Γενικευμένο μαθηματικό πλαίσιο για τη στοχαστική προσομοίωση και πρόγνωση υδρολογικών χρονοσειρών

D. Koutsoyiannis, A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series, Water Resources Research, 36 (6), 1519–1533, doi:10.1029/2000WR900044, 2000.

[Γενικευμένο μαθηματικό πλαίσιο για τη στοχαστική προσομοίωση και πρόγνωση υδρολογικών χρονοσειρών]

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[Αγγλικά]

Προτείνεται μια γενικευμένη μεθοδολογία για προβλήματα προσομοίωσης και πρόγνωσης μιας και πολλών μεταβλητών στη στοχαστική υδρολογία. Η μεθοδολογία είναι κατάλληλη για ανελίξεις με βραχυπρόθεσμη και μακροπρόθεσμη εμμονή και διατηρεί το συντελεστή Hurst ακόμη και σε πολυμεταβλητά προβλήματα με διαφορετικό συντελεστή Hurst σε κάθε θέση. Ταυτόχρονα, διατηρεί άμεσα τους συντελεστές ασυμμετρίας των ανελίξεων. Η μεθοδολογία που προτείνεται ενσωματώνει μοντέλα βραχυπρόθεσμης εμμονής (αυτοπαλινδρόμησης - κυλιόμενου μέσου) και μακροπρόθεσμης εμμονής (κλασματικού Γκαουσιανού θορύβου), θεωρώντας τα ως ειδικές περιπτώσεις μιας παραμετρικά ορισμένης γενικής συνάρτησης αυτοσυνδιασποράς, η οποία είναι ευρύτερη από αυτές που χρησιμοποιούνται στις εν λόγω κατηγορίες μοντέλων. Η γενικευμένη συνάρτηση αυτοσυνδιασποράς υλοποιείται με ένα γενικευμένο σχήμα γεννήτριας, τύπου κυλιόμενου μέσου, που παρέχει μια νέα συμμετρική ως προς το χρόνο έκφραση, τα πλεονεκτήματα της οποίας μελετώνται. Αναπτύσσονται ταχείς αλγόριθμοι για τον υπολογισμό των εσωτερικών παραμέτρων της γεννήτριας, κατάλληλοι για προβλήματα που περιλαμβάνουν ακόμη και χιλιάδες παραμέτρους. Επίσης, το σχήμα γέννησης που προτείνεται διασκευάζεται κατάλληλα, μέσω μιας γενικευμένης μεθοδολογίας, σε τρόπο ώστε να λειτουργεί, πέρα από την προσομοίωση, και σε μορφή πρόγνωσης. Τέλος, εξετάζεται μια ειδική μορφή του μοντέλου για προβλήματα όπου η αυτοσυσχέτιση μπορεί να οριστεί μόνο για ένα πεπερασμένο αριθμό υστερήσεων. Η διευκρίνιση των χαρακτηριστικών και της επίδοσης των διάφορων συνιστωσών της μεθοδολογίας γίνονται μέσω σειράς παραδειγμάτων.

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Βλέπε επίσης: http://dx.doi.org/10.1029/2000WR900044

Σημείωση:

Η μεθοδολογία αξιοποιήθηκε στην ανάπτυξη του πακέτου λογισμικού για τη στοχαστική προσομοίωση υδρολογικών μεταβλητών "ΚΑΣΤΑΛΙΑ".

Εργασίες μας στις οποίες αναφέρεται αυτή η εργασία:

1. D. Koutsoyiannis, and E. Foufoula-Georgiou, A scaling model of storm hyetograph, Water Resources Research, 29 (7), 2345–2361, doi:10.1029/93WR00395, 1993.
2. D. Koutsoyiannis, and A. Manetas, Simple disaggregation by accurate adjusting procedures, Water Resources Research, 32 (7), 2105–2117, doi:10.1029/96WR00488, 1996.
3. D. Koutsoyiannis, Optimal decomposition of covariance matrices for multivariate stochastic models in hydrology, Water Resources Research, 35 (4), 1219–1229, doi:10.1029/1998WR900093, 1999.
4. D. Koutsoyiannis, An advanced method for preserving skewness in single-variate, multivariate and disaggregation models in stochastic hydrology, 24th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 1, The Hague, 346, doi:10.13140/RG.2.1.1749.2725, European Geophysical Society, 1999.

