Staff View: Generation of rainfall sequence using fourier series

Generation of rainfall sequence using fourier series

The generation of rainfall sequence at subdaily scale is needed for various applications in hydrology. In this study a clustered point process model the Neyman Scott Rectangular Pulse Model (NSRP) with mixed exponential distribution for cell intensity is selected to produce synthetic hourly rainfall...

Full description

Saved in:

Bibliographic Details
Main Authors:	A., Norzaida, M. D., Zalina, Y., Fadhilah
Format:	Conference or Workshop Item
Published:	2009
Subjects:	Q Science (General)
Online Access:	http://eprints.utm.my/id/eprint/15233/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:100543
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.utm.15233
record_format	eprints
spelling	my.utm.152332020-07-30T07:38:48Z http://eprints.utm.my/id/eprint/15233/ Generation of rainfall sequence using fourier series A., Norzaida M. D., Zalina Y., Fadhilah Q Science (General) The generation of rainfall sequence at subdaily scale is needed for various applications in hydrology. In this study a clustered point process model the Neyman Scott Rectangular Pulse Model (NSRP) with mixed exponential distribution for cell intensity is selected to produce synthetic hourly rainfall sequence of the Klang Valley, Malaysia. In the NSRP model, storms arrive following a Poisson process. Each storm generates rain cells with the position of cells relative to storm origin are determined by the exponential distribution. Individual cell has width and height which correspond to the cell’s duration and intensity respectively. The NSRP model with mixed exponential distribution has seven parameters, X, v , B, n, a, and 0 that characterize respectively the storm origin, number of cells, positions of cells, duration of cells, mixing probability and the intensity of cells. The model’s parameters were estimated by employing the Shuffle Complex Evolution (SCEMJA) method. The model’s setback which requires the parameters to be estimated monthly to account for seasonality is dealt with by incorporating Fourier Series. Fourier coeftlcients for each paranieter were derived based on significant harmonics which best describe the parameter. Historical hourly data of ten years were used for model assessment. Results indicate that statistical properties of the simulated rainfall series were able to match most of those of the historical series. The preservation of these properties exhibits the ability of Fourier Series to capture the seasonal pattern of rainfall process. 2009 Conference or Workshop Item PeerReviewed A., Norzaida and M. D., Zalina and Y., Fadhilah (2009) Generation of rainfall sequence using fourier series. In: International Conference on Mathemathical and Statistical and their application (ICMSA 2009), 2009, Padang, Sumatera, Indonesia. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:100543
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	Q Science (General)
spellingShingle	Q Science (General) A., Norzaida M. D., Zalina Y., Fadhilah Generation of rainfall sequence using fourier series
description	The generation of rainfall sequence at subdaily scale is needed for various applications in hydrology. In this study a clustered point process model the Neyman Scott Rectangular Pulse Model (NSRP) with mixed exponential distribution for cell intensity is selected to produce synthetic hourly rainfall sequence of the Klang Valley, Malaysia. In the NSRP model, storms arrive following a Poisson process. Each storm generates rain cells with the position of cells relative to storm origin are determined by the exponential distribution. Individual cell has width and height which correspond to the cell’s duration and intensity respectively. The NSRP model with mixed exponential distribution has seven parameters, X, v , B, n, a, and 0 that characterize respectively the storm origin, number of cells, positions of cells, duration of cells, mixing probability and the intensity of cells. The model’s parameters were estimated by employing the Shuffle Complex Evolution (SCEMJA) method. The model’s setback which requires the parameters to be estimated monthly to account for seasonality is dealt with by incorporating Fourier Series. Fourier coeftlcients for each paranieter were derived based on significant harmonics which best describe the parameter. Historical hourly data of ten years were used for model assessment. Results indicate that statistical properties of the simulated rainfall series were able to match most of those of the historical series. The preservation of these properties exhibits the ability of Fourier Series to capture the seasonal pattern of rainfall process.
format	Conference or Workshop Item
author	A., Norzaida M. D., Zalina Y., Fadhilah
author_facet	A., Norzaida M. D., Zalina Y., Fadhilah
author_sort	A., Norzaida
title	Generation of rainfall sequence using fourier series
title_short	Generation of rainfall sequence using fourier series
title_full	Generation of rainfall sequence using fourier series
title_fullStr	Generation of rainfall sequence using fourier series
title_full_unstemmed	Generation of rainfall sequence using fourier series
title_sort	generation of rainfall sequence using fourier series
publishDate	2009
url	http://eprints.utm.my/id/eprint/15233/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:100543
_version_	1674066117357731840
score	13.211869

Generation of rainfall sequence using fourier series

Similar Items