Anthropogenic forcing decreases the probability of the 2020 Yangtze River extreme flood and future risk

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Xiao Li , Liping Zhang , Gangsheng Wang , Hui Cao , Hairong Zhang , Benjun Jia , Zhiling Zhou , Lina Liu , Lu Zhang
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引用次数: 0

Abstract

The Yangtze River basin experienced extreme flooding during the summer of 2020, leading to widespread impact and significant economic losses. However, there is a lack of specific and quantitative anthropogenic attribution analysis. Here, we used the VIC model and the Risk Ratio framework to isolate the contributions of two anthropogenic (ANT) forcings, aka greenhouse gas (GHG) and aerosol (AER), to this event and the associated potential risk. We also assessed future risk by employing projections from four simulations under the SSP2–4.5 scenario in 2041–2100. Our findings reveal that ANT forcing reduces the probability by 74 %, while GHG forcing increase it by 6 %, and AER forcing decreases it by 92 % at the downstream Datong station. At the middle-stream Cuntan station, ANT forcing decreases the probability of extreme floodings similar to the 2020 event by 87 %, while GHG forcing decreases it by 82 %, and AER forcing decreases it by 95 %. In the future period under the SSP2–4.5 scenario, ANT forcing reduces the probability of extreme flood events like 2020 by 78 % and 82 % at the Cuntan and Datong stations, respectively. And The GHG and AER forcings contribute positively and negatively to the probability of flooding in the Yangtze River Basin, respectively, mainly through influencing the probability of extreme precipitation and potential evapotranspiration. Our study provides valuable insights for policymakers to comprehend the anthropogenic influence on extreme flooding and to guide effective risk management strategies.

Plain language summary

The Yangtze River basin experienced severe flooding in the summer of 2020, but there is no specific and quantitative anthropogenic attribution analysis yet. Therefore, we performed an attribution analysis using the hydrological model and global climate models to isolate the anthropogenic (ANT) contribution for the 1961–2020 and 2041–2100 periods. We find that ANT forcing decreases the risk of extreme flooding, similar to the 2020 event, at the middle-stream Cuntan station and the downstream Datong station. In the future, ANT forcing significantly reduces the probability of potential extreme flood events in both stations. Additionally, we discovered that the net effect of ANT forcing on extreme flood events is determined by the counterbalance of anthropogenic greenhouse gas and aerosol forcings. Our study aims to help policymakers gain a better understanding of the human impact on extreme flooding and develop effective risk management strategies.

人为因素降低了 2020 年长江特大洪水的概率和未来风险
2020 年夏季,长江流域发生特大洪水,造成广泛影响和重大经济损失。然而,目前还缺乏具体和定量的人为因素归因分析。在此,我们利用 VIC 模型和风险比框架,分离出温室气体(GHG)和气溶胶(AER)这两种人为(ANT)影响因素对此次事件的贡献以及相关的潜在风险。我们还利用 2041-2100 年 SSP2-4.5 情景下的四次模拟预测评估了未来风险。我们的研究结果表明,在下游的大同站,ANT 迫力将概率降低了 74%,温室气体迫力将概率提高了 6%,而 AER 迫力将概率降低了 92%。在中游的寸滩站,ANT 迫力使类似 2020 年的极端洪水发生概率降低了 87%,温室气体迫力使其降低了 82%,AER 迫力使其降低了 95%。在未来 SSP2-4.5 情景下,ANT 迫力可将寸滩站和大同站发生类似 2020 年极端洪水事件的概率分别降低 78% 和 82%。而温室气体和AER强迫分别对长江流域的洪水发生概率有正和负的影响,主要是通过影响极端降水概率和潜在蒸散量。我们的研究为政策制定者理解人为因素对极端洪水的影响并指导有效的风险管理策略提供了有价值的见解。因此,我们利用水文模型和全球气候模型进行了归因分析,以分离 1961-2020 年和 2041-2100 年期间的人为(ANT)贡献。我们发现,ANT 迫力降低了中游寸滩站和下游大同站的特大洪水风险,与 2020 年事件类似。在未来,ANT 强化将大大降低这两个站点发生潜在极端洪水事件的概率。此外,我们还发现,ANT 迫力对极端洪水事件的净影响取决于人为温室气体和气溶胶迫力的平衡。我们的研究旨在帮助决策者更好地了解人类对极端洪水的影响,并制定有效的风险管理战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
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