Εργασίες μας που αναφέρονται σ' αυτή την εργασία:

1. D. Koutsoyiannis, Coupling stochastic models of different time scales, Water Resources Research, 37 (2), 379–391, doi:10.1029/2000WR900200, 2001.
2. D. Koutsoyiannis, The Hurst phenomenon and fractional Gaussian noise made easy, Hydrological Sciences Journal, 47 (4), 573–595, doi:10.1080/02626660209492961, 2002.
3. D. Koutsoyiannis, A. Efstratiadis, and G. Karavokiros, A decision support tool for the management of multi-reservoir systems, Journal of the American Water Resources Association, 38 (4), 945–958, doi:10.1111/j.1752-1688.2002.tb05536.x, 2002.
4. I. Nalbantis, E. Rozos, G. M. T. Tentes, A. Efstratiadis, and D. Koutsoyiannis, Integrating groundwater models within a decision support system, Proceedings of the 5th International Conference of European Water Resources Association: "Water Resources Management in the Era of Transition", edited by G. Tsakiris, Athens, 279–286, European Water Resources Association, 2002.
5. D. Koutsoyiannis, Climate change, the Hurst phenomenon, and hydrological statistics, Hydrological Sciences Journal, 48 (1), 3–24, doi:10.1623/hysj.48.1.3.43481, 2003.
6. D. Koutsoyiannis, and A. Economou, Evaluation of the parameterization-simulation-optimization approach for the control of reservoir systems, Water Resources Research, 39 (6), 1170, doi:10.1029/2003WR002148, 2003.
7. D. Koutsoyiannis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, and A. Christofides, A decision support system for the management of the water resource system of Athens, Physics and Chemistry of the Earth, 28 (14-15), 599–609, doi:10.1016/S1474-7065(03)00106-2, 2003.
8. Δ. Κουτσογιάννης, και Α. Ευστρατιάδης, Εμπειρία από την ανάπτυξη συστημάτων υποστήριξης αποφάσεων για τη διαχείριση μεγάλης κλίμακας υδροσυστημάτων της Ελλάδας, Πρακτικά της Ημερίδας " Μελέτες και Έρευνες Υδατικών Πόρων στον Κυπριακό Χώρο", επιμέλεια Ε. Σιδηρόπουλος και Ι. Ιακωβίδης, Λευκωσία, 159–180, Τμήμα Αναπτύξεως Υδάτων Κύπρου, Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Θεσσαλονίκη, 2003.
9. A. Efstratiadis, D. Koutsoyiannis, and D. Xenos, Minimizing water cost in the water resource management of Athens, Urban Water Journal, 1 (1), 3–15, doi:10.1080/15730620410001732099, 2004.
10. D. Koutsoyiannis, Uncertainty, entropy, scaling and hydrological stochastics, 2, Time dependence of hydrological processes and time scaling, Hydrological Sciences Journal, 50 (3), 405–426, doi:10.1623/hysj.50.3.405.65028, 2005.
11. A. Christofides, A. Efstratiadis, D. Koutsoyiannis, G.-F. Sargentis, and K. Hadjibiros, Resolving conflicting objectives in the management of the Plastiras Lake: can we quantify beauty?, Hydrology and Earth System Sciences, 9 (5), 507–515, doi:10.5194/hess-9-507-2005, 2005.
12. A. Langousis, and D. Koutsoyiannis, A stochastic methodology for generation of seasonal time series reproducing overyear scaling behaviour, Journal of Hydrology, 322, 138–154, 2006.
13. D. Koutsoyiannis, Nonstationarity versus scaling in hydrology, Journal of Hydrology, 324, 239–254, doi:10.1016/j.jhydrol.2005.09.022, 2006.
14. D. Koutsoyiannis, A. Efstratiadis, and K. Georgakakos, Uncertainty assessment of future hydroclimatic predictions: A comparison of probabilistic and scenario-based approaches, Journal of Hydrometeorology, 8 (3), 261–281, doi:10.1175/JHM576.1, 2007.
15. D. Koutsoyiannis, H. Yao, and A. Georgakakos, Medium-range flow prediction for the Nile: a comparison of stochastic and deterministic methods, Hydrological Sciences Journal, 53 (1), 142–164, doi:10.1623/hysj.53.1.142, 2008.
