Comparison of rainfall sampling schemes using a calibrated Stochastic Rainfall Generator

Abstract

Accurate rainfall measurements are critical to river flow predictions. Areal and gauge rainfall measurements create different descriptions of the same storms. The purpose of this study is to characterize those differences. A stochastic rainfall generator was calibrated using an automatic search algorithm. Statistics describing several rainfall characteristics of interest were used in the error function. The calibrated model was then used to generate storms which were exhaustively sampled, sparsely sampled and sampled areally with 4X4 km grids. The sparsely sampled rainfall was also kriged to 4X4 km blocks. The differences between the four schemes were characterized by comparing statistics computed from each of the sampling methods. The possibility of predicting areal statistics from gauge statistics was explored. It was found that areally measured storms appeared to move more slowly, appeared larger, appeared less intense and have shallower intensity gradients.