16 results on '"Tapoglou, Evdokia"'
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2. Wave power resource dynamics for the period 1980-2021 in Atlantic Europe's Northwest seas
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Rizaev, Igor, Dorrel, Robert, Oikonomou, Charikleia, Tapoglou, Evdokia, Hall, Carrie, Aggidis, George, Parsons, Daniel, Rizaev, Igor, Dorrel, Robert, Oikonomou, Charikleia, Tapoglou, Evdokia, Hall, Carrie, Aggidis, George, and Parsons, Daniel
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This paper explores the variability of wave power in space and time using a 42-year high-resolution hindcast wave model from the Copernicus Marine Environment Monitoring Service for the North-West European shelf. We calculate the wave energy flux using significant wave height and wave energy period. To improve wave power assessment, we use knowledge about mean wavelengths and bathymetry, which is necessary given the nature of the intermediate and shallow waters in the region. The results provide monthly, seasonal, and inter-annual estimates of wave power variability based on 122,728 modeled wave measurements. The study advances the understanding of wave energy resources within the domain.
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- 2023
3. A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation
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Tapoglou, Evdokia, Karatzas, George P., Trichakis, Ioannis C., and Varouchakis, Emmanouil A.
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- 2014
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4. Time‐Domain Implementation and Analyses of Multi‐Motion Modes of Floating Structures
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Sheng, Wanan, Tapoglou, Evdokia, Ma, Xiandong, Taylor, C. James, Dorrell, Robert M., Parsons, Daniel R., Aggidis, George, Sheng, Wanan, Tapoglou, Evdokia, Ma, Xiandong, Taylor, C. James, Dorrell, Robert M., Parsons, Daniel R., and Aggidis, George
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The study of wave‐structure interactions involving nonlinear forces would often make use of the popular hybrid frequency–time domain method. In the hybrid method, the frequency‐domain analysis could firstly provide the reliable and accurate dynamic parameters and responses; then these parameters and responses are transformed to the parameters to establishing the basic time domain equation. Additionally, with the addition of the required linear and nonlinear forces, the time‐domain analysis can be used to solve for the practical problems. However, the transformation from the frequency domain to the time domain is not straightforward, and the implementation of the time‐domain equation could become increasingly complicated when different modes of motion are coupled. This research presents a systematic introduction on how to implement the time‐domain analysis for floating structures, including the parameter transformations from the frequency domain to the time domain, and the methods for calculating and approximating the impulse functions and the fluid‐memory effects, with special attention being paid to the coupling terms among the different motion modes, and the correctness of the time‐domain‐equation implementation. The main purpose of this article is to provide relevant information for those who wish to build their own time‐domain analyses with the open‐source hydrodynamic analysis packages, although commercial packages are available for time‐domain analyses.
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- 2022
5. Hydrodynamic studies of floating structures:Comparison of wave-structure interaction modelling
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Sheng, Wanan, Tapoglou, Evdokia, Ma, Xiandong, Taylor, C. James, Dorrell, Robert M., Parsons, Daniel R., Aggidis, George, Sheng, Wanan, Tapoglou, Evdokia, Ma, Xiandong, Taylor, C. James, Dorrell, Robert M., Parsons, Daniel R., and Aggidis, George
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Current panel methods for wave-structure interactions employ the potential flow theory, which provide fast, reliable and relatively accurate predictions for the marine structures, and now some open source packages, NEMOH and HAMS, are available. In this research, the relative utility and performance of NEMOH and HAMS is compared with the well-known, state-of-art software, WAMIT. To bring focus to these comparisons, this research is based on three different floating structures: the truncated cylinder; the truncated cylinder with heave plate; and a novel multi-axis TALOS wave energy converter. To make the comparison more useful, this research investigates the incomplete and overlapped panels for the simple cylinder, to examine whether the respective code can handle these and still provide a meaningful solution. The comparisons may help us to understand whether the incomplete and/or overlapped panels can be used for simplifying the numerical modelling of those very complicated marine structures. From the comparisons, it can be seen the open source software, NEMOH and HAMS, both could produce very good results for the simple single marine structure, but also exhibit different capacities in dealing with more complicated marine structures. Specifically, HAMS could handle the thin structures and the overlapped panels effectively as WAMIT.
