FUTURE CLIMATE CHANGE IMPACT USING STATISTICAL DOWNSCALING MODEL (SDSM) AND HYDROLOGICAL MODELLING SYSTEM (HEC-HMS) IN BUKIT MERAH SUB-BASIN

• Main Author: MALIK, ALIA FARHANA
• Format: Thesis
• Language: English; English; English
• Published: 2024
• Subjects: TA170-171 Environmental engineering
• Online Access: http://eprints.uthm.edu.my/12635/

It is deemed that climate change especially changes in temperature and rainfall will have significant impacts on water basin including runoff and hydrological systems. This study investigated the applicability of statistical downscaling model (SDSM) for temperature and rainfall downscaling in the Bukit Merah Sub-basin Perak, Malaysia, under Representative Concentration Pathway (RCP) 4.5 and 8.5. This study also comprised the calibration of the SDSM model through the use of large-scale atmospheric variables that incorporated the reanalysed data from the National Centre for Environmental Prediction (NCEP). Findings showed that the minimum temperature in Ipoh Station (48625) decreased by 2.11% and 2.25% for RCP4.5 and RCP8.5 from current data, 220C. In contrast, maximum temperature increased by 1.09% and 1.40% from current data, 330C in 2080s for RCP4.5 and RCP8.5. The coefficient of determination (R²) value for calibration of minimum and maximum temperature ranged from 0.56-0.68 while for validation was from 0.70-0.76. Moreover, future average monthly rainfall trend of Pondok Tanjung Station (5007020) showed an increasing trend for both RCPs. The simulation results were used as input for a hydrological model known as the Engineering Center’s Hydraulic Modeling System (HEC-HMS). This HEC-HMS was used to predict the future runoff for the Bukit Merah reservoir. R2 value of HEC-HMS perform well for calibration and validation which closed to 1, 0.91 and 0.96. The results at Pondok Tanjung streamflow station (5007421) demonstrated that the lowest recorded runoff ranged from 19.98 m3/s while 22.92 m3/s in 2020 for RCP4.5 and RCP 8.5 and the trend began to increase until the end of the century. In conclusion, this study has successfully contributed to the development of models using hydrologic model and statistical methods for sustainable water resources planning from the future prediction data simulated from both models.