Sa'adi Zulfaqar, Yusop Zulkifli, Alias Nor Eliza, Shiru Mohammed Sanusi, Muhammad Mohd Khairul Idlan, Ramli Muhammad Wafiy Adli
Centre for Environmental Sustainability and Water Security, Research Institute for Sustainable Environment, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor Bahru, Malaysia; Department of Water and Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor Bahru, Malaysia.
Department of Environmental Sciences, Faculty of Science, Federal University Dutse, P.M.B 7156 Dutse, Nigeria.
Sci Total Environ. 2023 Sep 20;892:164471. doi: 10.1016/j.scitotenv.2023.164471. Epub 2023 May 30.
This paper aims to select the most appropriate rain-based meteorological drought index for detecting drought characteristics and identifying tropical drought events in the Johor River Basin (JRB). Based on a multi-step approach, the study evaluated seven drought indices, including the Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), China-Z Index (CZI), Modified China-Z Index (MCZI), Percent of Normal (PN), Deciles Index (DI), and Z-Score Index (ZSI), based on the CHIRPS rainfall gridded-based datasets from 1981 to 2020. Results showed that CZI, MCZI, SPI, and ZSI outperformed the other indices based on their correlation and linearity (R = 0.96-0.99) along with their ranking based on the Compromise Programming Index (CPI). The historical drought evaluation revealed that MCZI, SPI, and ZSI performed similarly in detecting drought events, but SPI was more effective in detecting spatial coverage and the occurrence of 'very dry' and 'extremely dry' drought events. Based on SPI, the study found that the downstream area, north-easternmost area, and eastern boundary of the basin were more prone to higher frequency and longer duration droughts. Furthermore, the study found that prolonged droughts are characterized by episodic drought events, which occur with one to three months of 'relief period' before another drought event occurs. The study revealed that most drought events that coincide with El Niño, positive Indian Ocean Dipole (IOD), and negative Madden-Julian Oscillation (MJO) events, or a combination of these events, may worsen drought conditions. The application of CHIRPS datasets enables better spatiotemporal mapping and prediction of drought for JRB, and the output is pertinent for improving water management strategies and adaptation measures. Understanding spatiotemporal drought conditions is crucial to ensuring sustainable development and policies through better regulation of human activities. The framework of this research can be applied to other river basins in Malaysia and other parts of Southeast Asia.
本文旨在选择最合适的基于降雨的气象干旱指数,以检测柔佛河流域(JRB)的干旱特征并识别热带干旱事件。基于多步骤方法,该研究基于1981年至2020年的CHIRPS网格化降雨数据集,评估了七个干旱指数,包括降雨异常指数(RAI)、标准化降水指数(SPI)、中国-Z指数(CZI)、修正中国-Z指数(MCZI)、距平百分率(PN)、十分位数指数(DI)和Z分数指数(ZSI)。结果表明,基于相关性和线性(R = 0.96 - 0.99)以及基于折衷规划指数(CPI)的排名,CZI、MCZI、SPI和ZSI优于其他指数。历史干旱评估表明,MCZI、SPI和ZSI在检测干旱事件方面表现相似,但SPI在检测空间覆盖范围以及“非常干燥”和“极其干燥”干旱事件的发生方面更有效。基于SPI,该研究发现流域的下游地区、最东北端地区和东部边界更容易发生频率更高、持续时间更长的干旱。此外,该研究发现长期干旱的特征是间歇性干旱事件,在另一次干旱事件发生之前会有一到三个月的“缓解期”。该研究表明,大多数与厄尔尼诺、正印度洋偶极子(IOD)和负马登-朱利安振荡(MJO)事件或这些事件的组合同时发生的干旱事件,可能会使干旱状况恶化。CHIRPS数据集的应用使得能够更好地对JRB的干旱进行时空映射和预测,其结果对于改进水资源管理策略和适应措施具有重要意义。了解时空干旱状况对于通过更好地规范人类活动来确保可持续发展和政策至关重要。本研究框架可应用于马来西亚的其他流域以及东南亚其他地区。