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Global terrestrial drought and its projected socioeconomic implications under different warming targets.
He, Nan; Yin, Jiabo; Slater, Louise J; Liu, Rutong; Kang, Shengyu; Liu, Pan; Liu, Dedi; Xiong, Lihua.
Afiliação
  • He N; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China.
  • Yin J; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China. Electronic address: jboyn@whu.edu.cn.
  • Slater LJ; School of Geography and the Environment, University of Oxford, Oxford, UK.
  • Liu R; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China.
  • Kang S; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China.
  • Liu P; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China.
  • Liu D; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China.
  • Xiong L; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, PR China.
Sci Total Environ ; 946: 174292, 2024 Jul 02.
Article em En | MEDLINE | ID: mdl-38960192
ABSTRACT
Droughts are increasingly frequent as the Earth warms, presenting adaptation challenges for ecosystems and human communities worldwide. A strategic environmental assessment (SEA) and the integration of adaptation strategies into policies, plans, and programs (PPP) are two important approaches for enhancing climate resilience and fostering sustainable development. This study developed an innovative approach to strengthen the SEA of droughts by quantifying the impacts of future temperature increases. A novel method for projecting drought events was integrated into the SEA process by leveraging multiple data sources, including atmospheric reanalysis, reconstructions, satellite-based observations, and model simulations. We identified drought conditions using terrestrial water storage (TWS) anomalies and applied a random forest (RF) model for disentangling the drivers behind drought events. We then set two global warming targets (2.0 °C and 2.5 °C) and analyzed drought changes under three shared socioeconomic pathways (SSP126, SSP370, SSP585). In a 2.0 °C warming world, over 50 % of the global surface will face increased drought risk. With an additional 0.5 °C increase, >60 % of the land will be prone to further drought escalation. We utilized copulas to build the joint distribution for drought duration and severity, estimating the joint return periods (JRP) for bivariate drought hazard. In tropical and subtropical regions, JRP reductions exceeding half are projected for >33 % of the regional land surface under 2.0 °C warming and for >50 % under 2.5 °C warming. Finally, we projected the impacts of drought events on population and gross domestic product (GDP). Among the three SSPs, under SSP370, population exposure is highest and GDP exposure is minimal under 2.0 °C warming. Global GDP and population risks from drought are projected to increase by 37 % and 24 %, respectively, as warming continues. This study enhances the accuracy of SEA in addressing drought risks and vulnerabilities, supporting climate-resilient planning and adaptive strategies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article