022.128323
103. Incorporating climate change in flood estimation guidance C. Wasko et al. 10.1098/rsta.2019.0548
104. Probabilistic Numerical Modeling of Compound Flooding Caused by Tropical Storm Matthew Over a Data‐Scarce Coastal Environment Y. Zhang & M. Najafi 10.1029/2020WR028565
105. A multi-hazard framework for spatial-temporal impact analysis S. De Angeli et al. 10.1016/j.ijdrr.2022.102829
106. Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction M. Vrac 10.5194/hess-22-3175-2018
107. Estimating a Coastal Compound Flood Standard for the Taehwa River Basin K. Kim et al. 10.9798/KOSHAM.2024.24.4.217
108. An Insight into the Factors Controlling Delta Flood Events: The Case of the Evros River Deltaic Plain (NE Aegean Sea) S. Poulos et al. 10.3390/w14030497
109. A framework to evaluate the impact of a hazard chain and geographical covariates on spatial extreme water levels: A case study in the Pearl River Delta Z. She et al. 10.1016/j.scitotenv.2024.172066
110. Exploring the combined effects of drought and drought-flood abrupt alternation on vegetation using interpretable machine learning model and r-vine copula function L. Xie et al. 10.1016/j.agrformet.2025.110568
111. A flood risk assessment framework for interdependent infrastructure systems in coastal environments M. Najafi et al. 10.1016/j.scs.2020.102516
112. Tracing Uncertainty Contributors in the Multi‐Hazard Risk Analysis for Compound Extremes Y. Fan et al. 10.1029/2021EF002280
113. Broadening the scope of anthropogenic influence in extreme event attribution A. Jézéquel et al. 10.1088/2752-5295/ad7527
114. Quantifying the role of individual flood drivers and their correlations in flooding of coastal river reaches M. Bermúdez et al. 10.1007/s00477-019-01733-8
115. Measuring compound flood potential from river discharge and storm surge extremes at the global scale A. Couasnon et al. 10.5194/nhess-20-489-2020
116. Vine copula and cloud model-based programming approach for agricultural water allocation under uncertainty B. Shan et al. 10.1007/s00477-021-01985-3
117. Assessing the Potential for Compound Storm Surge and Extreme River Discharge Events at the Catchment Scale with Statistical Models: Sensitivity Analysis and Recommendations for Best Practice R. Jane et al. 10.1061/(ASCE)HE.1943-5584.0002154
118. Flood risk influenced by the compound effect of storm surge and rainfall under climate change for low-lying coastal areas S. Hsiao et al. 10.1016/j.scitotenv.2020.144439
119. Floods and droughts: a multivariate perspective M. Brunner 10.5194/hess-27-2479-2023
120. Vine-Copula-Based Quantile Regression for Cascade Reservoirs Management W. El Hannoun et al. 10.3390/w13070964
121. An accuracy-improved flood risk and ecological risk assessment in an interconnected river–lake system based on a copula-coupled hydrodynamic risk assessment model R. Yang et al. 10.1016/j.jhydrol.2021.127042
122. A Flood Risk Framework Capturing the Seasonality of and Dependence Between Rainfall and Sea Levels—An Application to Ho Chi Minh City, Vietnam A. Couasnon et al. 10.1029/2021WR030002
123. Quantifying effects of compound dry-hot extremes on vegetation in Xinjiang (China) using a vine-copula conditional probability model H. Li et al. 10.1016/j.agrformet.2021.108658
124. A hazard model of sub-freezing temperatures in the United Kingdom using vine copulas S. Koumoutsaris 10.5194/nhess-19-489-2019
125. Compound flooding from lake seiche and river flow in a freshwater coastal river A. Saharia et al. 10.1016/j.jhydrol.2021.126969
126. Joint probabilistic assessments of four-dimensional flood characteristics using the vine copula-based methodology N. Jafry et al. 10.1007/s12665-024-11743-7
127. Brief communication: The role of using precipitation or river discharge data when assessing global coastal compound flooding E. Bevacqua et al. 10.5194/nhess-20-1765-2020
128. Agricultural Drought Prediction Based on Conditional Distributions of Vine Copulas H. Wu et al. 10.1029/2021WR029562
