72 citations as recorded by crossref.

1. Linear, nonlinear, parametric and nonparametric regression models for nonstationary flood frequency analysis M. Chen et al. https://doi.org/10.1016/j.jhydrol.2022.128772
2. An improved SWAT snowmelt model and its application in non-stationary spring flood frequency analysis in alpine regions: a case study of the upper Jinsha River basin Y. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.133808
3. Nonstationary hydrological frequency analysis in light of model parameters and climate projections uncertainty Y. Hu et al. https://doi.org/10.1016/j.jhydrol.2023.129120
4. Nonstationary frequency analysis of the recent extreme precipitation events in the United States T. Vu & A. Mishra https://doi.org/10.1016/j.jhydrol.2019.05.090
5. Reliability, return periods, and risk under nonstationarity L. Read & R. Vogel https://doi.org/10.1002/2015WR017089
6. Parsimonious nonstationary flood frequency analysis J. Serago & R. Vogel https://doi.org/10.1016/j.advwatres.2017.11.026
7. Design considerations for riverine floods in a changing climate – A review B. François et al. https://doi.org/10.1016/j.jhydrol.2019.04.068
8. Linking temperature to catastrophe damages from hydrologic and meteorological extremes C. Wasko et al. https://doi.org/10.1016/j.jhydrol.2021.126731
9. Estimating the scale parameter of the norming constants method in analysing nonstationary annual maximum floods W. Xu et al. https://doi.org/10.1002/hyp.14797
10. Nonstationary Frequency Analysis of Annual Maximum Flow Series: Climate Change Versus Land Use/Land Cover Change M. Yegin et al. https://doi.org/10.1007/s11269-025-04277-5
11. Design flood estimation in flood hazard studies: a three-decade systematic review of practices in Canada C. Vidrio-Sahagún et al. https://doi.org/10.1080/07011784.2025.2462603
12. An Adaptive Metropolis-Hastings Optimization Algorithm of Bayesian Estimation in Non-Stationary Flood Frequency Analysis W. Xu et al. https://doi.org/10.1007/s11269-017-1873-5
13. Estimating Optimal Design Frequency and Future Hydrological Risk in Local River Basins According to RCP Scenarios J. Ryu et al. https://doi.org/10.3390/w14060945
14. Comparing Flood Projection Approaches Across Hydro‐Climatologically Diverse United States River Basins K. Schlef et al. https://doi.org/10.1029/2019WR025861
15. Beyond Simple Trend Tests: Detecting Significant Changes in Design‐Flood Quantiles C. Awasthi et al. https://doi.org/10.1029/2023GL103438
16. USO DE MODELAGEM NA DETERMINAÇÃO DE REGIÕES COM RISCO DE INUNDAÇÃO: UMA REVISÃO SISTEMÁTICA D. Bahia et al. https://doi.org/10.24857/rgsa.v18n1-100
17. Return period and risk analysis of nonstationary low-flow series under climate change T. Du et al. https://doi.org/10.1016/j.jhydrol.2015.04.041
18. Model Selection Challenges in Non-Stationary Precipitation Estimation: The Role of AIC, BIC, and Covariate Choice M. Yegin et al. https://doi.org/10.1007/s11269-025-04357-6
19. Comparison of time trend- and precipitation-informed models for assessing design discharges in variable climate M. Šraj & N. Bezak https://doi.org/10.1016/j.jhydrol.2020.125374
20. 21st Century flood risk projections at select sites for the U.S. National Park Service P. Van Dusen et al. https://doi.org/10.1016/j.crm.2020.100211
21. Incorporating climate change projections into riparian restoration planning and design L. Perry et al. https://doi.org/10.1002/eco.1645
22. Comparison of four nonstationary hydrologic design methods for changing environment L. Yan et al. https://doi.org/10.1016/j.jhydrol.2017.06.001
23. Hydrological extremes across the Commonwealth of Massachusetts in a changing climate R. Siddique et al. https://doi.org/10.1016/j.ejrh.2020.100733
24. Time-varying copula and average annual reliability-based nonstationary hazard assessment of extreme rainfall events P. Xu et al. https://doi.org/10.1016/j.jhydrol.2021.126792
