Spatial interpolation of weekly rainfall depth in the dry zone of Sri Lanka

Abstract

Daily rainfall data recorded at 13 stations were analyzed to study the spatial patterns of rainfall in the dry zone of Sri Lanka. Principal component analysis was utilized to classify the dominant spatial regions. The first 2 eigenvectors accounted for 70.2% (the first eigenvector 54.8% and the second 15.4%) of the total variation, which clearly supports the commonly used major climatic division of Sri Lanka into wet and dry zones. Both the inverse distance weighting method and kriging successfully estimated weekly average rainfall in the North Central dry zone of Sri Lanka. For both methods, high correlation coefficients of 0.88 and 0.91 were observed for the southwest and northeast monsoon periods, respectively, with slightly lower values for intermonsoon periods. For inter-monsoon periods, the inverse distance weighting method produced better results than kriging. This work shows that the strength of the predictions depends on the rainfall seasons as well as the geometrical placement of the stations in the dry zone.