Abdul Talib Shaidatul Azdawiyah, Idris Wan Mohd Razi, Neng Liew Ju, Lihan Tukimat, Abdul Rasid Muhammad Zamir
Malaysian Agricultural Research and Development Institute (MARDI), Ibu Pejabat MARDI, Persiaran MARDI-UPM, 43400, Serdang, Selangor, Malaysia.
Department of Earth Sciences and Environment, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, 43600, UKM, Bangi, Selangor, Malaysia.
Heliyon. 2024 Apr 27;10(9):e30324. doi: 10.1016/j.heliyon.2024.e30324. eCollection 2024 May 15.
Due to its effect on weather and its propensity to cause catastrophic incidents, climate change has garnered considerable global attention. Depending on the area, the effects of climate change may vary. Rainfall is among the most significant meteorological factors associated with climate change. In Malaysia, changes in rainfall distribution pattern have led to many floods and droughts events which lead to La Nina and El Nino where Johor is one of the states in southern part that usually affected. Thus, rainfall trend analysis is important to identify changes in rainfall pattern as it gives an initial overview for future analysis. This research aims to evaluate historical rainfall data of Johor between 1991 and 2020. Normality and homogeneity tests were used to ensure the quality of data followed by Mann-Kendall and Sen's slope analysis to determine rainfall trend as the rainfall data is not normally distributed (p > 0.05). Standardized precipitation anomaly, coefficient of variation, precipitation concentration index and rainfall anomaly index were used to identify rainfall variability and intensity while standard precipitation index was used to evaluate drought severity. The lowest annual rainfall recorded was 1725.07 mm in 2016 and the highest was 2993.19 mm in 2007. Annual rainfall and seasonal rainfall showed a declining trend although it is not statistically significant (p > 0.05). Results reveal that Johor experienced extreme wet and dry years, leading to drought and flood incidents. Major floods arose in 2006, 2007, 2008, 2010 and 2011 while driest years occurred in 1997, 1998 and 2016 which led to El Nino phenomenon. March and April were identified as the driest months among all. Thus, the findings from this study would assist researchers and decision-makers in the development of applicable adaptation and mitigation strategies to reduce climate change impact. It is recommended that more data analysis from more stations should be done in the future research study to obtain a clearer view and more comprehensive results.
由于其对天气的影响以及引发灾难性事件的倾向，气候变化已引起全球广泛关注。根据地区不同，气候变化的影响可能会有所差异。降雨是与气候变化相关的最重要气象因素之一。在马来西亚，降雨分布模式的变化导致了许多洪水和干旱事件，进而引发拉尼娜现象和厄尔尼诺现象，柔佛州是南部通常受影响的州之一。因此，降雨趋势分析对于识别降雨模式的变化非常重要，因为它为未来的分析提供了初步概述。本研究旨在评估柔佛州1991年至2020年的历史降雨数据。使用正态性和同质性检验来确保数据质量，随后采用曼-肯德尔检验和森斜率分析来确定降雨趋势，因为降雨数据不服从正态分布（p>0.05）。使用标准化降水异常、变异系数、降水集中度指数和降雨异常指数来识别降雨变异性和强度，同时使用标准降水指数来评估干旱严重程度。记录到的最低年降雨量是2016年的1725.07毫米，最高是2007年的2993.19毫米。年降雨量和季节降雨量呈下降趋势，尽管在统计上不显著（p>0.05）。结果表明，柔佛州经历了极端湿润和干燥的年份，导致了干旱和洪水事件。2006年、2007年、2008年、2010年和2011年发生了重大洪水，而最干旱的年份是1997年、1998年和2016年，导致了厄尔尼诺现象。3月和4月被确定为全年最干旱的月份。因此，本研究的结果将有助于研究人员和决策者制定适用 的适应和缓解策略，以减少气候变化的影响。建议在未来的研究中对更多站点进行更多的数据分析，以获得更清晰的观点和更全面的结果。
