Η παρούσα διδακτορική διατριβή είχε ως αντικείμενο την ανάπτυξη μιας ολοκληρωμένης μεθοδολογίας με καινοτόμα στοιχεία για την αξιόπιστη και βέλτιστη συνδυασμένη εφαρμογή των κλιματικών και των υδρολογικών-υδρογεωλογικών μοντέλων σε υδροφορείς με ελάχιστα ή και χωρίς παρατηρούμενα μετεωρολογικά και υδρολογικά-υδρογεωλογικά δεδομένα. Για την επίτευξη του στόχου συνδυάστηκαν διαφορετικά μοντέλα (κλιματικά μοντέλα, μοντέλα υδρολογίας και προσομοίωσης υπόγειας ροής), επιστημονικά εργαλεία (Συστήματα Γεωγραφικών Πληροφοριών-GIS), καθώς και στατιστικά πακέτα (πακέτο γλώσσας προγραμματισμού R). Η εφαρμογή της μεθοδολογίας πραγματοποιήθηκε στον αλλουβιακό υδροφορέα, που αναπτύσσεται στο παράκτιο τμήμα της λεκάνης απορροής του ποταμού Χαβρία Χαλκιδικής. Για την εκτίμηση της κλιματικής αλλαγής, χρησιμοποιήθηκε το περιοχικό κλιματικό μοντέλο RegCM4, στο οποίο ενσωματώθηκαν τα μοντέλα γενικής κυκλοφορίας MPI και HadGEM2 με χωρική ανάλυση 50 x 50 km, ακολουθώντας μια από τις πλέον πρόσφατες προσεγγίσεις και συγκεκριμένα, το πιο ακραίο σενάριο εκπομπών RCP8.5. Για τη ρεαλιστική αναπαράσταση του παροντικού κλίματος και την εκτίμηση του μελλοντικού κλίματος της περιοχής έρευνας δημιουργήθηκε μια βάση δεδομένων, αποτελούμενη από κλιματικές παραμέτρους υψηλής χωροχρονικής κλίμακας, η οποία επιτεύχθηκε μέσω της χωροχρονικής μεθόδου βέλτιστης παρεμβολής Kriging. Από την εφαρμογή της χωροχρονικής μεθόδου βέλτιστης παρεμβολής Kriging στις μελλοντικές παραμέτρους των δεδομένων εισόδου του περιοχικού κλιματικού μονέλου RegCM4, εκτιμήθηκαν οι μεταβολές των κλιματικών παραμέτρων για τις μελλοντικές περιόδους 2031-2050 και 2080-2099. Τα ποσοστά μείωσης και αύξησης των κλιματικών παραμέτρων, που προέκυψαν, διαφέρουν ανάλογα με το μοντέλο γενικής κυκλοφορίας, που χρησιμοποιείται ως δεδομένο εισόδου στο περιοχικό κλιματικό μοντέλο RegCM4. Η προσομοίωση της υπόγειας ροής του παράκτιου υδροφορέα της λεκάνης απορροής του ποταμού Χαβρία σε συνθήκες κλιματικής αλλαγής πραγματοποιήθηκε μέσω της εφαρμογής του κώδικα MODFLOW. Για τον προσδιορισμό του παροντικού και του μελλοντικού εμπλουτισμού του υδροφορέα, που γίνεται μέσω της κατείσδυσης του νερού της βροχόπτωσης, της διήθησης από τον ποταμό Χαβρία και των επιστροφών άρδευσης, χρησιμοποιήθηκε το υδρολογικό μοντέλο ArcSWAT. Από τα αποτελέσματα της συνδυασμένης εφαρμογής του υδρολογικού μοντέλου ArcSWAT με το περιοχικό κλιματικό μοντέλο RegCM4, παρατηρήθηκε τάση μείωσης της κατείσδυσης έως το τέλος του 21ου αιώνα, που ποικίλει ανάλογα με το μοντέλο γενικής κυκλοφορορίας και κυμαίνεται από 4,5-11% (περίοδος 2031-2050) έως 15-27% (περίοδος 2080-2099). Επιπρόσθετα, διαπιστώθηκε ότι όχι μόνο οι μεταβολές στη βροχόπτωση αλλά και οι μεταβολές στη θερμοκρασία επιδρούν καθοριστικά στις συνιστώσες του υδρολογικού ισοζυγίου. Τέλος, η διερεύνηση των επιπτώσεων της κλιματικής αλλαγής στη στάθμη του υπόγειου νερού επιτεύχθηκε μέσω της εφαρμογής του κώδικα MODFLOW με δεδομένα εισαγωγής τα αποτελέσματα της εφαρμογής του υδρολογικού μοντέλου ArcSWAT με τα διάφορα κλιματικά δεδομένα. Από την προσομοίωση του παράκτιου αλλουβιακού υδροφορέα σε συνθήκες κλιματικής αλλαγής προέκυψε η συνεχής ταπείνωση της στάθμης του υπόγειου νερού έως το τέλος του 21ου αιώνα, ως επακόλουθο της μείωσης της κατείσδυσης και κατ’επέκταση της επανατροφοδοσίας του. Η ελάττωση του διαθέσιμου υδατικού δυναμικού και η διείσδυση του θαλασσινού νερού προς την ενδοχώρα εκτιμάται ότι θα προκαλέσει την ποσοτική μείωση και ποιοτική υποβάθμιση του υδροφόρου συστήματος. Το γεγονός αυτό θα αποτελέσει τροχοπέδη για την κάλυψη των υδρευτικών και αρδευτικών αναγκών της περιοχής έρευνας, καθώς συνδέονται άμεσα με το υπόγειο νερό.

