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008			240419t20232023my a|||fr|||| 000 0 eng d
020			_aTHE0009831 (Local) _qHardback
040			_aUMPSA _beng _cUMP _erda
090			_aFTKA .A45 2023 r Thesis
100	1		_aWan Amirul Syahmi Bin Wan Mazlan, _eauthor.
245	1	0	_aDevelopment of improving intensity duration frequency (IDF) curve considering the climate change impacts – case study at Hulu Terengganu / _cWan Amirul Syahmi Bin Wan Mazlan
264		1	_aKuantan, Pahang : _bUMPSA, _c2023
264		4	_c©2023
300			_axiv, 206 pages : _billustrations ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Civil Engineering Technology
502			_aThesis (Master of Science) -- Universiti Malaysia Pahang – 2023
504			_aIncludes bibliographical references
520	3		_aClimate change has a significant impact on the hydrological cycle by altering rainfall patterns in both intensity and frequency which can cause unexpected flooding in some areas, and flooding in low-lying areas will inevitably worsen. The intensity-durationfrequency (IDF) curve is the most commonly used form as a reference to estimate the peak of flood discharge. 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 develop the IDF curves considering the climate change impacts on Hulu Terengganu. Besides, future rainfall under the climate change scenarios was generated to compare with historical data, and the best disaggregation method for constructing hourly rainfall was determined. There were four active rainfall stations selected to provide 33 years (1988-2020) of observed daily and hourly historical rainfall data. The climate simulation data from the three GCMs (MRI-ESM2-0, CMCC-CM2- SR5, and GFDL-ESM4) for SSP1-2.6, SSP2-4.5, and SSP5-8.5 from the CMIP6 model were used in this study. The statistical downscaling of the linear scaling method (SD-LS) was employed to correct the biases of the three GCMs. Then, the performance of three distinct empirical disaggregation methods: Scaling Properties (SP), Indian Reduction Formula (IRF), and Stochastic Method (SM) has been evaluated using three statistical analyses, and the statistical properties of the hourly historical data and disaggregated data have also been compared. The annual maximum hourly rainfall data obtained from the disaggregation process were fitted into the Gumbel distribution to generate the future IDF curves for the return periods of 2, 5, 10, 20, 50, 100, and 200 years for the rainfall duration of 1 to 24 hours. The maximum rainfall intensities in Δ2050s and Δ2080s for each rainfall station are selected across all climate scenarios to be compared with the current IDF curves used in MSMA2. 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. The increment of rainfall projected by the SSPs is expected to reach 17.11% in Δ2050s with December having the highest intensity and 10.31% in Δ2080s with January having the highest intensity. Besides, the analysis shows that the SP method is the most accurate and adequate empirical method utilised to disaggregate the daily rainfall data to hourly compared to other methods. Finally, the future rainfall intensities of extreme rainfall events for various durations with different return periods are all likely to increase over time. The largest increases are anticipated in the range of 2.0% to 86.0% in Δ2050s and 22.0% to 91.0% in Δ2080s. It proved that climate change has a significant influence on the development of the IDF curve. Therefore, the current IDF curves used as an infrastructure design tool in the MSMA2 need to be improved by considering the impact of future climate trends.
610	2	0	_aFaculty of Civil Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
942			_2lcc _cTHESIS