141 citations as recorded by crossref.

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27. Aesthetical Issues of Leonardo Da Vinci’s and Pablo Picasso’s Paintings with Stochastic Evaluation G. Sargentis et al. https://doi.org/10.3390/heritage3020017
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30. The mode of the climacogram estimator for a Gaussian Hurst-Kolmogorov process P. Dimitriadis & D. Koutsoyiannis https://doi.org/10.2166/hydro.2019.038
31. Stochastic investigation of daily air temperature extremes from a global ground station network K. Glynis et al. https://doi.org/10.1007/s00477-021-02002-3
32. A blueprint for process‐based modeling of uncertain hydrological systems A. Montanari & D. Koutsoyiannis https://doi.org/10.1029/2011WR011412
33. Unsurprising Surprises: The Frequency of Record‐breaking and Overthreshold Hydrological Extremes Under Spatial and Temporal Dependence F. Serinaldi & C. Kilsby https://doi.org/10.1029/2018WR023055
34. Generic Framework for Downscaling Statistical Quantities at Fine Time-Scales and Its Perspectives towards Cost-Effective Enrichment of Water Demand Records P. Kossieris et al. https://doi.org/10.3390/w13233429
35. Randomness: a property of the mathematical and physical systems A. Tsonis https://doi.org/10.1080/02626667.2014.992434
36. Spatiotemporal clustering of streamflow extremes and relevance to flood insurance claims: a stochastic investigation for the contiguous USA K. Papoulakos et al. https://doi.org/10.1007/s11069-024-06766-z
37. Understanding Persistence to Avoid Underestimation of Collective Flood Risk F. Serinaldi & C. Kilsby https://doi.org/10.3390/w8040152
38. A Stochastic View of Varying Styles in Art Paintings G. Sargentis et al. https://doi.org/10.3390/heritage4010021
39. Modern Use of Traditional Rainwater Harvesting Practices: An Assessment of Cisterns’ Water Supply Potential in West Mani, Greece T. Iliopoulou et al. https://doi.org/10.3390/heritage5040152
40. A decade of Predictions in Ungauged Basins (PUB)—a review M. Hrachowitz et al. https://doi.org/10.1080/02626667.2013.803183
41. So how much of your error is epistemic? Lessons from Japan and Italy K. Beven https://doi.org/10.1002/hyp.9648
42. An overview of current applications, challenges, and future trends in distributed process-based models in hydrology S. Fatichi et al. https://doi.org/10.1016/j.jhydrol.2016.03.026
43. Negligent killing of scientific concepts: the stationarity case D. Koutsoyiannis & A. Montanari https://doi.org/10.1080/02626667.2014.959959
44. A Multilayer Perceptron Model for Stochastic Synthesis E. Rozos et al. https://doi.org/10.3390/hydrology8020067
45. On the Sensitivity of Standardized-Precipitation-Evapotranspiration and Aridity Indexes Using Alternative Potential Evapotranspiration Models A. Tegos et al. https://doi.org/10.3390/hydrology10030064
46. Long‐Lead Drought Forecasting Across the Continental United States Using Burg Entropy Spectral Analysis With a Multiresolution Approach J. Han & V. Singh https://doi.org/10.1029/2022WR034188
47. Knowable moments for high-order stochastic characterization and modelling of hydrological processes D. Koutsoyiannis https://doi.org/10.1080/02626667.2018.1556794
48. Predictability in dice motion: how does it differ from hydro-meteorological processes? P. Dimitriadis et al. https://doi.org/10.1080/02626667.2015.1034128
49. Do probabilistic forecasts lead to better decisions? M. Ramos et al. https://doi.org/10.5194/hess-17-2219-2013
50. Climate Consensus and ‘Misinformation’: A Rejoinder to Agnotology, Scientific Consensus, and the Teaching and Learning of Climate Change D. Legates et al. https://doi.org/10.1007/s11191-013-9647-9
51. Stochastic Modeling of Hydroclimatic Processes Using Vine Copulas G. Pouliasis et al. https://doi.org/10.3390/w13162156
52. Reconciling the signal and noise of atmospheric warming on decadal timescales R. Jones & J. Ricketts https://doi.org/10.5194/esd-8-177-2017
53. Hydrological time series forecasting using simple combinations: Big data testing and investigations on one-year ahead river flow predictability G. Papacharalampous & H. Tyralis https://doi.org/10.1016/j.jhydrol.2020.125205
54. Preface—Special Issue: Facets of Uncertainty A. Carsteanu et al. https://doi.org/10.1080/02626667.2016.1186919
55. Investigation on the stochastic nature of the solar radiation process G. Koudouris et al. https://doi.org/10.1016/j.egypro.2017.08.076
56. Stochastic assessment of temperature–CO₂ causal relationship in climate from the Phanerozoic through modern times D. Koutsoyiannis https://doi.org/10.3934/mbe.2024287
57. Just a Single-Layer CNN for Stochastic Modeling: A Discriminator-Free Approach E. Rozos https://doi.org/10.3390/hydrology12070170
58. Revisiting the global hydrological cycle: is it intensifying? D. Koutsoyiannis https://doi.org/10.5194/hess-24-3899-2020
