Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli
A good quality of rainfall data is highly necessary in hydrological and meteorological analyses. Lack of quality in rainfall data will influence the process of analyses and subsequently, produce misleading results. Thus, this study is aimed to propose modified missing rainfall data treatment methods...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Penerbit UiTM (UiTM Press)
2016
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| Online Access: | https://ir.uitm.edu.my/id/eprint/16134/2/16134.pdf |
| _version_ | 1796900380836102144 |
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| author | Amin Burhanuddin, Siti Nur Zahrah Mohd Deni, Sayang Mohamed Ramli, Norazan |
| author_facet | Amin Burhanuddin, Siti Nur Zahrah Mohd Deni, Sayang Mohamed Ramli, Norazan |
| author_sort | Amin Burhanuddin, Siti Nur Zahrah |
| collection | UITM |
| description | A good quality of rainfall data is highly necessary in hydrological and meteorological analyses. Lack of quality in rainfall data will influence the process of analyses and subsequently, produce misleading results. Thus, this study is aimed to propose modified missing rainfall data treatment methods that produced more accurate estimation results. In this study, the old normal ratio method and the modified normal ratio based on trimmed mean are combined with geographical coordinate method. The performances of these modified methods were tested on various levels of the missing data of 36 years complete daily rainfall records from eighteen meteorology stations in Peninsular Malaysia. The results indicated that both modified methods improved the estimation of missing rainfall values at the target station based on the least error measurements. Modified normal ratio based on trimmed mean with geographical coordinate method is found to be the most appropriate method for station Batu Kurau and Sg. Bernam while modified old normal ratio with geographical coordinate is the most accurate in estimating the missing data at station Genting Klang. |
| first_indexed | 2024-03-06T01:34:21Z |
| format | Article |
| id | oai:ir.uitm.edu.my:16134 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T01:34:21Z |
| publishDate | 2016 |
| publisher | Penerbit UiTM (UiTM Press) |
| record_format | dspace |
| spelling | oai:ir.uitm.edu.my:161342023-04-27T07:51:41Z https://ir.uitm.edu.my/id/eprint/16134/ Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli srj Amin Burhanuddin, Siti Nur Zahrah Mohd Deni, Sayang Mohamed Ramli, Norazan Data processing Prediction analysis A good quality of rainfall data is highly necessary in hydrological and meteorological analyses. Lack of quality in rainfall data will influence the process of analyses and subsequently, produce misleading results. Thus, this study is aimed to propose modified missing rainfall data treatment methods that produced more accurate estimation results. In this study, the old normal ratio method and the modified normal ratio based on trimmed mean are combined with geographical coordinate method. The performances of these modified methods were tested on various levels of the missing data of 36 years complete daily rainfall records from eighteen meteorology stations in Peninsular Malaysia. The results indicated that both modified methods improved the estimation of missing rainfall values at the target station based on the least error measurements. Modified normal ratio based on trimmed mean with geographical coordinate method is found to be the most appropriate method for station Batu Kurau and Sg. Bernam while modified old normal ratio with geographical coordinate is the most accurate in estimating the missing data at station Genting Klang. Penerbit UiTM (UiTM Press) 2016 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/16134/2/16134.pdf Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli. (2016) Scientific Research Journal <https://ir.uitm.edu.my/view/publication/Scientific_Research_Journal/>, 13 (1). pp. 84-97. ISSN 1675-7009 https://srj.uitm.edu.my/ |
| spellingShingle | Data processing Prediction analysis Amin Burhanuddin, Siti Nur Zahrah Mohd Deni, Sayang Mohamed Ramli, Norazan Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli |
| title | Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli |
| title_full | Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli |
| title_fullStr | Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli |
| title_full_unstemmed | Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli |
| title_short | Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli |
| title_sort | revised normal ratio methods for imputation of missing rainfall data siti nur zahrah amin burhanuddin sayang mohd deni and norazan mohamed ramli |
| topic | Data processing Prediction analysis |
| url | https://ir.uitm.edu.my/id/eprint/16134/2/16134.pdf |
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