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

Romeo Kondouw (Faculty of Mathematics and Natural Sciences, University of Sumatera Utara, Medan)
Kerista Tarigan (Faculty of Mathematics and Natural Sciences, University of Sumatera Utara, Medan)
Syahrul Humaidi (Faculty of Mathematics and Natural Sciences, University of Sumatera Utara, Medan)
Marhaposan Situmorang (Faculty of Mathematics and Natural Sciences, University of Sumatera Utara, Medan)
Mardiningsi Mardiningsi (Faculty of Mathematics and Natural Sciences, University of Sumatera Utara, Medan)
Yahya Darmawan (Faculty of Mathematics and Natural Sciences, University of Sumatera Utara, Medan)

Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram
Vol 11, No 2: April 2023

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.