Implementation of Monte Carlo Simulation in Evaluation of The Uncertainty of Rainfall Measurement

Abstract

Many factors trigger the uncertainty of rainfall measurement. Several factors can be related to the instruments, weather conditions, and acquisition methods. The degree of uncertainty could be obtained through the calibration process. In principle, rain gauges are calibrated based on the standard process ruled by ISO/IEC 17025 using the law of propagation of uncertainty (LPU). However, LPU requires complex and complicated mathematical calculations. An alternative approach is needed to evaluate measurement uncertainty besides the LPU method. This research used the Monte Carlo method to determine the uncertainty during the rainfall measurement. This method involves repeated random simulations by providing probability distribution on the input and output of rainfall measurement. The results showed that the Monte Carlo method can accurately determine the uncertainty of rainfall measurement. In addition, the uncertainty analysis also showed that instrument inaccuracy is the most significant factor that causes the uncertainty of rainfall measurement.