129. Linking statistical and hydrodynamic modeling for compound flood hazard assessment in tidal channels and estuaries H. Moftakhari et al. 10.1016/j.advwatres.2019.04.009
130. Compound events in Germany in 2018: drivers and case studies E. Xoplaki et al. 10.5194/nhess-25-541-2025
131. A study on compound flood prediction and inundation simulation under future scenarios in a coastal city M. Zhong et al. 10.1016/j.jhydrol.2023.130475
132. Asymmetric Dependence in Hydrological Extremes C. Deidda et al. 10.1029/2023WR034512
133. Compounding effects of sea level rise and fluvial flooding H. Moftakhari et al. 10.1073/pnas.1620325114
134. Combined statistical and hydrodynamic modelling of compound flooding in coastal areas - Methodology and application A. Olbert et al. 10.1016/j.jhydrol.2023.129383
135. Characterizing interactive compound flood drivers in the Pearl River Estuary: A case study of Typhoon Hato (2017) Q. Lin et al. 10.1016/j.jhydrol.2024.132270
136. A Bayesian copula-based nonstationary framework for compound flood risk assessment along US coastlines K. Naseri & M. Hummel 10.1016/j.jhydrol.2022.128005
137. Development of a Joint Probabilistic Rainfall‐Runoff Model for High‐to‐Extreme Flow Projections Under Changing Climatic Conditions K. Li et al. 10.1029/2021WR031557
138. Consideration of compound drivers and impacts in the disaster risk reduction cycle B. van den Hurk et al. 10.1016/j.isci.2023.106030
139. Nature-based solutions on the coast in face of climate change: The case of Benidorm (Spain) I. Toledo et al. 10.1016/j.uclim.2024.101816
140. Frequency, duration, severity of energy drought and its propagation in hydro-wind-photovoltaic complementary systems H. Lei et al. 10.1016/j.renene.2024.120845
141. Which droughts are becoming more frequent? A copula entropy analysis on the return period of droughts in Europe P. Alencar & E. Paton 10.1007/s11069-024-06848-y
142. Assessing future urban flood hazard: A comprehensive approach to estimating the implications of future rainfall scenarios H. Moon et al. 10.1111/jfr3.13000
143. Trivariate Frequency Analysis of Extreme Sediment Events of Compound Floods Based on Vine Copula: A Case Study of the Middle Yellow River in China F. Zhao et al. 10.1061/JHYEFF.HEENG-6303
144. Evaluating the efficacy of bivariate extreme modelling approaches for multi-hazard scenarios A. Tilloy et al. 10.5194/nhess-20-2091-2020
145. Understanding the impacts of predecessor rain events on flood hazard in a changing climate A. Khatun et al. 10.1002/hyp.14500
146. Review article: A comprehensive review of compound flooding literature with a focus on coastal and estuarine regions J. Green et al. 10.5194/nhess-25-747-2025
147. Parametric Vine Copula Framework in the Trivariate Probability Analysis of Compound Flooding Events S. Latif & S. Simonovic 10.3390/w14142214
148. Robust DC optimal power flow with modeling of solar power supply uncertainty via R-vine copulas K. Aigner et al. 10.1007/s11081-022-09761-0
149. Trivariate joint frequency analysis of water resources deficiency signatures using vine copulas M. Nazeri Tahroudi et al. 10.1007/s13201-022-01589-4
150. Time‐varying copula‐based compound flood risk assessment of extreme rainfall and high water level under a non‐stationary environment M. Song et al. 10.1111/jfr3.13032
151. Modelling compound flooding: a case study from Jakarta, Indonesia W. Bennett et al. 10.1007/s11069-023-06001-1
152. A Copula-Based Bayesian Network for Modeling Compound Flood Hazard from Riverine and Coastal Interactions at the Catchment Scale: An Application to the Houston Ship Channel, Texas A. Couasnon et al. 10.3390/w10091190
153. Ten-year return levels of sub-daily extreme precipitation over Europe B. Poschlod et al. 10.5194/essd-13-983-2021
154. Convolutional conditional neural processes for local climate downscaling A. Vaughan et al. 10.5194/gmd-15-251-2022
155. A framework for exploring environmental risk of the longest inter-basin water diversion project under the influence of multiple factors: A case study in China C. Zhang et al. 10.1016/j.jenvman.2022.116036
