Irregularity and time-series trend analysis of rainfall in Baybay City, Leyte, Philippines
DOI:
https://doi.org/10.32945/atr4717.2025Keywords:
Fluctuations, Rainfall Analysis, Trend, VariabilityAbstract
This study examined rainfall trends and variability in Baybay City, Leyte, Philippines, from 1991 to 2020. Utilizing the Mann–Kendall test, Sen's slope method, and Coefficient of Variation (CV), the analysis reveals a 26.41% increase in mean annual rainfall compared to earlier decades. However, annual and seasonal trends lack statistical significance, suggesting random fluctuations. Seasonal variability is highest during MAM (March, April, May), with CV of 59.76% followed by DJF (December, January, February), with a CV of 40.72%. These fluctuations are influenced by transitional monsoons and the intertropical convergence zone (ITCZ). Despite Baybay City's Type IV climate with year-round rainfall distribution, fluctuations reflect natural variability and extreme weather events. The findings emphasize the need for adaptive measures in water resource management, agriculture, and infrastructure to address climate variability and ensure community resilience.
References
Aben, E. L., Crismundo, M. U., Antonio, R. F., & De Vera, E. B. (2011, January 5). Floods displace 452,999 persons in 19 provinces. Manila Bulletin.
Achite, M., Caloiero, T., Wałęga, A., Krakauer, N., & Hartani, T. (2021). Analysis of the spatiotemporal annual rainfall variability in the Wadi Cheliff Basin (Algeria) over the period 1970 to 2018. Water, 13(11), 1477. https://doi.org/10.3390/w13111477
Chou, C., Chiang, J. C. H., Lan, C., Chung, C., Liao, Y., & Lee, C. (2013). Increase in the range between wet and dry season precipitation. Nature Geoscience, 6(4), 263–267. https://doi.org/10.1038/ngeo1744
City of Baybay, Leyte. (2016, December 21). About the City of Baybay—City of Baybay, Leyte. https://baybaycity.gov.ph/about/
Climate.gov. (2011, August 17). 2010 Climate events connected to El Niño or La Niña. NOAA Climate.gov. https://www.climate.gov/news-features/features/2010-climate-events-connected-el-ni%C3%B1o-or-la-ni%C3%B1a
Coronas, J. (1920). The Climate and Weather of the Philippines, 1903–1918. (Vol. 25). Bureau of printing.
Dahal, V., Gautam, S., & Bhattarai, R. (2018). Analysis of the long-term precipitation trend in Illinois and its implications for agricultural production. Water, 10(4), 433. https://doi.org/10.3390/w10040433
Ioannidis, K., Karagrigoriou, A., & Lekkas, D. F. (2015). Analysis and modeling of rainfall events. Mathematics in Engineering, Science and Aerospace, 6(4), 607–614.
Lgubaybay. (2013, November 7). [Blog Post]. WordPress.com. https://lgubaybay.wordpress.com/2023/11.04/78/
PAGASA. (n.d.). Climate of the Philippines. https://www.pagasa.dost.gov.ph/information/climate-philippines
PAGASA. (2018). Observed and projected climate change in the Philippines. Philippine Atmospheric, Geophysical and Astronomical Services Administration.
Qian, J., Robertson, A. W., & Moron, V. (2013). Diurnal cycle in different weather regimes and rainfall variability over Borneo Associated with ENSO. Journal of Climate, 26(5), 1772–1790. https://doi.org/10.1175/jcli-d-12-00178.1
Senapati, A. K. (2020). Weather effects and their long‐term impact on agricultural yields in Odisha, East India: Agricultural policy implications using NARDL approach. Journal of Public Affairs, 22(3), e2498. https://doi.org/10.1002/pa.2498
Rahman, M., & Abdullah, A. (2022). Analysis of long-term rainfall trends in Bangladesh. Research Square. https://doi.org/10.21203/rs.3.rs-564948/v2
Villafuerte, M. Q., Matsumoto, J., Akasaka, I., Takahashi, H., Kubota, H., & Cinco, T. A. (2014). Long-term trends and variability of rainfall extremes in the Philippines. Atmospheric Research, 137, 1–13. https://doi.org/10.1016/j.atmosres.2013.09.021
Villarin, J. R. T., Perez, R. T., Cruz, F. A. T., Olaguera, L. M. P., Villafuerte II, M. Q., Agustin, W. A., Avila, F. B., Basconcillo, J. Q., Calde, D. M., Cayanan, E. O., Cinco, T. A., Dado, J. M. B., Duran, G. A. M., Jamero, M. L. D., Lambrento, J. C. A., Magnaye, A. M. T., Manalo, J. A., & Tibig, L. V. (2024). 2024 Philippine climate change assessment: The physical science basis. The Oscar M. Lopez Center for Climate Change Adaptation and Disaster Risk Management Foundation, Inc.
Vivekanandan, N. (2007). Analysis of trend in rainfall using non-parametric statistical methods. American Institute of Physics Conference Proceedings, 923, 101–113. https://doi.org/10.1063/1.2767019
Yumul, G., Jr., Dimalanta, C., Servando, N., & Hilario, F. (2010). The 2009-2010 El Niño Southern Oscillation in the context of climate uncertainty: The Philippine setting. Philippine Journal of Science, 139(1), 119–126.
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