Spatial variability of rainfall in urban catchment

The rapid urbanization process has created massive pressure on the environment and interrupted the water balance. In this research, Penchala River was chosen as the research area. Spatial variability of rainfall can lead to significant error in rainfall–runoff processes and hydrological modeling, sp...

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Main Authors: Haris, H., Chow, M.F., Sidek, L.M.
Format: Book chapter
Language:English
Published: 2019
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spelling my.uniten.dspace-117852020-03-17T05:11:41Z Spatial variability of rainfall in urban catchment Haris, H. Chow, M.F. Sidek, L.M. The rapid urbanization process has created massive pressure on the environment and interrupted the water balance. In this research, Penchala River was chosen as the research area. Spatial variability of rainfall can lead to significant error in rainfall–runoff processes and hydrological modeling, specifically in the urban area. Thus, one-way analysis of variance (ANOVA) was used to determine whether there are any statistically significant differences between the means of rainfall data from selected rainfall stations. The yearly and monthly data of all eight rainfall stations during the period of the year, 2012–2015 was used for this analysis. The post hoc test was used to identified, in which rainfall station differed among each other during the study. The null hypothesis (no significant difference) is accepted, when the computed p value is more than 0.05. The results showed that there is no significant statistical difference in the rainfall data between the rain gauges of S1–S8 with the p-values 0.945 (2012), 0.954 (2013), 0.342 (2014), and 0.427 (2015). It can be concluded that none of the gauge used for the determination of rainfall dataset contained systematic errors. © Springer Nature Singapore Pte Ltd. 2019. 2019-03-13T03:37:44Z 2019-03-13T03:37:44Z 2019 Book chapter 10.1007/978-981-10-8016-6_76 en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description The rapid urbanization process has created massive pressure on the environment and interrupted the water balance. In this research, Penchala River was chosen as the research area. Spatial variability of rainfall can lead to significant error in rainfall–runoff processes and hydrological modeling, specifically in the urban area. Thus, one-way analysis of variance (ANOVA) was used to determine whether there are any statistically significant differences between the means of rainfall data from selected rainfall stations. The yearly and monthly data of all eight rainfall stations during the period of the year, 2012–2015 was used for this analysis. The post hoc test was used to identified, in which rainfall station differed among each other during the study. The null hypothesis (no significant difference) is accepted, when the computed p value is more than 0.05. The results showed that there is no significant statistical difference in the rainfall data between the rain gauges of S1–S8 with the p-values 0.945 (2012), 0.954 (2013), 0.342 (2014), and 0.427 (2015). It can be concluded that none of the gauge used for the determination of rainfall dataset contained systematic errors. © Springer Nature Singapore Pte Ltd. 2019.
format Book chapter
author Haris, H.
Chow, M.F.
Sidek, L.M.
spellingShingle Haris, H.
Chow, M.F.
Sidek, L.M.
Spatial variability of rainfall in urban catchment
author_facet Haris, H.
Chow, M.F.
Sidek, L.M.
author_sort Haris, H.
title Spatial variability of rainfall in urban catchment
title_short Spatial variability of rainfall in urban catchment
title_full Spatial variability of rainfall in urban catchment
title_fullStr Spatial variability of rainfall in urban catchment
title_full_unstemmed Spatial variability of rainfall in urban catchment
title_sort spatial variability of rainfall in urban catchment
publishDate 2019
_version_ 1662758764597477376
score 13.160551