90 citations as recorded by crossref.

1. Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale K. Mikołajewski et al. https://doi.org/10.1016/j.scitotenv.2022.154588
2. A web-based pesticide risk assessment tool for drinking water protection zones in Sweden A. Lindahl et al. https://doi.org/10.1016/j.jenvman.2024.120700
3. Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves? P. Ganguli & P. Coulibaly https://doi.org/10.5194/hess-21-6461-2017
4. Flood risk assessment for informal settlements R. De Risi et al. https://doi.org/10.1007/s11069-013-0749-0
5. Multivariate non-parametric Euclidean distance model for hourly disaggregation of daily climate data C. Görner et al. https://doi.org/10.1007/s00704-020-03426-7
6. Space‐time conditional disaggregation of precipitation at high resolution via simulation A. Bárdossy & G. Pegram https://doi.org/10.1002/2015WR018037
7. Revisiting the Statistical Scaling of Annual Discharge Maxima at Daily Resolution with Respect to the Basin Size in the Light of Rainfall Climatology A. Perdios & A. Langousis https://doi.org/10.3390/w12020610
8. Recent changes to the hydrological cycle of an Arctic basin at the tundra–taiga transition S. Krogh & J. Pomeroy https://doi.org/10.5194/hess-22-3993-2018
9. Temporal rainfall disaggregation using a micro-canonical cascade model: possibilities to improve the autocorrelation H. Müller-Thomy https://doi.org/10.5194/hess-24-169-2020
10. Incorporation of weather parameters in MMRC-K model for rainfall disaggregation D. Chowdhury et al. https://doi.org/10.1007/s00477-024-02863-4
11. Random cascade driven rainfall disaggregation for urban hydrology: An evaluation of six models and a new generator P. Licznar et al. https://doi.org/10.1016/j.atmosres.2010.12.014
12. ANALYTICAL APPROXIMATION TO THE DISTRIBUTION OF BREAKDOWN COEFFICIENTS FOR BINARY BETA-LOGNORMAL DISCRETE MULTIFRACTAL CASCADES A. LANGOUSIS et al. https://doi.org/10.1142/S0218348X25501208
13. Controls on atrazine leaching through a soil-unsaturated fractured limestone sequence at Brévilles, France S. Roulier et al. https://doi.org/10.1016/j.jconhyd.2005.12.004
14. Disaggregation of rainfall from daily to 1-hour scale through integrated MMRC-copula modelling P. Biswas & U. Saha https://doi.org/10.1016/j.jhydrol.2024.132338
15. A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities M. Anis & M. Rode https://doi.org/10.1002/hyp.10227
16. Assessment of rainfall spatial variability and its influence on runoff modelling: A case study in the Brue catchment, UK J. Zhang & D. Han https://doi.org/10.1002/hyp.11250
17. A simple approximation to multifractal rainfall maxima using a generalized extreme value distribution model A. Langousis et al. https://doi.org/10.1007/s00477-013-0687-0
18. Innovative use of reanalysis data in Slovenia: Enhancing precipitation time series with a multiplicative cascade model H. Müller-Thomy et al. https://doi.org/10.1016/j.ejrh.2025.102530
19. Statistical framework to simulate daily rainfall series conditional on upper-air predictor variables A. Langousis & V. Kaleris https://doi.org/10.1002/2013WR014936
20. Distributions of microcanonical cascade weights of rainfall at small timescales P. Licznar et al. https://doi.org/10.2478/s11600-011-0014-4
21. Spatiotemporal characteristics of rainfall process in a small mountainous catchment J. Cheng et al. https://doi.org/10.1007/s11629-024-8902-7
22. Temporal rainfall disaggregation using a multiplicative cascade model for spatial application in urban hydrology H. Müller & U. Haberlandt https://doi.org/10.1016/j.jhydrol.2016.01.031
23. Variability in the scale properties of high‐resolution precipitation data in the Alpine climate of Switzerland P. Molnar & P. Burlando https://doi.org/10.1029/2007WR006142
24. New asymptotic and preasymptotic results on rainfall maxima from multifractal theory D. Veneziano et al. https://doi.org/10.1029/2009WR008257
25. Evaluating changes and estimating seasonal precipitation for the Colorado River Basin using a stochastic nonparametric disaggregation technique A. Kalra & S. Ahmad https://doi.org/10.1029/2010WR009118
26. Temporal Rainfall Disaggregation with a Cascade Model: From Single-Station Disaggregation to Spatial Rainfall H. Müller & U. Haberlandt https://doi.org/10.1061/(ASCE)HE.1943-5584.0001195
27. Temperature-Driven Rise in Extreme Sub-Hourly Rainfall G. Bürger et al. https://doi.org/10.1175/JCLI-D-19-0136.1
28. Stochastic temporal disaggregation of monthly precipitation for regional gridded data sets S. Thober et al. https://doi.org/10.1002/2014WR015930
29. Obtaining daily precipitation parameters from meteorological yearbooks F. Meza https://doi.org/10.1016/j.agrformet.2006.04.007
30. Developing a framework for attribution analysis of urban pluvial flooding to human-induced climate impacts H. Tabari et al. https://doi.org/10.1016/j.jhydrol.2021.126352