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- 2022
6. Time-Domain Implementation and Analyses of Multi-Motion Modes of Floating Structures
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Sheng, Wanan, primary, Tapoglou, Evdokia, additional, Ma, Xiandong, additional, Taylor, C. James, additional, Dorrell, Robert, additional, Parsons, Daniel R., additional, and Aggidis, George, additional
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- 2022
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7. Correction: Tapoglou, E., et al. Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete. Water 2019, 11, 587
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Tapoglou, Evdokia, primary, Vozinaki, Anthi Eirini, additional, and Tsanis, Ioannis, additional
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- 2019
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8. Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion
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Alexakis, Dimitrios D., primary, Tapoglou, Evdokia, additional, Vozinaki, Anthi-Eirini K., additional, and Tsanis, Ioannis K., additional
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- 2019
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9. Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete
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Tapoglou, Evdokia, primary, Vozinaki, Anthi, additional, and Tsanis, Ioannis, additional
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- 2019
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10. Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization
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Tapoglou, Evdokia, primary, Trichakis, Ioannis C., additional, Dokou, Zoi, additional, Nikolos, Ioannis K., additional, and Karatzas, George P., additional
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- 2014
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11. Erosivity parameters estimation using Artificial Neural Networks and Satellite imageries.
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Alexakis, Dimitrios D., Tapoglou, Evdokia, Vozinaki, Anthi-Eirini K., and Tsanis, Ioannis K.
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ARTIFICIAL neural networks , *REMOTE-sensing images , *MONTE Carlo method , *PARAMETER estimation , *KRIGING , *HUMUS , *GEOLOGICAL statistics , *SOIL testing - Abstract
In this study, satellite imageries, soil analysis and artificial intelligence were employed in order to improve the prediction of K-factor (erosivity factor). Real in-situ data were available through the collection and analysis of soil samples from 30 different locations at Akrotiri Peninsula in Chania, Crete, Greece. These data were used as a training set for an Artificial Neural Network (ANN) together with the satellite images data available in a number of spectral bands and the location (X and Y coordinates) of the sampling point. For the needs of the study, Sentinel-2 satellite images were used at 20m resolution. The simulation parameters investigated separately were the Soil Organic Matter (SOM), CaCO3 and the K-factor. Due to the small size of available data timeseries and in order to reduce the uncertainty involved, a Monte Carlo ensemble of ANNs was used. Specifically, 100 different realizations of each ANN were deployed, having different training/testing and evaluation datasets as well as different initial random neural weights. The ANN results are presented as the mean of the 100 simulations performed, as well as the minimum and maximum values. The spatial distribution of the parameters is presented in GIS environment and is compared, in terms of accuracy, with standard spatial interpolation methods, such as Co-Kriging. The results suggest a successful simulation, having a mean R-square value of 0.87 for SOM, 0.82 for CaCO3 and 0.6 for K-factor simulation. Especially in the case of SOM and CacO3 the results are very close to the observed field values, while in the case of K-factor the performance of the ANNs is decreased. In any case, results suggest that using satellite images in conjunction with real soil data, combined through artificial intelligence methods, can produce reliable spatial maps with finer resolution compared to maps produced by real data combined with interpolation methods.Keywords: Erosivity, ANN, Sentinel - 2, Kriging, CreteThe research leading to these results has received funding from the H2020 under grant agreement n° 677407 (SOILCARE). [ABSTRACT FROM AUTHOR]