The object of the dissertation thesis is to introduce a comprehensive methodology, which can be implemented into any ungauged or data-scarce aquifer, reducing the uncertainties in hydrogeological-hydrological simulation due to the limited observed hydrogeological-hydrological and meteorological data. Overall, the proposed methodology leads to the reliable estimation of the potential climate change impacts on an aquifer. For this purpose, climate, hydrological and groundwater flow models, tools (GIS) and statistical packages (R statistical program) were coupled. The proposed methodology was carried out in a coastal alluvial aquifer, being part of the Havrias river basin (Chalkidiki, Greece). The general circulation models (GCMs), Hadley Global Environment Model 2 (HadGME2) and MPI Earth System Model running on mixed resolution grid (MPI) under the extreme RCP8.5 pathway were used as forcing data to the Regional Climate Model Version 4 (RegCM4) in order to represent the future climate over the research area. The reliability of the RegCM4 climate model to represent the climate conditions over the research area was enhanced by applying the spatio-temporal Kriging approach. The spatio-temporal Kriging was also implemented into the climate model simulations for the future periods (2031-2050 and 2080-2099). Based on the results, the changes (increase/decrease) in the future climate parameters vary between the General Circulation models (GCMs). Then, the MODFLOW was employed to simulate the groundwater system of the coastal aquifer of the Havrias river basin under climate change conditions. The aquifer’s recharge was quantified by using the ArcSWAT hydrological model. The aquifer is mainly recharged mainly by rainfall infiltration, infiltration through torrent beds and irrigation returns. The potential climate change effects on the hydrological components (infiltration, surface runoff and evapotranspiration) over the research area until the end of the 21st century were investigated by driving the ArcSWAT model with the Regional Climate Model Version 4 (RegCM4) forcing data, resulted from the spatio-temporal Kriging approach. According to the results, the response of the hydrological components varies between the climate model simulations. In particular, the infiltration reduction ranges between 4.5-11% (2031-2050) and 15-27% (2080-2099). Moreover, it is proved that both precipitation and temperature are the most influential climate parameters in determining the water balance of the study area. Τhe results from the SWAT application with the climate model data, namely the estimated infiltration and runoff, were used as input data to drive the MODFLOW model. The groundwater simulation indicated that the reduce in infiltration resulted in the groundwater level decline until the end of the 21st century. The estimated decline of the groundwater level implies the decrease in the water resources availability and the seawater intrusion, causing the qualitative and quantitative deterioration of the aquifer system. In conclusion, the above methodology can be applied into any ungauged or data-scarce aquifer for the reasonable assessment of hydrogeological-hydrological impacts of climate change.

Ελληνική Βιβλιογραφία

Βεράνης, Ν. κ.ά. 2010. Υδρογεωλογική Μελέτη-Υδροφόρα Συστήματα Επανομής-Μουδανιών, Κασσάνδρας, Ορμύλιας και Σιθωνίας του Υδατικού Διαμερίσματος Κεντρικής Μακεδονίας (ΥΔ10), ΙΓΜΕ, Τομέας Υδατικών Πόρων και Περιβάλλοντος-Διεύθυνση Υδρογεωλογίας-Περιφερειακή Μονάδα Κεντρικής Μακεδονίας, Γ ΚΠΣ Επιχειρησιακό Πρόγραμμα Ανταγωνιστικότητα

Βουδούρης, Κ. 2013. Τεχνική Υδρογεωλογία, Υπόγεια Νερά, Εκδόσεις Τζιόλα, Θεσσαλονίκη

Βουδούρης, Κ. 2015. Εκμετάλλευση και Διαχείριση Υπόγειου Νερού, Εκδόσεις Τζιόλα, Θεσσαλονική

Καλλιώρας, Α. 2007. Διαχείριση υπόγειων υδατικών πόρων σε υδροφορείς που υπόκεινται σε καθεστώς θαλάσσιας διείσδυσης. Η περίπτωση του δυτικού παράκτιου τμήματος της Ροδόπης. Διδακτορική διατριβή, Τμήμα Πολιτικών Μηχανικών, Ξάνθη, σελ. 290

Καπαγερίδης, Ι. 2006. Εισαγωγή στην Γεωστατιστική, Εκδόσεις Ιων, Αθήνα

Μουντράκης, Δ. 2010. Γεωλογία της Ελλάδας, Εκδόσεις University Studio Press, Θεσσαλονίκη

Λουκάς, Α. 2015. Υδρολογική Προσομοίωση και Πρόγνωση: Γεωστατιστική, Διαδυκτιακές Σημειώσεις, Εργαστήριο Υδρολογίας και Ανάλυσης Υδατικών Συστημάτων, Τμήμα Πολιτικών Μηχανικών, Πολυτεχνική Σχολή, Πανεπιστήμιο Θεσσαλίας

Παπαζαφειρίου, Ζ.Γ. 1999. Οι ανάγκες σε νερό των καλλιεργειών. Εκδόσεις ΖΗΤΗ, Θεσσαλονίκη

Χρηστάρας Β., και Χατζηαγγέλου Μ., 2011. Απλά Βήματα στην Εδαφομηχανική, Εκδόσεις University Studio Press, Θεσσαλονίκη.