16. E. Rozos, and D. Koutsoyiannis, Error analysis of a multi-cell groundwater model, Journal of Hydrology, 392 (1-2), 22–30, 2010.
17. D. Koutsoyiannis, and A. Langousis, Precipitation, Treatise on Water Science, edited by P. Wilderer and S. Uhlenbrook, 2, 27–78, doi:10.1016/B978-0-444-53199-5.00027-0, Academic Press, Oxford, 2011.
18. D. Koutsoyiannis, Hurst-Kolmogorov dynamics and uncertainty, Journal of the American Water Resources Association, 47 (3), 481–495, doi:10.1111/j.1752-1688.2011.00543.x, 2011.
19. D. Koutsoyiannis, A. Paschalis, and N. Theodoratos, Two-dimensional Hurst-Kolmogorov process and its application to rainfall fields, Journal of Hydrology, 398 (1-2), 91–100, doi:10.1016/j.jhydrol.2010.12.012, 2011.
20. S.M. Papalexiou, D. Koutsoyiannis, and A. Montanari, Can a simple stochastic model generate rich patterns of rainfall events?, Journal of Hydrology, 411 (3-4), 279–289, 2011.
21. Χ. Ιωάννου, Γ. Τσεκούρας, Α. Ευστρατιάδης, και Δ. Κουτσογιάννης, Στοχαστική ανάλυση και προσομοίωση υδρομετεωρολογικών διεργασιών για τη βελτιστοποίηση ενός υβριδικού συστήματος ανανεώσιμης ενέργειας, Πρακτικά 2ου Πανελλήνιου Συνεδρίου Φραγμάτων και Ταμιευτήρων, Αθήνα, Αίγλη Ζαππείου, doi:10.13140/RG.2.1.3787.0327, Ελληνική Επιτροπή Μεγάλων Φραγμάτων, 2013.
22. G. Tsekouras, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy, Renewable Energy, 63, 624–633, doi:10.1016/j.renene.2013.10.018, 2014.
23. D. Koutsoyiannis, Entropy: from thermodynamics to hydrology, Entropy, 16 (3), 1287–1314, doi:10.3390/e16031287, 2014.
24. A. Efstratiadis, Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence, Environmental Modelling and Software, 62, 139–152, doi:10.1016/j.envsoft.2014.08.017, 2014.
25. A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Hydrological modelling of temporally-varying catchments: Facets of change and the value of information, Hydrological Sciences Journal, 60 (7-8), 1438–1461, doi:10.1080/02626667.2014.982123, 2015.
26. I. Tsoukalas, and C. Makropoulos, Multiobjective optimisation on a budget: Exploring surrogate modelling for robust multi-reservoir rules generation under hydrological uncertainty, Environmental Modelling and Software, 69, 396–413, doi:10.1016/j.envsoft.2014.09.023, 2015.
27. I. Tsoukalas, and C. Makropoulos, A surrogate based optimization approach for the development of uncertainty-aware reservoir operational rules: the case of Nestos hydrosystem, Water Resources Management, 29 (13), 4719–4734, doi:10.1007/s11269-015-1086-8, 2015.
28. D. Koutsoyiannis, Generic and parsimonious stochastic modelling for hydrology and beyond, Hydrological Sciences Journal, 61 (2), 225–244, doi:10.1080/02626667.2015.1016950, 2016.
29. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of turbulence and hydrometeorological processes, Hydrological Sciences Journal, 61 (9), 1623–1640, doi:10.1080/02626667.2015.1085988, 2016.
30. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, 556, 980–992, doi:10.1016/j.jhydrol.2016.07.015, 2018.
31. P. Dimitriadis, and D. Koutsoyiannis, Stochastic synthesis approximating any process dependence and distribution, Stochastic Environmental Research & Risk Assessment, 32 (6), 1493–1515, doi:10.1007/s00477-018-1540-2, 2018.
32. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Stochastic periodic autoregressive to anything (SPARTA): Modelling and simulation of cyclostationary processes with arbitrary marginal distributions, Water Resources Research, 54 (1), 161–185, WRCR23047, doi:10.1002/2017WR021394, 2018.
