87 citations as recorded by crossref.

1. On some aspects of peaks-over-threshold modeling of floods under nonstationarity using climate covariates A. Silva et al. 10.1007/s00477-015-1072-y
2. Climate variability and floods in China - A review Z. Kundzewicz et al. 10.1016/j.earscirev.2020.103434
3. What are the hydro-meteorological controls on flood characteristics? M. Nied et al. 10.1016/j.jhydrol.2016.12.003
4. Should seasonal rainfall forecasts be used for flood preparedness? E. Coughlan de Perez et al. 10.5194/hess-21-4517-2017
5. Non-stationary rainfall and natural flows modeling at the watershed scale M. Egüen et al. 10.1016/j.jhydrol.2016.04.061
6. Study of rainfall variabilities in Southeast Asia using long-term gridded rainfall and its substantiation through global climate indices V. Singh & X. Qin 10.1016/j.jhydrol.2019.124320
7. Projecting flood hazard under climate change: an alternative approach to model chains J. Delgado et al. 10.5194/nhess-14-1579-2014
8. Machine Learning Modeling of Climate Variability Impact on River Runoff M. Norel et al. 10.3390/w13091177
9. Low frequency global‐scale modes and its influence on rainfall extremes over India: Nonstationary and uncertainty analysis S. Jha et al. 10.1002/joc.6935
10. Complex picture for likelihood of ENSO-driven flood hazard R. Emerton et al. 10.1038/ncomms14796
11. Effect of ENSO on annual maximum floods and volume over threshold in the southwestern region of Iran B. Saghafian et al. 10.1080/02626667.2017.1296229
12. Ensemble flood forecasting: Current status and future opportunities W. Wu et al. 10.1002/wat2.1432
13. Annual flood damage influenced by El Niño in the Kan River basin, Iran F. Hooshyaripor et al. 10.5194/nhess-20-2739-2020
14. Modelling Water Balance Components of River Basins Located in Different Regions of the Globe E. Gusev et al. 10.1134/S0097807818060246
15. Extreme flood modeling and mechanism over Crisul Alb basin in Romania M. Caian et al. 10.1016/j.catena.2020.104923
16. Shifting signals: Correlations among freshwater, marine and climatic indices often investigated in Pacific salmon studies J. Gosselin et al. 10.1016/j.ecolind.2020.107167
17. Towards Probabilistic Multivariate ENSO Monitoring T. Zhang et al. 10.1029/2019GL083946
18. Defining high-flow seasons using temporal streamflow patterns from a global model D. Lee et al. 10.5194/hess-19-4689-2015
19. Preparedness for slow-onset environmental disasters: Drawing lessons from three decades of El Niño impacts R. Staupe-Delgado et al. 10.1002/sd.1719
20. Beyond El Niño: Unsung climate modes drive African floods A. Ficchì et al. 10.1016/j.wace.2021.100345
21. The role of climate variability in extreme floods in Europe G. Nobre et al. 10.1088/1748-9326/aa7c22
22. Fluvial sediment supply to a mega-delta reduced by shifting tropical-cyclone activity S. Darby et al. 10.1038/nature19809
23. Revealing Hidden Climate Indices from the Occurrence of Hydrologic Extremes B. Renard & M. Thyer 10.1029/2019WR024951
24. A global analysis of the asymmetric effect of ENSO on extreme precipitation X. Sun et al. 10.1016/j.jhydrol.2015.09.016
25. On the spatial and temporal variability of ENSO precipitation and drought teleconnection in mainland Southeast Asia T. Räsänen et al. 10.5194/cp-12-1889-2016
26. Design considerations for riverine floods in a changing climate – A review B. François et al. 10.1016/j.jhydrol.2019.04.068
27. Using Climate-Flood Links and CMIP5 Projections to Assess Flood Design Levels Under Climate Change Scenarios: A Case Study in Southern Brazil A. Silva & M. Portela 10.1007/s11269-018-2058-6
28. Forecast-based financing: an approach for catalyzing humanitarian action based on extreme weather and climate forecasts E. Coughlan de Perez et al. 10.5194/nhess-15-895-2015
29. Temporal variability of streamflow and plant species abundance on islets as they relate to ENSO events downstream from an inversion-type reservoir S. Dubeau et al. 10.1002/rra.3218
30. Identifying El Niño–Southern Oscillation influences on rainfall with classification models: implications for water resource management of Sri Lanka T. De Silva M. & G. Hornberger 10.5194/hess-23-1905-2019