Ξενόγλωσση Βιβλιογραφία

AASHO, 1961. The classification of soils and soil-aggregate mixtures for highway construction purposes. In Standard specifications for highway materials and methods for sampling and testing, 8th ed., Part 1, Specifications, Am. Assoc. State Highway Officials, 45-51

Abbaspour, K.C., Vaghefi, S.A. and Srinivasan, R. 2017. A Guideline for Successful Calibration and Uncertainty Analysis for Soil and Water Assessment: A Review of Papers from the 2016 International SWAT Conference, Water 2018, 10(6); doi:10.3390/w10010006

Allen, R.G. 1986. A Penman for all seasons, J. Irrig. and Drain Engng., ASCE, 112(4), 348-368

Allen, R.G., Jensen, M.E., Wright, J.L. and Burman R.D. 1989. Operational estimates of evapotranspiration, Agron. J., 81, 650-662

Anderson, M.D. and Woessner, W.W. 1992. Applied Ground Water Modeling: Simulation of flow and adjective transport. Academic Press, 372

Andreu, M., Martínez-Santos, P., Pulido-Bosch, A., García-Sánchez, E. 2010. Resources Assessment of a Small Karstic Mediterranean Aquifer (South-Eastern, Spain), J. Advances in Research in Karst Media, 13, doi: 10.1007/978-3-642-12486-0

Arnold, J.G., Srinivasan, R., Muttiah, R.S. and Williams, J.R. 1998. Large area hydrologic modeling and assessment part I: model development. Journal of the American Water Resources Association, 34 (1), 73–89. doi:10.1111/j.1752-1688.1998.tb05961.x

Arnold, J.G., et al., 2012. SWAT: model use, calibration, and validation. Transactions of the ASABE, 55 (4), 1491–1508. doi:10.13031/2013.42256

Artale, V., Calmanti, S., Carillo, A., Dell’Aquila, A., et al. 2010. An atmosphere–ocean regional climate model for the Mediterranean area: assessment of a present climate simulation. Clim Dyn, 35, 721–740

Anthes, R.A., Hsie, E.Y., Kuo, Y.H. 1987. Description of the Penn State/NCAR Mesoscale Model Version 4 (MM4). National Center for Atmospheric Research Tech Note TN-282+ STR, NCAR, Boulder, CO

Baltas, E. and Karaliolidou, M.C. 2007. Hydrological effects of land use and climate changes in northern Greece, Journal of Land Use Science, 2(4), 225–241, doi: 10.1080=17474230701622908

Bilas, G., Dionysiou, N., Karapetsas, N., Silleos, K., Misopolinos, N. 2016. Development of a national geodatabase (Greece) for soil surveys and land evaluation using space technology and GIS, European Geosciences Union General Assembly, Vienna, Austria ,17–22 April 2016

Binger, R.L., 1996. Runoff simulated from Goodwin Creek watershed using SWAT, Transaction of the American Society of Agricultural Engineering (ASAE), 19, 85-90

Bilonick, R.A. 1988. Monthly hydrogen ion deposition maps for the northeastern U.S. from July 1982 to September 1984. Atmospheric Environment 22(9), 1909–1924, doi:10.1016/00046981(88)90080-7

Brassel, K.E., and Douglas, R., 1979. A Procedure to Generate Thiessen Polygons. Geographic Analysis, 11(3), 290-303, doi: 0016-7363/79/0779-0289$00.!50/0

Bretherton, C.S., McCaa, J.R., Grenier, H. 2004. A new parameterization for shallow cumulus convection and its application to marine subtropical cloud-topped boundary layers. I. Description and 1D results. Mon Weather Rev 132, 864–882

Brouziyne, Y., Abouabdillah, A., Bouabid, R., Benaabidate L., Oueslati, O. 2017. SWAT manual calibration and parameters sensitivity analysis in a semi-arid watershed in North-western Morocco, Arab J Geosci, 10: 427, doi 10.1007/s12517-017-3220-9

Candela, L., Wolf von Igel F, Elorza, J., Aronica, G., 2009. Ιmpact assessment of combined climate and management scenarios on groundwater resources and associated wetland (Majorca, Spain), Journal of Hydrology 376: 510–52

Candela, L., Tamoh, K., Olivares, O., Gomez, M. 2012. Modelling impacts of climate change on water resources in ungauged and data-scarce watersheds. Application to the Siurana catchment (NE Spain). Science of the Total Environment 440, 253-260. 10.1016/j.scitotenv.2012.06.062

Collins, W.J., Bellouin, N., and Doutriaux-Boucher M, et. al 2011. Development and evaluation of an Earth-system model HadGEM2. Geosci. Model Dev. Discuss., 4, 997–1062, doi:10.5194/gmdd-4-9972011

Coppola, E., Giorgi, F., Mariotti, L., Bi, X. 2012. RegT-Band: a tropical band version of RegCM4. Clim Res, 52, 115–133

Cressie, N.A.C. 1993. Statistics for Spatial Data. Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics. New York: John Wiley & Sons, Inc

Cressie, N.A.C., and Wikle, C.K. 2011. Statistics for Spatio-Temporal Data. Wiley, 204, 205

Dee, P., Uppala, M.S., Simmons, A.J., et. al 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Royal Meteorological Society, 137, 553–597

De Cesare, L. Myers, D., and Posa, D. 2001. Estimating and modeling space-time correlation structures. Statistics & Probability Letters, 51(1), 9–14, doi: 10.1016/S0167-7152(00)00131-0

De Iaco, S., Myers, D., and Posa, D. 2001. Space-time analysis using a general product-sum model. Statistics & Probability Letters, 52(1), 21–28, doi: 10.1016/S0167-7152(00)00200-5

Demircan, M., Hüdaverdi Gürkan, H., Eskioğlu, O., Arabacı, H., Coşkun, M. 2017. Climate Change Projections for Turkey: Three Models and Two Scenarios, Turkish Journal of Water Science & Management, 1(1), 22-43

Dickinson, R.E., Henderson-Sellers, A., Kennedy, P. 1993. Bio sphere–atmosphere transfer scheme (BATS) version 1e as coupled to the NCAR community climate model. Tech Rep, National Center for Atmospheric Research Tech Note NCAR.TN-387+STR, NCAR, Boulder, CO