33. D. Koutsoyiannis, P. Dimitriadis, F. Lombardo, and S. Stevens, From fractals to stochastics: Seeking theoretical consistency in analysis of geophysical data, Advances in Nonlinear Geosciences, edited by A.A. Tsonis, 237–278, doi:10.1007/978-3-319-58895-7_14, Springer, 2018.
34. I. Tsoukalas, C. Makropoulos, and D. Koutsoyiannis, Simulation of stochastic processes exhibiting any-range dependence and arbitrary marginal distributions, Water Resources Research, 54 (11), 9484–9513, doi:10.1029/2017WR022462, 2018.
35. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.
36. D. Koutsoyiannis, Knowable moments for high-order stochastic characterization and modelling of hydrological processes, Hydrological Sciences Journal, 64 (1), 19–33, doi:10.1080/02626667.2018.1556794, 2019.
37. D. Koutsoyiannis, Time’s arrow in stochastic characterization and simulation of atmospheric and hydrological processes, Hydrological Sciences Journal, 64 (9), 1013–1037, doi:10.1080/02626667.2019.1600700, 2019.
38. P. Kossieris, I. Tsoukalas, C. Makropoulos, and D. Savic, Simulating marginal and dependence behaviour of water demand processes at any fine time scale, Water, 11 (5), 885, doi:10.3390/w11050885, 2019.
39. G.-F. Sargentis, R. Ioannidis, G. Karakatsanis, S. Sigourou, N. D. Lagaros, and D. Koutsoyiannis, The development of the Athens water supply system and inferences for optimizing the scale of water infrastructures, Sustainability, 11 (9), 2657, doi:10.3390/su11092657, 2019.
40. D. Koutsoyiannis, Simple stochastic simulation of time irreversible and reversible processes, Hydrological Sciences Journal, 65 (4), 536–551, doi:10.1080/02626667.2019.1705302, 2020.
41. T. Iliopoulou, and D. Koutsoyiannis, Projecting the future of rainfall extremes: better classic than trendy, Journal of Hydrology, 588, doi:10.1016/j.jhydrol.2020.125005, 2020.
42. I. Tsoukalas, P. Kossieris, and C. Makropoulos, Simulation of non-Gaussian correlated random variables, stochastic processes and random fields: Introducing the anySim R-Package for environmental applications and beyond, Water, 12 (6), 1645, doi:10.3390/w12061645, 2020.
43. A. Efstratiadis, I. Tsoukalas, and D. Koutsoyiannis, Generalized storage-reliability-yield framework for hydroelectric reservoirs, Hydrological Sciences Journal, 66 (4), 580–599, doi:10.1080/02626667.2021.1886299, 2021.
44. P. Dimitriadis, D. Koutsoyiannis, T. Iliopoulou, and P. Papanicolaou, A global-scale investigation of stochastic similarities in marginal distribution and dependence structure of key hydrological-cycle processes, Hydrology, 8 (2), 59, doi:10.3390/hydrology8020059, 2021.
45. L. Katikas, P. Dimitriadis, D. Koutsoyiannis, T. Kontos, and P. Kyriakidis, A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series, Applied Energy, 295, 116873, doi:10.1016/j.apenergy.2021.116873, 2021.
46. D. Koutsoyiannis, and P. Dimitriadis, Towards generic simulation for demanding stochastic processes, Sci, 3, 34, doi:10.3390/sci3030034, 2021.
47. P. Kossieris, I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Generic framework for downscaling statistical quantities at fine time-scales and its perspectives towards cost-effective enrichment of water demand records, Water, 13 (23), 3429, doi:10.3390/w13233429, 2021.
48. D. Koutsoyiannis, Stochastics of Hydroclimatic Extremes - A Cool Look at Risk, Εκδοση 3, ISBN: 978-618-85370-0-2, 391 pages, doi:10.57713/kallipos-1, Kallipos Open Academic Editions, Athens, 2023.

