Διάφορες κλιματολογικές, υδρολογικές και περιβαλλοντικές μελέτες απαιτούν ακριβή γνώση της χωρικής κατανομής των σταθερών ισοτόπων του υδρογόνου και του οξυγόνου στον υετό. Δεδομένου ότι ο αριθμός των σταθμών συλλογής δειγμάτων υετού για ισοτοπική ανάλυση είναι μικρός και όχι ομογενώς κατανεμημένος σε πλανητικό επίπεδο, η πλανητκή κατανομή των σταθερών ισοτόπων μπορεί να υπολογισθεί μέσω της δημιουργίας πλεγματικών ισοτοπικών δεδομένων, για τη δημιουργία των οποίων έχουν προταθεί διάφορες μέθοδοι. Ορισμένες χρησιμοποιούν εμπειρικές σχέσεις και γεωστατιστικές μεθόδους ώστε να ελαχιστοποιήσουν τα σφάλματα λόγω παρεμβολής. Στην εργασία αυτή γίνεται μια προσπάθεια να δημιουργηθούν βάσεις πλεγματικών δεδομένων της ισοτοπικής σύστασης του υετού με ανάλυση 10΄ × 10΄ για την περιοχή της Κεντρικής και Ανατολικής Μεσογείου. Προσδιορίζονται στατιστικά πρότυπα λαμβάνοντας υπ’ όψιν γεωγραφικές και μετεωρολογικές παραμέτρους, ως ανεξάρτητες μεταβλητές. Η αρχική μεθοδολογία χρησιμοποιεί μόνο το υψόμετρο της περιοχής και το γεωγραφικό της πλάτος ως ανεξάρτητες μεταβλητές. Επειδή η ισοτοπική σύσταση εξαρτάται και από το γεωγραφικό μήκος προστέθηκαν στα υφιστάμενα πρότυπα, εκτός των γεωγραφικών μεταβλητών και μετεωρολογικές. Προτείνεται σειρά προτύπων τα οποία περιλαμβάνουν είτε ορισμένες είτε συνδυασμό αυτών των παραμέτρων. Η αξιολόγηση των προτύπων γίνεται με εφαρμογή των μεθόδων Thin Plate Splines (TPSS) και Ordinary Kriging (ΟΚ). / Several climatic, hydrological and environmental studies require the accurate knowledge of the spatial distribution of stable isotopes in precipitation. Since the number of rain sampling stations for isotope analysis is small and not evenly distributed around the globe, the global distribution of stable isotopes can be calculated via the production of gridded isotopic data sets. Several methods have been proposed for this purpose. Some of them use empirical equations and geostatistical methods in order to minimize eventual errors due to interpolation. In this work a methodology is proposed for the development of 10΄ × 10΄ gridded isotopic data of precipitation in Central and Eastern Mediterranean. Statistical models are developed taking into account geographical and meteorological parameters as independent variables. The initial methodology takes into account only the altitude and latitude of an area. Since however the isotopic composition of precipitation depends also on longitude, the existing models have been modified by adding meteorological parameters as independent variables also. A series of models is proposed taking into account some or a combination of the above mentioned variables. The models are validated using the Thin Plate Smoothing Splines (TPSS) and the Ordinary Kriging (OK) methods.

Thesis (MSc (Geography and Environmental Studies))--University of Stellenbosch, 2007. / Due to the relative scarcity of weather stations, the climate conditions of large areas are not adequately represented by a weather station. This is especially true for regions with complex topographies or low population densities. Various interpolation techniques and software packages are available with which the climate of such areas can be calculated from surrounding weather stations’ data. This study investigates the possibility of using the software package ANUSPLIN to create accurate climate maps for the Western Cape, South Africa. ANUSPLIN makes use of thin plate smoothing splines and a digital elevation model to convert point data into grid format to represent an area’s climatic conditions. This software has been used successfully throughout the world, therefore a large body of literature is available on the topic, highlighting the limitations and successes of this interpolation method. Various factors have an effect on a region’s climate, the most influential being location (distance from the poles or equator), topography (height above sea level), distance from large water bodies, and other topographical factors such as slope and aspect. Until now latitude, longitude and the elevation of a weather station have most often been used as input variables to create climate grids, but the new version of ANUSPLIN (4.3) makes provision for additional variables. This study investigates the possibility of incorporating the effect of the surrounding oceans and topography (slope and aspect) in the interpolation process in order to create climate grids with a resolution of 90m x 90m. This is done for monthly mean daily maximum and minimum temperature and the mean monthly rainfall for the study area for each month of the year. Not many projects where additional variables have been incorporated in the interpolation process using ANUSPLIN are to be found in the literature, thus further investigation into the correct transformation and the units of these variables had to be done before they could be successfully incorporated. It was found that distance to oceans influences a region’s maximum and minimum temperatures, and to a lesser extent rainfall, while aspect and slope has an influence on a region’s rainfall. In order to assess the accuracy of the interpolation process, two methods were employed, namely statistical values produced during the spline function calculations by ANUSPLIN, and the removal of a selected number of stations in order to compare the interpolated values with the actual measured values. The analysis showed that more accurate maps were obtained when additional variables were incorporated into the interpolation process. Once the best transformations and units were identified for the additional variables, climate maps were produced in order to compare them with existing climate grids available for the study area. In general the temperatures were higher than those of the existing grids. For the rainfall grids ANUSPLIN’s produced higher rainfall values throughout the study region compared to the existing grids, except for the Southwestern Cape where the rainfall values were lower on north-facing slopes and high-lying area