Sa'adi Zulfaqar, Alias Nor Eliza, Yusop Zulkifli, Iqbal Zafar, Houmsi Mohamad Rajab, Houmsi Lama Nasrallah, Ramli Muhammad Wafiy Adli, Muhammad Mohd Khairul Idlan
Centre for Environmental Sustainability and Water Security (IPASA), School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 UTM Sekudai, Johor, Malaysia; Department of Water & Environmental Engineering, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia.
Department of Water & Environmental Engineering, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia; NUST Institute of Civil Engineering-SCEE, National University of Sciences and Technology (NUST), H-12, Islamabad 44000, Pakistan.
Sci Total Environ. 2024 Feb 20;912:169187. doi: 10.1016/j.scitotenv.2023.169187. Epub 2023 Dec 12.
The most recent set of General Circulation Models (GCMs) derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) was used in this work to analyse the spatiotemporal patterns of future rainfall distribution across the Johor River Basin (JRB) in Malaysia. A group of 23 GCMs were chosen for comparative assessment in simulating basin-scale rainfall based on daily rainfall from the historical period of the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS). The methodological novelty of this study lies in the application of relative importance metrics (RIM) to rank and select historical GCM simulations for reproducing rainfall at 109 CHIRPS grid points within the JRB. In order to choose the top GCMs, the rankings given by RIM were aggregated using the compromise programming index (CPI) and Jenks optimised classification (JOC). It was found that ACCESS-ESM1-5 and CMCC-ESM2 were ranked the highest in most of the grid. The final GCM was then bias-corrected using the linear scaling method before being ensemble based on the Bayesian model averaging (BMA) technique. The spatiotemporal assessment of the ensemble model for the different months over the near-future period 2021-2060 and far-future period 2061-2100 was compared with those under Shared Socioeconomic Pathways (SSPs), namely, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Heterogeneous changes in rainfall were projected across the JRB, with both increasing and decreasing trends. In the near-future and far-future scenarios, higher rainfall was projected for December, indicating an elevated risk of flooding during the end of the North East monsoon (NEM). Conversely, August showed a decreasing trend in rainfall, implying an increasing risk of severe drought. The findings of this study provide valuable insights for effective water resource management and climate change adaptation in the region.
本研究使用了源自耦合模式比较计划第6阶段(CMIP6)的最新一组全球气候模式(GCMs),来分析马来西亚柔佛河流域(JRB)未来降雨分布的时空格局。基于气候灾害组红外降水与站点数据(CHIRPS)历史时期的日降雨量,选择了一组23个GCMs进行流域尺度降雨模拟的比较评估。本研究的方法新颖之处在于应用相对重要性指标(RIM)对历史GCM模拟进行排名和选择,以再现JRB内109个CHIRPS网格点的降雨情况。为了选择最佳的GCMs,使用折衷规划指数(CPI)和Jenks优化分类(JOC)对RIM给出的排名进行汇总。结果发现,ACCESS-ESM1-5和CMCC-ESM2在大多数网格中排名最高。然后,使用线性缩放方法对最终的GCM进行偏差校正,再基于贝叶斯模型平均(BMA)技术进行集合。将近期2021 - 2060年和远期2061 - 2100年不同月份的集合模型时空评估结果与共享社会经济路径(SSPs)下的结果进行比较,即SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5。预计JRB各地降雨将出现异质变化,有增加和减少的趋势。在近期和远期情景中,预计12月降雨量较高,这表明东北季风(NEM)末期洪水风险升高。相反,8月降雨量呈下降趋势,这意味着严重干旱风险增加。本研究结果为该地区有效的水资源管理和气候变化适应提供了有价值的见解。