Comparison of some schemes for determining the optimal number of rain gauges in a specific area: A case study in an urban area of South Sulawesi, Indonesia

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Abstract

Improving the accuracy of rainfall forecasts is related to the number of rain gauges needed in an area, so determining the optimal number of rain gauges is very important. This study aimed to determine the best method for calculating the optimal number of rain gauges. Generally, the calculation of the optimal number of rain gauges using the coefficient of variation only takes into account the accumulation of rainfall at the station. The distance between the location and height of the rain gauge is not taken into account. The phenomenon of rain that occurs in the tropics is very dynamic, where one place compared to another tends to have different rain intensity and duration. In addition, the height and distance factors also greatly affect the measured rainfall. Therefore, it is very important to know the best method to calculate the optimal number of rain gauges needed in a particular area. This study implements 3 methods to determine the appropriate method to be used in determining the optimal rain gauge number for urban areas: Namely, World Meteorological Organization (WMO) criteria, coefficient of variation, and Kagan-Rodda. In this study, rainfall data from 2010 to 2019 at 5 locations in Makassar were used in calculating the optimal number of rain gauges required. The results showed that the optimal number of rain gauges in Makassar as an urban area following the WMO recommendation was 9-18, where small islands around it are not considered. Another result obtained is that if the rainfall data for the Sudiang area, which is located at the coordinates (119.522° E, 5.085° S), is not included in the calculation, it will greatly reduce the accuracy in determining the optimal number of rain gauges in the Makassar area.

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Sunusi, N., & Giarno. (2022). Comparison of some schemes for determining the optimal number of rain gauges in a specific area: A case study in an urban area of South Sulawesi, Indonesia. AIMS Environmental Science, 9(3), 244–260. https://doi.org/10.3934/environsci.2022018

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