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Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique
Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135133/ https://www.ncbi.nlm.nih.gov/pubmed/25152911 http://dx.doi.org/10.1155/2014/379763 |
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author | Adham, M. I. Shirazi, S. M. Othman, F. Rahman, S. Yusop, Z. Ismail, Z. |
author_facet | Adham, M. I. Shirazi, S. M. Othman, F. Rahman, S. Yusop, Z. Ismail, Z. |
author_sort | Adham, M. I. |
collection | PubMed |
description | Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling. |
format | Online Article Text |
id | pubmed-4135133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41351332014-08-24 Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique Adham, M. I. Shirazi, S. M. Othman, F. Rahman, S. Yusop, Z. Ismail, Z. ScientificWorldJournal Research Article Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling. Hindawi Publishing Corporation 2014 2014-07-24 /pmc/articles/PMC4135133/ /pubmed/25152911 http://dx.doi.org/10.1155/2014/379763 Text en Copyright © 2014 M. I. Adham et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Adham, M. I. Shirazi, S. M. Othman, F. Rahman, S. Yusop, Z. Ismail, Z. Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique |
title | Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique |
title_full | Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique |
title_fullStr | Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique |
title_full_unstemmed | Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique |
title_short | Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique |
title_sort | runoff potentiality of a watershed through scs and functional data analysis technique |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135133/ https://www.ncbi.nlm.nih.gov/pubmed/25152911 http://dx.doi.org/10.1155/2014/379763 |
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