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The fluctuation of long-term streamflow pattern with considered the climate change impacts / Misriyah Helman

By:

Misriyah Helman [author.]

Material type: Text

text
text

Media type:

unmediated
computer

Carrier type:

volume
computer disc

ISBN:

THE0008214(Local)

Subject(s):

Dissertation note: Project Paper (Bachelor of Civil Engineering) -- Universiti Malaysia Pahang – 2018 Abstract: The 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.

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Holdings ( 2 )
Title notes ( 4 )

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Final Year Report	UMPLIB GAMBANG Reference	Reference	FKASA .M57 2018 r Bc. (Browse shelf(Opens below))	Not for loan		0000126991
Final Year Report	UMPLIB GAMBANG		CD11915 (Browse shelf(Opens below))	Not for loan		0000126992

Faculty of Civil Engineering and Earth Resources

Project Paper (Bachelor of Civil Engineering) -- Universiti Malaysia Pahang – 2018

Includes bibliographical references

The 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.