Effect of Local Errors of Tipping-Bucket Rain Gauges on Rainfall-Runoff Simulations

Abstract

This study investigates the effect of local systematic and random errors of the commonly used tipping-bucket (TB) rain gauges on the accuracy of runoff predictions. A physically-based rainfall-runoff model is applied to analyze several storms in a humid midsize watershed in south Louisiana. Two types of systematic TB errors are considered, wind-induced losses and underestimation of high rainfall intensities due to the lack of gauge dynamic calibration. The effect of the TB errors is assessed by comparing hydrographs simulated using uncorrected and corrected rainfall input. The results indicate that wind and dynamic calibration effects can cause differences in estimating runoff volumes and peaks on the order of 5 to 15%. We also analyze the effect of random TB errors caused by the discrete gauge sampling mechanism. The computed runoff differences caused by the TB random errors were dependent on the magnitude of the runoff discharge, and on the temporal resolution of the rainfall input. However, the effect of random errors was found to be rather small, especially for large discharge.