Diggle, P. and Ribeiro, P.J. 2007. Model-Based Geostatistics, Springer Series in Statistics, Springer

Douglas-Makin, K.R., Srinivasan, R., Arnold, J.G. 2010. Soil and Water Assessment Tool (SWAT) model: Current developments and applications, American Society of Agricultural and Biological Engineers, 53(5), 1423-1431

El Yaouti F., El Mandour A., Khattach D. and Kaufmann, O. 2008. Modelling groundwater flow and advective contaminant transport in the Bou-Areg unconfined aquifer (NE Morocco), Journal of Hydro-environment Research, 2, 192-209

Emam, A.R., Kappas, M., Linh, N.H.K., Renchin, T. 2017. Hydrological Modeling and Runoff Mitigation in an Ungauged Basin of Central Vietnam Using SWAT Model. Hydrology 4(16), 10.3390/hydrology4010016 hydrology

Emanuel, K.A. and Zivkovic-Rothman, M. 1999. Development and evaluation of a convection scheme for use in climate models, J Atmos Sci 56, 1766–1782

Essink, H.P. 2000. Groundwater Modeling. Academic Publishing of Utrecht University, f.15

Essou, G.R.C., Sabarly, F., Lucas-Picher, P., Brissette, F., Poulin, A. 2016. Can precipitation and temperature from meteorological reanalyses be used for hydrological modelling? J. Hydrometeorol. 17, 1929–1950

Fadil, A., Rhinane, H, Kaoukaya, A., Kharchaf, Y, Alami Bachir, O. 2011. Hydrologic modeling of Bouregreg watershed (Morocco) Using GIS and SWAT model, J Geogr Inf Syst 3, 279–289

Fayez, A. and Tamer, A. 2006. Modeling of groundwater flow for Mujib aquifer, Jordan, J. Earth Syst. Sci., 115(3), 289-297

Felzer, B. and Heard, P.1999. Precipitation differences amongst GCMs used for the U.S. national assessment, Journal of the American Water Resources Association, 35, 1327–1339

Ficklin, D.L., Luo, Y., Luedeling, E., Zhang, M. 2009. Climate change sensitivity assessment of a highly agricultural watershed using SWAT. Journal of Hydrology, 374, 16-29, doi: 10.1016/j.hydrol.2009.05.016

Gassman, P.W., Reyes, M.R., Green, C.H. and Arnold, J.G. 2007. The Soil and Water Assessment Tool: historical development, applications, and future research directions. Transactions of the ASABE, 50 (4), 1211–1250. doi:10.13031/2013.23637

Gassman, P.W., et al., 2014a. The SWAT literature database: overview of database structure and key SWAT literature trends. In: Proceedings of the 2014 SWAT conference, 28 July–1 August 2014 Pernambuco. Texas Water Resource Institute Technical Report no. TR-472. Available from: http://swat.tamu.edu/ conferences/2014/ [Accessed 10 March 2015]

Gassman, P.W., Sadeghi, A.M., and Srinivasan, R., 2014b. Applications of the SWAT Model, special section: overview and insights. Journal of Environmental Quality, 43, 1–8. doi:10.2134/jeq2013.11.0466

Gething, P., Atkinson, P., Noor A, Gikandi, P., Hay, S., and Nixon, M. 2007. A local space-time kriging approach applied to a national outpatient malaria data set, Computer Geosciences, 33(10), 1337–1350, doi:10.1016/j.cageo.2007.05.006

Ghazavi, R., and Ebrahimi, K. 2019. Predicting the impacts of climate change on groundwater recharge in an arid environment using modeling approach, International Journal of Climate Change Strategies and Management, 11(1), 88-99, doi:10.1108/IJCCSM-04-2017-0085

Giorgetta, M.A., Jungclaus, J., Reick, C.H., et. al 2011. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. Journal of Advances in Modeling Earth Systems, 5, 572–597, doi:10.1002/jame.20038

Giorgi, F., Marinucci M. R, Bates G. T. 1993a. Development of a second generation regional climate model (RegCM2). Part I: Boundary layer and radiative transfer process. Monthly Weather Review, 121, 2794-2813

Giorgi, F., Marinucci M. R, Bates G. T, DeCanio G. 1993b. Development of a second generation regional climate model (RegCM2). Part II: Convective processes and assimilation of lateral boundary conditions. Monthly Weather Review, 121, 2814-2832.

Giorgi, F., and Mearns, L.O. 1999. Introduction to special section: regional climate modeling revisited, Journal of Geophysical Research, 104, 6335-6352

Giorgi, F., Francisco, R., Pal, J.S. 2003. Effects of a sub-grid scale topography and landuse scheme on surface climate and hydrology. I. Effects of temperature and water vapor disaggregation. J Hydrometeorol 4, 317–333

Giorgi, F., Coppola, E., Solmon, F., et. al 2012. RegCM4: model description and preliminary tests over multiple CORDEX domains. Climate Research, 52, 7–29, doi:0.3354/cr01018

Gräler, B., Gerharz, L., and Pebesma, E. 2016. Spatio-Temporal Interpolation using gstat. The R Journal, 8(1), 204-218

Green, W.H. and Ampt, G.A. 1911. Studies on soil physics, 1. The flow of air and water through soils, Journal of Agricultural Sciences, 4:11-24

Grell, G.A. 1993. Prognostic evaluation of assumptions used by cumulus parameterizations. Mon Weather Rev, 121, 764–787

Harbaugh, A.W., Banta E. R., Hill M.C. and McDonald M.G. 2000. Modflow–2000, the U.S. Geological Survey Modular Groundwater Model: User guide to modularization concepts and groundwater flow process. U.S. Geological Survey Open – File Report, 00 - 92

