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

Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Pub Date : 2023-04-30 DOI:10.33394/j-ps.v11i2.7820

Romeo Kondouw, Kerista Tarigan, S. Humaidi, M. Situmorang, Mardiningsi Mardiningsi, Yahya Darmawan

{"title":"Implementation of Monte Carlo Simulation in Evaluation of The Uncertainty of Rainfall Measurement","authors":"Romeo Kondouw, Kerista Tarigan, S. Humaidi, M. Situmorang, Mardiningsi Mardiningsi, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7820","DOIUrl":null,"url":null,"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.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33394/j-ps.v11i2.7820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

蒙特卡罗模拟在雨量测量不确定度评定中的应用

许多因素引发了降雨量测量的不确定性。几个因素可能与仪器、天气条件和采集方法有关。不确定度可以通过校准过程获得。原则上，雨量计是根据ISO/IEC 17025规定的标准过程，使用不确定度传播定律（LPU）进行校准的。然而，LPU需要复杂的数学计算。除了LPU方法外，还需要一种替代方法来评估测量不确定度。本研究采用蒙特卡罗方法来确定降雨测量过程中的不确定性。该方法通过提供降雨测量输入和输出的概率分布，涉及重复的随机模拟。结果表明，蒙特卡罗方法可以准确地确定降雨测量的不确定度。此外，不确定度分析还表明，仪器不准确是造成降雨量测量不确定度的最重要因素。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram

自引率

0.00%

发文量

审稿时长

24 weeks