Βαθμονόμηση ημικατανεμημένου μοντέλου για συνδυασμένη προσομοίωση των επιφανειακών και υπόγειων ροών

E. Rozos, A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows, Hydrological Sciences Journal, 49 (5), 819–842, doi:10.1623/hysj.49.5.819.55130, 2004.

[Βαθμονόμηση ημικατανεμημένου μοντέλου για συνδυασμένη προσομοίωση των επιφανειακών και υπόγειων ροών]

[doc_id=630]

[Αγγλικά]

Αναπτύχθηκε ένα μοντέλο υδρολογικής προσομοίωσης για τη συνδυασμένη αναπαράσταση των επιφανειακών και υπόγειων διεργασιών. Αποτελείται από ένα εννοιολογικό μοντέλο συγκέντρωσης της εδαφικής υγρασίας, βασισμένο σε μια εμπλουτισμένη έκδοση του μοντέλου δεξαμενής εδαφικής υγρασίας του Thornthwaite, ένα πολυκυτταρικό μοντέλο υπόγειας ροής τύπου Darcy, και ένα μοντέλο επιμερισμού των απολήψεων από τους διάφορους υδατικούς πόρους. Το προκύπτον ολοκληρωμένο σχήμα είναι εξαιρετικά ευέλικτο όσον αφορά την επιλογή της χρονικής (μηνιαία ή ημερήσια) και της χωρικής (λεκάνης απορροής, υδροφορέας) κλίμακας. Η βαθμονόμηση του μοντέλου περιελάμβανε διαδοχικές φάσεις εμπειρικής και αυτόματης βαθμονόμησης. Για την τελευταία, επινοήθηκε μια πρωτότυπη μέθοδος βελτιστοποίησης, με την ονομασία εξελικτικός αλγόριθμος ανόπτησης-απλόκου. Η αντικειμενική συνάρτηση περιλαμβάνει σταθμισμένα κριτήρια καλής προσαρμογής για πολλαπλές μεταβλητές και διαφορετικές περιόδους παρατηρήσεων, καθώς και όρους ποινής για τον περιορισμό των μη ρεαλιστικών τάσεων στην αποθήκευση του νερού και των αποκλίσεων από την παρατηρημένη στείρευση των πηγών. Το μοντέλο εφαρμόζεται στην εξαιρετικά πολύπλοκη λεκάνη απορροής του Βοιωτικού Κηφισό, στην Ελλάδα, για την οποία αναπαράγει με ακρίβεια τις κύριες αποκρίσεις, ήτοι τη απορροή εξόδου καθώς και άλλες σημαντικές συνιστώσες. Δίνεται έμφαση στην αρχή της φειδούς, η οποία συμβάλλει στην υπολογιστικά αποτελεσματική μοντελοποίηση. Αυτό είναι κρίσιμο, δεδομένου ότι το μοντέλο πρόκειται να ολοκληρωθεί σε ένα πλαίσιο στοχαστικής προσομοίωσης.

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Βλέπε επίσης: http://dx.doi.org/10.1623/hysj.49.5.819.55130

Εργασίες μας στις οποίες αναφέρεται αυτή η εργασία:

1. G. C. Koukis, and D. Koutsoyiannis, Greece, Geomorphological hazards in Europe, edited by C.&C. Embleton, 215–241, doi:10.1016/S0928-2025(97)80010-7, Elsevier, 1997.
2. Ι. Ναλμπάντης, και Ε. Ρόζος, Σύστημα προσομοίωσης του υδρολογικού κύκλου στη λεκάνη Β. Κηφισού, Εκσυγχρονισμός της εποπτείας και διαχείρισης του συστήματος των υδατικών πόρων ύδρευσης της Αθήνας, Τεύχος 10, 72 pages, Τομέας Υδατικών Πόρων, Υδραυλικών και Θαλάσσιων Έργων – Εθνικό Μετσόβιο Πολυτεχνείο, Αθήνα, Δεκέμβριος 2000.
3. 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.
4. A. Efstratiadis, and D. Koutsoyiannis, An evolutionary annealing-simplex algorithm for global optimisation of water resource systems, Proceedings of the Fifth International Conference on Hydroinformatics, Cardiff, UK, 1423–1428, doi:10.13140/RG.2.1.1038.6162, International Water Association, 2002.
5. 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.
6. 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.

