78 citations as recorded by crossref.

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3. Flood Seasonality Analysis in Iran: A Circular Statistics Approach M. Bagheri-Gavkosh & S. Hosseini https://doi.org/10.1061/JHYEFF.HEENG-5786
4. Flood Inundation Generation Mechanisms and Their Changes in 1953–2004 in Global Major River Basins Y. Mao et al. https://doi.org/10.1029/2019JD031381
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6. Climate and rivers G. McGregor https://doi.org/10.1002/rra.3508
7. A Flood Forecasting Method in the Francolí River Basin (Spain) Using a Distributed Hydrological Model and an Analog-Based Precipitation Forecast D. Carril-Rojas et al. https://doi.org/10.3390/hydrology12080220
8. Unveiling hidden risks in healthcare from flood-induced transportation disruption in Germany J. Wassmer et al. https://doi.org/10.1038/s43247-025-02645-y
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10. Historical and future changes in global flood magnitude – evidence from a model–observation investigation H. Do et al. https://doi.org/10.5194/hess-24-1543-2020
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15. Attributing Global Changes in Flood Seasonality to Anthropogenic Climate Change and Land-Surface Human Activities Y. Wang et al. https://doi.org/10.3390/hydrology13100270
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18. Unveiling Changes in the Seasonality of Extreme Precipitation Shows an Anticipation of Short-Duration Extremes D. Treppiedi et al. https://doi.org/10.1007/s41748-026-01178-4
19. A Novel Method of Design Flood Hydrographs Estimation for Flood Hazard Mapping W. Gądek et al. https://doi.org/10.3390/w14121856
20. Reliance on daily mean streamflow data biases inferred flood seasonality B. Anderson et al. https://doi.org/10.1088/1748-9326/ae8e90
21. The great 1983 floods in South American large rivers: a continental hydrological modelling approach A. Fleischmann et al. https://doi.org/10.1080/02626667.2020.1747622
22. Changes in Magnitude and Shifts in Timing of the Latvian River Annual Flood Peaks E. Apsīte et al. https://doi.org/10.3390/atmos15091139
23. Performance comparison of GPM IMERG V07 with its predecessor V06 and its application in extreme precipitation clustering over Türkiye H. Aksu & S. Yaldiz https://doi.org/10.1016/j.atmosres.2024.107840
24. The Timing of Global Floods and Its Association With Climate and Topography P. Torre Zaffaroni et al. https://doi.org/10.1029/2022WR032968
25. Characterising the coincidence of soil moisture – precipitation extremes as a possible precursor to European floods A. Manoj J et al. https://doi.org/10.1016/j.jhydrol.2023.129445
26. Iso-severity flood hazard patterns in diverse relief and climatic regions to support flood management R. Mostafazadeh et al. https://doi.org/10.1007/s11069-025-07492-w
27. Economic consequences of cascading drought-flood events: evidence from central Europe S. Deng et al. https://doi.org/10.1088/1748-9326/ae0f43
28. Mapping dynamic changes in hydrological time series using the average directional index M. Shamseddin & H. Elmeski https://doi.org/10.1080/15715124.2020.1776302
29. Hydro Explorer: An interactive web app to investigate changes in runoff timing and runoff seasonality all over the world E. Rottler et al. https://doi.org/10.1002/rra.3772
30. Hydroclimatic time series features at multiple time scales G. Papacharalampous et al. https://doi.org/10.1016/j.jhydrol.2023.129160
31. Regional flood risk analysis for agricultural crops: Insights from the implementation of AGRIDE-c in central Italy A. Scorzini et al. https://doi.org/10.1016/j.ijdrr.2020.101999
32. Uncovering Flooding Mechanisms Across the Contiguous United States Through Interpretive Deep Learning on Representative Catchments S. Jiang et al. https://doi.org/10.1029/2021WR030185
33. Modeling riverine flood seasonality with mixtures of circular probability density functions W. Veatch & G. Villarini https://doi.org/10.1016/j.jhydrol.2022.128330
34. Clustering Simultaneous Occurrences of the Extreme Floods in the Neckar Catchment E. Modiri & A. Bárdossy https://doi.org/10.3390/w13040399
35. Diverging trends in large floods across Europe in a warming climate B. Fang et al. https://doi.org/10.1038/s43247-025-02734-y
36. Timescale-based flood typing to estimate temporal changes in flood frequencies S. Fischer et al. https://doi.org/10.1080/02626667.2019.1679376
37. Global‐Scale Prediction of Flood Timing Using Atmospheric Reanalysis H. Do et al. https://doi.org/10.1029/2019WR024945
38. Model-based assessment of flood generation mechanisms over Poland: The roles of precipitation, snowmelt, and soil moisture excess N. Venegas-Cordero et al. https://doi.org/10.1016/j.scitotenv.2023.164626
39. Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity G. Papacharalampous et al. https://doi.org/10.1016/j.scitotenv.2020.144612
40. Understanding meteorological and physio-geographical controls of variability of flood event classes in headstream catchments of China Y. Zhang et al. https://doi.org/10.5194/hess-29-3257-2025
41. Identification of homogeneous regions in terms of flood seasonality using a complex network approach W. Yang et al. https://doi.org/10.1016/j.jhydrol.2019.06.082
42. Nature-based solutions for hydro-meteorological hazards: Revised concepts, classification schemes and databases S. Debele et al. https://doi.org/10.1016/j.envres.2019.108799
