Πολυμεταβλητό στοχαστικό μοντέλο για τη γέννηση συνθετικών χρονοσειρών σε πολλαπλές χρονικές κλίμακες που αναπαράγει τη μακροχρόνια εμμονή

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.

[Πολυμεταβλητό στοχαστικό μοντέλο για τη γέννηση συνθετικών χρονοσειρών σε πολλαπλές χρονικές κλίμακες που αναπαράγει τη μακροχρόνια εμμονή]

[doc_id=1488]

[Αγγλικά]

Παρουσιάζεται μια γεννήτρια χρονοσειρών που υλοποιεί ένα εύρωστο πολυμεταβλητό σχήμα τριών κλιμάκων, για τη στοχαστική προσομοίωση συσχετισμένων διεργασιών. Αυτή διατηρεί τα στοιχειώδη στατιστικά χαρακτηριστικά των ιστορικών δεδομένων σε τρεις χρονικές κλίμακες (ετήσια, μηνιαία, ημερήσια), χρησιμοποιώντας μια προσέγγιση επιμερισμού. Ακόμα, αναπαράγει βασικές ιδιότητες των υδρομετεωρολογικών και γεωφυσικών διεργασιών, συγκεκριμένα τη μακροχρόνια εμμονή (συμπεριφορά Hurst-Kolmogorov), την περιοδικότητα και τη διαλείπουσα δίαιτα. Η αποτελεσματικότητα της μεθόδου αναδεικνύεται μέσω δύο μελετών περίπτωσης στην Ελλάδα. Η πρώτη αποσκοπεί στη γέννηση μηνιαίων δεδομένων απορροής και βροχόπτωσης στους τρεις ταμιευτήρες του υδροσυστήματος της Αθήνας. Η δεύτερη εφαρμογή αφορά στη γέννηση ημερήσιων βροχοπτώσεων σε πέντε σταθμούς, για την προσομοίωση πλημμυρών. Στην πρώτη εφαρμογή δίνεται έμφαση στη μακροχρόνια εμμονή – ένα κυρίαρχο χαρακτηριστικό των διαχείρισης υδροσυστημάτων μεγάλης κλίμακας, που περιλαμβάνουν ταμιευτήρες υπερετήσιας αποθηκευτικής ικανότητας. Στη δεύτερη εφαρμογή δίνεται προσοχή στη συνεπή αναπαραγωγή της διαλείπουσας συμπεριφοράς και ασυμμετρίας της ημερήσιας βροχόπτωσης, καθώς και στην κατανομή των ετήσιων ημερήσιων μεγίστων.

Το πλήρες κείμενο διατίθεται μόνο στο δίκτυο του ΕΜΠ λόγω νομικών περιορισμών

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Βλέπε επίσης: http://dx.doi.org/10.1016/j.envsoft.2014.08.017

Εργασίες μας στις οποίες αναφέρεται αυτή η εργασία:

1. Δ. Κουτσογιάννης, Μοντέλο Επιμερισμού Σημειακής Βροχόπτωσης, Διδακτορική διατριβή, 310 pages, doi:10.12681/eadd/0910, Εθνικό Μετσόβιο Πολυτεχνείο, Αθήνα, 1988.
2. D. Koutsoyiannis, A stochastic disaggregation method for design storm and flood synthesis, Journal of Hydrology, 156, 193–225, doi:10.1016/0022-1694(94)90078-7, 1994.
3. D. Koutsoyiannis, and A. Manetas, Simple disaggregation by accurate adjusting procedures, Water Resources Research, 32 (7), 2105–2117, doi:10.1029/96WR00488, 1996.
4. 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.
5. 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.
6. D. Koutsoyiannis, Coupling stochastic models of different time scales, Water Resources Research, 37 (2), 379–391, doi:10.1029/2000WR900200, 2001.
7. Α. Ευστρατιάδης, Διερεύνηση μεθόδων αναζήτησης ολικού βελτίστου σε προβλήματα υδατικών πόρων, MSc thesis, 139 pages, Τομέας Υδατικών Πόρων, Υδραυλικών και Θαλάσσιων Έργων – Εθνικό Μετσόβιο Πολυτεχνείο, Αθήνα, Μάιος 2001.
8. D. Koutsoyiannis, The Hurst phenomenon and fractional Gaussian noise made easy, Hydrological Sciences Journal, 47 (4), 573–595, doi:10.1080/02626660209492961, 2002.
9. 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.
10. D. Koutsoyiannis, C. Onof, and H. S. Wheater, Multivariate rainfall disaggregation at a fine timescale, Water Resources Research, 39 (7), 1173, doi:10.1029/2002WR001600, 2003.
11. 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.
12. 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.
13. Α. Ευστρατιάδης, και Δ. Κουτσογιάννης, Κασταλία (έκδοση 2.0) - Σύστημα στοχαστικής προσομοίωσης υδρολογικών μεταβλητών, Εκσυγχρονισμός της εποπτείας και διαχείρισης του συστήματος των υδατικών πόρων ύδρευσης της Αθήνας, Τεύχος 23, 103 pages, Τομέας Υδατικών Πόρων, Υδραυλικών και Θαλάσσιων Έργων – Εθνικό Μετσόβιο Πολυτεχνείο, Αθήνα, Ιανουάριος 2004.
14. 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.
15. D. Koutsoyiannis, and A. Montanari, Statistical analysis of hydroclimatic time series: Uncertainty and insights, Water Resources Research, 43 (5), W05429, doi:10.1029/2006WR005592, 2007.
16. 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.
17. 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.
18. I. Nalbantis, A. Efstratiadis, E. Rozos, M. Kopsiafti, and D. Koutsoyiannis, Holistic versus monomeric strategies for hydrological modelling of human-modified hydrosystems, Hydrology and Earth System Sciences, 15, 743–758, doi:10.5194/hess-15-743-2011, 2011.
19. Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A computer system for the stochastic disaggregation of monthly into daily hydrological time series as part of a three–level multivariate scheme, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-290, doi:10.13140/RG.2.2.23814.98885, European Geosciences Union, 2011.
20. Ι. Διαλυνάς, Ανάπτυξη υπολογιστικού συστήματος για τον πολυμεταβλητό στοχαστικό επιμερισμό μηνιαίων σε ημερήσιες υδρολογικές χρονοσειρές, Διπλωματική εργασία, 337 pages, Τομέας Υδατικών Πόρων και Περιβάλλοντος – Εθνικό Μετσόβιο Πολυτεχνείο, Αθήνα, Μάρτιος 2011.
21. S.M. Papalexiou, and D. Koutsoyiannis, Battle of extreme value distributions: A global survey on extreme daily rainfall, Water Resources Research, 49 (1), 187–201, doi:10.1029/2012WR012557, 2013.
22. A. Venediki, S. Giannoulis, C. Ioannou, L. Malatesta, G. Theodoropoulos, G. Tsekouras, Y. Dialynas, S.M. Papalexiou, A. Efstratiadis, and D. Koutsoyiannis, The Castalia stochastic generator and its applications to multivariate disaggregation of hydro-meteorological processes, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-11542, doi:10.13140/RG.2.2.15675.41764, European Geosciences Union, 2013.
23. 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.
24. 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.

