Application of CHIRPS dataset in the selection of rain-based indices for drought assessments in Johor River Basin, Malaysia

Sa'adi Z 1 , Yusop Z 2 , Alias NE 3 , Shiru MS 4 , Muhammad MKI 5 , Ramli MWA 6

Affiliations 

  • 1 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. Electronic address: zulfaqar@utm.my
  • 2 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. Electronic address: zulyusop@utm.my
  • 3 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. Electronic address: noreliza@utm.my
  • 4 Department of Environmental Sciences, Faculty of Science, Federal University Dutse, P.M.B 7156 Dutse, Nigeria
  • 5 Department of Water & Environmental Engineering, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Malaysia. Electronic address: mohdkhairulidlan@utm.my
  • 6 Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Malaysia
Sci Total Environ, 2023 Sep 20;892:164471.
PMID: 37257620 DOI: 10.1016/j.scitotenv.2023.164471

Abstract

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 (R2 = 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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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