Rainfall Variability Analysis Using Rolling Statistics in Chiang Rai Province

Authors

  • Noppharat Techaphanrattanakul Faculty of Science and Agricultural Technology, Rajamangala University of Technology Lanna, Chiang Mai 50300, Thailand
  • Kanoktip Anorat Faculty of Science and Agricultural Technology, Rajamangala University of Technology Lanna, Chiang Rai 57120, Thailand
  • Suruswadee Nanglae Mathematics and Computing Science Program, Faculty of Science and Technology, Chiang Rai Rajabhat University, Chiang Rai 57100, Thailand
  • Pongpan Kanjanakaroon Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Lanna, Chiang Rai 57120, Thailand
  • Mongkonkorn Srivichai Center of Creative Engineering for Sustainable Development, Rajamangala University of Technology Lanna, Chiang Rai 57120, Thailand

DOI:

https://doi.org/10.59796/jcst.V16N2.2026.179

Keywords:

Chiang Rai, rainfall variability, rolling statistics, Mann–Kendall test, climate change

Abstract

This study analyzed long-term rainfall variability in Chiang Rai Province (1981–2024) using rolling statistics and the non-parametric Mann–Kendall test to detect temporal changes in both the mean and variability of annual rainfall. Annual rainfall data from five meteorological locations were examined using 3-, 5-, 7-, and 12-year moving windows to characterize short-, medium-, and decadal-scale fluctuations. Although previous studies in northern Thailand have examined trends in total or extreme rainfall, multi-scale variability has not been systematically assessed, leaving uncertainty about how rainfall behavior is changing across different temporal windows. Results indicate that mean annual rainfall remains statistically stable (p > 0.05) at most locations, except for Wiang Pa Pao, which shows a significant upward trend (Z = 3.79–5.35). In contrast, the rolling standard deviation increased consistently across all locations, suggesting intensifying interannual variability. These findings indicate that rainfall in northern Thailand has become more unpredictable, with larger departures from the mean despite relatively stable long-term averages. The results point to practical needs for updating design-rainfall criteria and integrating variability-based assessments into regional water-resource and climate-adaptation planning.

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Published

2026-03-25

How to Cite

Techaphanrattanakul, N., Anorat, K. ., Nanglae, S. ., Kanjanakaroon, P. ., & Srivichai, M. (2026). Rainfall Variability Analysis Using Rolling Statistics in Chiang Rai Province. Journal of Current Science and Technology, 16(2), 179. https://doi.org/10.59796/jcst.V16N2.2026.179