ASSESSING THE EFFECT OF INCORPORATING TOPOGRAPHICAL DATA WITH GEOSTATISTICAL INTERPOLATION FOR MONTHLY RAINFALL AND TEMPERATURE IN PING BASIN, THAILAND

This paper aims to assess the effect of incorporating topographical data with geostatistical interpolation for monthly rainfall and temperature in Ping Basin, Thailand. The spatial interpolation techniques based on 11 semivariogram models of 4 main sub-types of cokriging with 3 topographical variables: elevation, longitude, and latitude have been applied in this study. The best interpolation models from cokriging technique on mean monthly rainfall and mean monthly temperature are selected by Akaike Information Criterion (AIC) based on partial sill, range and nugget that the best monthly models of kriging technique is operated in same mentioned selection. In addition, an assessment of the effective results of the cokriging interpolation models is performed by 2 approaches: i) comparing the errors of the best results from other interpolations excluding topographic data with the least MAE, MRE and RMSE value and ii) comparing the accuracy of results from Multiple Linear Regression (MLR) with the coefficient of determination (r(2)). It was found that cokriging models of mean monthly rainfall and mean monthly temperature have more effectiveness than other interpolations excluding topographic data and MLR including topographic data. Therefore, this study can use the best results of sub-type and semivariogram model from cokriging including topographic variables for mean monthly rainfall and mean monthly temperature surface interpolation.