| Abstract: | Abstract Methods were evaluated for interpolating precipitation (P), evapotranspiration (ET), and runoff (RO) at ungauged points on Shikoku Island, Japan, using data gathered from gauged stations on the same island. Two methods were examined: a “local” cubic spline interpolator, which, for a given point, fitted the function exactly to nearby gauged data points; and a “global” multivariate regression interpolator, which fitted the function to all gauged data points based on their topographic positions (i.e. latitude, longitude, altitude). Local and global interpolators did not generate similar results for P and temperature (T). The spatial density of gauged data points used in the interpolation affected the performance of the interpolators. With any given density of gauged data points included in the interpolation, the local interpolator outperformed the global interpolator. The findings indicate that local interpolators are more accurate predictors of the spatial distribution of water balance components in mountainous regions such as Shikoku Island. |
