Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China
Study region: Yuan River Basin in China. Study focus: This study aims to identify temporal variations and non-stationarity in the annual maximum Peak Flow (PF) and Peak Water Level (PWL) series, along with their occurrence dates and intervals series at three stations (Anjiang, Pushi, and Taoyuan). T...
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Elsevier
2025-02-01
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| Series: | Journal of Hydrology: Regional Studies |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581824004804 |
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| author | Ting Wang Dehua Mao Meirong Deng Chang Feng Guangwei Hu Jingya Zhang Yang Zou |
| author_facet | Ting Wang Dehua Mao Meirong Deng Chang Feng Guangwei Hu Jingya Zhang Yang Zou |
| author_sort | Ting Wang |
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| description | Study region: Yuan River Basin in China. Study focus: This study aims to identify temporal variations and non-stationarity in the annual maximum Peak Flow (PF) and Peak Water Level (PWL) series, along with their occurrence dates and intervals series at three stations (Anjiang, Pushi, and Taoyuan). Temporal variations were detected and non-stationary models were developed by incorporating physically-based covariates under climate change and human activities using the Mann-Kendall test, Pettitt test, and the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework. New hydrological insights for the region: (1) The intervals between Pushi and Taoyuan stations for both PF and PWL series have significantly shortened over the past 40 years, while the Taoyuan station showed no significant upward trend over the past 70 years. (2) Covariates associated with precipitation, Normalized Difference Vegetation Index (NDVI), Reservoir Index, and Impervious Area (IA) showed a significantly increased trend within the basin, particularly the annual maximum daily precipitation (P1) at the Pushi station. (3) The non-stationary models performed best when incorporating either the 7-day or 15-day accumulated antecedent precipitation before the flood occurrence date for the flood extremes series, while the inclusion of the IA and mean NDVI three months before the flood occurrence month provided superior fitting for the occurrence dates series. (4) The variability of P1, 3-day accumulated precipitation and their overlap with 7-day and 15-day accumulated precipitation were most likely key factors in triggering typical flood extremes. |
| format | Article |
| id | doaj-art-dd8744f4e7aa48a48effeb9c82410e46 |
| institution | Kabale University |
| issn | 2214-5818 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj-art-dd8744f4e7aa48a48effeb9c82410e462025-01-22T05:42:09ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-02-0157102131Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, ChinaTing Wang0Dehua Mao1Meirong Deng2Chang Feng3Guangwei Hu4Jingya Zhang5Yang Zou6School of Geographic Sciences, Hunan Normal University, Changsha 410081, ChinaSchool of Geographic Sciences, Hunan Normal University, Changsha 410081, China; Hunan Provincial Key Laboratory for Eco-environmental Changes and Carbon Sequestration of the Dongting Lake Basin, Changsha 410081, China; Corresponding author at: School of Geographic Sciences, Hunan Normal University, Changsha 410081, China.School of Geographic Sciences, Hunan Normal University, Changsha 410081, China; Hunan Provincial Key Laboratory for Eco-environmental Changes and Carbon Sequestration of the Dongting Lake Basin, Changsha 410081, China; College of Geography and Tourism, Hengyang Normal University, Hengyang 421002, ChinaCollege of Geography and Tourism, Hengyang Normal University, Hengyang 421002, ChinaSchool of Economics and Management, Economic research institute, Dali University, Dali 671003, ChinaSchool of Geographic Sciences, Hunan Normal University, Changsha 410081, China; Hunan Provincial Key Laboratory for Eco-environmental Changes and Carbon Sequestration of the Dongting Lake Basin, Changsha 410081, ChinaSchool of Geographic Sciences, Hunan Normal University, Changsha 410081, ChinaStudy region: Yuan River Basin in China. Study focus: This study aims to identify temporal variations and non-stationarity in the annual maximum Peak Flow (PF) and Peak Water Level (PWL) series, along with their occurrence dates and intervals series at three stations (Anjiang, Pushi, and Taoyuan). Temporal variations were detected and non-stationary models were developed by incorporating physically-based covariates under climate change and human activities using the Mann-Kendall test, Pettitt test, and the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework. New hydrological insights for the region: (1) The intervals between Pushi and Taoyuan stations for both PF and PWL series have significantly shortened over the past 40 years, while the Taoyuan station showed no significant upward trend over the past 70 years. (2) Covariates associated with precipitation, Normalized Difference Vegetation Index (NDVI), Reservoir Index, and Impervious Area (IA) showed a significantly increased trend within the basin, particularly the annual maximum daily precipitation (P1) at the Pushi station. (3) The non-stationary models performed best when incorporating either the 7-day or 15-day accumulated antecedent precipitation before the flood occurrence date for the flood extremes series, while the inclusion of the IA and mean NDVI three months before the flood occurrence month provided superior fitting for the occurrence dates series. (4) The variability of P1, 3-day accumulated precipitation and their overlap with 7-day and 15-day accumulated precipitation were most likely key factors in triggering typical flood extremes.http://www.sciencedirect.com/science/article/pii/S2214581824004804Climate changeFlood non-stationarityGAMLSSHuman activitiesPhysically-based covariatesYuan River Basin |
| spellingShingle | Ting Wang Dehua Mao Meirong Deng Chang Feng Guangwei Hu Jingya Zhang Yang Zou Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China Journal of Hydrology: Regional Studies Climate change Flood non-stationarity GAMLSS Human activities Physically-based covariates Yuan River Basin |
| title | Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China |
| title_full | Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China |
| title_fullStr | Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China |
| title_full_unstemmed | Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China |
| title_short | Non-stationarity analysis of flood extremes under climate change and human activities in the Yuan River Basin, China |
| title_sort | non stationarity analysis of flood extremes under climate change and human activities in the yuan river basin china |
| topic | Climate change Flood non-stationarity GAMLSS Human activities Physically-based covariates Yuan River Basin |
| url | http://www.sciencedirect.com/science/article/pii/S2214581824004804 |
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