31. Circulation pattern based parameterization of a multiplicative random cascade for disaggregation of observed and projected daily rainfall time series D. Lisniak et al. https://doi.org/10.5194/hess-17-2487-2013
32. Assessing the short, medium, and long-term impacts of climate change on crop water availability of maize and paddy A. Bashir et al. https://doi.org/10.1007/s12040-026-02801-8
33. The impact of tipping‐bucket raingauge measurement errors on design rainfall for urban‐scale applications A. Molini et al. https://doi.org/10.1002/hyp.5646
34. Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model J. Ding et al. https://doi.org/10.1002/hyp.10725
35. Suction Stress–Based Rainfall Intensity–Duration Method for Slope Instability Prediction N. Lu et al. https://doi.org/10.1061/JGGEFK.GTENG-12597
36. Rainfall Generation Revisited: Introducing CoSMoS‐2s and Advancing Copula‐Based Intermittent Time Series Modeling S. Papalexiou https://doi.org/10.1029/2021WR031641
37. Quantitative assessment of annual maxima, peaks-over-threshold and multifractal parametric approaches in estimating intensity-duration-frequency curves from short rainfall records S. Emmanouil et al. https://doi.org/10.1016/j.jhydrol.2020.125151
38. Estimation of intensity–duration–frequency curves using max-stable processes H. Tyralis & A. Langousis https://doi.org/10.1007/s00477-018-1577-2
39. Intra‐event intermittency of rainfall: an analysis of the metrics of rain and no‐rain periods D. Dunkerley https://doi.org/10.1002/hyp.10454
40. Flood hazard mapping using FLO-2D and local management strategies of Dire Dawa city, Ethiopia S. Erena et al. https://doi.org/10.1016/j.ejrh.2018.09.005
41. Assessing the performance of daily to subdaily temporal disaggregation methods for the IDF curve generation under climate change F. Alzahrani et al. https://doi.org/10.2166/wcc.2023.507
42. The global space–time cascade structure of precipitation: Satellites, gridded gauges and reanalyses S. Lovejoy et al. https://doi.org/10.1016/j.advwatres.2012.03.024
43. Sustainable Development of Storm-water Systems in African Cities Considering Climate Change F. De Paola et al. https://doi.org/10.1016/j.proeng.2015.08.970
44. Analysis and modelling of rainfall fields at different resolutions in southern Italy D. De Luca https://doi.org/10.1080/02626667.2014.926013
45. Improving the accuracy of tipping-bucket rain records using disaggregation techniques A. Molini et al. https://doi.org/10.1016/j.atmosres.2004.12.013
46. Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities F. De Paola et al. https://doi.org/10.1186/2193-1801-3-133
47. An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.1) K. Förster et al. https://doi.org/10.5194/gmd-9-2315-2016
48. Precipitation variability within an urban monitoring network via microcanonical cascade generators P. Licznar et al. https://doi.org/10.5194/hess-19-485-2015
49. Spatial random downscaling of rainfall signals in Andean heterogeneous terrain A. Posadas et al. https://doi.org/10.5194/npg-22-383-2015
50. Incorporating parameter dependencies into temporal downscaling of extreme rainfall using a random cascade approach N. McIntyre et al. https://doi.org/10.1016/j.jhydrol.2016.09.057
51. Assessing the Effect of Bias Correction Methods on the Development of Intensity–Duration–Frequency Curves Based on Projections from the CORDEX Central America GCM-RCM Multimodel-Ensemble M. Mendez et al. https://doi.org/10.3390/w16233473
52. Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling J. Sheffield et al. https://doi.org/10.1175/JCLI3790.1
53. Time scale and intensity dependency in multiplicative cascades for temporal rainfall disaggregation D. Rupp et al. https://doi.org/10.1029/2008WR007321
54. Assessment of future changes in intensity-duration-frequency curves for Southern Ontario using North American (NA)-CORDEX models with nonstationary methods P. Ganguli & P. Coulibaly https://doi.org/10.1016/j.ejrh.2018.12.007
55. Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model S. Krogh et al. https://doi.org/10.1016/j.jhydrol.2017.05.042
56. Temporal Disaggregation of Rainfall Based on Microcanonical Cascade Model (A Software Development and Case Study) M. Ghorbani et al. https://doi.org/10.29252/jwmr.9.17.96
57. Interactions between soil structure dynamics, hydrological processes, and organic matter cycling: A new soil‐crop model N. Jarvis et al. https://doi.org/10.1111/ejss.13455
58. A stochastic model for daily rainfall disaggregation into fine time scale for a large region Y. Gyasi-Agyei & S. Mahbub https://doi.org/10.1016/j.jhydrol.2007.09.047
59. Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model P. Molnar & P. Burlando https://doi.org/10.1016/j.atmosres.2004.10.024