59. On the long-range dependence properties of annual precipitation using a global network of instrumental measurements H. Tyralis et al. https://doi.org/10.1016/j.advwatres.2017.11.010
60. 3D stochastic modeling of flow and solute transport in karst vadose zone D. Zeqiraj https://doi.org/10.1016/j.cscee.2022.100217
61. Stochastic investigation of long-term persistence in two-dimensional images of rocks P. Dimitriadis et al. https://doi.org/10.1016/j.spasta.2018.11.002
62. Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms G. Papacharalampous et al. https://doi.org/10.3390/w11102126
63. Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices J. Haas & S. Birk https://doi.org/10.5194/hess-21-2421-2017
64. Global Sensitivity Analysis for Multiple Interpretive Models With Uncertain Parameters A. Dell'Oca et al. https://doi.org/10.1029/2019WR025754
65. Stochastic simulation of wind wave parameters for energy production K. Kardakaris et al. https://doi.org/10.1016/j.oceaneng.2023.114029
66. Knowable Moments in Stochastics: Knowing Their Advantages D. Koutsoyiannis https://doi.org/10.3390/axioms12060590
67. On Hens, Eggs, Temperatures and CO2: Causal Links in Earth’s Atmosphere D. Koutsoyiannis et al. https://doi.org/10.3390/sci5030035
68. Time’s arrow in stochastic characterization and simulation of atmospheric and hydrological processes D. Koutsoyiannis https://doi.org/10.1080/02626667.2019.1600700
69. Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale G. Papacharalampous et al. https://doi.org/10.1016/j.gsf.2022.101349
70. Developing the Actual Precipitation Probability Distribution Based on the Complete Daily Series W. Zhai et al. https://doi.org/10.3390/su151713136
71. Landscape Planning of Infrastructure through Focus Points’ Clustering Analysis. Case Study: Plastiras Artificial Lake (Greece) G. Sargentis et al. https://doi.org/10.3390/infrastructures6010012
72. Irreversibility and complex network behavior of stream flow fluctuations F. Serinaldi & C. Kilsby https://doi.org/10.1016/j.physa.2016.01.043
73. Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale G. Papacharalampous et al. https://doi.org/10.1016/j.advwatres.2019.103470
74. Characterisation of hydroclimatological trends and variability in the Lake Naivasha basin, Kenya V. Odongo et al. https://doi.org/10.1002/hyp.10443
75. Can we tell more than we can know? The limits of bivariate drought analyses in the United States F. Serinaldi https://doi.org/10.1007/s00477-015-1124-3
76. Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy G. Tsekouras & D. Koutsoyiannis https://doi.org/10.1016/j.renene.2013.10.018
77. Global Investigation of Double Periodicity οf Hourly Wind Speed for Stochastic Simulation; Application in Greece I. Deligiannis et al. https://doi.org/10.1016/j.egypro.2016.10.001
78. A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes P. Dimitriadis et al. https://doi.org/10.3390/hydrology8020059
79. The tales that the distribution tails of non-Gaussian autocorrelated processes tell: efficient methods for the estimation of the k -length block-maxima distribution I. Tsoukalas https://doi.org/10.1080/02626667.2021.2014056
80. The Spatial Scale Dependence of The Hurst Coefficient in Global Annual Precipitation Data, and Its Role in Characterising Regional Precipitation Deficits within a Naturally Changing Climate E. O’Connell et al. https://doi.org/10.3390/hydrology9110199
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83. Facets of uncertainty: epistemic uncertainty, non-stationarity, likelihood, hypothesis testing, and communication K. Beven https://doi.org/10.1080/02626667.2015.1031761
84. Projecting the future of rainfall extremes: Better classic than trendy T. Iliopoulou & D. Koutsoyiannis https://doi.org/10.1016/j.jhydrol.2020.125005
85. Unlocking the potential of stochastic simulation through Bluecat: Enhancing runoff predictions in arid and high‐altitude regions J. Jorquera & A. Pizarro https://doi.org/10.1002/hyp.15046
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88. Stochastic synthesis approximating any process dependence and distribution P. Dimitriadis & D. Koutsoyiannis https://doi.org/10.1007/s00477-018-1540-2
89. Time scale and influencing factor variations of water and heat fluxes in sandy land X. Li et al. https://doi.org/10.2166/nh.2022.020
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94. Climacogram versus autocovariance and power spectrum in stochastic modelling for Markovian and Hurst–Kolmogorov processes P. Dimitriadis & D. Koutsoyiannis https://doi.org/10.1007/s00477-015-1023-7
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98. An analysis of change in alpine annual maximum discharges: implications for the selection of design discharges A. Castellarin & A. Pistocchi https://doi.org/10.1002/hyp.8249
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