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

Romeo Kondouw, Kerista Tarigan, Syahrul Humaidi, Marhaposan Situmorang, Mardiningsi Mardiningsi, Yahya Darmawan

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.

Keywords


Rainfall, Calibration, Monte Carlo Method, Uncertainty Measurement

Full Text:

PDF

References


Adriaan M. H. van der Veen1 • Maurice G. Cox2 (2021). Getting started with uncertainty evaluation using the Monte Carlo method in R. https://doi.org/10.1007/s00769-021-01469-5

Harshvardhan Choudharya , Girija Moonab , D Vaithiyanathana & Harish Kumara (2021). Implementation of Monte Carlo Simulation in Evaluation of Uncertainty of Measurement of a Force Transducer. Indian Journal of Pure & Applied Physics Vol. 59, March 2021, pp. 271-276

Ian Farrance, Robert Frenkel (2014). Uncertainty in Measurement: A Review of Monte Carlo Simulation Using Microsoft Excel for the Calculation of Uncertainties Through Functional Relationships, Including Uncertainties in Empirically Derived Constants. The Clinical Biochemist Reviews Vol. 35, Feb 2014, pp. 37-61

ISO/IEC 17025 (2017). General requirements for the competence of testing and calibration laboratories, 3rd edn. ISO, International Organization for Standardization, Geneva, Switzerland

JCGM 101: (2008). Evaluation of measurement data - Supplement 1 to the “Guide to the expression of uncertainty in measurement” – Propagation of distributions using a Monte Carlo method. Joint Committee for Guides in Metrology

JCGM 100: (2008) – Evaluation of measurement data – Guide to the expression of uncertainty in measurement. Joint Committee for Guides in Metrology

JCGM 200: (2012) – International Vocabulary of Metrology – Basic and General Concepts and Associated Terms (VIM). Joint Committee for Guides in Metrology

Montgomery, D. C., & Runger, G. C. (2018). Probabilitas dan Statistika Terapan Edisi Kelima. Jakarta: Salemba Empat

Paulo Roberto Guimarães Couto, Jailton Carreteiro Damasceno and Sérgio Pinheiro de Oliveira (2013). Monte Carlo Simulations Applied to Uncertainty in Measurement. https://doi.org/10.5772/53014

Rubinstein, R. Y. (2016). Simulation and the Monte Carlo Method. John Wiley & Sons, Inc. Wiley series in probability and statistic. 2017

Walpole, R. E., Myers, R. H., Myers, S. L., & Ye, K. (2011). Probabilitas dan Statistika untuk Insinyur dan Ilmuwan Edisi Keenam Jilid 1. Jakarta: PT. Gramedia Pustaka Utama.

WMO (2018). Guide to Meteorological Instruments and Methods of Observation. World Meteorological Organization. WMO-No.08. Geneva.




DOI: https://doi.org/10.33394/j-ps.v11i2.7820

Refbacks

  • There are currently no refbacks.




Copyright (c) 2023 Romeo Kondouw, Kerista Tarigan, Syahrul Humaidi, Marhaposan Situmorang, Mardiningsi Mardiningsi, Yahya Darmawan

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License
J-PS (Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram) p-ISSN (print) 2338-4530, e-ISSN (online) 2540-7899 is licensed under a Creative Commons Attribution 4.0 International License.

View My Stats