Εργασίες μας που αναφέρονται σ' αυτή την εργασία:

1. A. Efstratiadis, and D. Koutsoyiannis, The multiobjective evolutionary annealing-simplex method and its application in calibrating hydrological models, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04593, doi:10.13140/RG.2.2.32963.81446, European Geosciences Union, 2005.
2. D. Koutsoyiannis, A toy model of climatic variability with scaling behaviour, Journal of Hydrology, 322, 25–48, doi:10.1016/j.jhydrol.2005.02.030, 2006.
3. D. Koutsoyiannis, Nonstationarity versus scaling in hydrology, Journal of Hydrology, 324, 239–254, doi:10.1016/j.jhydrol.2005.09.022, 2006.
4. 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.
5. C. Cudennec, C. Leduc, and D. Koutsoyiannis, Dryland hydrology in Mediterranean regions -- a review, Hydrological Sciences Journal, 52 (6), 1077–1087, doi:10.1623/hysj.52.6.1077, 2007.
6. A. Efstratiadis, I. Nalbantis, A. Koukouvinos, E. Rozos, and D. Koutsoyiannis, HYDROGEIOS: A semi-distributed GIS-based hydrological model for modified river basins, Hydrology and Earth System Sciences, 12, 989–1006, doi:10.5194/hess-12-989-2008, 2008.
7. C. Makropoulos, D. Koutsoyiannis, M. Stanic, S. Djordevic, D. Prodanovic, T. Dasic, S. Prohaska, C. Maksimovic, and H. S. Wheater, A multi-model approach to the simulation of large scale karst flows, Journal of Hydrology, 348 (3-4), 412–424, 2008.
8. A. Efstratiadis, and D. Koutsoyiannis, Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach, Practical hydroinformatics: Computational intelligence and technological developments in water applications, edited by R.J. Abrahart, L. M. See, and D. P. Solomatine, 259–273, doi:10.1007/978-3-540-79881-1_19, Springer, 2008.
9. A. Efstratiadis, and N. Mamassis, Evaluating models or evaluating modelling practices? - Interactive comment on HESS Opinions “Crash tests for a standardized evaluation of hydrological models”, Hydrology and Earth System Sciences Discussions, 6, C1404–C1409, 2009.
10. N. Evelpidou, N. Mamassis, A. Vassilopoulos, C. Makropoulos, and D. Koutsoyiannis, Flooding in Athens: The Kephisos River flood event of 21-22/10/1994, International Conference on Urban Flood Management, Paris, doi:10.13140/RG.2.1.4065.5601, UNESCO, 2009.
11. A. Efstratiadis, and D. Koutsoyiannis, One decade of multiobjective calibration approaches in hydrological modelling: a review, Hydrological Sciences Journal, 55 (1), 58–78, doi:10.1080/02626660903526292, 2010.
12. E. Rozos, and D. Koutsoyiannis, Error analysis of a multi-cell groundwater model, Journal of Hydrology, 392 (1-2), 22–30, 2010.
13. 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.
14. D. Koutsoyiannis, N. Mamassis, A. Efstratiadis, N. Zarkadoulas, and Y. Markonis, Floods in Greece, Changes of Flood Risk in Europe, edited by Z. W. Kundzewicz, Chapter 12, 238–256, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2012.
15. H. Tyralis, D. Koutsoyiannis, and S. Kozanis, An algorithm to construct Monte Carlo confidence intervals for an arbitrary function of probability distribution parameters, Computational Statistics, 28 (4), 1501–1527, doi:10.1007/s00180-012-0364-7, 2013.
16. H. Tyralis, and D. Koutsoyiannis, A Bayesian statistical model for deriving the predictive distribution of hydroclimatic variables, Climate Dynamics, 42 (11-12), 2867–2883, doi:10.1007/s00382-013-1804-y, 2014.
17. 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.
18. 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.
19. T. Vergou, A. Efstratiadis, and D. Dermatas, Water balance model for evaluation of landfill malfunction due to leakage, Proceedings of ISWA 2016 World Congress, Novi Sad, Ιnternational Solid Waste Association, 2016.
20. E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, A curve number approach to formulate hydrological response units within distributed hydrological modelling, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2016-627, 2016.
21. E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, The curve number concept as a driver for delineating hydrological response units, Water, 10 (2), 194, doi:10.3390/w10020194, 2018.

