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Trend Analysis of the Effects of Climate Change on the Pan Evaporation Rate in Sabah, Malaysia

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Proceedings of International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 322))

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Abstract

The pan evaporation rate is an important measurement that can be used to derive other meteorological parameter such as the evapotranspiration and drought indices. Learning the trend of pan evaporation rate is useful to project the possible trends of other important parameters. In this study, trend analysis of pan evaporation rate was conducted at four stations, namely at Station 96471 (Kota Kinabalu), Station 96477 (Kudat), Station 96481 (Tawau) and at Station 96491 (Sandakan), to evaluate the effect of climate change on the pattern of pan evaporation rate from January 1985 to December 2019. The Mann Kendall (MK) test (assisted by the Sen’s slope estimator) and the Holt’s Linear Trend Method (HLTM) were used to perform the trend analysis. It was found that the pan evaporation rate was sensitive to climatic conditions such as drought and rainfall. Generally, the trend reported in the MK test and Sen’s Slope estimator tallied with that of the HLTM. However, in some instances, the HLTM was less sensitive as it could not detect the trends that were alerted by the MK test and Sen’s slope estimator. Overall, the findings of this study was in agreement with other researchers conducted in similar regions, and therefore could be a useful tool in the decision making process.

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Acknowledgements

This research was funded by Universiti Tunku Abdul Rahman (UTAR), Malaysia through the Universiti Tunku Abdul Rahman Research Fund under project number IPSR/RMC/UTARRF/2018-C2/K03. The meteorological data were supplied by the Malaysian Meteorological Department (MMD).

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Correspondence to Yuk Feng Huang .

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Chia, M.Y., Huang, Y.F., Koo, C.H., Tan, Y.Z. (2022). Trend Analysis of the Effects of Climate Change on the Pan Evaporation Rate in Sabah, Malaysia. In: Al-Emran, M., Al-Sharafi, M.A., Al-Kabi, M.N., Shaalan, K. (eds) Proceedings of International Conference on Emerging Technologies and Intelligent Systems. ICETIS 2021. Lecture Notes in Networks and Systems, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-85990-9_2

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