Staff View: Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin

Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin

Water authority has been dealing with missing precipitation data of Kuantan River Basin (KRB) for decades and with recent flash flood events in the state of Pahang has highlighted the importance of climate data in flood prediction to reduce the severity of flood damage in future. However, climate da...

Full description

Saved in:

Bibliographic Details
Main Authors:	Lin, Shirline Leong Ai, Gisen, Jacqueline Isabella Anak, Muhammad Amiruddin, Zulkifli, Muhamad Amin, Kamaruddin, Shairul Rohaziawati, Samat
Format:	Conference or Workshop Item
Language:	English English
Published:	AIP Publishing 2024
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/42984/1/Evaluation%20of%20Alternative%20Approach%20for%20Missing%20Rainfall%20Data%20Filling%20in%20Kuantan%20River%20Basin%20-%20Intro.pdf http://umpir.ump.edu.my/id/eprint/42984/2/Evaluation%20of%20Alternative%20Approach%20for%20Missing%20Rainfall%20Data%20Filling%20in%20Kuantan%20River%20Basin.pdf http://umpir.ump.edu.my/id/eprint/42984/ https://doi.org/10.1063/5.0202430
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.ump.umpir.42984
record_format	eprints
spelling	my.ump.umpir.429842024-11-27T06:15:23Z http://umpir.ump.edu.my/id/eprint/42984/ Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin Lin, Shirline Leong Ai Gisen, Jacqueline Isabella Anak Muhammad Amiruddin, Zulkifli Muhamad Amin, Kamaruddin Shairul Rohaziawati, Samat TA Engineering (General). Civil engineering (General) Water authority has been dealing with missing precipitation data of Kuantan River Basin (KRB) for decades and with recent flash flood events in the state of Pahang has highlighted the importance of climate data in flood prediction to reduce the severity of flood damage in future. However, climate data collected on site often contains gaps affecting the quality of rainfall data resulting in inaccuracy in analysis results. The main objective of this study is to evaluate the relationship between observed and remotely sensed (TRMM) rainfall data whether there is any established relationship that is fit to act as an alternative approach to fill missing observed rainfall data for KRB. The rainfall data were collected from three different sources which are observed rainfall data from Department of Irrigation and Drainage (DID), meteorological rainfall data from Malaysia Meteorological Department (MMD) and TRMM rainfall data from NASA website. It was found that correlation between the untreated observed rainfall data and remotely sensed rainfall data is not strong enough to be an alternative approach. The most noticeable finding was from Kg Sg Soi station where the correlation coefficient between TRMM and DID observed rainfall was found to be 0.56 and the relationship between TRMM and MMD rainfall data appear to have better correlation with a coefficient of 0.57. However, when rainfall data was analysed by month, correlation was as high as 0.74 which proved that correlation is easier to be established in months during wet season. Subsequently, XLSTATS Software was used to input the missing observed rainfall values for 8 active rainfall stations to find out the best imputation method for KRB’s missing observed rainfall data. To assess the method’s performance, the results were compared to the conventional approach which is station average method. The outcomes for this study have proved that Replace by Mean, MCMC and Nearest Neighbor method are the best approach to estimate the missing rainfall data for all the station in KRB. This study’s findings provide a full observed rainfall dataset and the best imputation approaches for all 8 active rainfall stations that can be utilized for future hydrological studies. AIP Publishing 2024 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42984/1/Evaluation%20of%20Alternative%20Approach%20for%20Missing%20Rainfall%20Data%20Filling%20in%20Kuantan%20River%20Basin%20-%20Intro.pdf pdf en http://umpir.ump.edu.my/id/eprint/42984/2/Evaluation%20of%20Alternative%20Approach%20for%20Missing%20Rainfall%20Data%20Filling%20in%20Kuantan%20River%20Basin.pdf Lin, Shirline Leong Ai and Gisen, Jacqueline Isabella Anak and Muhammad Amiruddin, Zulkifli and Muhamad Amin, Kamaruddin and Shairul Rohaziawati, Samat (2024) Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin. In: AIP Conference Proceedings. The 2nd international conference of sustainable earth resources engineering 2022 , 18–20 October 2022 , Langkawi, Malaysia. pp. 1-7., 3014 (1). ISSN 0094-243X (Published) https://doi.org/10.1063/5.0202430
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Lin, Shirline Leong Ai Gisen, Jacqueline Isabella Anak Muhammad Amiruddin, Zulkifli Muhamad Amin, Kamaruddin Shairul Rohaziawati, Samat Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin
description	Water authority has been dealing with missing precipitation data of Kuantan River Basin (KRB) for decades and with recent flash flood events in the state of Pahang has highlighted the importance of climate data in flood prediction to reduce the severity of flood damage in future. However, climate data collected on site often contains gaps affecting the quality of rainfall data resulting in inaccuracy in analysis results. The main objective of this study is to evaluate the relationship between observed and remotely sensed (TRMM) rainfall data whether there is any established relationship that is fit to act as an alternative approach to fill missing observed rainfall data for KRB. The rainfall data were collected from three different sources which are observed rainfall data from Department of Irrigation and Drainage (DID), meteorological rainfall data from Malaysia Meteorological Department (MMD) and TRMM rainfall data from NASA website. It was found that correlation between the untreated observed rainfall data and remotely sensed rainfall data is not strong enough to be an alternative approach. The most noticeable finding was from Kg Sg Soi station where the correlation coefficient between TRMM and DID observed rainfall was found to be 0.56 and the relationship between TRMM and MMD rainfall data appear to have better correlation with a coefficient of 0.57. However, when rainfall data was analysed by month, correlation was as high as 0.74 which proved that correlation is easier to be established in months during wet season. Subsequently, XLSTATS Software was used to input the missing observed rainfall values for 8 active rainfall stations to find out the best imputation method for KRB’s missing observed rainfall data. To assess the method’s performance, the results were compared to the conventional approach which is station average method. The outcomes for this study have proved that Replace by Mean, MCMC and Nearest Neighbor method are the best approach to estimate the missing rainfall data for all the station in KRB. This study’s findings provide a full observed rainfall dataset and the best imputation approaches for all 8 active rainfall stations that can be utilized for future hydrological studies.
format	Conference or Workshop Item
author	Lin, Shirline Leong Ai Gisen, Jacqueline Isabella Anak Muhammad Amiruddin, Zulkifli Muhamad Amin, Kamaruddin Shairul Rohaziawati, Samat
author_facet	Lin, Shirline Leong Ai Gisen, Jacqueline Isabella Anak Muhammad Amiruddin, Zulkifli Muhamad Amin, Kamaruddin Shairul Rohaziawati, Samat
author_sort	Lin, Shirline Leong Ai
title	Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin
title_short	Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin
title_full	Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin
title_fullStr	Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin
title_full_unstemmed	Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin
title_sort	evaluation of alternative approach for missing rainfall data filling in kuantan river basin
publisher	AIP Publishing
publishDate	2024
url	http://umpir.ump.edu.my/id/eprint/42984/1/Evaluation%20of%20Alternative%20Approach%20for%20Missing%20Rainfall%20Data%20Filling%20in%20Kuantan%20River%20Basin%20-%20Intro.pdf http://umpir.ump.edu.my/id/eprint/42984/2/Evaluation%20of%20Alternative%20Approach%20for%20Missing%20Rainfall%20Data%20Filling%20in%20Kuantan%20River%20Basin.pdf http://umpir.ump.edu.my/id/eprint/42984/ https://doi.org/10.1063/5.0202430
_version_	1822924757684715520
score	13.232492

Evaluation of alternative approach for missing rainfall data filling in Kuantan river basin

Similar Items