Harbaugh, A.W. and McDonald M. G. 1996. User’s documentation for MODFLOW–96, an update to the U.S. Geological Survey modular finite- difference groundwater flow model. U.S. Geological Survey Open – File Report, 96-485

Hargreaves, G.H. and Samani, Z.A. 1985. Reference crop evapotranspiration from temperature. Transaction of ASAE 1(2), 96-99

Hengl, T., Heuvelink, G.B.M., Perˇcec Tadic, M., and Pebesma, E.J. 2012. Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images. Theor. Appl. Climatol., 107

Her, Y., Frankenberger, J., Chaubey, I., and Srinivasan R. 2015. Threshold Effects in HRU definition of the Soil Assessment Water Tool. American Society of Agricultural and Biological Engineers, 58(2), 367-378, doi: 10.13031/trans.58.10805

Heuvelink, G.B.M., and Griffith, D.A. 2010. Space-time geostatistics for geography: A case study of radiation monitoring across parts of Germany. Geog. Anal., 42(2), 161–179, doi:10.1111/j.1538-4632.2010.00788.x

Heuvelink, G.B.M., Griffith, D.A., Hengl, T., and Melles, S.J. 2012. Sampling Design Optimization for Space-Time Kriging. John Wiley, Oxford, 207–230, doi:10.1007/s00704-011-0464-2

Hofstra, N., Haylock, M., New, M., Jones, P., and Frei, C. 2008. Comparison of six methods for the interpolation of daily, European climate data. J. Geophys. Res., 113, D21110, doi:10.1029/2008JD010100

Holtslag, A., de Bruijn, E, Pan, H.L. 1990. A high resolution air mass transformation model for short-range weather forecasting. Mon Weather Rev, 118, 1561–1575

Hostetler, S.W., Bates, G.T., Giorgi, F. 1993. Interactive nesting of a lake thermal model within a regional climate model for climate change studies. J Geophys Res, 98, 5045–5057

Hutchinson, M.F. 1889. Calculation of hydrologically sound digital elevation models, Third International Symposium on Spatial Data Handling at Sydney. Australia, vol 3(1):120-127

IAEG 1981. Rock and soil description and classification for engineering geological mapping. Report by the IAEG Commission on Engineering Geological Mapping. Bull. IAEG, 24, 235-274

IPCC 2007. Climate Change 2007. Synthesis Report

IPCC 2013. Climate Change 2013. Synthesis Report

Isaaks, E. H. and Srivastana R.M. 1989. An introduction to applied geostatistics. Oxford University, New York, 592.

Jha, M.K., Pan, Z., Takle, E.S. 2004. Impacts of climate change on streamflow in the Upper Mississippi River Basin: A regional climate model perspective, Journal of

Geophysical Research, Atmospheres 109, D09105, doi:10.1029/ 2003JD003686

Jones, C.D., Hughes, J.K., Belloin, N., et. al. 2011. The HadGEM2-ES implementation of CMIP5 centennial simulations, Geosci. Model Dev., 4, 543–570, doi:10.5194/gmd-4-543-2011

Journel, A.G. and Huijbregts, Ch. J. 1978. Mining geostatistics. Academic Press, London

Kallioras, A, Pliakas, F.K. and Diamantis, J. 2010. Simulation of Groundwater Flow in a Sedimentary Aquifer System Subjected to Overexploitation, Water Air and Soil Pollution, 211(1), 177-201, doi: 10.1007/s11270-009-0291-6

Kalogeropoulos, K. and Chalkias, C. 2013. Modelling the impacts of climate change on surface runoff in small Mediterranean catchments: empirical evidence from Greece, Water and Environment Journal, 27, 505–513

Kiehl, J., Hack, J., Bonan, G., Boville, B., Breigleb, B., Williamson, D., Rasch, P. 1996. Description of the NCAR Commun ity Climate Model (CCM3). National Center for Atmospheric Research Tech Note NCAR/TN-420+STR, NCAR, Boulder, CO

Kilibarda, Μ., Hengl, T., and Heuvelink, G.B.M., et. al 2014. Spatio-temporal interpolation of daily temperatures for global land areas at1 km resolution. Journal of Geophysical Research, Atmospheres, 2294-2313 doi: 10.1002/2013JD020803

Köppen, W., 1954. Classification of climates and world patterns. G.T. Trewartha (Ed.), An Introduction to Climate. McGraw-Hill, New York, 225–226

Kirshen, P.H. 2002. Potential impacts of global warming on groundwater in Eastern Massachusetts, Journal of Water Resources Planning and Management, 128 (3), 216-226

Krishnan, N., Cibin, R., Chaubey, I. and Sudheer, K.P. 2018. Parameter estimation of SWAT and quantification of consequent confidence bands of model simulations, Environmental Earth Sciences, 77(470), https://doi.org/10.1007/s12665-018-7619-8

Krysanova, V., Vetter, T., Eisner, S., Huang, S., , Pechlivanidis, I., Strauch, M. , Gelfan, A., Kumar R., Valentin Aich, V., Arheimer, B., Chamorro, A., van Griensven, A.,

Kund,D., Lobanova, A., Mishra, V., Plotner S., Reinhardt, J., Seidou, O., Wang, X., Wortmann, M., Zeng, X., and Hattermann, F.F. 2017. Intercomparison of regional-scale

hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesis, Environmental Research Letter, 12, 105002, http://dx.doi.org/10.1088/1748-9326/aa8359

Krysanova, V., and White, M. 2015. Advances in water resources assessment with SWAT-an overview, Hydrological Sciences Journal – Journal des Sciences Hydrologiques, Special issue: Evaluation of Water Resources with SWAT, 60(5), 771-782, http://dx.doi.org/10.1080/02626667.2015.1029482

