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Zhou Z, Ding Y, Fu Q, Wang C, Wang Y, Cai H, Liu S, Huang S, Shi H. Insights from CMIP6 SSP scenarios for future characteristics of propagation from meteorological drought to hydrological drought in the Pearl River Basin. Sci Total Environ 2023; 899:165618. [PMID: 37474042 DOI: 10.1016/j.scitotenv.2023.165618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 07/15/2023] [Accepted: 07/16/2023] [Indexed: 07/22/2023]
Abstract
Drought is a common and widely distributed natural hazard. Analyzing and predicting drought characteristics and propagation are important for the early warning, prevention, and mitigation of drought disasters. This study used the precipitation and runoff outputs from General Circulation Models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) to evaluate the meteorological drought (MD) and hydrological drought (HD) characteristics in the Pearl River Basin (PRB) under two Shared Socioeconomic Pathways (SSPs) (i.e., SSP2-4.5 and SSP5-8.5). The propagation characteristics of external propagation (response between different type of drought) and internal propagation (drought development and recovery stages of a single type of drought) were also comprehensively investigated based on CMIP6. The results revealed that: 1) the percentage of grids within the dry range of MD and HD will decrease from the historical period to the future period under the two scenarios. The PRB is projected to exhibit wetter patterns; 2) Higher emission scenarios (SSP5-8.5) are more likely to weaken dryness conditions; 3) regarding the external propagation, the drought response time from MD to HD would be 2 months, and there would be no significant change under two scenarios; and 4) regarding the internal propagation, during three study periods (1971-2010, 2021-2060 and 2061-2100), the MD (HD) average recovery time changed from 3.90 (3.36) to 3.75 (3.41) and then to 3.95 (3.43) months under the SSP2-4.5 scenario, and changed from 3.93 (3.46) to 3 (3.51) and then to 3.7 (3.25) months under the SSP5-8.5 scenario. These results aid in understanding future drought characteristics and drought propagation under climate change.
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Affiliation(s)
- Zhaoqiang Zhou
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China; Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Yibo Ding
- Yellow River Engineering Consulting Co., Ltd., Zhengzhou 450003, China
| | - Qiang Fu
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China
| | - Can Wang
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Yao Wang
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Hejiang Cai
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Department of Civil and Environmental Engineering, National University of Singapore, Singapore
| | - Suning Liu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Shengzhi Huang
- State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, China
| | - Haiyun Shi
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
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