156. Sub-seasonal prediction of compound hot and dry extremes in India I. Malik & V. Mishra 10.1007/s00382-025-07668-x
157. Assessing compound flood hazards in the Pearl river Delta: A Scenario-Based Integration of trivariate fluvial conditions and extreme storm events H. Du et al. 10.1016/j.jhydrol.2025.133104
158. Flash drought and heatwave compound events increased in strength and length from 1980 to 2022 in China K. Fu et al. 10.1016/j.wace.2024.100720
159. Application of Copula Functions for Bivariate Analysis of Rainfall and River Flow Deficiencies in the Siminehrood River Basin, Iran M. Nazeri Tahroudi et al. 10.1061/(ASCE)HE.1943-5584.0002207
160. Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands V. Santos et al. 10.5194/hess-25-3595-2021
161. A classification algorithm for selective dynamical downscaling of precipitation extremes E. Meredith et al. 10.5194/hess-22-4183-2018
162. A review of quantification methodologies for multi-hazard interrelationships A. Tilloy et al. 10.1016/j.earscirev.2019.102881
163. The response of agricultural drought to meteorological drought modulated by air temperature X. Wei et al. 10.1016/j.jhydrol.2024.131626
164. Evaluation and prediction of compound geohazards in highly urbanized regions across China's Greater Bay Area K. He et al. 10.1016/j.jclepro.2024.141641
165. Study on the up-downstream water level correlation and the extreme water levels under flood-tide encounters of the Feiyun River main stream Z. Qin et al. 10.1007/s12665-024-11552-y
166. Exploring the spatial and temporal changes of compound disasters: A case study in Gaoping River, Taiwan T. Chen et al. 10.1016/j.crm.2024.100617
167. Predicting compound agricultural drought and hot events using a Cascade Modeling framework combining Bayesian Model Averaging ensemble with Vine Copula (CaMBMAViC) H. Wu et al. 10.1016/j.jhydrol.2024.131901
168. Soil moisture deficits triggered by increasing compound drought and heat events during the growing season in Arid Central Asia Q. Wang et al. 10.1016/j.jhydrol.2025.133397
169. Statistical behavior of temporally compounding multi-peak flood events G. Cazzaniga et al. 10.1088/1748-9326/add0c8
170. Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods W. Zhang et al. 10.3389/feart.2021.673495
171. Simultaneous flood risk analysis and its future change among all the 109 class-A river basins in Japan using a large ensemble climate simulation database d4PDF T. Tanaka et al. 10.1088/1748-9326/abfb2b
172. Guidelines for Studying Diverse Types of Compound Weather and Climate Events E. Bevacqua et al. 10.1029/2021EF002340
173. Compounding Effects of Fluvial Flooding and Storm Tides on Coastal Flooding Risk in the Coastal-Estuarine Region of Southeastern China W. Lu et al. 10.3390/atmos13020238
174. Compound Impact of Storm Surge and Flood Characteristics in Coastal Area Based on Copula Z. Zhu et al. 10.3390/w16020270
175. Advancing research on compound weather and climate events via large ensemble model simulations E. Bevacqua et al. 10.1038/s41467-023-37847-5
176. A typology of compound weather and climate events J. Zscheischler et al. 10.1038/s43017-020-0060-z
177. Research progresses and prospects of multi-sphere compound extremes from the Earth System perspective Z. Hao & Y. Chen 10.1007/s11430-023-1201-y
178. Seasonal impact-based mapping of compound hazards J. Hillier & R. Dixon 10.1088/1748-9326/abbc3d
179. A Hybrid Framework for Rapidly Locating Transition Zones: A Comparison of Event‐ and Response‐Based Return Water Levels in the Suwannee River FL R. Jane et al. 10.1029/2022WR032481
180. Trivariate Joint Distribution Modelling of Compound Events Using the Nonparametric D-Vine Copula Developed Based on a Bernstein and Beta Kernel Copula Density Framework S. Latif & S. Simonovic 10.3390/hydrology9120221
181. A hybrid statistical–dynamical framework for compound coastal flooding analysis Z. Wang et al. 10.1088/1748-9326/ad96ce