60. Identification of hydrological models for operational flood forecasting in St. John’s, Newfoundland, Canada D. Wijayarathne & P. Coulibaly https://doi.org/10.1016/j.ejrh.2019.100646
61. On temporal stochastic modeling of precipitation, nesting models across scales A. Paschalis et al. https://doi.org/10.1016/j.advwatres.2013.11.006
62. GEV Parameter Estimation and Stationary vs. Non-Stationary Analysis of Extreme Rainfall in African Test Cities F. De Paola et al. https://doi.org/10.3390/hydrology5020028
63. Generating hourly mean areal precipitation times series with an at-site weather generator in Switzerland K. Maloku et al. https://doi.org/10.1007/s00477-024-02757-5
64. A Multi criteria Decision Making based nonparametric method of fragments to disaggregate daily precipitation V. Manikanta et al. https://doi.org/10.1016/j.jhydrol.2022.128994
65. Nordic contributions to stochastic methods in hydrology D. Rosbjerg et al. https://doi.org/10.2166/nh.2022.137
66. A continuous modelling approach for design flood estimation on sub-daily time scale B. Winter et al. https://doi.org/10.1080/02626667.2019.1593419
67. Use of observed scaled daily storm profiles in a copula based rainfall disaggregation model Y. Gyasi-Agyei https://doi.org/10.1016/j.advwatres.2011.11.003
68. Applicability of statistical and deep-learning models for rainfall disaggregation at metropolitan stations in India D. Bhattacharyya et al. https://doi.org/10.1016/j.ejrh.2023.101616
69. Temporal downscaling rainfall and streamflow records through a deterministic fractal geometric approach M. Maskey et al. https://doi.org/10.1016/j.jhydrol.2018.09.014
70. Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries I. Pohle et al. https://doi.org/10.1016/j.jhydrol.2018.04.063
71. Improvement of extreme rainfall characteristics for disaggregation of rainfall using MMRC with machine learning based DBSCAN clustering algorithm D. Chowdhury & U. Saha https://doi.org/10.1007/s12145-024-01309-3
72. Long‐Term Effects of No‐Till Systems on Soil Structure and Function Under Climate Change: An Exploratory Modelling Study M. Feifel et al. https://doi.org/10.1111/ejss.70259
73. Stochastic disaggregation of daily rainfall into one-hour time scale Y. Gyasi-Agyei https://doi.org/10.1016/j.jhydrol.2004.11.018
74. Modern proposal of methodology for retrieval of characteristic synthetic rainfall hyetographs P. Licznar et al. https://doi.org/10.1051/e3sconf/20172200104
75. Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data N. Ebers et al. https://doi.org/10.5194/nhess-24-2025-2024
76. Statistical performances of various deterministic and stochastic models for rainfall series disaggregation B. Hingray & M. Ben Haha https://doi.org/10.1016/j.atmosres.2004.10.023
77. Rainfall stochastic disaggregation models: Calibration and validation of a multiplicative cascade model E. Gaume et al. https://doi.org/10.1016/j.advwatres.2006.11.007
78. Current Awareness https://doi.org/10.1002/hyp.538
79. A methodology for temporal disaggregation of daily rain gauge data using satellite precipitation product for improved accuracy in hydrologic simulation N. Kachhawa & P. Agnihotri https://doi.org/10.2166/wpt.2023.199
80. Introduction of k-means clustering into random cascade model for disaggregation of rainfall from daily to 1-hour resolution with improved preservation of extreme rainfall P. Deka & U. Saha https://doi.org/10.1016/j.jhydrol.2023.129478
81. Sub-daily rainfall simulation using multifractal canonical disaggregation: a parsimonious calibration strategy based on intensity-duration-frequency curves F. Cappelli et al. https://doi.org/10.1007/s00477-024-02827-8
82. Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows U. Haberlandt & I. Radtke https://doi.org/10.5194/hess-18-353-2014
83. Stochastic Space–Time Disaggregation of Rainfall into DSD fields M. Schleiss & A. Berne https://doi.org/10.1175/JHM-D-12-013.1
84. A new discrete multiplicative random cascade model for downscaling intermittent rainfall fields M. Schleiss https://doi.org/10.5194/hess-24-3699-2020
85. Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model K. Maloku et al. https://doi.org/10.5194/hess-27-3643-2023
86. Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand D. Sharma et al. https://doi.org/10.5194/hess-11-1373-2007
87. Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model? H. Müller-Thomy & A. Sikorska-Senoner https://doi.org/10.1080/02626667.2019.1638926
88. Modelling the dependence and internal structure of storm events for continuous rainfall simulation Y. Gyasi-Agyei & C. Melching https://doi.org/10.1016/j.jhydrol.2012.07.014
89. Multisite multivariate disaggregation of climate parameters using multiplicative random cascades A. Gaur & M. Lacasse https://doi.org/10.1016/j.uclim.2018.08.010
90. Evaluation of medium-range runoff forecasts for a 50 km2 watershed D. Kneis et al. https://doi.org/10.1016/j.jhydrol.2011.11.005