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- 2019
12. Correction: Climate change impact on the frequency of hydrometeorological extremes in the Island of Crete. [Water (2019) 11, 587] doi 10.3390/w11030587
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Tapoglou Evdokia, Vozinaki Anthi-Eirini, and Tsanis Ioannis
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Drought indicators ,Climate change ,Frequency analysis ,Extreme events - Abstract
Summarization: The authors wish to make the following corrections to this paper [1]: The journal paper [30] in References [30] Samuel, J.; Coulibaly, P.; Metcalfe, R.A. Estimation of continuous streamflow in Ontario ungauged basins: Comparison of regionalization methods. J. Hydrol. Eng. 2011, 16, 447-459. Be replaced by the following journal paper: [30] Grillakis, M.G.; Koutroulis, A.G.; Daliakopoulos, I.N.; Tsanis, I.K. A method to preserve trends in quantile mapping bias correction of climate modeled temperature. Earth Syst. Dyn. 2017, 8, 889-900. Presented on
13. Uncertainty analysis of a combined artificial neural network – fuzzy logic – kriging system for spatial and temporal simulation of hydraulic head
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Tapoglou Evdokia, Karatzas Giorgos, Trichakis Ioannis, and Varouchakis Emmanouil
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Artificial neural networks,Nets, Neural (Computer science),Networks, Neural (Computer science),Neural nets (Computer science),neural networks computer science,artificial neural networks,nets neural computer science,networks neural computer science,neural nets computer science ,Engineering, Hydraulic,hydraulic engineering,engineering hydraulic - Abstract
Summarization: The purpose of this study is to evaluate the uncertainty, using various methodologies, in a combined Artificial Neural Network (ANN) – Fuzzy logic – Kriging system, which can simulate spatially and temporally the hydraulic head in an aquifer. This system uses ANNs for the temporal prediction of hydraulic head in various locations, one ANN for every location with available data, and Kriging for the spatial interpolation of ANN's results. A fuzzy logic is used for the interconnection of these two methodologies. The full description of the initial system and its functionality can be found in Tapoglou et al. (2014). Two methodologies were used for the calculation of uncertainty for the implementation of the algorithm in a study area. First, the uncertainty of Kriging parameters was examined using a Bayesian bootstrap methodology. In this case the variogram is calculated first using the traditional methodology of Ordinary Kriging. Using the parameters derived and the covariance function of the model, the covariance matrix is constructed. A common method for testing a statistical model is the use of artificial data. Normal random numbers generation is the first step in this procedure and by multiplying them by the decomposed covariance matrix, correlated random numbers (sample set) can be calculated. These random values are then fitted into a variogram and the value in an unknown location is estimated using Kriging. The distribution of the simulated values using the Kriging of different correlated random values can be used in order to derive the prediction intervals of the process. In this study 500 variograms were constructed for every time step and prediction point, using the method described above, and their results are presented as the 95th and 5th percentile of the predictions. The second methodology involved the uncertainty of ANNs training. In this case, for all the data points 300 different trainings were implemented having different training datasets each time. These datasets were created by choosing randomly 80% of the observed input/output data at every location. In every case, the remaining 20% of the input/output patterns were used for the testing of the corresponding ANN. Moreover, the initial weight values were also randomized at the beginning of every training. All the resulting network trainings were consequently used for the simulation of the hydraulic head spatially and temporally. The results are again presented as the 95th and 5th percentile and represent the 90% confidence interval of the prediction. Παρουσιάστηκε στο: EGU General Assembly 2015
