Σχεδιάγραμμα για τη διεργασιακή μοντελοποίηση αβέβαιων υδρολογικών συστημάτων

A. Montanari, and D. Koutsoyiannis, A blueprint for process-based modeling of uncertain hydrological systems, Water Resources Research, 48, W09555, doi:10.1029/2011WR011412, 2012.

[Σχεδιάγραμμα για τη διεργασιακή μοντελοποίηση αβέβαιων υδρολογικών συστημάτων]

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

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Βλέπε επίσης: http://dx.doi.org/10.1029/2011WR011412

Εργασίες μας στις οποίες αναφέρεται αυτή η εργασία:

1. D. Koutsoyiannis, Nonstationarity versus scaling in hydrology, Journal of Hydrology, 324, 239–254, doi:10.1016/j.jhydrol.2005.09.022, 2006.
2. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.
3. D. Koutsoyiannis, A random walk on water, Hydrology and Earth System Sciences, 14, 585–601, doi:10.5194/hess-14-585-2010, 2010.
4. 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.

Εργασίες μας που αναφέρονται σ' αυτή την εργασία:

1. D. Koutsoyiannis, Hydrology and Change, Hydrological Sciences Journal, 58 (6), 1177–1197, doi:10.1080/02626667.2013.804626, 2013.
2. A. Montanari, G. Young, H. H. G. Savenije, D. Hughes, T. Wagener, L. L. Ren, D. Koutsoyiannis, C. Cudennec, E. Toth, S. Grimaldi, G. Blöschl, M. Sivapalan, K. Beven, H. Gupta, M. Hipsey, B. Schaefli, B. Arheimer, E. Boegh, S. J. Schymanski, G. Di Baldassarre, B. Yu, P. Hubert, Y. Huang, A. Schumann, D. Post, V. Srinivasan, C. Harman, S. Thompson, M. Rogger, A. Viglione, H. McMillan, G. Characklis, Z. Pang, and V. Belyaev, “Panta Rhei – Everything Flows”, Change in Hydrology and Society – The IAHS Scientific Decade 2013-2022, Hydrological Sciences Journal, 58 (6), 1256–1275, doi:10.1080/02626667.2013.809088, 2013.
3. D. Koutsoyiannis, Reconciling hydrology with engineering, Hydrology Research, 45 (1), 2–22, doi:10.2166/nh.2013.092, 2014.
4. D. Koutsoyiannis, Entropy: from thermodynamics to hydrology, Entropy, 16 (3), 1287–1314, doi:10.3390/e16031287, 2014.
5. A. Montanari, and D. Koutsoyiannis, Reply to comment by G. Nearing on ‘‘A blueprint for process-based modeling of uncertain hydrological systems’’, Water Resources Research, 50 (7), 6264–6268, doi:10.1002/2013WR014987, 2014.
6. S. Ceola, A. Montanari, and D. Koutsoyiannis, Toward a theoretical framework for integrated modeling of hydrological change, WIREs Water, 1 (5), 427–438, doi:10.1002/wat2.1038, 2014.
7. A. Montanari, and D. Koutsoyiannis, Modeling and mitigating natural hazards: Stationarity is immortal!, Water Resources Research, 50 (12), 9748–9756, doi:10.1002/2014WR016092, 2014.
8. A. Sikorska, A. Montanari, and D. Koutsoyiannis, Estimating the uncertainty of hydrological predictions through data-driven resampling techniques, Journal of Hydrologic Engineering (ASCE), 20 (1), doi:10.1061/(ASCE)HE.1943-5584.0000926, 2015.
9. D. Koutsoyiannis, and A. Montanari, Negligent killing of scientific concepts: the stationarity case, Hydrological Sciences Journal, 60 (7-8), 1174–1183, doi:10.1080/02626667.2014.959959, 2015.
10. 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.
11. 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.
12. H. Tyralis, and D. Koutsoyiannis, On the prediction of persistent processes using the output of deterministic models, Hydrological Sciences Journal, 62 (13), 2083–2102, doi:10.1080/02626667.2017.1361535, 2017.
13. D. Koutsoyiannis, Entropy production in stochastics, Entropy, 19 (11), 581, doi:10.3390/e19110581, 2017.
14. T. Iliopoulou, C. Aguilar , B. Arheimer, M. Bermúdez, N. Bezak, A. Ficchi, D. Koutsoyiannis, J. Parajka, M. J. Polo, G. Thirel, and A. Montanari, A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers, Hydrology and Earth System Sciences, 23, 73–91, doi:10.5194/hess-23-73-2019, 2019.
15. 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.
