Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model
Study region: The Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. Study focus: Using hourly rain gauge data and CMORPH data, we use the duration-dependent generalized extreme value (d-GEV) model and the scaling invariant GEV model inferred by the Bayesian hierarchical model to derive the in...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581823000149 |
| _version_ | 1797867697841635328 |
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| author | Xuezhi Tan Qiying Mai Guixing Chen Bingjun Liu Zhaoli Wang Chengguang Lai Xiaohong Chen |
| author_facet | Xuezhi Tan Qiying Mai Guixing Chen Bingjun Liu Zhaoli Wang Chengguang Lai Xiaohong Chen |
| author_sort | Xuezhi Tan |
| collection | DOAJ |
| description | Study region: The Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. Study focus: Using hourly rain gauge data and CMORPH data, we use the duration-dependent generalized extreme value (d-GEV) model and the scaling invariant GEV model inferred by the Bayesian hierarchical model to derive the intensity-duration-frequency IDF characteristics of extreme precipitation in GBA and adjust their uncertainties. New hydrological insights for the region: The GEV location and scale parameters of IDF curves in GBA show similar spatial distribution and the higher-resolution CMORPH can capture more local details than rain gauge data. Meanwhile, compared with the rain gauge data, CMORPH produces significantly lower rainfall intensity of storms with short durations, which leads to large uncertainties of IDF curves derived from CMORPH for the short-duration rainfall. Additionally, the uncertainties of IDF curves can be substantially reduced by using the scaling invariant model that was inferred by the Bayesian hierarchical model, compared with the ordinary d-GEV method. Therefore, the Bayesian inference is suggested to be adopted for regional estimation of IDF curves, especially for regions of limited sub-daily gauge data. |
| first_indexed | 2024-04-09T23:44:18Z |
| format | Article |
| id | doaj.art-ea4c1f441b274285a1f51378458418ed |
| institution | Directory Open Access Journal |
| issn | 2214-5818 |
| language | English |
| last_indexed | 2024-04-09T23:44:18Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj.art-ea4c1f441b274285a1f51378458418ed2023-03-18T04:41:11ZengElsevierJournal of Hydrology: Regional Studies2214-58182023-04-0146101327Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical modelXuezhi Tan0Qiying Mai1Guixing Chen2Bingjun Liu3Zhaoli Wang4Chengguang Lai5Xiaohong Chen6Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, PR China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, PR China; Corresponding author at: Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, PR China.Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, PR ChinaSchool of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou 510275, PR China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, PR ChinaCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, PR ChinaSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, PR ChinaSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, PR ChinaCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, PR ChinaStudy region: The Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. Study focus: Using hourly rain gauge data and CMORPH data, we use the duration-dependent generalized extreme value (d-GEV) model and the scaling invariant GEV model inferred by the Bayesian hierarchical model to derive the intensity-duration-frequency IDF characteristics of extreme precipitation in GBA and adjust their uncertainties. New hydrological insights for the region: The GEV location and scale parameters of IDF curves in GBA show similar spatial distribution and the higher-resolution CMORPH can capture more local details than rain gauge data. Meanwhile, compared with the rain gauge data, CMORPH produces significantly lower rainfall intensity of storms with short durations, which leads to large uncertainties of IDF curves derived from CMORPH for the short-duration rainfall. Additionally, the uncertainties of IDF curves can be substantially reduced by using the scaling invariant model that was inferred by the Bayesian hierarchical model, compared with the ordinary d-GEV method. Therefore, the Bayesian inference is suggested to be adopted for regional estimation of IDF curves, especially for regions of limited sub-daily gauge data.http://www.sciencedirect.com/science/article/pii/S2214581823000149Extreme precipitationIntensity-duration-frequency curvesDuration-dependent GEVScaling invariantBayesian hierarchical model |
| spellingShingle | Xuezhi Tan Qiying Mai Guixing Chen Bingjun Liu Zhaoli Wang Chengguang Lai Xiaohong Chen Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model Journal of Hydrology: Regional Studies Extreme precipitation Intensity-duration-frequency curves Duration-dependent GEV Scaling invariant Bayesian hierarchical model |
| title | Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model |
| title_full | Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model |
| title_fullStr | Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model |
| title_full_unstemmed | Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model |
| title_short | Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model |
| title_sort | intensity duration frequency curves in the guangdong hong kong macao greater bay area inferred from the bayesian hierarchical model |
| topic | Extreme precipitation Intensity-duration-frequency curves Duration-dependent GEV Scaling invariant Bayesian hierarchical model |
| url | http://www.sciencedirect.com/science/article/pii/S2214581823000149 |
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