14. Predicting spatial and temporal changes in groundwater levels using artificial Neural networks and geostatistical methods
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Tapoglou Evdokia, Καρατζας Γιωργος, Karatzas Giorgos, Νικολαιδης Νικολαος, Nikolaidis Nikolaos, Νικολος Ιωαννης, Nikolos Ioannis, Χρυσικοπουλος Κωνσταντινος, Chrysikopoulos Constantinos, Τσανης Γιαννης, Tsanis Giannis, Χριστοπουλος Διονυσιος, Christopoulos Dionysios, Λουκάς Αθανάσιος, Επιβλέπων: Καρατζας Γιωργος, Advisor: Karatzas Giorgos, Μέλος επιτροπής: Νικολαιδης Νικολαος, Committee member: Nikolaidis Nikolaos, Μέλος επιτροπής: Νικολος Ιωαννης, Committee member: Nikolos Ioannis, Μέλος επιτροπής: Χρυσικοπουλος Κωνσταντινος, Committee member: Chrysikopoulos Constantinos, Μέλος επιτροπής: Τσανης Γιαννης, Committee member: Tsanis Giannis, Μέλος επιτροπής: Χριστοπουλος Διονυσιος, Committee member: Christopoulos Dionysios, and Μέλος επιτροπής: Λουκάς Αθανάσιος
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Groundwater simulation ,Artificial neural networks,Nets, Neural (Computer science),Networks, Neural (Computer science),Neural nets (Computer science),neural networks computer science,artificial neural networks,nets neural computer science,networks neural computer science,neural nets computer science ,Geological statistics,Geostatistics,geology statistical methods,geological statistics,geostatistics - Abstract
Διδακτορική διατριβή που υποβλήθηκε στη σχολή Μηχανικών Περιβάλλοντος Περίληψη: Σκοπός της παρούσας διατριβής είναι η δημιουργία ενός προγράμματος χωρικής και χρονικής προσομοίωσης του υδραυλικού ύψους ενός υδροφορέα, με χρήση μεθόδων υπολογιστικής νοημοσύνης και γεωστατιστικών μεθόδων. Τα Τεχνητά Νευρωνικά Δίκτυα είναι η μέθοδος που επιλέχθηκε για τη χρονική προσομοίωση, καθώς έχει αποδειχθεί ήδη στην βιβλιογραφία ότι η χρήση της φέρει καλά αποτελέσματα χωρίς την απαίτηση πολύπλοκων και δυσεύρετων δεδομένων εισόδου. Η μεθοδολογία του Kriging ακολουθήθηκε για τη χωρική προσομοίωση και παρεμβολή των αποτελεσμάτων των τεχνητών νευρωνικών δικτύων στο χώρο. Για το συνδυασμό των δύο αυτών μεθοδολογιών χρησιμοποιήθηκε ένα σύστημα ασαφούς λογικής.Το πρώτο βήμα που ακολουθείται στην προτεινόμενη προσέγγιση είναι η συλλογή όλων των διαθέσιμων δεδομένων. Στην παρούσα διατριβή συλλέχθηκαν δεδομένα και έγινε προσομοίωση του υδραυλικού ύψους για δύο περιοχές μελέτης μια στην Βαυαρία της Γερμανίας και μια στο Μαϊάμι της πολιτείας Φλόριντα των ΗΠΑ. Οι δύο αυτές περιοχές έχουν πολύ διαφορετικά χαρακτηριστικά μεταξύ τους και για αυτό το λόγο η επιτυχής προσομοίωση του υδραυλικού ύψους σε αυτές μπορεί να επιβεβαιώσει την αξιοπιστία του μοντέλου. Ακολουθεί η προσομοίωση με χρήση τεχνητών νευρωνικών δικτύων και ταυτόχρονα δοκιμάστηκε και η χρήση συστήματος ασαφούς λογικής για την επιλογή των κατάλληλων γειτόνων που στην συνέχεια χρησιμοποιούνται από τον αλγόριθμο του kriging. Τέλος, εφαρμόζεται η μεθοδολογία της παρεμβολής με kriging, με χρήση τριών διαφορετικών βαριογραμμάτων σε κάθε περίπτωση. Τα αποτελέσματα αξιολογούνται μέσω μιας σειράς δεικτών σφάλματος σε δεδομένα διασταυρωμένης επικύρωσης και προσδιορίζεται το πιο κατάλληλο θεωρητικό μοντέλο βαριογράμματος για κάθε περιοχή μελέτης ξεχωριστά. Για την πρώτη περιοχή μελέτης στη Βαυαρία, καταλληλότερο βαριόγραμμα ήταν το δυναμονομικό με τιμή για τη ρίζα του μέσου τετραγωνικού σφάλματος (RMSE) ίση με 7.6·10-3 m,ενώ για την δεύτερη περιοχή μελέτης καταλληλότερο βαριόγραμμα ήταν το εκθετικό με τιμή για το δείκτη σφάλματος RMSE ίση με 0.962 m. Βασική διαφορά που οδηγεί σε αυτή την απόκλιση στις τιμές του σφάλματος ήταν ότι στην πρώτη περίπτωση προσομοιώνεται η διαφορά του υδραυλικού ύψους, ενώ στη δεύτερη περιοχή μελέτης προσομοιώνεται το υδραυλικό ύψος αυτό καθ’ αυτό, διαφορά που οφείλεται στα στατιστικά χαρακτηριστικά των χρονοσειρών. Για την επιβεβαίωση του μοντέλου και την πιστοποίηση της ακρίβειας του, πραγματοποιήθηκε ανάλυση αβεβαιότητας στα επιμέρους κομμάτια της μεθοδολογίας.