Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting

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...

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Main Author:	Ahmad Tarmizi, ‘Aainaa Hatin
Format:	Thesis
Language:	English English English
Published:	2020
Subjects:	QA75-76.95 Calculating machines
Online Access:	http://eprints.uthm.edu.my/982/1/24p%20%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI.pdf http://eprints.uthm.edu.my/982/2/%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/982/3/%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI%20WATERMARK.pdf
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spelling	my-uthm-ep.9822021-09-19T07:31:07Z Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting 2020-09 Ahmad Tarmizi, ‘Aainaa Hatin QA75-76.95 Calculating machines 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, RCP2.6, RCP4.5 and RCP8.5 for interval year of Δ2030, Δ2050 and Δ2080. In addition, the annual future rainfall trend and harvested rainwater volume estimation for the first interval year of Δ2030 were also made. Daily rainfall series from eight (8) stations in Johor capturing 30 years period (1988-2017) with less than 10% missing data were chosen. Of all 26 predictors, only five (5) were chosen for each station to form a rainfall equation at each station for prediction analyses. It can be observed that the temperature (nceptemp), surface specific humidity (ncepshum) and near-surface relative humidity (nceprhum) had a strongest influence in the local weather formations with R values ranged from 0.5 to 0.7. The annual mean rainfall for RCP 2.6, 4.5 and 8.5 was predicted increase by of 17.5%, 18.1% and 18.3%, respectively as compared to historical data. Kluang was predicted to receive the highest amount of rainfall, and the lowest was in Segamat. Moreover, the Mann-Kendall 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. Volume harvested rainwater ( 2020-09 Thesis http://eprints.uthm.edu.my/982/ http://eprints.uthm.edu.my/982/1/24p%20%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI.pdf text en public http://eprints.uthm.edu.my/982/2/%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/982/3/%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA75-76.95 Calculating machines
spellingShingle	QA75-76.95 Calculating machines Ahmad Tarmizi, ‘Aainaa Hatin Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
description	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, RCP2.6, RCP4.5 and RCP8.5 for interval year of Δ2030, Δ2050 and Δ2080. In addition, the annual future rainfall trend and harvested rainwater volume estimation for the first interval year of Δ2030 were also made. Daily rainfall series from eight (8) stations in Johor capturing 30 years period (1988-2017) with less than 10% missing data were chosen. Of all 26 predictors, only five (5) were chosen for each station to form a rainfall equation at each station for prediction analyses. It can be observed that the temperature (nceptemp), surface specific humidity (ncepshum) and near-surface relative humidity (nceprhum) had a strongest influence in the local weather formations with R values ranged from 0.5 to 0.7. The annual mean rainfall for RCP 2.6, 4.5 and 8.5 was predicted increase by of 17.5%, 18.1% and 18.3%, respectively as compared to historical data. Kluang was predicted to receive the highest amount of rainfall, and the lowest was in Segamat. Moreover, the Mann-Kendall 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. Volume harvested rainwater (
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Ahmad Tarmizi, ‘Aainaa Hatin
author_facet	Ahmad Tarmizi, ‘Aainaa Hatin
author_sort	Ahmad Tarmizi, ‘Aainaa Hatin
title	Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
title_short	Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
title_full	Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
title_fullStr	Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
title_full_unstemmed	Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
title_sort	forecasting of rainfall using statistical downscaling model (sdsm) – general circulation model (gcm) for future estimation of rainwater harvesting
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2020
url	http://eprints.uthm.edu.my/982/1/24p%20%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI.pdf http://eprints.uthm.edu.my/982/2/%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/982/3/%E2%80%98AAINAA%20HATIN%20AHMAD%20TARMIZI%20WATERMARK.pdf
_version_	1747830723118628864

Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting

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