25. Multi-covariate non-stationary flood frequency analysis for assessing flood hazard over the Mahanadi River basin, India S. Bhere & M. Janga Reddy https://doi.org/10.1080/02626667.2024.2421972
26. A novel decomposition-based approach for non-stationary hub-height wind speed modelling Z. Yang & S. Dong https://doi.org/10.1016/j.energy.2023.129081
27. Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China Y. Liu et al. https://doi.org/10.1002/joc.8373
28. Using Climate and Weather Data to Support Regional Vulnerability Screening Assessments of Transportation Infrastructure L. Dundon et al. https://doi.org/10.3390/risks4030028
29. Adaptive reservoir flood limited water level for a changing environment X. Zhang et al. https://doi.org/10.1007/s12665-017-7086-7
30. Trends in hydrological extremes in the Senegal and Niger Rivers C. Wilcox et al. https://doi.org/10.1016/j.jhydrol.2018.07.063
31. Daily maximum runoff frequency analysis under non-stationary conditions due to climate change in the future period: Case study Ghareh Sou basin N. Sadeghi Loyeh & A. Massah Bavani https://doi.org/10.2166/wcc.2021.074
32. Flood risk analysis integrating of Bayesian-based time-varying model and expected annual damage considering non-stationarity and uncertainty in the coastal city X. Guan et al. https://doi.org/10.1016/j.jhydrol.2022.129038
33. Bridge Adaptation and Management under Climate Change Uncertainties: A Review A. Mondoro et al. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000270
34. A non-stationary cost-benefit based bivariate extreme flood estimation approach W. Qi & J. Liu https://doi.org/10.1016/j.jhydrol.2017.12.045
35. Introduction of the neural framework for stationary and nonstationary probability distribution modelling of hydroclimatological extremes in Canada, and performance comparison with classical models S. Latif & T. Ouarda https://doi.org/10.1016/j.ejrh.2026.103265
36. A General Methodology for Climate‐Informed Approaches to Long‐Term Flood Projection—Illustrated With the Ohio River Basin K. Schlef et al. https://doi.org/10.1029/2018WR023209
37. Updating urban design floods for changes in central tendency and variability using regression J. Hecht & R. Vogel https://doi.org/10.1016/j.advwatres.2019.103484
38. A systematic review of climate change science relevant to Australian design flood estimation C. Wasko et al. https://doi.org/10.5194/hess-28-1251-2024
39. Response of Water Resources to Future Climate Change in a High-Latitude River Basin P. Qi et al. https://doi.org/10.3390/su11205619
40. Assessing the impact of climate on annual and seasonal discharges at the Sremska Mitrovica station on the Sava River, Serbia I. Leščešen et al. https://doi.org/10.2166/ws.2021.277
41. Spatial and Temporal Patterns in Nonstationary Flood Frequency across a Forest Watershed: Linkage with Rainfall and Land Use Types X. Huang et al. https://doi.org/10.3390/f9060339
42. Integrated Modeling Approach for the Development of Climate-Informed, Actionable Information D. Judi et al. https://doi.org/10.3390/w10060775
43. A risk-based analytical framework for quantifying non-stationary flood risks and establishing infrastructure design standards in a changing environment K. Byun & A. Hamlet https://doi.org/10.1016/j.jhydrol.2020.124575
44. Techniques for assessing water infrastructure for nonstationary extreme events: a review J. Salas et al. https://doi.org/10.1080/02626667.2018.1426858
45. Conditional Value-at-Risk for Nonstationary Streamflow and Its Application for Derivation of the Adaptive Reservoir Flood Limited Water Level X. Zhang et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000906
46. A methodological framework to assess PMP and PMF in snow-dominated watersheds under changing climate conditions – A case study of three watersheds in Québec (Canada) H. Rouhani & R. Leconte https://doi.org/10.1016/j.jhydrol.2018.04.047
47. Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins R. Mantilla et al. https://doi.org/10.5194/hess-28-1373-2024
48. Assessment of Climate Change Impact on Flood Hazard Zones T. Dysarz et al. https://doi.org/10.1007/s11269-024-04002-8