182. Changes in compound hot and dry day and population exposure across China under climate change Y. Feng et al. 10.1002/joc.7399
183. A Statistical Analysis of the Occurrences of Critical Waves and Water Levels for the Management of the Operativity of the MoSE System in the Venice Lagoon G. Tomasicchio et al. 10.1007/s00477-021-02133-7
184. Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline A. Nasr et al. 10.5194/hess-25-6203-2021
185. Detecting human interventions by spatial dependence of extreme water levels using a high dimensional conditional probability approach over the Pearl River Delta Z. She et al. 10.1016/j.jhydrol.2023.129681
186. Increased probability of compound long-duration dry and hot events in Europe during summer (1950–2013) C. Manning et al. 10.1088/1748-9326/ab23bf
187. A Framework of Dependence Modeling and Evaluation System for Compound Flood Events X. Wang & Y. Shen 10.1029/2023WR034718
188. An Efficient Data-Driven Conditional Joint Wind Power Scenario Generation for Day-Ahead Power System Operations Planning A. Krishna & A. Abhyankar 10.1109/TPWRS.2023.3298004
189. A statistical simulation method for joint time series of non-stationary hourly wave parameters W. Jäger et al. 10.1016/j.coastaleng.2018.11.003
190. Dynamical systems theory sheds new light on compound climate extremes in Europe and Eastern North America P. De Luca et al. 10.1002/qj.3757
191. Risks to Coastal Critical Infrastructure from Climate Change I. Pal et al. 10.1146/annurev-environ-112320-101903
192. Joint Action of Wind and Temperature on Long-Span Concrete-Filled Steel Tube Bridges in the Yellow River Basin J. Liu et al. 10.3390/buildings15040633
193. Streamflow forecasting method with a hybrid physical process-mathematical statistic S. Wang et al. 10.1007/s00477-023-02542-w
194. Flood risk assessment of artificial islands under compound rain-tide-wind effects during tropical cyclones Y. Li et al. 10.1016/j.jhydrol.2022.128736
195. Temporal changes in dependence between compound coastal and inland flooding drivers around the contiguous United States coastline A. Nasr et al. 10.1016/j.wace.2023.100594
196. Bernstein copula-based spatial cosimulation for petrophysical property prediction conditioned to elastic attributes V. Le et al. 10.1016/j.petrol.2020.107382
197. Assessment of the joint impact of extreme rainfall and storm surge on the risk of flooding in a coastal area B. Zellou & H. Rahali 10.1016/j.jhydrol.2018.12.028
198. How Probable Is Widespread Flooding in the United States? M. Brunner et al. 10.1029/2020WR028096
199. Assessment of vegetation response to compound dry-hot events in Central Asia based on the Vine-Copula conditional probability model C. Yang et al. 10.1016/j.ecolind.2024.112910
200. Trends in Compound Flooding in Northwestern Europe During 1901–2014 P. Ganguli & B. Merz 10.1029/2019GL084220
201. Soil Moisture Drought in Europe: A Compound Event of Precipitation and Potential Evapotranspiration on Multiple Time Scales C. Manning et al. 10.1175/JHM-D-18-0017.1
202. Accelerated soil drying linked to increasing evaporative demand in wet regions Y. Qing et al. 10.1038/s41612-023-00531-y
203. Improved Hidden Markov Model Incorporated with Copula for Probabilistic Seasonal Drought Forecasting S. Zhu et al. 10.1061/(ASCE)HE.1943-5584.0001901
204. Compound Effects of Flood Drivers and Wetland Elevation Correction on Coastal Flood Hazard Assessment D. Muñoz et al. 10.1029/2020WR027544
205. R-statistic based predictor variables selection and vine structure determination approach for stochastic streamflow generation considering temporal and spatial dependence X. Wang & Y. Shen 10.1016/j.jhydrol.2023.129093
206. A storm-centered multivariate modeling of extreme precipitation frequency based on atmospheric water balance Y. Liu & D. Wright 10.5194/hess-26-5241-2022
207. Compounding joint impact of rainfall, storm surge and river discharge on coastal flood risk: an approach based on 3D fully nested Archimedean copulas S. Latif & S. Simonovic 10.1007/s12665-022-10719-9