Άλλες εργασίες που αναφέρονται σ' αυτή την εργασία: Δείτε τις στο Google Scholar ή στο ResearchGate

Άλλες εργασίες που αναφέρονται σ' αυτή την εργασία (αυτός ο κατάλογος μπορεί να μην είναι ενημερωμένος):

1. Clifford, N.J., Hydrology: the changing paradigm, Progress in Physical Geography, 26(2), 290-301, 2002.
2. Ochoa-Rivera, J.C., R. Garcia-Bartual and J. Andreu, Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks, Hydrology & Earth System Siences, 6 (4), 641-654, 2002.
3. Gneiting, T., and M. Schlather, Stochastic models that separate fractal dimension and the Hurst effect, Society for Industrial and Applied Mathematics Review, 46(2), 269-282, 2004.
4. Srinivas, V.V., and K. Srinivasan, Hybrid moving block bootstrap for stochastic simulation of multi-site multi-season streamflows, Journal of Hydrology, 302(1-4), 307-330, 2005.
5. Cohn, T.A., and H. F. Lins, Nature's style: Naturally trendy, Geophysical Research Letters, 32(23), art. no. L23402, 2005.
6. Srinivas, V. V., and K. Srinivasan, Hybrid matched-block bootstrap for stochastic simulation of multiseason streamflows, Journal of Hydrology, 329(1-2), 1-15, 2006.
7. Muniandy, S.V., and R. Uning, Characterization of exchange rate regimes based on scaling and correlation properties of volatility for ASEAN-5 countries, Physica A - Statistical Mechanics and its Applications, 371(2), 585-598, 2006.
8. Wong, H., W.-c. Ip, R. Zhang and J. Xia, Non-parametric time series models for hydrological forecasting, Journal of Hydrology, 332(3-4), 337-347, 2007.
9. Ochoa-Rivera, J.C., J. Andreu and R. Garcia-Bartual, Influence of inflows modeling on management simulation of water resources system, Journal of Water Resources Planning and Management, 133(2), 106-116, 2007.
10. Mackey, R., Rhodes Fairbridge and the idea that the solar system regulates the Earth's climate, Journal of Coastal Research, Special Issue 50, Proceedings ICS2007, 955-968, 2007.
11. #Chen, Y.Q., R, Sun and A. Zhou, An overview of fractional order signal processing (FOSP) techniques, Proc. ASME 2007 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, 1205-1222, 2007.
12. Hamed, K.H., Trend detection in hydrologic data: The Mann-Kendall trend test under the scaling hypothesis, Journal of Hydrology, 349(3-4), 350-363, 2008.
13. Yang, Z.P., W.X. Lu, Y.Q. Long and P. Li, Application and comparison of two prediction models for groundwater levels: A case study in Western Jilin Province, China, Journal of Arid Environments, 73 (4-5), 487-492, 2009.
14. Hamed, K.H., Enhancing the effectiveness of prewhitening in trend analysis of hydrologic data, Journal of Hydrology, 368(1-4), 143-155, 2009.
15. Wang, D., V. P. Singh, Y.-s. Zhu and J.-c. Wu, Stochastic observation error and uncertainty in water quality evaluation, Advances in Water Resources, 32 (10), 1526-1534, 2009.
16. Wang, W., S. Hu and Y. Li, Wavelet transform method for synthetic generation of daily streamflow, Water Resources Management, 25, (1), 41-57, DOI: 10.1007/s11269-010-9686-9, 2011.
17. Srivastav, R. K., K. Srinivasan and K. P. Sudheer, Simulation-optimization framework for multi-season hybrid stochastic models, Journal of Hydrology, 404 (3-4), 209-225, 2011.
18. #Kulasiri, D., Computational Modelling of Multi-Scale Non-Fickian Dispersion in Porous Media - An Approach Based on Stochastic Calculus, InTech, ISBN 978-953-307-726-0, 231 pp., 2011.
19. Henley, B. J., M. A. Thyer, G. Kuczera, and S. W. Franks, Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleo data, Water Resour. Res., 47, W11509, doi: 10.1029/2010WR010034, 2011.
