Kriging Interpolation Method for Estimation of Continuous Spatial Distribution of Precipitation in Cyprus
Fotios Maris
Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, GR-68200 Orestiada, Greece
Kyriaki Kitikidou *
Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, GR-68200 Orestiada, Greece
Panagiotis Angelidis
Department of Civil Engineering, Democritus University of Thrace, GR-67100 Xanthi, Greece.
Simeon Potouridis
Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, GR-68200 Orestiada, Greece.
*Author to whom correspondence should be addressed.
Abstract
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_ R2=65.1%, 62.6% and 99.7%, respectively).
Conclusion: This approach, as presented in this paper, could potentially be applied to Cyprus’ climate research.
Keywords: Cyprus, kriging interpolation, multiple regression, precipitation