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. Ireson, A., C. Makropoulos and C. Maksimovic, Water resources modelling under data scarcity: Coupling MIKE BASIN and ASM groundwater model, Water Resources Management, 20(4), 567-590, 2006.
2. Goswami, M., and K.M. O'Connor, Comparative assessment of six automatic optimization techniques for calibration of a conceptual rainfall-runoff model, Hydrological Sciences Journal, 52(3), 432-449, 2007.
3. #Watershed Science Centre, Research Priorities for Source Water Protection: Filling the Gap between Science and Implementation, Final Report, 333 p., Trent University, Ontario, 2007.
4. #Burton, A., H. Fowler, C. Kilsby, and M. Marani, Investigation of intensity and spatial representations of rainfall within stochastic rainfall model, AquaTerra: Integrated modelling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change, Deliverable H1.8, 57 pp., 2007.
5. Malpica, J.A., J.G. Rejas, and M.C. Alonso, A projection pursuit algorithm for anomaly detection in hyperspectral imagery, Pattern Recognition, 41(11), 3313-3327, 2008.
6. Burton, A., C.G. Kilsby, H.J. Fowler, P.S.P. Cowpertwait, and P.E. O'Connell, RainSim: A spatial–temporal stochastic rainfall modelling system, Environmental Modelling and Software, 23(12), 1356-1369, 2008.
7. Kourakos, G., and A. Mantoglou, Pumping optimization of coastal aquifers based on evolutionary algorithms and surrogate modular neural network models, Advances in Water Resources, 32(4), 507-521, 2009.
8. Wang, G.-S, J. Xia, and J.-F. Chen, A multi-parameter sensitivity and uncertainty analysis method to evaluate relative importance of parameters and model performance, Geographical Research, 29(2), 263-270, 2010.
9. Kustamar, S., S. Sari, Y. Erni, and Sunik, ITN-2 River basin hydrology model: A distributed conceptual model for predicting flood without using calibration, Dinamika Teknik Sipil, 10(3), 233-240, 2010.
10. #SIRRIMED (Sustainable use of irrigation water in the Mediterranean Region), D4.2 and D5.2 Report on Models to be Implemented in the District Information Systems (DIS) and Watershed Information Systems (WIS), 95 pp., Universidad Politécnica de Cartagena, 2011.
11. Mediero, L., L. Garrote, and F. J. Martín-Carrasco, Probabilistic calibration of a distributed hydrological model for flood forecasting, Hydrological Sciences Journal, 56(7), 1129–1149, 2011.
12. Flipo, N., C. Monteil, M. Poulin, C. de Fouquet, and M. Krimissa, Hybrid fitting of a hydrosystem model: Long term insight into the Beauce aquifer functioning (France), Water Recourses Research, 48, W05509, doi: 10.1029/2011WR011092, 2012.
13. Korichi, K., and A. Hazzab, Hydrodynamic investigation and numerical simulation of intermittent and ephemeral flows in semi-arid Regions: Wadi Mekerra, Algeria, Journal of Hydrology and Hydromechanics, 60(2), 125-142, 2012.
14. Wang, W.-C., C.-T. Cheng, K.-W. Chau, and D.-M. Xu, Calibration of Xinanjiang model parameters using hybrid genetic algorithm based fuzzy optimal model, Journal of Hydroinformatics, 14 (3), 784-799, 2012.
15. Evrenoglou, L., S. A. Partsinevelou, P. Stamatis, A. Lazaris, E. Patsouris, C. Kotampasi, and P. Nicolopoulou-Stamati, Children exposure to trace levels of heavy metals at the north zone of Kifissos River, Science of The Total Environment, 443(15), 650-661, 2013.