Krysanova, V. and Srinivasan, R. 2015. Assessment of climate and land use change impacts with SWAT, Regional Environmental Change, 15, 431–434. doi:10.1007/s10113-014-0742-5

Kundzewicz Z.W., Krysanova, V., R.E. Benestad R.E., Hov, Ø., PiniewskiI. M., and Otto, M. 2018. Uncertainty in climate change impacts on water resources, Environmental Science and Policy, 79, 1-8, https://doi.org/10.1016/j.envsci.2017.10.008

Lachaal, F., Mlayah, A., Bédir, M., Jamila Tarhouni, J., Leduc, C. 2012. Implementation of a 3-D groundwater flow model in a semi-arid region using MODFLOW and GIS tools: The Zéramdine–Béni Hassen Miocene aquifer system (east-central Tunisia), Computers & Geosciences, 48, 187–198, http://dx.doi.org/10.1016/j.cageo.2012.05.00

Lasinio, G.J., Sahu, S.K., and Mardia, K.V. 2007. Modeling rainfall data using a Bayesian Kriged-Kalman model. In: Upadhyay, S. K.; Singh, Umesh, Dey, Dipak K. (Ed.). Bayesian statistics and its applications. Tunbridge Wells, UK: Anshan., 61-86

Lazoglou, G., Anagnostopoulou, C., Koundouras, S., 2018. Climate change projections for Greek viticulture as simulated by a regional climate model, Theoretical and applied climatology, 133(1-2), 551-567, 10.1007/s00704-017-2198-2

Lee, S., Yeo, I.Y., Sadeghi, A.M., McCarty, G.W., Hively, W.D., Megan W. Lang, W.D. and Amir Sharifi, A. 2018. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model, Hydrol. Earth Syst. Sci., 22, 689-708, https://doi.org/10.5194/hess-22-689-2018

Lichtenstern, A. 2013. Kriging methods in spatial statistics, Bachelor’s thesis, Technische Universität München, Department of Mathematics

Loukas, A., Mylopoulos, N., and Vasiliades, L. 2007. A Modelling System for the Evaluation of Water Resources Management Scenarios in Thessaly, Greece, Water Resources Management, 21, 1673 – 1702.

Mair, A., and Fares, A., 2011. Comparison of rainfall interpolation methods in a mountainous region of a tropical island, Journal of Hydrologic Engineering, 371-383

Matheron, G. 1962. Traité de Geostatistique Appliquée. Memoires du Bureau de Recherches Geologiques et Minieres, Tome I(14). Paris: Editions Technip (in French)

McDonald, M.G. and Harbaugh, A.W. 2003. The history of MODFLOW, Ground –Water, 41(2), 280-283

Moriasi, D.N., Arnold, J.G., Liew, M.W., Binger, R.L., Harmel, R.D., Veith, T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885-900

Nakicenovic, N. and Swart, R. 2000. Emissions Scenarios. A Special Report of Working Group II of the Intergovernmental Panel on Climate Change, Publisher: Cambridge University Press, Cambridge, UK, ISBN: 0521800811, 570

Nkiaka, E., Nawaz, N.R. and Lovett, J.C. 2017. Evaluating Global Reanalysis Datasets as Input for Hydrological Modelling in the Sudano-Sahel Region, Hydrology, 4(13), doi:10.3390/hydrology4010013

Neitsch, S.L., Arnold, J.G., Kiniry, J.R. and Williams, J.R. 2005. Soil and water assessment tool-version 2005-Theoretical documentation, Grassland, Soil and Water Research Laboratory, Temple, TX

Nikitopoulou, Th., Proedrou, M., Cartalis, C. (1996). Study of Climatic Changes for the European and Greek Regions as Deduced from the Use of the ESCAPEN Climatic Model. Proceedings of International Conference Protection and Restoration of the Environment III, Chania, Crete 28-30 August, 1996.

Nilawar, A.P. and Waikar, M.L 2018. Use of SWAT to determine the effects of climate and land use changes on streamflow and sediment concentration in the Purna River basin, India, Environmental Earth Sciences, 77(783), https://doi.org/10.1007/s12665-018-7975-4

Odusanya, A.E., Mehdi, B., Schürz, C., Oke, A.O., Awokola, O.S., Awomeso, J.A., Adejuwon, J.O., Schulz, K. 2019. Multi-site calibration and validation of SWAT with satellite-based evapotranspiration in a data-sparse catchment in southwestern Nigeria. Hydrol. Earth Syst. Sci. 23, 1113–1144. https://doi.org/10.5194/hess-23-1113-2019

Ozturk, T., Tufan Turp, M, Türkeş, M., Kurnaz, L. 2018. Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4, Atmospheric Research, 206, 87-107, https://doi.org/10.1016/j.atmosres.2018.02.009

Pal, J.S., Small, E., Eltahir, E. 2000. Simulation of regional-scale water and energy budgets: representation of subgrid cloud and precipitation processes within RegCM. J Geophys Res, 105, 29579–29594

Pal, J.S., Giorgi, F., Elguindi, X.Bi., et. al 2007. Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bulletin of the American Meteorological Society, 88, 1395-1409

Panagopoulos, Y., Makropoulos, C., Baltas, E., Mimikou, M. 2011. SWAT parameterization for the identification of critical diffuse pollution source area under data limitations, Ecological Modelling, 222, 3500-3512. 10.1016/j.ecolmodel.2011.08.008

Panagopoulos, G. 2012. Application of MODFLOW for simulating groundwater flow in the Trifilia karst aquifer in Greece, Environ Earth Sci, 67, 1877-1889

