Assessment of the Flood and Drought Occurrence Using Statistically Downscaled Local Climate Models: A Case Study in Langat River Basin, Malaysia

Abstract

Abstract Climate change is a complex and multi-layer issue with global and local entanglement. In this study, Langat River Basin is chosen. Secondary data was used including the historical flood and drought event reports, Standardized Precipitation Index-1 data and Canadian Earth System Model (CanESM2) along with Australian Community Climate and Earth System Simulator Coupled Model (ACCESS CM-2). These data were used to determine the monthly flood and drought precipitation risk based on five regions of Langat River Basin. The CanESM2 and ACCESS CM-2 based on RCP 4.5 and RCP 8.5 scenarios were downscaled and bias corrected for this study. The reliability of these models was then analyzed with Pearson correlation and probability density function (PDF). The future flood and drought risks from year 2020 to 2100 were predicted using the most reliable local climate model local climate hazard thresholds. The CanESM2 RCP 4.5 scenario was identified to have moderate relationship with the historical precipitation trend in Langat River Basin. The Pearson correlation outcomes were then verified by analyzing the PDF curve between models and historical precipitation. The result shows that the downscaled CanESM2 RCP 4.5 was determined to have moderate correlation r = 0.30, whereas highest similarity with the historical precipitation trend 98.63 % based on 2006 to 2018 period. The scenario is consistent with medium emission coupled with increasing mitigation efforts in Malaysia. Furthermore, the flood and drought risk assessment outcomes show that the occurrence rate for Central, Northern, Southern, Western, and Eastern region in Langat River Basin were determined as 41.97 %, 60.19 %, 40.23 %, 20.16 %, and 34.98% respectively. The Central region was predicted having two drought incidences (February 2069 and February 2099) due to extreme dry season predicted based on 2020 to 2100 period.