16. G. Papacharalampous, H. Tyralis, A. Langousis, A. W. Jayawardena, B. Sivakumar, N. Mamassis, A. Montanari, and D. Koutsoyiannis, Probabilistic hydrological post-processing at scale: Why and how to apply machine-learning quantile regression algorithms, Water, doi:10.3390/w11102126, 2019.
17. G. Papacharalampous, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models, Advances in Water Resources, 136, 103471, doi:10.1016/j.advwatres.2019.103471, 2020.
18. G. Papacharalampous, H. Tyralis, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale, Advances in Water Resources, 136, 103470, doi:10.1016/j.advwatres.2019.103470, 2020.
19. D. Koutsoyiannis, An open letter to the Editor of Frontiers, doi:10.13140/RG.2.2.34248.39689/1, Δεκέμβριος 2021.
20. D. Koutsoyiannis, and A. Montanari, Bluecat: A local uncertainty estimator for deterministic simulations and predictions, Water Resources Research, 58 (1), e2021WR031215, doi:10.1029/2021WR031215, 2022.
21. D. Koutsoyiannis, and A. Montanari, Climate extrapolations in hydrology: The expanded Bluecat methodology, Hydrology, 9, 86, doi:10.3390/hydrology9050086, 2022.
22. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 2. Applications, Proceedings of The Royal Society A, 478 (2261), 20210836, doi:10.1098/rspa.2021.0836, 2022.
23. 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. Montanari, A., Hydrology of the Po River: looking for changing patterns in river discharge, Hydrol. Earth Syst. Sci., 16, 3739-3747, 2012.
2. Tauro, F., G. Mocio, E. Rapiti, S. Grimaldi and M. Porfiri, Assessment of fluorescent particles for surface flow analysis, Sensors, 12, 15827-15840, 2012.
3. Beven, K., So how much of your error is epistemic? Lessons from Japan and Italy, Hydrological Processes, 27 (11), 1677-168, 2013.
4. Zambrano-Bigiarini, M., and R. Rojas, A model-independent Particle Swarm Optimisation software for model calibration, Environmental Modelling & Software, 43, 5-25, 2013.
5. Weijs, S. V., N. van de Giesen and M.B. Parlange, HydroZIP: How hydrological knowledge can be used to improve compression of hydrological data, Entropy, 15, 1289-1310, 2013.
6. Del Giudice, D., M. Honti, A. Scheidegger, C. Albert, P. Reichert and J. Rieckermann, Improving uncertainty estimation in urban hydrological modeling by statistically describing bias, Hydrol. Earth Syst. Sci., 17, 4209-4225, 2013.
7. Hrachowitz, M., H.H.G. Savenije, G. Blöschl, J.J. McDonnell, M. Sivapalan, J.W. Pomeroy, B. Arheimer, T. Blume, M.P. Clark, U. Ehret, F. Fenicia, J.E. Freer, A. Gelfan, H.V. Gupta, D.A. Hughes, R.W. Hut, A. Montanari, S. Pande, D. Tetzlaff, P.A. Troch, S. Uhlenbrook, T. Wagener, H.C. Winsemius, R.A. Woods, E. Zehe, and C. Cudennec, A decade of Predictions in Ungauged Basins (PUB) — a review, Hydrological Sciences Journal, 58(6), 1198-1255, 2013.
8. Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari and G. and Blöschl, Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene, Hydrol. Earth Syst. Sci., 17, 5013-5039, 2013.
9. Beven, K., and P. Young, A guide to good practice in modelling semantics for authors and referees, Water Resources Research, 10.1002/wrcr.20393, 2013.
10. Beven, K., and A. Binley, GLUE: twenty years on, Hydrological Processes, 10.1002/hyp.10082, 2013.
11. Sikorska, A. E., A. Scheidegger, K. Banasik and J. Rieckermann, Considering rating curve uncertainty in water level predictions, Hydrol. Earth Syst. Sci., 17, 4415-4427, 2013.
12. Paschalis, A., P. Molnar, S. Fatichi and P. Burlando, A stochastic model for high resolution space‐time precipitation simulation, Water Resources Research, 49 (12), 8400-8417, 2013.
13. Hall, J., B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z.W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione and G. Blöschl, Understanding flood regime changes in Europe: a state-of-the-art assessment, Hydrol. Earth Syst. Sci., 18, 2735-2772, 10.5194/hess-18-2735-2014, 2014.