31. Climatology and Interannual Variability of Floods during the TRMM Era (1998–2013) Y. Yan et al. 10.1175/JCLI-D-19-0415.1
32. Declining vulnerability to river floods and the global benefits of adaptation B. Jongman et al. 10.1073/pnas.1414439112
33. Increasing stress on disaster-risk finance due to large floods B. Jongman et al. 10.1038/nclimate2124
34. Combining information from multiple flood projections in a hierarchical Bayesian framework N. Le Vine 10.1002/2015WR018143
35. Copernicus Marine Service Ocean State Report K. von Schuckmann et al. 10.1080/1755876X.2018.1489208
36. Effect of Upper Tropospheric Vertical Thermal Contrast Over the Mediterranean Region on Convection over the Western Tibetan Plateau during ENSO Years B. Vaid & X. Liang 10.1080/07055900.2020.1751048
37. Hydrological response to large-scale climate variability across the Pearl River basin, China: Spatiotemporal patterns and sensitivity X. Gu et al. 10.1016/j.gloplacha.2016.12.016
38. At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions F. Cassalho et al. 10.1007/s11269-017-1810-7
39. Spatio-Temporal Variability of Rainfall Indices and their Teleconnections with El Niño-Southern Oscillation for Tapi Basin, India L. Gehlot et al. 10.1007/s13143-020-00179-1
40. The Influence of the Pacific Decadal Oscillation on Annual Floods in the Rivers of Western Canada S. Gurrapu et al. 10.1111/1752-1688.12433
41. Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0 R. Emerton et al. 10.5194/gmd-11-3327-2018
42. Assessment of the effects of climate and land cover changes on river discharge and sediment yield, and an adaptive spatial planning in the Jakarta region . Poerbandono et al. 10.1007/s11069-014-1083-x
43. Impacts of El Niño-Southern Oscillation on surface dust levels across the world during 1982–2019 J. Li et al. 10.1016/j.scitotenv.2020.144566
44. Exploring the ENSO Impact on Basin‐Scale Floods Using Hydrological Simulations and TRMM Precipitation Y. Yan et al. 10.1029/2020GL089476
45. What is the most useful approach for forecasting hydrological extremes during El Niño? R. Emerton et al. 10.1088/2515-7620/ab114e
46. Influence analysis of central and Eastern Pacific El Niños to seasonal rainfall patterns over China using the intentional statistical simulations C. Heng et al. 10.1016/j.atmosres.2019.104706
47. Investigating Relationships Between Australian Flooding and Large-Scale Climate Indices and Possible Mechanism J. Liu et al. 10.1029/2017JD028197
48. Climate Change Impacts on Water and Agriculture Sectors in Southern Africa: Threats and Opportunities for Sustainable Development C. Nhemachena et al. 10.3390/w12102673
49. Climate-driven interannual variability of water scarcity in food production potential: a global analysis M. Kummu et al. 10.5194/hess-18-447-2014
50. A hybrid approach for El Niño prediction based on Empirical Mode Decomposition and convolutional LSTM Encoder-Decoder S. Wang et al. 10.1016/j.cageo.2021.104695
51. Flood impact on Mainland Southeast Asia between 1985 and 2018—The role of tropical cyclones A. Chen et al. 10.1111/jfr3.12598
52. Impacts and effects of a historical high and ENSO linked freshwater inflow in the tropical estuary Nha Phu, southeast Vietnam L. Lund-Hansen et al. 10.1016/j.rsma.2017.11.012
53. The great 1983 floods in South American large rivers: a continental hydrological modelling approach A. Fleischmann et al. 10.1080/02626667.2020.1747622
54. Recent changes in climate, hydrology and sediment load in the Wadi Abd, Algeria (1970–2010) M. Achite & S. Ouillon 10.5194/hess-20-1355-2016
55. Identification of symmetric and asymmetric responses in seasonal streamflow globally to ENSO phase D. Lee et al. 10.1088/1748-9326/aab4ca
56. Response of lower Yellow River bank breachings to La Niña events since 924 CE J. Xu & F. Li 10.1016/j.catena.2019.01.012
57. Causes and trends of water scarcity in food production M. Porkka et al. 10.1088/1748-9326/11/1/015001
