Staff View: Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy

Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy

The occurrence of floods has the potential to escalate the transmission of infectious diseases. To enhance our comprehension of the health impacts of flooding and facilitate effective planning for mitigation strategies, it is necessary to explore the flood risk management. The variability present in...

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Main Authors:	Nur Amalina, Mat Jan, Muhammad Fadhil, Marsani, Loshini, Thiruchelvam, Nur Balqishanis, Zainal Abidin, Ani, Shabri, Sarah A'fifah, Abdullah Sani
Format:	UTAR Academic Staff Publication
Published:	Geospatial Health 2023
Subjects:	GB Physical geography RA0421 Public health. Hygiene. Preventive Medicine
Online Access:	http://eprints.utar.edu.my/6162/1/gh%2D18%2D2%2D1236.pdf https://geospatialhealth.net/index.php/gh/article/view/1236 http://eprints.utar.edu.my/6162/
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id	my-utar-eprints.6162
record_format	eprints
spelling	my-utar-eprints.61622023-12-15T08:17:54Z Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy Nur Amalina, Mat Jan Muhammad Fadhil, Marsani Loshini, Thiruchelvam Nur Balqishanis, Zainal Abidin Ani, Shabri Sarah A'fifah, Abdullah Sani GB Physical geography RA0421 Public health. Hygiene. Preventive Medicine The occurrence of floods has the potential to escalate the transmission of infectious diseases. To enhance our comprehension of the health impacts of flooding and facilitate effective planning for mitigation strategies, it is necessary to explore the flood risk management. The variability present in hydrological records is an important and neglecting non-stationary patterns in flood data can lead to significant biases in estimating flood quantiles. Consequently, adopting a non-stationary flood frequency analysis appears to be a suitable approach to challenge the assumption of independent and identically distributed observations in the sample. This research employed the generalized extreme value (GEV) distribution to examine annual maximum flood series. To estimate non-stationary models in the flood data, several statistical tests, including the TL-moment method was utilized on the data from ten stream-flow stations in Johor, Malaysia, which revealed that two stations, namely Kahang and Lenggor, exhibited non-stationary behaviour in their annual maximum streamflow. Two non-stationary models efficiently described the data series from these two specific stations, the control of which could reduce outbreak of infectious diseases when used for controlling the development measures of the hydraulic structures. Thus, the application of these models may help prevent biased prediction of flood occurrences leading to lower number of cases infected by disease. Geospatial Health 2023 UTAR Academic Staff Publication NonPeerReviewed application/pdf http://eprints.utar.edu.my/6162/1/gh%2D18%2D2%2D1236.pdf https://geospatialhealth.net/index.php/gh/article/view/1236 Nur Amalina, Mat Jan and Muhammad Fadhil, Marsani and Loshini, Thiruchelvam and Nur Balqishanis, Zainal Abidin and Ani, Shabri and Sarah A'fifah, Abdullah Sani (2023) Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy. Geospatial Health. http://eprints.utar.edu.my/6162/
institution	Universiti Tunku Abdul Rahman
building	UTAR Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tunku Abdul Rahman
content_source	UTAR Institutional Repository
url_provider	http://eprints.utar.edu.my
topic	GB Physical geography RA0421 Public health. Hygiene. Preventive Medicine
spellingShingle	GB Physical geography RA0421 Public health. Hygiene. Preventive Medicine Nur Amalina, Mat Jan Muhammad Fadhil, Marsani Loshini, Thiruchelvam Nur Balqishanis, Zainal Abidin Ani, Shabri Sarah A'fifah, Abdullah Sani Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy
description	The occurrence of floods has the potential to escalate the transmission of infectious diseases. To enhance our comprehension of the health impacts of flooding and facilitate effective planning for mitigation strategies, it is necessary to explore the flood risk management. The variability present in hydrological records is an important and neglecting non-stationary patterns in flood data can lead to significant biases in estimating flood quantiles. Consequently, adopting a non-stationary flood frequency analysis appears to be a suitable approach to challenge the assumption of independent and identically distributed observations in the sample. This research employed the generalized extreme value (GEV) distribution to examine annual maximum flood series. To estimate non-stationary models in the flood data, several statistical tests, including the TL-moment method was utilized on the data from ten stream-flow stations in Johor, Malaysia, which revealed that two stations, namely Kahang and Lenggor, exhibited non-stationary behaviour in their annual maximum streamflow. Two non-stationary models efficiently described the data series from these two specific stations, the control of which could reduce outbreak of infectious diseases when used for controlling the development measures of the hydraulic structures. Thus, the application of these models may help prevent biased prediction of flood occurrences leading to lower number of cases infected by disease.
format	UTAR Academic Staff Publication
author	Nur Amalina, Mat Jan Muhammad Fadhil, Marsani Loshini, Thiruchelvam Nur Balqishanis, Zainal Abidin Ani, Shabri Sarah A'fifah, Abdullah Sani
author_facet	Nur Amalina, Mat Jan Muhammad Fadhil, Marsani Loshini, Thiruchelvam Nur Balqishanis, Zainal Abidin Ani, Shabri Sarah A'fifah, Abdullah Sani
author_sort	Nur Amalina, Mat Jan
title	Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy
title_short	Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy
title_full	Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy
title_fullStr	Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy
title_full_unstemmed	Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy
title_sort	mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in malaysia based on natural disaster reduction strategy
publisher	Geospatial Health
publishDate	2023
url	http://eprints.utar.edu.my/6162/1/gh%2D18%2D2%2D1236.pdf https://geospatialhealth.net/index.php/gh/article/view/1236 http://eprints.utar.edu.my/6162/
_version_	1787140958682349568
score	13.211869

Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy

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