Kriging Interpolation Method for Estimation ofContinuous Spatial Distribution of Precipitationin Cyprus

摘要

Aims: Development of a precipitation prediction model for Cyprus.Study Design: Precipitation data collected at 78 stations were used: data from 66 stations for model development and data from 12 stations for additional tests. Four topographic factors – altitude, slope, longitude, and latitude – were taken into account for model development.Place and Duration of Study: All variables were obtained from the observation archives of the Water Development Department of the Ministry of Agriculture, Natural Resources and Environment of Cyprus, between 1961 and 1990.Methodology: Multiple regression analysis, combined with residuals correction, was carried out to develop a precipitation prediction model.Results: The multiple regression model can explain 61.3% of the spatial variability of precipitation over the whole year, 57.5% of variability in the wet season (October–April), and 99.6% of variability in the dry season (May–September). Interpolation-based residuals correction improved the accuracy of our model ( Adj_ R ~( 2 )=65.1%, 62.6% and 99.7%, respectively).Conclusion: This approach, as presented in this paper, could potentially be applied to Cyprus’ climate research.