58. Temporal clustering of floods in Germany: Do flood-rich and flood-poor periods exist? B. Merz et al. 10.1016/j.jhydrol.2016.07.041
59. Changes of precipitation extremes in arid Central Asia M. Zhang et al. 10.1016/j.quaint.2016.12.024
60. Atmosphere-Land Bridge between the Pacific and Tropical North Atlantic SST’s through the Amazon River basin during the 2005 and 2010 droughts A. Builes-Jaramillo et al. 10.1063/1.5020502
61. What Will the Weather Do? Forecasting Flood Losses Based on Oscillation Indices G. Guimarães Nobre et al. 10.1029/2019EF001450
62. Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally D. Lee et al. 10.1002/2017WR021205
63. Effects of climate change on peak runoff and flood levels in Qu River Basin, East China C. Gao et al. 10.1016/j.jher.2018.02.005
64. The Effect of El Niño on Flood Damages in the Western United States T. Corringham & D. Cayan 10.1175/WCAS-D-18-0071.1
65. Achieving the reduction of disaster risk by better predicting impacts of El Niño and La Niña G. Guimarães Nobre et al. 10.1016/j.pdisas.2019.100022
66. Flood frequencies and durations and their response to El Niño Southern Oscillation: Global analysis P. Ward et al. 10.1016/j.jhydrol.2016.05.045
67. Assessment of flood discharge sensitivity to climate indexes in West Africa J. Hounkpè et al. 10.5194/piahs-384-219-2021
68. Impacts of El Niño –southern oscillation on global runoff: Characteristic signatures and potential mechanisms Y. You et al. 10.1002/hyp.14367
69. Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950–2015 N. Wang et al. 10.1007/s00477-021-02007-y
70. Streamflow variability and its linkage to ENSO events in the Ethiopian Rift Valley Lakes Basin A. Worako et al. 10.1016/j.ejrh.2021.100817
71. Evaluation of Nonstationarity in Annual Maximum Flood Series and the Associations with Large-scale Climate Patterns and Human Activities J. Li et al. 10.1007/s11269-014-0900-z
72. Climate Variability and Floods—A global Review . Kundzewicz et al. 10.3390/w11071399
73. Climate influences on flood probabilities across Europe E. Steirou et al. 10.5194/hess-23-1305-2019
74. Floods and climate: emerging perspectives for flood risk assessment and management B. Merz et al. 10.5194/nhess-14-1921-2014
75. Dependence of model-based extreme flood estimation on the calibration period: case study of the Kamp River (Austria) P. Brigode et al. 10.1080/02626667.2015.1006632
76. Informing Stochastic Streamflow Generation by Large-Scale Climate Indices at Single and Multiple Sites M. Zaerpour et al. 10.1016/j.advwatres.2021.104037
77. The monetary benefit of early flood warnings in Europe F. Pappenberger et al. 10.1016/j.envsci.2015.04.016
78. The Global Streamflow Indices and Metadata Archive (GSIM) – Part 1: The production of a daily streamflow archive and metadata H. Do et al. 10.5194/essd-10-765-2018
79. Phosphorus Loadings to the World's Largest Lakes: Sources and Trends G. Fink et al. 10.1002/2017GB005858
80. Influence of three phases of El Niño–Southern Oscillation on daily precipitation regimes in China A. Lv et al. 10.5194/hess-23-883-2019
81. A 2000-year documentary record of levee breaches on the lower Yellow River and their relationship with climate changes and human activities W. Li et al. 10.1177/0959683620972764
82. Spatial coherence of flood-rich and flood-poor periods across Germany B. Merz et al. 10.1016/j.jhydrol.2018.02.082
83. Correlations Between Extreme Atmospheric Hazards and Global Teleconnections: Implications for Multihazard Resilience H. Steptoe et al. 10.1002/2017RG000567
84. From extreme rainfall to drought: 250 years of annually resolved sediment deposition in Santa Barbara Basin, California I. Hendy et al. 10.1016/j.quaint.2015.01.026
85. Sensitivity of water scarcity events to ENSO-driven climate variability at the global scale T. Veldkamp et al. 10.5194/hess-19-4081-2015
86. Strong influence of El Niño Southern Oscillation on flood risk around the world P. Ward et al. 10.1073/pnas.1409822111
87. Atmospheric Circulation Patterns Associated with Extreme United States Floods Identified via Machine Learning K. Schlef et al. 10.1038/s41598-019-43496-w