16. Kallioras, A., and P. Marinos, Water resources assessment and management of karst aquifer systems in Greece, Environmental Earth Sciences, 74(1), 83-100, doi:10.1007/s12665-015-4582-5, 2015.
17. #Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers using radial basis function metamodels, Proceedings of 9th World Congress EWRA “Water Resources Management in a Changing World: Challenges and Opportunities”, Istanbul, 2015.
18. Christelis, V., and A. Mantoglou, Coastal aquifer management based on the joint use of density-dependent and sharp interface models, Water Resources Management, 30(2), 861-876, doi:10.1007/s11269-015-1195-4, 2016.
19. Merheb, M., R. Moussa, C. Abdallah, F. Colin, C. Perrin, and N. Baghdadi, Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis, Hydrological Sciences Journal, 61(14), 2520-2539, doi:10.1080/02626667.2016.1140174, 2016.
20. Tigkas, D., V. Christelis, and G. Tsakiris, Comparative study of evolutionary algorithms for the automatic calibration of the Medbasin-D conceptual hydrological model, Environmental Processes, 3(3), 629–644, doi:10.1007/s40710-016-0147-1, 2016.
21. Liao, S.-L., G. Li, Q.-Y. Sun, and Z.F. Li, Real-time correction of antecedent precipitation for the Xinanjiang model using the genetic algorithm, Journal of Hydroinformatics, 18(5), 803-815, doi:10.2166/hydro.2016.168, 2016.
22. Charizopoulos, N., and A. Psilovikos, Hydrologic processes simulation using the conceptual model Zygos: the example of Xynias drained Lake catchment (central Greece), Environmental Earth Sciences, 75:777, doi:10.1007/s12665-016-5565-x, 2016.
23. Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers assisted by adaptive metamodelling methods and radial basis functions, Water Resources Management, 30(15), 5845–5859, doi:10.1007/s11269-016-1337-3, 2016.
24. Yu, X., C. Duffy, Y. Zhang, G. Bhatt, and Y. Shi, Virtual experiments guide calibration strategies for a real-world watershed application of coupled surface-subsurface modeling, Journal of Hydrologic Engineering, 04016043, doi:10.1061/(ASCE)HE.1943-5584.0001431, 2016.
25. Partsinevelou, Α.-S., and L. Evrenoglou, Heavy metal contamination in surface water and impacts in public health. The case of Kifissos River, Athens, Greece, International Journal of Energy and Environment, 10, 213-218, 2016.
26. #Christelis, V., V. Bellos, and G. Tsakiris, Employing surrogate modelling for the calibration of a 2D flood simulation model, Sustainable Hydraulics in the Era of Global Change: Proceedings of the 4th IAHR Europe Congress (Liege, Belgium, 27-29 July 2016), A. S. Erpicum, M. Pirotton, B. Dewals, P. Archambeau (editors), CRC Press, 2016.
27. Charizopoulos, N., A. Psilovikos, and E. Zagana, A lumped conceptual approach for modeling hydrological processes: the case of Scopia catchment area, Central Greece, Environmental Earth Sciences, 76:18, doi:10.1007/s12665-017-6967-0, 2017.
28. Christelis, V., and A. Mantoglou, Physics-based and data-driven surrogate models for pumping optimization of coastal aquifers, European Water, 57, 481-488, 2017.