Εργασίες μας που αναφέρονται σ' αυτή την εργασία:

1. 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.
2. 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.
3. I. Tsoukalas, P. Dimas, and C. Makropoulos, Hydrosystem optimization on a budget: Investigating the potential of surrogate based optimization techniques, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, 2015.
4. 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.
5. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.
6. S.M. Papalexiou, Y. Dialynas, and S. Grimaldi, Hershfield factor revisited: Correcting annual maximum precipitation, Journal of Hydrology, 542, 884–895, doi:10.1016/j.jhydrol.2016.09.058, 2016.
7. F. Lombardo, E. Volpi, D. Koutsoyiannis, and F. Serinaldi, A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall, Water Resources Research, 53 (6), 4586–4605, doi:10.1002/2017WR020529, 2017.
8. I. Tsoukalas, C. Makropoulos, and A. Efstratiadis, Stochastic simulation of periodic processes with arbitrary marginal distributions, 15th International Conference on Environmental Science and Technology (CEST2017), Rhodes, Global Network on Environmental Science and Technology, 2017.
9. K. Papoulakos, G. Pollakis, Y. Moustakis, A. Markopoulos, T. Iliopoulou, P. Dimitriadis, D. Koutsoyiannis, and A. Efstratiadis, Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability, Energy Procedia, 125, 405–414, doi:10.1016/j.egypro.2017.08.078, 2017.
10. M. Chalakatevaki, P. Stamou, S. Karali, V. Daniil, P. Dimitriadis, K. Tzouka, T. Iliopoulou, D. Koutsoyiannis, P. Papanicolaou, and N. Mamassis, Creating the electric energy mix in a non-connected island, Energy Procedia, 125, 425–434, doi:10.1016/j.egypro.2017.08.089, 2017.
11. 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.
12. 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.
13. 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.
14. I. Tsoukalas, S.M. Papalexiou, A. Efstratiadis, and C. Makropoulos, A cautionary note on the reproduction of dependencies through linear stochastic models with non-Gaussian white noise, Water, 10 (6), 771, doi:10.3390/w10060771, 2018.
15. 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.
16. 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.
17. 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.