43. GRUN: an observation-based global gridded runoff dataset from 1902 to 2014 G. Ghiggi et al. https://doi.org/10.5194/essd-11-1655-2019
44. On the Uncertainty and Changeability of the Estimates of Seasonal Maximum Flows I. Markiewicz et al. https://doi.org/10.3390/w12030704
45. Study on the Staged Operation of a Multi-Purpose Reservoir in Flood Season and Its Effect Evaluation C. Mo et al. https://doi.org/10.3390/w13182563
46. Improving Estuarine Flood Risk Knowledge through Documentary Data Using Multiple Correspondence Analysis A. Rilo et al. https://doi.org/10.3390/w14193161
47. Observation‐Constrained Projection of Global Flood Magnitudes With Anthropogenic Warming W. Liu et al. https://doi.org/10.1029/2020WR028830
48. Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe D. Lun et al. https://doi.org/10.1029/2019WR026575
49. Statistical spatiotemporal analysis of hydro-morphological processes in China during 1950–2015 N. Wang et al. https://doi.org/10.1007/s00477-021-02007-y
50. Understanding flood seasonality and flood regime shift in the Congo River Basin G. Bola et al. https://doi.org/10.1080/02626667.2022.2083966
51. Warming-driven runoff increase and shifted seasonality in the glacierized Hotan Basin in Central Asia X. Xu et al. https://doi.org/10.1016/j.gloplacha.2026.105579
52. Seasonality, persistency, regionalization, and control mechanism of extreme rainfall over complex terrain A. Akbas https://doi.org/10.1007/s00704-023-04440-1
53. Machine learning models for river flow forecasting in small catchments M. Luppichini et al. https://doi.org/10.1038/s41598-024-78012-2
54. Climate impact on flood changes – an Austrian-Ukrainian comparison S. Snizhko et al. https://doi.org/10.2478/johh-2023-0017
55. Detection of trends in observed river floods in Poland N. Venegas-Cordero et al. https://doi.org/10.1016/j.ejrh.2022.101098
56. Shifting in the global flood timing G. Fang et al. https://doi.org/10.1038/s41598-022-23748-y
57. Exploring multidecadal changes in climate and reservoir storage for assessing nonstationarity in flood peaks and risks worldwide by an integrated frequency analysis approach Y. Zhou https://doi.org/10.1016/j.watres.2020.116265
58. How extreme are flood peak distributions? A quasi-global analysis of daily discharge records M. Zaerpour et al. https://doi.org/10.1016/j.jhydrol.2024.130849
59. Simulating flash flood hydrographs and behavior metrics across China: Implications for flash flood management X. Zhai et al. https://doi.org/10.1016/j.scitotenv.2020.142977
60. Türkiye’de Taşkınların FlooDOT Tabanlı İncelenmesi ve Farklı Veri Kaynaklarının Mekânsal Karşılaştırılması A. Akbaş et al. https://doi.org/10.18400/tjce.1618212
61. The dynamics of peak head responses at Dutch canal dikes and the impact of climate change B. Strijker & M. Kok https://doi.org/10.5194/nhess-25-3355-2025
62. River flooding mechanisms and their changes in Europe revealed by explainable machine learning S. Jiang et al. https://doi.org/10.5194/hess-26-6339-2022
63. Changing Water Cycle under a Warming Climate: Tendencies in the Carpathian Basin I. Jánosi et al. https://doi.org/10.3390/cli11060118
64. Improving flash-flood and debris-flow susceptibility mapping using stacking-based ensemble learning T. Van Phong et al. https://doi.org/10.1007/s13762-026-07477-7
65. Gauging ungauged catchments – Active learning for the timing of point discharge observations in combination with continuous water level measurements S. Pool & J. Seibert https://doi.org/10.1016/j.jhydrol.2021.126448
66. Current European flood-rich period exceptional compared with past 500 years G. Blöschl et al. https://doi.org/10.1038/s41586-020-2478-3
67. Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning W. Liang et al. https://doi.org/10.1038/s41612-025-00918-z
68. Comparing Satellite, Reanalysis, Fused and Gridded (In Situ) Precipitation Products Over Türkiye A. Akbas & H. Ozdemir https://doi.org/10.1002/joc.8671
69. Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management L. Slater et al. https://doi.org/10.5194/hess-25-3897-2021
70. Sustainability of mining activities in the European Mediterranean region in terms of a spatial groundwater stress index E. Varouchakis et al. https://doi.org/10.1016/j.spasta.2022.100625
71. Flood frequency analysis of the Rasina River in Serbia L. Stričević et al. https://doi.org/10.37040/geografie.2026.002
72. An increase in the spatial extent of European floods over the last 70 years B. Fang et al. https://doi.org/10.5194/hess-28-3755-2024
73. Causes, seasonality and climate variability of floods in southern Brazil V. Kuchinski & R. Cauduro Dias de Paiva https://doi.org/10.1080/02626667.2026.2651371
74. Occasional Floods On The Rivers Of Russian Plain In The 20^Th –21^St Centuries M. Kireeva et al. https://doi.org/10.24057/2071-9388-2020-29
75. Trends in Global Flood and Streamflow Timing Based on Local Water Year C. Wasko et al. https://doi.org/10.1029/2020WR027233
76. Deoxynivalenol Occurrence in Triticale Crops in Romania during the 2012–2014 Period with Extreme Weather Events V. Gagiu et al. https://doi.org/10.3390/toxins13070456
77. The effects of rising temperatures on flood quantiles in the Italian Alps can be amplified by different catchment morphologies G. Evangelista et al. https://doi.org/10.1016/j.jhydrol.2025.134014
78. A Probabilistic Model of the Economic Risk to Britain's Railway Network from Bridge Scour During Floods R. Lamb et al. https://doi.org/10.1111/risa.13370