Η καινοτομία της παρούσας διδακτορικής διατριβής είναι η ανάπτυξη ενός μοντέλου με βάση τα δεδομένα το οποίο μπορεί να χρησιμοποιηθεί για τη χωρική και χρονική προσομοίωση του υδραυλικού ύψους, χωρίς την απαίτηση γεωλογικών δεδομένων. Η χρήση της ασαφούς λογικής για τον προσδιορισμό των γειτόνων του kriging αποτελεί καινοτομία της παρούσας εργασίας και μπορεί να βελτιώσει τα αποτελέσματα της μεθόδου. Η εφαρμογή του μοντέλου σε δύο διαφορετικού γεωλογικού υπόβαθρου περιοχές μελέτης, μια προσχωματική και μια καρστική, αποδεικνύει την αποτελεσματικότητα του κάτω από διάφορες συνθήκες. Summarization: The purpose of this study is to create a spatial and temporal simulation program for the estimation of the hydraulic heads in an aquifer, using computational intelligence and geostatistical methods. Artificial neural networks were chosen for the temporal simulation, due to their proven ability, established in literature. This choice is further reinforced by the fact that their implementation does not require complex and hard to obtain input data. The methodology was completed by using the Kriging method for the spatial interpolation of the artificial neural network’ simulation results. A fuzzy logic system was employed to combine these two methodologies.The first step in the proposed approach is the collection of all available data. In this study, data were collected and the hydraulic head was simulated for two study areas; one in Bavaria, Germany and one in Miami, Florida, USA. These two regions have very different characteristics (geological, climatic and land use) and for this reason the successful simulation of hydraulic head in these regions can confirm the reliability of the model. Next, the simulation using artificial neural networks was performed, while at the same time the use of a fuzzy logic system for the selection of suitable neighbors for Kriging algorithm was tested. In this way, the use the fuzzy logic system was proven to be the more effective. Finally, the interpolation of the point hydraulic head estimation was performed by kriging using three different variogram models in each case. The results are evaluated through a series of cross-validation results error indicators. For the first study area in Bavaria, the power-law variogram was the most appropriate variogram yielding a root mean square error (RMSE) equal to 7.6·10-3 m, while for the second study area in Miami, the most appropriate variogram was the exponential one with error indicator of RMSE = 0.962 m. The key difference between the two case studies, leading to this deviation in RMSE values is that, the first case the hydraulic head change per time step was simulated, while in the second study area the hydraulic head itself was simulated. This difference in output parameters was due to the dataset involved in every case. Uncertainty analysis in different components of the methodology was performed in order to validate the model and verify its accuracy. The results of these processes showed that the methodology used was efficient, accurate and stable with regards to its results and errors.The innovation of this thesis is the development of a data-based model which can be used to predict the hydraulic head in an aquifer both spatially and temporally, without having knowledge about the geological characteristics of the study area. Instead data available for a long time and is easy monitor can be used. Moreover, the use of fuzzy logic to determine the kriging neighbors is an innovation of this study and improves considerably the results. The implementation of the model in two study areas with different geological background, an alluvial and a karstic proves its effectiveness under various conditions.
