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The intensity-duration-frequency (IDF) curves are the most common form of design rainfall data used for peak discharge estimation. Thus, the IDF curve needs to be improved with the expectation that rainfall intensity and frequency have increased as a result of climate change. The main purpose of this study was to investigate the changes of IDF curves considering the climate change impacts on Hulu Terengganu. The climate projection from MRI-ESM2-0, CMCC-CM2-SR5, and GFDL-ESM4 under 3 different scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) were used to provide the climate changes pattern in the future year (∆2050). In order to downscale the climate projection, the statistical downscaling method (SD-LS) was employed to correct the biases of these three GCMs. The IDF curves for the return periods of 2, 5, 10, 20, 50, 100, and 200 year were then developed based on the maximum rainfall intensity that were projected by the SD-LS model. The results clearly indicated that there are possibilities for increasing patterns in the projected annual and monthly rainfall for both time periods compared to historical data. Thus, the future extreme rainfall events for various durations with different return periods are all likely to increase over time. The largest potential increase is predicted at Sg. Gawi (+2.0% to +86.0%) based on the different return periods and rainfall durations. It could change the pattern of IDF curve that been developed based on projected rainfall by various SSPs. The developed IDF curves shows higher rainfall intensities in a shorter duration under the same return periods. Therefore, comprehensive action must be taken immediately to regulate and manage the effects of climate change.

Changes in the spatial and temporal rainfall pattern affected by the climate change need to be investigated as its significant characteristics are often used for managing water resources. In this study, the impacts of climate change on rainfall variability in Johor was investigated by using General Circulation Model (GCM) on the availability of daily simulation for three representative concentration pathways (RCP) scenarios, RCP 2.6, RCP 4.5 and RCP 8.5 for interval year of ?2030, ?2050 and ?2080. In addition, the annual future rainfall trend for the first interval year of ?2030 was also made. Daily rainfall series from eight (8) stations in Johor, Malaysia capturing 30 years period (1988-2017) with less than 10% missing data were chosen. The annual mean rainfall for RCP 2.6, 4.5 and 8.5 was predicted increase by 17.5%, 18.1% and 18.3%, respectively as compared to historical data. Moreover, the Mann-Kendall (MK) test was used to detect the trend and resulted in no trend for RCP 2.6. Even so, RCP 4.5 showed a significant upward trend in Muar and Kota Tinggi, and for RCP 8.5, all regions were detected to have an upwards trend except for Pontian and Kluang. In general, the concentration of greenhouse gases from RCP 8.5 gave the highest rainfall in future.

Uncertainty of climate extreme nowadays causes an alteration in the local climate trend and variability. Terengganu, Malaysia recorded series of extreme drought and flood events throughout a year affected by North-East monsoon which will change the next climate pattern. Thus, it will affecting the long-term planning and sustainability that related to the water resources in the long-term. The objective of this study was to analyse the trend changes of rainfall and temperature at Kuala Terengganu, Malaysia due to climate changes impact. The trends changes were analysed using Man-Kendall and Sen’s Slope. The climate projection result shows the annual mean temperature is expected to have decreasing trend until end of century. However Mar to June are expected to bit higher than historical reach to 29oC by RCP8.5. Then it will be dropped to 24oC (-5% from historical) during Northeast monsoon. Consistent to the annual rainfall, it was expected to have increasing trend over time. The highest increasing trend was expected to occur on Nov to Dec more than 40% by RCP8.5.

Changes in the spatial and temporal rainfall pattern which affected by the climate change need to be investigated as its significant characteristics are often used for managing water resources. This paper implemented the statistical modelling to study the spatial and temporal distribution changes of rainfall pattern in the long term analysis. A daily rainfall series from eight (8) stations in Johor capturing 30 years period (1988-2017) with less than 10% missing data were chosen. To build the predictor-predictand relationship, it depends on the monthly correlation coefficient (R) with the large scale of atmospheric characteristic and performances of calibrated and validated of statistical equation using Statistical Downscaling Model (SDSM). The results showed that the temperature (nceptemp), surface specific humidity (ncepshum) and near surface relative humidity (nceprhum) had strong influence in the local weather formations. As proved, all these stations were successfully produced low standard error (SE) ranged from 3.82% to 11.64%. The annual temporal rainfall was expected to increase to 3058.13 mm (15.4%) at the end of century. The eastern of Johor was expecting to receive higher rainfall intensity and then disperse to the western of Johor. The predictions of rainfall are a bit alarming, therefore, mitigation planning on climate change effects is needed.