Partsinevelou A.S Using the SWAT model in analyzing hard rock hydrogeological environments: Application in Naxos Island, Greece, Bulletin of the Geological Society of Greece, 2017, doi: http://dx.doi.org/10.12681/bgsg.11960

Pebesma, E., 2004. Multivariable Geostatistics in S: The gstat package. Comput. Geosci., 30(7), 683–691, doi:10.1016/j.cageo.2004.03.012

Pebesma, E., 2012. Spacetime: Spatio-temporal data in R. Journal of Statistical Software, 51(7), 1–30, doi: 10.18637/jss.v051.i07

Pebesma, E., and Gräler, B. 2017. Introduction to Spatio-Temporal Variography. Institute for Geoinformatics University of Münster, 1-11

Penman, H.L. 1956. Evaporation: An introductory survey, Netherlands Journal of Agricultural Science 4, 7-29

Pissinaras, V. (2016). Assessment of future climate change impacts in a Mediterranean aquifer, Global NEST Journal, 18(1), 119-130

Popke, D., Stevens., B., and Voigt, A, 2013. Climate and climate change in a radiative-convective equilibrium version of ECHAM6. Journal of Advances in Modeling Earth Systems, 5, 1–14, doi:10.1029/2012MS000191

Priestley, C.H.B. and Taylor, R.J. 1972. On the assessment of surface heat flux and evaporation using large scale parameters, Mon. Wea. Rev., 100, 81-92

R Core Team 2016. A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria., see https://www.R-project.org/

Ratnam, J.V., Giorgi, F., Kaginalkar, A., Cozzini, S. 2009. Simulation of the Indian monsoon using the RegCM3-ROMS regional coupled model. Clim Dyn, 33,119–139

Romanazzi, A., Gentile, F., Polemio, M. 2015. Modelling and management of a Mediterranean karstic coastal aquifer under the effects of seawater intrusion and climate change, Environ Earth Sci, 74, 115–128, doi:10.1007/s12665-015-4423-6

Romanou, A., Tselioudis, G., Zerefos, C.S., Clayson, A., Curry, J.A., Andersson, A. 2010. Evaporation–precipitation variability over the Mediterranean and the Black Seas from satellite and reanalysis estimates, Journal of Climate 23(19), 5268-5287. 10.1175/2010JCLI3525.1

Ruti, P.M., Somot, S, Giorgi, F. et al. (2016) MED-CORDEX initiative for Mediterranean Climate studies. Bull. Amer. Meteor. Soc., 97(7), 1187-1208

Serpa, D., Nunes, J.P., Santos, J., Sampaio, E., Jacinto, R., Veiga, S., Lima, J.C., Moreira, M., Corte-Real, J., Keizer, J.J., Abrantes, N. 2015. Impacts of climate and land use changes on the hydrological and erosion process of two contrasting Mediterranean catchments, Science of the Total Environment, http://dx.doi.org/10.1016/j.scitotenv.2015.08.033

Scibek, J. and Allen, D.M. 2006. Modeled impacts of predicted climate change on recharge and groundwater levels, Water Resources Research, 42, W11405, 18p

Sibson, R. 1981. A brief description of natural neighbour interpolation, in Interpreting Multivariate Data. John Wiley and Sons, Chichester UK, 21–36

Sidiropoulos, P., Mylopoulos, N., and Loukas, A. 2016. Reservoir-aquifer combined optimization for groundwater restoration: The case of Lake Karla watershed, Greece, Water Utility Journal 12, 17-26

Singh, A. 2014. Groundwater resources management through the applications of simulation modeling: A review, Science of the Total Environment, 499(15), 414-423, doi: https://doi.org/10.1016/j.scitotenv.2014.05.048

Snepvangers, J., Heuvelink, G., and Huisman, J. 2003. Soil water content interpolation using spatio-temporal kriging with external drift. Geoderma, 112(3–4), 253–271, doi: 10.1016/S0016-7061(02)00310-5

Solmon, F., Giorgi, F., Liousse, C. 2006. Aerosol modeling for regional climate studies: application to anthropogenic particles and evaluation over a European/African domain. Tellus Ser B Chem Phys Meterol, 58, 51–72

Sood, A., Muthuwatta, L. and & McCartney, M. 2013. A SWAT evaluation of the effect of climate change on the hydrology of the Volta River basin, Water International, 38(3), 297–311, http://dx.doi.org/10.1080/02508060.2013.792404

Soil Conservation Service, 1972. Section 4: Hydrology in National Engineering Handbook, SCS

Spadavecchia, L., and Williams Μ. 2009: Can spatio‐temporal geostatistical methods improve high resolution regionalization of meteorological variables? Agric. For. Meteorol., 149(6), 1105–1117

Srinivasan, R., Zhang, X., Arnold, J. 2010. SWAT ungauged hydrological budget and crop yield predictions in the Upper Mississippi River Basin. Transactions of the ASABE American Society of Agricultural and Biological Engineers (53)5, 1533-1546

Stehr, Α., Debels, P., Romero, F., Alcayaga, H. 2008. Hydrological modelling with SWAT under conditions of limited data availability: evaluation of results from a Chilean case study. Hydrological Sciences, 53(3), 588-601. 10.1623/hysj.53.3.588

Steiner, A.L., Pal, J.S., Rauscher, S.A., Bell, J.L. et al. 2009. Land surface coupling in regional climate simulations of the West Africa monsoon. Clim Dyn, 33, 869–892

Stigter, J., Nunes, P., Pisani, B., Fakir, Y., Hugman, R.,Li, Y., Tome, S., Ribeiro, L., Samper, J., Oliveira, R., Monteiro, J.P., Silva, A., Tavares, P.C.F., Shapouri, M., Cancela da