15. Uncertainty Estimations in Different Components of a Hybrid ANN - Fuzzy - Kriging Model for Water Table Level Simulation
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Tapoglou, Evdokia, primary, Varouchakis, Emmanouil A., additional, and Karatzas, George P., additional
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16. Εκτίμηση υδατικού δυναμικού της ανατολικής Κρήτης σε σενάρια κλιματικής αλλαγής με χρήση του λογισμικού ΥΔΡΟΝΟΜΕΑΣ
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Ρετσα Αννα http://users.isc.tuc.gr/~aretsa, Retsa Anna http://users.isc.tuc.gr/~aretsa, Τσανης Γιαννης, Tsanis Giannis, Χρυσικοπουλος Κωνσταντινος, Chrysikopoulos Constantinos, Ταπογλου Ευδοκια, Tapoglou Evdokia, Επιβλέπων: Τσανης Γιαννης, Advisor: Tsanis Giannis, Μέλος επιτροπής: Χρυσικοπουλος Κωνσταντινος, Committee member: Chrysikopoulos Constantinos, Μέλος επιτροπής: Ταπογλου Ευδοκια, and Committee member: Tapoglou Evdokia
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Water resources management ,Διαχείριση υδατικών πόρων ,Κλιματική αλλαγή ,Climatic change - Abstract
Διπλωματική Εργασία Περίληψη: Στο πλαίσιο της παρούσας διπλωματικής εργασίας, εκτιμάται το υδατικό δυναμικό της ανατολικής Κρήτης για σενάρια κλιματικής αλλαγής με χρήση του λογισμικού ΥΔΡΟΝΟΜΕΑΣ. Από την πληθώρα κλιματικών μοντέλων και σεναρίων για το μέλλον που έχει αναπτυχθεί για την κατανόηση και αξιολόγηση των επιπτώσεων της κλιματικής αλλαγής στις μετεωρολογικές και υδρολογικές παραμέτρους, στην παρούσα εργασία έχουν χρησιμοποιηθεί 4 Περιοχικά Κλιματικά Μοντέλα (RCMs), σε δύο διαφορετικά αντιπροσωπευτικά μονοπάτια συγκέντρωσης (RCP 4.5 και RCP 8.5). Ως περιοχή μελέτης ορίζεται η περιοχή της ανατολικής Κρήτης, η οποία χαρακτηρίζεται ως περιοχή ευαίσθητη στις επιπτώσεις της κλιματικής αλλαγής. Οι πιέσεις είναι τόσο φυσικές, σχετιζόμενες με τις μειωμένες βροχοπτώσεις και τους λιγότερους υδάτινους πόρους που διαθέτει σε σχέση με τη δυτική Κρήτη, όσο και ανθρωπογενείς, με υψηλές ανάγκες άρδευσης και αυξημένες ανάγκες ύδρευσης καθώς περιλαμβάνει το μεγάλο αστικό κέντρο του Ηρακλείου. Η μεθοδολογία που ακολουθείται διακρίνεται σε επιμέρους βήματα. Αρχικά γίνεται η σχηματοποίηση του υδροσυστήματος, δηλαδή ο μετασχηματισμός των συνιστωσών του πραγματικού συστήματος της περιοχής μελέτης σε συνιστώσες του μοντέλου «ΥΔΡΟΝΟΜΕΑΣ» που αναπαριστά το εν λόγω σύστημα. Η σχηματοποίηση βασίζεται στο διαχειριστικό ομοίωμα της Κρήτης που αναπτύχθηκε από την Περιφέρεια Κρήτης στο διαχειριστικό μοντέλο RIBASIM (River Basin Simulation Model). Ακολουθεί η εισαγωγή των δεδομένων εισόδου του συστήματος: τα χαρακτηριστικά των συνιστωσών και οι χρονοσειρές εισροών νερού στο δίκτυο αλλά και εισροών και απωλειών των ταμιευτήρων. Ο καθορισμός των στόχων και λειτουργικών προσδιορισμών ολοκληρώνει την ανάπτυξη του μοντέλου. Οι στόχοι αφορούν τις απαιτήσεις σε νερό (ύδρευση και άρδευση) και τη διασφάλιση μιας ελάχιστης παροχής σε υδατορεύματα (οικολογική παροχή). Η προσομοίωση λειτουργίας του συστήματος γίνεται αρχικά για την ιστορική περίοδο (1978-1996) με δεδομένα παρατήρησης και κατόπιν έγινε η σύγκριση των αποτελεσμάτων με τα αποτελέσματα που προέκυψαν από την προσομοίωση με δεδομένα των τεσσάρων κλιματικών μοντέλων για την ίδια περίοδο. Η καλή συσχέτιση μεταξύ των αποτελεσμάτων, που προέκυψε, επέτρεψε την ασφαλή συνέχεια στα επόμενα βήματα χωρίς να απαιτείται η προσαρμογή των κλιματικών δεδομένων των μοντέλων. Επομένως, ακολούθησε η προσαρμογή στην μελλοντική κατάσταση συγκεκριμένων δεδομένων του συστήματος (εισροές στο δίκτυο και απαιτήσεις νερού) και τέλος, η προσομοίωση λειτουργίας του συστήματος για τα δύο