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Role of measurement uncertainty in the comparison of average areal rainfall methods
Author(s) -
A. Ribeiro,
M. C. Almeida,
M G Cox,
J. A. Sousa,
L. Lages Martins,
D. Loureiro,
Rita Salgado Brito,
M Silva,
A C Soares
Publication year - 2021
Publication title -
metrologia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 79
eISSN - 1681-7575
pISSN - 0026-1394
DOI - 10.1088/1681-7575/ac0d49
Subject(s) - computer science , relevance (law) , monte carlo method , environmental science , metrology , precipitation , propagation of uncertainty , conformity , meteorology , statistics , econometrics , mathematics , geography , algorithm , political science , law
The main motivation for this research is the growing awareness of the impact of climate change and the increasing relevance of the United Nations Sustainable Development Goals, aiming to contribute to the measurement of quantities like precipitation and rate of rainfall. This knowledge is widely used in hydrology, climatology and meteorology, providing data and information applied in modelling, pattern definition and recognition, and forecasting. This work is concerned with estimating the average areal rainfall in a stipulated region from rainfall intensity observations made at measurement stations within that region. It focuses on three straightforward estimation approaches: the arithmetic mean method, the Thiessen polygon method and the isohyetal method. The evaluation of the associated measurement uncertainty, for which the law of propagation of uncertainty and a Monte Carlo method as described in guidance documents from the Joint Committee for Guides in Metrology are applied, is the main consideration. The approaches described may be readily applied by practitioners. A comparison of results from applying these methods to a simple example is made. Such results are required for conformity assessment and support in urban management and water resources management worldwide.

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