Fonseca, L., El Himer, H., 2012. Comparative assessment of climate change and its impacts on three coastal aquifers in the Mediterranean, Reg Environ Change (2014) 14 (Suppl 1):S41–S56, doi:10.1007/s10113-012-0377-3

Taylor, Κ.Ε. 2001. Summarizing multiple aspects of model performance in a single diagram, Journal of Geophysical Research, 106(D7), 7183–7192

Theodosiou, N. 2016. Assessing the Impacts of Climate Change on the Sustainability of Groundwater Aquifers. Application in Moudania Aquifer in N. Greece, Environmental Processes, 3(4), 1045-1061

Thornthwaite, C.W. and Mather, J.R. 1955. The water balance. Centerton, NJ: Drexel Institute of Technology - Laboratory of Climatology, (Publications in Climatology, vol.VIII, n.1), 104

Tiedtke, M. 1989. A comprehensive mass-flux scheme for cumulus parameterization in large-scale models. Mon Weather Rev, 117, 1779–1800

Tizro, T., Fryar, A.E., Pour, M.K, K.S. Voudouris, K.S., Mashhadian, M.J. 2019. Groundwater conditions related to climate change in the semi-arid area of western Iran A. Groundwater for Sustainable Development, 9, https://doi.org/10.1016/j.gsd.2019.100273

Tolika, K., Maheras, P., Flocas, H.A., Arseni-Papadimitriou, A. 2006. An evaluation of a general circulation model (GCM) and the NCEP-NCAR reanalysis data of winter precipitation in Greece, International Journal of Climatology, 26(7), 935-955, https://doi.org/10.1002/joc.1290

Tuppad P, Douglas-Mankin, K.R., Srinivasan, R., Arnold, J.G. 2011. Soil and Water Assessment Tool (SWAT) hydrologic/water quality model: Extended capability and wider adoption, Trans ASABE, 54, 1677– 1684

USAE, 1953. The United Soil Classification System (USC), U.S. Army Eng. Wa-terw. Exp. Stn., Tech. Memo, 3-357, 1, 30

Van Vuuren, D.P., Emonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G.C., Kram, T., Krey, V., Lamarque, J.F., Masui, T., Meinshausen, M., Nakicenovic N,

Smith SJ, Rose SK 2001. The representative concentration pathways: An Overview, Climatic Change 109:5-31, 10.1007/s10584-011-0148-z

Varanou E., Gkouvatsou, E., Baltas, E. and Mimikou, M. 2007. Quantity and Quality Integrated Management Modeling under Climate Change with use of the Soil and Water Assessment Tool, Journal Hydrol. Eng. 7(3), 228-244

Venetsanou, P., Kazakis N., Anagnostopoulou C., and Voudouris, K. 2016. Impacts of Rainfall changes on groundwater balance of a coastal aquifer: A case study of Thermaikos Gulf, North Greece, Global Nest: The International Journal, 18, 185-196

Venetsanou, P., Anagnostopoulou, C., Loukas, A., Voudouris, K. 2018. Analysis of climate future projections using spatio-temporal Kriging method, 14o Διεθνές Συνέδριο Μετεωρολογίας, Κλιματολογίας και Ατμοσφαιρικής Φυσικής, Αλεξανδρούπολη

Venetsanou, P., Anagnostopoulou C., Loukas, A., Lazoglou G., Voudouris, K. 2019. Minimizing the uncertainties of RCMs climate data by using spatio-temporal geostatistical modeling, Earth Science Informatics, 12, 183–196 https://doi.org/10.1007/s12145-018-0361-7

Wackernagel, H. 2003. Multivariate Geostatistics: An Introduction with Applications (3rd ed.). Berlin, Heidelberg: Springer

Webster, R. and Oliver, M.A. 2007. Geostatistics for Environmental Scientists, 2nd Edition, Willey

Wilby, R. and T.M.L. Wigley, T.M.L. 1997. Downscaling general circulation model output: a review of methods and limitations, Progress in Physical Geography, 21, 530–548

Winchell, M., Srinivasan, R., Di Luzio, M. and Arnold, J. 2007. Arc-SWAT interface for SWAT2005 user’s guide, Texas Agricultural Experiment Station and United States Department of Agriculture, Temple, TX

Woldeamlak, S. T., Batelaan, O. and De Smedt, F. 2007. Effects of climate change on the groundwater system in the Grote-Nete catchment, Belgium, Hydrogeology Journal, 15(5), 891-901

Wong, K.W, P Wong P.M., T. D. Gedeon T.D., Fung C.C. 2003. Rainfall prediction model using soft computing technique. Soft Computing, 7(6):434–438

Yang, X., Xie, X., Liu Ji, F., and Wang, L. 2015. Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region. Hindawi Publishing Corporation Advances in Meteorology, 1-12. doi.org/10.1155/2015/563629

Zakey, A.S., Solmon, F., Giorgi, F. 2006. Implementation and testing of a desert dust module in a regional climate model. Atmos Chem Phys, 6, 4687–4704

Zakey, A.S., Giorgi, F., Bi, X. 2008. Modeling of sea salt in a regional climate model: fluxes and radiative forcing. J Geophys Res, 113, D14221, doi:10.1029/2007JD009209

Zeng, X., Zhao, M., Dickinson, R.E. 1998. Intercomparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using TOGA COARE and TAO data. J Clim, 11, 2628–2644

Zimmerman, D, Pavlik, C., Ruggles, A., and Armstrong, M.P. 1999. An Experimental Comparison of Ordinary and Universal Kriging and Inverse Distance Weighting. Mathematical Geology, 31(4), 375-390