208. Assessing the characteristics and drivers of compound flooding events around the UK coast A. Hendry et al. 10.5194/hess-23-3117-2019
209. Increased occurrence of high impact compound events under climate change N. Ridder et al. 10.1038/s41612-021-00224-4
210. Multi-reservoirs joint flood control scheduling using a two-layer hedging robust optimization method under uncertain inflows X. Yu et al. 10.1016/j.ejrh.2025.102244
211. Research on Spatiotemporal Heterogeneity of the Impact of Earthquakes on Global Copper Ore Supply Based on Geographically Weighted Regression C. Shang et al. 10.3390/su16041487
212. Climatic Challenges in the Growth Cycle of Winter Wheat in the Huang-Huai-Hai Plain: New Perspectives on High-Temperature–Drought and Low-Temperature–Drought Compound Events G. Chen et al. 10.3390/atmos15070747
213. Multivariate Frequency Analysis of Drought Characteristics in Finland Using Vine Copulas R. Mirabbasi et al. 10.1002/joc.8679
214. Compound Extremes in Hydroclimatology: A Review Z. Hao et al. 10.3390/w10060718
215. Statistical disclosure control for continuous variables using an extended skew‐t copula A. Chu et al. 10.1002/asmb.2650
216. Estimations of statistical dependence as joint return period modulator of compound events – Part 1: Storm surge and wave height T. Petroliagkis 10.5194/nhess-18-1937-2018
217. Numerical modelling and quantification of coastal urban compound flooding J. Yuan et al. 10.1016/j.jhydrol.2024.130716
218. Pan-European hydrodynamic models and their ability to identify compound floods D. Paprotny et al. 10.1007/s11069-020-03902-3
219. Contrasting vegetation response to compound temperature and moisture extremes across Northern Hemisphere L. Huang et al. 10.1016/j.jenvman.2025.124598
220. Diagnosing concurrent drivers of weather extremes: application to warm and cold days in North America D. Faranda et al. 10.1007/s00382-019-05106-3
221. A multivariate approach for statistical assessments of compound extremes Z. Hao et al. 10.1016/j.jhydrol.2018.08.025
222. Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries P. Ward et al. 10.1088/1748-9326/aad400
223. Extreme Coastal Water Levels Exacerbate Fluvial Flood Hazards in Northwestern Europe P. Ganguli & B. Merz 10.1038/s41598-019-49822-6
224. Maximum pseudo‐likelihood estimation based on estimated residuals in copula semiparametric models M. Omelka et al. 10.1111/sjos.12498
225. Evolution of Frequency and Intensity of Concurrent Heavy Precipitation and Storm Surge at the Global Scale: Implications for Compound Floods Y. Lai et al. 10.3389/feart.2021.660359
226. Evaluating vegetation vulnerability under compound dry and hot conditions using vine copula across global lands G. Zhang et al. 10.1016/j.jhydrol.2024.130775
227. Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling K. Jafarzadegan et al. 10.1029/2022RG000788
228. Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change E. Bevacqua et al. 10.1126/sciadv.aaw5531
229. Influence of data source and copula statistics on estimates of compound flood extremes in a river mouth environment K. Dubois et al. 10.5194/nhess-24-3245-2024
230. Compound Continental Risk of Multiple Extreme Floods in the United States N. Najibi et al. 10.1029/2023GL105297
231. Increasingly Seasonal Jet Stream Raises Risk of Co‐Occurring Flooding and Extreme Wind in Great Britain J. Hillier et al. 10.1002/joc.8763
232. Making the Output of Seasonal Climate Models More Palatable to Agriculture: A Copula-Based Postprocessing Method M. Li et al. 10.1175/JAMC-D-19-0093.1
233. A Framework for Exploring Joint Effects of Conditional Factors on Compound Floods Z. Liu et al. 10.1002/2017WR021662
234. Perspectives on Compound Flooding in Chinese Estuary Regions H. Xu et al. 10.1007/s13753-023-00482-1
235. ComHazAsTC-RRE: Compound Hazard Assessment of Tropical Cyclones within Repeatable, Reproducible, and Expandable Framework Z. Zhou et al. 10.1016/j.jag.2024.104314