Staff View: Comparative Analyses on Disaggregation Methods for the Rainfall Projection

Comparative Analyses on Disaggregation Methods for the Rainfall Projection

Climate modeling data are typically available in the daily climate time series for a particular year of observation. However, studies for urban drainage and stormwater management require rainfall data on sub-daily time scales for design such as the development of IDF curves. Most hydrological studie...

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Main Authors:	Wan Amirul Syahmi, Wan Mazlan, Nurul Nadrah Aqilah, Tukimat
Format:	Article
Language:	English English
Published:	Springer 2023
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/38250/1/2a.%20Comparative%20Analyses%20on%20Disaggregation%20Methods%20for%20the%20Rainfall%20Projection.pdf http://umpir.ump.edu.my/id/eprint/38250/2/Comparative%20Analyses%20on%20Disaggregation%20Methods.pdf http://umpir.ump.edu.my/id/eprint/38250/ https://doi.org/10.1007/s11269-023-03546-5
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id	my.ump.umpir.38250
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spelling	my.ump.umpir.382502023-08-07T03:22:21Z http://umpir.ump.edu.my/id/eprint/38250/ Comparative Analyses on Disaggregation Methods for the Rainfall Projection Wan Amirul Syahmi, Wan Mazlan Nurul Nadrah Aqilah, Tukimat T Technology (General) TA Engineering (General). Civil engineering (General) Climate modeling data are typically available in the daily climate time series for a particular year of observation. However, studies for urban drainage and stormwater management require rainfall data on sub-daily time scales for design such as the development of IDF curves. Most hydrological studies dealing with the impacts of climate change are particularly challenging due to this explicit requirement. Therefore, this study aims to establish more accurate disaggregation methods for constructing hourly rainfall under the projected climate scenarios. Three disaggregation methods with different theoretical underpinnings have been evaluated: Scaling Properties (SP), Indian Reduction Formula (IRF), and Stochastic Method (SM). The results show that the SP method generally outperforms the other methods based on statistical analyses and comparisons of statistical properties with historical data. The SP method performs well by having the lowest RMSE and percentage difference values across all rainfall stations. Moreover, the hourly mean and standard deviation of disaggregated rainfall from the SP method correspond well to the historical data. The projected rainfall data from 2025 to 2100 were obtained from the MRI-ESM2-0 model and disaggregated from daily-time to hourly-time series using the SP method. In general, the SSP5-8.5 scenario showed the highest projected rainfall compared with the other scenarios. Springer 2023-08 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/38250/1/2a.%20Comparative%20Analyses%20on%20Disaggregation%20Methods%20for%20the%20Rainfall%20Projection.pdf pdf en http://umpir.ump.edu.my/id/eprint/38250/2/Comparative%20Analyses%20on%20Disaggregation%20Methods.pdf Wan Amirul Syahmi, Wan Mazlan and Nurul Nadrah Aqilah, Tukimat (2023) Comparative Analyses on Disaggregation Methods for the Rainfall Projection. Water Resources Management, 37 (10). pp. 4195-4209. ISSN 0920-4741 (print); 1573-1650 (online). (Published) https://doi.org/10.1007/s11269-023-03546-5 10.1007/s11269-023-03546-5
institution	Universiti Malaysia Pahang
building	UMP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang
content_source	UMP Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	T Technology (General) TA Engineering (General). Civil engineering (General)
spellingShingle	T Technology (General) TA Engineering (General). Civil engineering (General) Wan Amirul Syahmi, Wan Mazlan Nurul Nadrah Aqilah, Tukimat Comparative Analyses on Disaggregation Methods for the Rainfall Projection
description	Climate modeling data are typically available in the daily climate time series for a particular year of observation. However, studies for urban drainage and stormwater management require rainfall data on sub-daily time scales for design such as the development of IDF curves. Most hydrological studies dealing with the impacts of climate change are particularly challenging due to this explicit requirement. Therefore, this study aims to establish more accurate disaggregation methods for constructing hourly rainfall under the projected climate scenarios. Three disaggregation methods with different theoretical underpinnings have been evaluated: Scaling Properties (SP), Indian Reduction Formula (IRF), and Stochastic Method (SM). The results show that the SP method generally outperforms the other methods based on statistical analyses and comparisons of statistical properties with historical data. The SP method performs well by having the lowest RMSE and percentage difference values across all rainfall stations. Moreover, the hourly mean and standard deviation of disaggregated rainfall from the SP method correspond well to the historical data. The projected rainfall data from 2025 to 2100 were obtained from the MRI-ESM2-0 model and disaggregated from daily-time to hourly-time series using the SP method. In general, the SSP5-8.5 scenario showed the highest projected rainfall compared with the other scenarios.
format	Article
author	Wan Amirul Syahmi, Wan Mazlan Nurul Nadrah Aqilah, Tukimat
author_facet	Wan Amirul Syahmi, Wan Mazlan Nurul Nadrah Aqilah, Tukimat
author_sort	Wan Amirul Syahmi, Wan Mazlan
title	Comparative Analyses on Disaggregation Methods for the Rainfall Projection
title_short	Comparative Analyses on Disaggregation Methods for the Rainfall Projection
title_full	Comparative Analyses on Disaggregation Methods for the Rainfall Projection
title_fullStr	Comparative Analyses on Disaggregation Methods for the Rainfall Projection
title_full_unstemmed	Comparative Analyses on Disaggregation Methods for the Rainfall Projection
title_sort	comparative analyses on disaggregation methods for the rainfall projection
publisher	Springer
publishDate	2023
url	http://umpir.ump.edu.my/id/eprint/38250/1/2a.%20Comparative%20Analyses%20on%20Disaggregation%20Methods%20for%20the%20Rainfall%20Projection.pdf http://umpir.ump.edu.my/id/eprint/38250/2/Comparative%20Analyses%20on%20Disaggregation%20Methods.pdf http://umpir.ump.edu.my/id/eprint/38250/ https://doi.org/10.1007/s11269-023-03546-5
_version_	1773543703722328064
score	13.211869

Comparative Analyses on Disaggregation Methods for the Rainfall Projection

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