σενάρια κλιματικής αλλαγής που εξετάζονται: RCP4.5 @ +2oC SSP3 για την περίοδο 2037-2066 και RCP8.5 @ +2oC SSP3 για την περίοδο 2026-2055. Στα τελικά αποτελέσματα της διερεύνησης των επιπτώσεων της κλιματικής αλλαγής στον σύστημα παρουσιάζονται οι συγκρίσεις τόσο μεταξύ των σεναρίων κλιματικής αλλαγής όσο και με την ιστορική περίοδο. Κύρια συμπεράσματα είναι τα προκύπτοντα υψηλά ελλείμματα νερού και οι αυξημένες αστοχίες στο σύστημα υπό καθεστώς κλιματικής αλλαγής. Με βάση τα συμπεράσματα της μελέτης διατυπώνονται προτάσεις ορθής διαχείρισης των υδάτων για τον περιορισμό των επιπτώσεων της κλιματικής αλλαγής όπως επίσης και προτάσεις για περαιτέρω έρευνα. Summarization: The present thesis assesses the potential of the water resources system for eastern Crete, for various scenarios of climate change, using the HYDRONOMEAS software. Of the plethora of climate models and future scenarios developed for understanding and evaluating the impact of climate change on the meteorological and hydrological parameters, the present study uses 4 Regional Climatic Models (RCMs), at 2 different Representative Concentration Pathways (RCP 4.5 and RCP 8.5). Eastern Crete has been considered as the study area, being an area sensitive to the impacts of climate change. Impacts are both natural, concerning the lower rainfalls and the less water resources compared to western Crete, and anthropogenic, concerning the high irrigation needs and the high public water supply needs as this area includes the city of Heraklion. The study methodology has the following steps: First, schematization of the hydrosystem was done, i.e., the transformation of the components of the original system to the component of the HYDRONOMEAS model that represents the original system. Schematization is based on the water management prototype of Crete developed by Region of Crete in the water management model RIBASIM (River Basin Simulation Model). This step is followed by entry of input data: the features of the components and the time series of water inflows in the network as well as inflows and spills of the reservoirs. The development of the model is concluded by the definition of the targets and operational determinations. Targets concern the water demands (irrigation and public water supply) and the assurance of a minimum river flow during droughts (ecological supply). The simulation of the original system operation is first conducted for the historical period (1978-1996) with observation data ∙ then the results were compared to the results deriving from the simulation conducted with the data of the four climate models for the same period. The good correlation found between the results, allowed the safe continuation to the following steps without the need to adjust the climate data of the models. Consequently, adjustment to the future state of specific system data was made (inflows in the network and water needs) and, at the end, simulation of the system operation was made for the two scenarios of climate change contemplated in this study: RCP4.5 @ +2oC SSP3 for period 2037-2066 and RCP8.5 @ +2oC SSP3 for period 2026-2055. The results of the study of climate change impacts on the system show comparisons both between the climate change scenarios and the historical period. The main conclusions include the resulting high water deficit and the increased system failure. Based on the conclusions of this study, suggestions are made pertaining to the correct water management to reduce the impacts of climate change as well as suggestions for further research.
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