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. Huo, S.-C., S.-L. Lo, C.-H. Chiu, P.-T. Chiueh, and C.-S. Yang, Assessing a fuzzy model and HSPF to supplement rainfall data for nonpoint source water quality in the Feitsui reservoir watershed, Environmental Modelling and Software, 72, 110-116, doi:10.1016/j.envsoft.2015.07.002, 2015.
2. Read, L., and R. M. Vogel, Reliability, return periods, and risk under nonstationarity, Water Resources Research, 51(8), 6381–6398, doi:10.1002/2015WR017089, 2015.
3. Steidl, J., J. Schuler, U. Schubert, O. Dietrich, and P. Zander, Expansion of an existing water management model for the analysis of opportunities and impacts of agricultural irrigation under climate change conditions, Water, 7, 6351-6377, doi:10.3390/w7116351, 2015.
4. Hao, Z., and V. P. Singh, Review of dependence modeling in hydrology and water resources, Progress in Physical Geography, 40(4), 549-578, doi:10.1177/0309133316632460, 2016.
5. 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.
6. Dialynas, Y. G., S. Bastola, R. L. Bras, E. Marin-Spiotta, W. L. Silver, E. Arnone, and L. V. Noto, Impact of hydrologically driven hillslope erosion and landslide occurrence on soil organic carbon dynamics in tropical watersheds, Water Resources Research, 52(11), 8895–8919, doi:10.1002/2016WR018925, 2016.
7. 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, 544, 555–566, doi:10.1016/j.jhydrol.2016.11.025, 2017.
8. Bardsley, E., A finite mixture approach to univariate data simulation with moment matching, Environmental Modelling & Software, 90, 27-33, doi:10.1016/j.envsoft.2016.11.019, 2017.
9. Dialynas, Y. D., R. L. Bras, and D. deB. Richter, Hydro-geomorphic perturbations on the soil-atmosphere CO2 exchange: How (un)certain are our balances?, Water Resources Research, 53(2), 1664–1682, doi:10.1002/2016WR019411, 2017.
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11. Stojković, M., J. Plavšić, and S. Prohaska, Annual and seasonal discharge prediction in the middle Danube River basin based on a modified TIPS (Tendency, Intermittency, Periodicity, Stochasticity) methodology, Journal of Hydrology and Hydromechanics, 65(2), doi:10.1515/johh-2017-0012, 2017.
12. Hanel, M., R. Kožín, M. Heřmanovský, and R. Roub, An R package for assessment of statistical downscaling methods for hydrological climate change impact studies, Environmental Modelling & Software, 95, 22–28, doi:10.1016/j.envsoft.2017.03.036, 2017.
13. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, 1, 28-35, doi:10.1016/j.wasec.2017.06.001, 2017.
14. #McLachlan, S., K. Dube, T. Gallagher, B. Daley, and J. Walonoski, The ATEN Framework for creating the realistic synthetic electronic health record, 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), Madeira, Portugal, 2018.
15. Salas, J. D., J. Obeysekera, and R. M. Vogel, Techniques for assessing water infrastructure for nonstationary extreme events: a review, Hydrological Sciences Journal, 63(3), 325-352, doi:10.1080/02626667.2018.1426858, 2018.
16. #Hnilica, J., M. Hanel, and V. Puš, Technical note: Changes of cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2018-7, 2018.
17. Hua, Y., and B. Cui, Environmental flows and its satisfaction degree forecasting in the Yellow River, Ecological Indicators, 92, 207-220, doi:10.1016/j.ecolind.2017.02.017, 2018.
18. Ilich, N., A. Gharib, and E. G. R. Davies, Kernel distributed residual function in a revised multiple order autoregressive model and its applications in hydrology, Hydrological Sciences Journal, 63(12), 1745-1758, doi:10.1080/02626667.2018.1541090, 2018.
19. Henao, F., Y. Rodriguez, J. P. Viteri, and I. Dyner, Optimising the insertion of renewables in the Colombian power sector, Renewable Energy, 132, 81-92, doi:10.1016/j.renene.2018.07.099, 2019.
20. Park, J., C. Onof, and D. Kim, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, 23, 989-1014, doi:10.5194/hess-23-989-2019, 2019.
21. Ferreira, D. M., C. V. S. Fernandes, E. Kaviski, and D. Fontane, Water quality modelling under unsteady state analysis: Strategies for planning and management, Journal of Environmental Management, 239, 150-158, doi:10.1016/j.jenvman.2019.03.047, 2019.
22. Seo, S. B., Y.-O. Kim, and S.-U. Kang, Time-varying discrete hedging rules for drought contingency plan considering long-range dependency in streamflow, Water Resources Management, 33(8), 2791-2807, doi:10.1007/s11269-019-02244-5, 2019.
23. #McLachlan, S., K. Dube, T. Gallagher, J. A. Simmonds, and N. E. Fenton, The ATEN Framework for creating the realistic synthetic electronic health record, Biomedical Engineering Systems and Technologies, BIOSTEC 2018, Communications in Computer and Information Science, Vol. 1024, Springer, Cham, doi:10.1007/978-3-030-29196-9_25, 2019.
24. Yu, Z., S. Miller, F. Montalto, and U. Lall, Development of a non-parametric stationary synthetic rainfall generator for use in hourly water resource simulations, Water, 11, 1728, doi:10.3390/w11081728, 2019.
25. Bermúdez, M., L. Cea, and J. Sopelana, Quantifying the role of individual flood drivers and their correlations in flooding of coastal river reaches, Stochastic Environmental Research and Risk Assessment, doi:10.1007/s00477-019-01733-8, 2019.

Κατηγορίες: Δυναμική Hurst-Kolmogorov, Στοχαστικός επιμερισμός, Λογισμικό, Στοχαστική, Εργασίες φοιτητών σε συνέδρια