Spatial interpolation of monthly rainfall data /
Febelyn Amihan Estoista.
- 2011
- 68 leaves.
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2011
Having a complete and continuous rainfall data set is one of the complex problems in most of the hydrological studies. In general, precipitation is never been measured at all points of the region but only to those points that can be reached by the rain gauges or the gauging points. Therefore, spatial interpolation has a big role in many hydrological studies for the reason that it can be used to estimate the values of those areas that have no measurements. This study was conducted to develop spatial interpolation models that could estimate the monthly rainfall in Caraga Region using ordinary kriging (exponential, Gaussian and spherical) and inverse distance weighting with power parameters from 1 to 5. The two spatial interpolations wee implemented using the R software. It covered the weight computations of the station that were used in the prediction as well as the semivariogram modeling, which determines the spatial variability of the study location. Accuracy of the model was evaluated using mean error, mean absolute error and root mean square error. The results obtained from the comparison of the two interpolation methods analyzed in the study indicate that the ordinary kriging was the most suitable method in estimating the monthly rainfall of the Caraga Region.