49. Intensity-duration-frequency curves in the municipality of Belo Horizonte from the perspective of non-stationarity A. Nunes et al. https://doi.org/10.1590/2318-0331.262120210017
50. Modelling climate change-induced nonstationarity in rainfall extremes: A comprehensive approach for hydrological analysis . Ankush et al. https://doi.org/10.1016/j.techfore.2024.123693
51. Incorporating climate change in flood estimation guidance C. Wasko et al. https://doi.org/10.1098/rsta.2019.0548
52. A non-stationary cost-benefit analysis approach for extreme flood estimation to explore the nexus of ‘Risk, Cost and Non-stationarity’ W. Qi https://doi.org/10.1016/j.jhydrol.2017.09.009
53. Modeling extremal streamflow using deep learning approximations and a flexible spatial process R. Majumder et al. https://doi.org/10.1214/23-AOAS1847
54. Frequency analysis of nonstationary annual maximum flood series using the time‐varying two‐component mixture distributions L. Yan et al. https://doi.org/10.1002/hyp.10965
55. Nonstationary frequency pairing reveals a highly sensitive peak flow regime to harvesting across a wide range of return periods X. Yu & Y. Alila https://doi.org/10.1016/j.foreco.2019.04.008
56. An appraisal of flood events using IMD, CRU, and CCSM4-derived meteorological data sets over the Vaigai river basin, Tamil Nadu (India) S. Nagalapalli et al. https://doi.org/10.1007/s40899-019-00325-2
57. Changing Seasonality of Annual Maximum Floods over the Conterminous US: Potential Drivers and Regional Synthesis B. Basu et al. https://doi.org/10.1061/JHYEFF.HEENG-5768
58. Understanding the organizing scales of winter flood hydroclimatology and the associated drivers over the coterminous United States J. Hwang et al. https://doi.org/10.1016/j.hydroa.2025.100200
59. Hydrologic State Influence on Riverine Flood Discharge for a Small Temperate Watershed (Fall Creek, United States): Negative Feedbacks on the Effects of Climate Change J. Knighton et al. https://doi.org/10.1175/JHM-D-16-0164.1
60. Bivariate Flood Frequency Analysis of Nonstationary Flood Characteristics N. Dong et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001770
61. Modelling and quantifying tomorrow's risks from natural hazards G. Cremen et al. https://doi.org/10.1016/j.scitotenv.2021.152552
62. Can direct CMIP6 model simulations reproduce mean annual historical streamflow change? Q. Huang et al. https://doi.org/10.1016/j.catena.2023.107650
63. Uncertainty introduced by flood frequency analysis in projections for changes in flood magnitudes under a future climate in Norway D. Lawrence https://doi.org/10.1016/j.ejrh.2020.100675
64. Inverse identification of pollution source release information for surface river chemical spills using a hybrid optimization model D. Jiang et al. https://doi.org/10.1016/j.jenvman.2021.113022
65. 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 https://doi.org/10.1007/s11269-018-2058-6
66. Review: Can temperature be used to inform changes to flood extremes with global warming? C. Wasko https://doi.org/10.1098/rsta.2019.0551
67. A deep learning synthetic likelihood approximation of a non-stationary spatial model for extreme streamflow forecasting R. Majumder & B. Reich https://doi.org/10.1016/j.spasta.2023.100755
68. Evaluating the Hydrologic Risk of n-Year Floods According to RCP Scenarios J. Lee et al. https://doi.org/10.3390/w13131805
69. Non-stationary flood frequency analysis and attribution of streamflow series: a case study of Periyar River, India N. Singh & P. Chinnasamy https://doi.org/10.1080/02626667.2021.1968406
70. Nonstationary Flood Hazard Analysis in Response to Climate Change and Population Growth L. Yan et al. https://doi.org/10.3390/w11091811
71. Quantifying multivariate flood risk under nonstationary condition R. Li et al. https://doi.org/10.1007/s11069-022-05716-x
72. Copula-based multivariate flood probability construction: a review S. Latif & F. Mustafa https://doi.org/10.1007/s12517-020-5077-6