29. Evrenoglou, L., A. S. Partsinevelou, and P. Nicolopoulou-Stamati, Correlation between concentrations of heavy metals in children’s scalp hair and the environment. A case study from Kifissos River in Attica, Greece, Global NEST Journal, 19, 2017.
30. Christelis, V., R. G. Regis, and A. Mantoglou, Surrogate-based pumping optimization of coastal aquifers under limited computational budgets, Journal of Hydroinformatics, 20(1), 164-176, doi:10.2166/hydro.2017.063, 2018.
31. Nguyen, V. T., and J. Dietrich, Modification of the SWAT model to simulate regional groundwater flow using a multi-cell aquifer, Hydrological Processes, 32(7), 939-953, doi:10.1002/hyp.11466, 2018.
32. Kopsiaftis, G., V. Christelis, and A. Mantoglou, Comparison of sharp interface to variable density models in pumping optimisation of coastal aquifers, Water Resources Management, 33(4), 1397-409, doi:10.1007/s11269-019-2194-7, 2019.
33. Christelis, V., G. Kopsiaftis, and A. Mantoglou, Performance comparison of multiple and single surrogate models for pumping optimization of coastal aquifers, Hydrological Sciences Journal, 64(3), 336-349, doi:10.1080/02626667.2019.1584400, 2019.
34. #Πετροπούλου, Μ., Ε. Ζαγγάνα, Ν. Χαριζόπουλος, Μ. Μιχαλοπούλου, Α. Μυλωνάς, και Κ. Περδικάρης, Εκτίμηση του υδρολογικού ισοζυγίου της λεκάνης απορροής του Πηνειού ποταμού Ηλείας με χρήση του μοντέλου «Ζυγός», 14ο Πανελλήνιο Συνέδριο της Ελληνικής Υδροτεχνικής Ένωσης (ΕΥΕ), Βόλος, 2019.
35. Rozos, E., A methodology for simple and fast streamflow modelling, Hydrological Sciences Journal, 65(7), 1084-1095, doi:10.1080/02626667.2020.1728475, 2020.
36. Oruc, S., I. Yücel, and A. Yılmaz, Investigation of the effect of climate change on extreme precipitation: Capital Ankara case, Teknik Dergi, 33(2), doi:10.18400/tekderg.714980, 2021.
37. Lafare, A. E. A., D. W. Peach, and A. G. Hughes, Use of point scale models to improve conceptual understanding in complex aquifers: an example from a sandstone aquifer in the Eden valley, Cumbria, UK, Hydrological Processes, 35(5), e14143, doi:10.1002/hyp.14143, 2021.
38. Hayder, A. M., and M. Al-Mukhtar, Modelling the IDF curves using the temporal stochastic disaggregation BLRP model for precipitation data in Najaf City, Arabian Journal of Geosciences, 14, 1957, doi:10.1007/s12517-021-08314-6, 2021.
39. Bemmoussat, A., K. Korichi, D. Baahmed, N. Maref, O. Djoukbala, Z. Kalantari, and S. M. Bateni, Contribution of satellite-based precipitation in hydrological rainfall-runoff modeling: Case study of the Hammam Boughrara region in Algeria, Earth Systems and Environment, 5, 873-881, doi:10.1007/s41748-021-00256-z, 2021.
40. Gutierrez, J. C. T., C. B. Caballero, S. M. Vasconcellos, F. M. Vanelli, and J. M. Bravo, Multi-objective calibration of Tank model using multiple genetic algorithms and stopping criteria, Brazilian Journal of Water Resources, 27, e31, doi:10.1590/2318-0331.272220220046, 2022.
41. Udoh, G. C., G. J. Udom, and E. U. Nnurum, Suitability of soils for foundation design, Uruan, South Southern Nigeria, International Journal of Multidisciplinary Research and Growth Evaluation, 4(4), 962-972, 2023.

Κατηγορίες: Υπόγεια νερά, Υδρολογικά μοντέλα, Εργασίες φοιτητών