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Spatial interpolation techniques for climate data in the GAP region in TurkeyHalit Apaydin*, F. Kemal Sonmez, Y. Ersoy YildirimDepartment of Farm Structures and Irrigation, Faculty of Agriculture, University of Ankara, 06110 Diskapi, Ankara, TurkeyABSTRACT: Six spatial interpolation techniques (inverse distance weighted, global polynomial interpolation, local polynomial interpolation, completely regularized spline, kriging and cokriging with 4 sub-types) were evaluated to determine the best spatial distribution of 6 different climate parameters (solar radiation, sunshine duration, temperature, relative humidity, wind speed and rainfall) in the region of the Southeastern Anatolia Project (GAP) of Turkey. Based on the root mean square error values of predictions made using measured values from 1971 to 1999, simple cokriging yielded the best results for temperature, solar radiation, relative humidity, wind speed and completely regularized spline for sunshine duration and rainfall.
KEY WORDS: Spatial interpolation · Climate · Southeastern Anatolia Project · Inverse distance weighted · Polynomial interpolation · Kriging · Cokriging · Completely regularized spline
Published in CR Vol.
28, No. 1
(2004) on December 31
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