20. Hamed, K. H., A probabilistic approach to calculating the reliability of over-year storage reservoirs with persistent Gaussian inflow, Journal of Hydrology, 448-449, 93-99, 2012.
21. Lee. T., Serial dependence properties in multivariate streamflow simulation with independent decomposition analysis, Hydrological Processes, 26 (7), 961-972, 2012.
22. Boukharouba, K., Annual stream flow simulation by ARMA processes and prediction by Kalman filter, Arab J. Geosci., 6 (7), 2193-2201, 2013.
23. De Michele, C., and M. Ignaccolo, New perspectives on rainfall from a discrete view, Hydrological Processes, 10.1002/hyp.9782, 2013.
24. #Kulasiri, D., Non-fickian Solute Transport in Porous Media, A Mechanistic and Stochastic Theory, Springer-Verlag Berlin Heidelberg, 2013.
25. Kumar, S., V. Merwade, J. L. Kinter III and D. Niyogi, Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 20th century climate simulations, Journal of Climate, 26(12), 4168-4185, 2013.
26. Olsina, F., R. Pringles, C. Larisson and F. Garcés, Reliability payments to generation capacity in electricity markets, Energy Policy, 10.1016/j.enpol.2014.05.014, 2014.
27. Nigam, R., S. Nigam and S.K. Mittal, The river runoff forecast based on the modeling of time series, Russian Meteorology and Hydrology, 39 (11), 750-761, 2014.
28. Nigam, R., S. Nigam and S.K. Mittal, Stochastic modelling of rainfall and runoff phenomenon: A time series approach review, International Journal of Hydrology Science and Technology, 4 (2), 81-109, 2014.
29. Marković, Đ., J. Plavšić, N. Ilich and S. Ilić, Non-parametric stochastic generation of streamflow series at multiple locations, Water Resources Management, 29(13), 4787-4801, 10.1007/s11269-015-1090-z, 2015.
30. Bekri, E., M. Disse, P. Yannopoulos, Optimizing water allocation under uncertain system conditions in Alfeios River Basin (Greece), Part A: Two-stage stochastic programming model with deterministic boundary intervals, Water, 7(10), 5305-5344, doi:10.3390/w7105305, 2015.
31. Bekri, E., M. Disse, P. Yannopoulos, Optimizing water allocation under uncertain system conditions in Alfeios River Basin (Greece), Part B: Fuzzy-boundary intervals combined with multi-stage stochastic programming Model, Water, 7(10), 6427-6466, doi:10.3390/w7116427, 2015.
32. Srivastav, R., K. Srinivasan, and S. P. Sudheer, Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling, Journal of Hydrology, 542, 506–531, doi:10.1016/j.jhydrol.2016.09.025, 2016.
33. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
34. Stojković, M., S. Kostić, J. Plavšić, and S. Prohaska, A joint stochastic-deterministic approach for long-term and short-term modelling of monthly flow rates, Journal of Hydrology, doi:10.1016/j.jhydrol.2016.11.025, 2016.
35. Brunner, M. I., A. Bárdossy, and R. Furrer, Technical note: Stochastic simulation of streamflow time series using phase randomization, Hydrology and Earth System Sciences, 23, 3175-3187, doi:10.5194/hess-23-3175-2019, 2019.
36. Lappas, I., Water balance parameters estimation through semi-distributed, rainfall-runoff and numerical models. Case Study: Atalanti Watershed (Central – Eastern Greece), SSRG International Journal of Agriculture & Environmental Science, 6(6), 91-102, doi:10.14445/23942568/IJAES-V6I6P113, 2019.
37. Kiem, A. S., G. Kuczera, P. Kozarovski, L. Zhang, and G. Willgoose, Stochastic generation of future hydroclimate using temperature as a climate change covariate, Water Resources Research, doi:10.1029/2020WR027331, 2021.

Κατηγορίες: Βιβλιογραφία μαθήματος: Στοχαστικές μέθοδοι, Δυναμική Hurst-Kolmogorov, Στοχαστική, Αβεβαιότητα