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. The hydro-stochastic interpolation method based on traditional block Kriginghas often been used to predict mean annual runoff in river basins. A caveatin such a method is that the statistic technique provides little physicalinsight into relationships between the runoff and its external forcing, suchas the climate and land cover. In this study, the spatial runoff isdecomposed into a deterministic trend and deviations from it caused bystochastic fluctuations. The former is described by the Budyko method (Fu'sequation) and the latter by stochastic interpolation. This coupled method isapplied to spatially interpolate runoff in the Huaihe River basin of China.Results show that the coupled method significantly improves the predictionaccuracy of the mean annual runoff. The error of the predicted runoff by thecoupled method is much smaller than that from the Budyko method and thehydro-stochastic interpolation method alone. The determination coefficientfor cross-validation, R cv 2 , from the coupled method is 0.87,larger than 0.81 from the Budyko method and 0.71 from the hydro-stochasticinterpolation. Further comparisons indicate that the coupled method has alsoreduced the error in overestimating low runoff and underestimating highrunoff suffered by the other two methods. These results confirm that thecoupled method offers an effective and more accurate way to predict the meanannual runoff in river basins.

Hydro-stochastic interpolation coupling with the Budyko approach for prediction of mean annual runoff