14. Mazzoleni, M., B. Bacchi, S. Barontini, G. Di Baldassarre, M. Pilotti and R. Ranzi, Flooding hazard mapping in floodplain areas affected by piping breaches in the Po River, Italy, J. Hydrol. Eng., 19 (4), 717-731, 2014.
15. Gupta, H. V., C. Perrin, G. Blöschl, A. Montanari, R. Kumar, M. Clark and V. Andréassian, Large-sample hydrology: a need to balance depth with breadth, Hydrol. Earth Syst. Sci. , 18, 463-477, 2014.
16. Evin, G., M. Thyer, D. Kavetski, D. McInerney and G. Kuczera, Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity, Water Resources Research, 10.1002/2013WR014185, 2014.
17. Gupta, H. V., and G. S. Nearing, Debates—the future of hydrological sciences: A (common) path forward? Using models and data to learn: A systems theoretic perspective on the future of hydrological science, Water Resources Research, 50 (6), 5351-5359, 2014.
18. Shahzad, K. M., and E. J. Plate, Flood forecasting for the Mekong with data‐based models, Water Resources Research, 10.1002/2013WR015072, 2014.
19. Nearing, G., Comment on “A blueprint for process‐based modeling of uncertain hydrological systems” by Alberto Montanari and Demetris Koutsoyiannis, Water Resources Research, 50 (7), 1944-7973, 10.1002/2013WR014812, 2014.
20. Peeters, L. J. M., G. M. Podger, T. Smith, T. Pickett, R. H. Bark and S. M. Cuddy, Robust global sensitivity analysis of a river management model to assess nonlinear and interaction effects, Hydrol. Earth Syst. Sci., 18, 3777-3785, 10.5194/hess-18-3777-2014, 2014.
21. Kumar Mishra, B., and S. Herath, Assessment of future floods in the Bagmati River Basin of Nepal using bias-corrected daily GCM precipitation data, J. Hydrol. Eng. , 10.1061/(ASCE)HE.1943-5584.0001090, 2014.
22. Shahzad, K.M., and E.J. Plate, Flood forecasting for river Mekong with data-based models, Water Resources Research, 50 (9), 7115-7133, 2014.
23. Beven, K., and P. Smith, Concepts of information content and likelihood in parameter calibration for hydrological simulation models, Journal of Hydrologic Engineering, 20 (1), 10.1061/(ASCE)HE.1943-5584.0000991, art. no. A4014010, 2015.
24. Mendoza, P.A., M.P. Clark, M. Barlage, B. Rajagopalan, L. Samaniego, G. Abramowitz and H. Gupta, Are we unnecessarily constraining the agility of complex process-based models?, Water Resources Research, 51 (1), 716-728, 2015.
25. Clark, M.P., B. Nijssen, J.D. Lundquist, D. Kavetski, D.E. Rupp, R.A. Woods, J.E. Freer, E.D. Gutmann, A.W. Wood, L.D. Brekke, J.R. Arnold, D.J. Gochis and R.M Rasmussen, A unified approach for process-based hydrologic modeling: 1. Modeling concept, Water Resources Research, 51 (4), 2498-2514, 2015.
26. Clark, M.P., B. Nijssen, J.D. Lundquist, D. Kavetski, D.E. Rupp, R.A. Woods, J.E. Freer, E.D. Gutmann, A.W. Wood, D.J. Gochis, R.M. Rasmussen, D.G. Tarboton, V. Mahat, G.N. Flerchinger and D.G. Marks, A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies, Water Resources Research, 51 (4), 2515-2542, 2015.
27. Ceola, S., B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione and T. Wagener, Virtual laboratories: New opportunities for collaborative water science, Hydrology and Earth System Sciences, 19 (4), 2101-2117, 2015.
28. Lundquist, J.D., N.E. Wayand, A. Massmann, M.P. Clark, F. Lott and N.C. Cristea, Diagnosis of insidious data disasters, Water Resources Research, 51 (5), 3815-3827, 2015.
29. Safari, A., and F. De Smedt, Improving the confidence in hydrologic model calibration and prediction by transformation of model residuals, Journal of Hydrologic Engineering, 20 (9), 10.1061/(ASCE)HE.1943-5584.0001141, 04015001, 2015.
30. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, doi:10.1016/j.wasec.2017.06.001, 2017.

Κατηγορίες: Ντετερμινισμός και στοχαστικότητα, Υδρολογικά μοντέλα, Αβεβαιότητα