A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Spatial Variability of Rainfall in Urban Catchment
Abstract 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.
Spatial Variability of Rainfall in Urban Catchment
Abstract 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.
Spatial Variability of Rainfall in Urban Catchment
Haris, H. (author) / Chow, M. F. (author) / Sidek, L. M. (author)
2018-05-13
12 pages
Article/Chapter (Book)
Electronic Resource
English
Spatial variability , Penchala river , Urban runoff , Rainfall analysis , ANOVA analysis , Boxplot analysis Engineering , Civil Engineering , Geotechnical Engineering & Applied Earth Sciences , Remote Sensing/Photogrammetry , Hydrology/Water Resources , Climate Change/Climate Change Impacts , Image Processing and Computer Vision
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