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008			191011t20182018my a|||| |||| 00| 0 eng d
020			_aTHE0008214(Local)
040			_aUMP _beng _cUMP _erda
090			_aFKASA .M57 2018 r Bc.
100	0		_aMisriyah Helman, _eauthor.
245	1	4	_aThe fluctuation of long-term streamflow pattern with considered the climate change impacts / _cMisriyah Helman
264		1	_aKuantan, Pahang : _bUMP, _c2018
264		4	_a© 2018
300			_axiii, 84 pages : _bIllustrations (some color) ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
337			_2rdamedia _acomputer
338			_2rdacarrier _avolume
338			_2rdacarrier _acomputer disc
347			_2rda _atext file _bPDF
500			_aFaculty of Civil Engineering and Earth Resources
502			_aProject Paper (Bachelor of Civil Engineering) -- Universiti Malaysia Pahang – 2018
504			_aIncludes bibliographical references
520	3		_aThe escalation of global surface temperature in response to the alter of composition of the atmosphere will notably effect upon local hydrological patterns and water resources. This circumstance will later lead to the necessity for an assessment of climate change impacts. The main purpose of this study is to determine the current climate pattern and predict the future streamflow by using the applicability of statistical downscaling model (SDSM) and identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) models, respectively. In this study, the investigation was done by the potentiality of IHACRES to predict the fluctuation of long-term streamflow influenced by large-scale atmospheric variables which focused on Sg. Yap, Pahang. The study was done by the calibration and validation of from 26 NCEP-reanalysis data and the general circulation models (GCMs) outputs, and the subsequent the prediction of future rainfall and temperature in term of three different greenhouse gas emission scenarios (RCP2.6, RCP4.5 and RCP8.5). Based on the calibration and validation results, SDSM produced good performance in temperature simulation and low performance in rainfall simulation. The projection of mean monthly temperature for future years (2020-2099) for each scenario, it is predicted there is decreasing mean temperature from September to December achieving -6.13% (RCP2.6), -5.94% (RCP4.5) and -6.25% (RCP8.5) while the increasing trends from January to August reaching +7.07% (RCP2.6), +6.80% (RCP4.5) and +7.00% (RCP8.5). Meanwhile, for average monthly rainfall projection in 2020-2099, the increasing monthly rainfall from September to December achieving +67.39% (RCP2.6), +71.14% (RCP4.5) and -+66.60% (RCP8.5) while the decreasing trends from January to August reaching -69.69% (RCP2.6), -46.11% (RCP4.5) and -39.00% (RCP8.5). On top of that, IHACRES model able to show reliable simulation of streamflow in this study. The projection of future streamflow pattern (2020-2099), corresponding to the downscaled future climate projection by comparing the future trends with the historical records, the average mean monthly streamflow is decreasing obviously with -52.00%, -54.68% and -53.05% for the scenario RCP2.6, RCP4.5 and RCP8.5, respectively. The fluctuation of future flows is can be clearly seen from its pattern of monthly, annual and decade inflow in the different scenarios.
610	2	0	_aFaculty of Civil Engineering and Earth Resources
650		0	_aDissertations _xUniversities and colleges
650		0	_aTheses
942			_2lcc _cPSM