Oh H, Kim HJ, Mehboob MS, Kim J, Kim Y. Sources and uncertainties of future global drought risk with ISIMIP2b climate scenarios and socioeconomic indicators.
THE SCIENCE OF THE TOTAL ENVIRONMENT 2023;
859:160371. [PMID:
36414061 DOI:
10.1016/j.scitotenv.2022.160371]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
The severity of potential drought impacts is influenced not only by physical characteristics, such as precipitation, soil moisture, and temperature but also by local socioeconomic conditions that influence a region's exposure and vulnerability. This study aims to demonstrate projected future global drought risk, which is quantified based on indicators representing three risk components, namely, hazard, exposure, and vulnerability. Drought hazard is evaluated using the standardized precipitation-evapotranspiration index. Drought exposure considers population and agricultural land use, and drought vulnerability accounts for gross domestic product, total water storage, and water consumption. This global-scale study was conducted for the historical and future periods of 1975-2005 and 2070-2099, respectively, and employed three combined scenarios consisting of Representative Concentration Pathways (RCPs) and Shared Socioeconomic Pathways (SSPs) with datasets from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). To evaluate the proposed approach, the results obtained for the historical period were compared with drought records. The projections suggest that in addition to increasing drought hazards caused by climate change, populous regions, or areas heavily dependent on agriculture are at a higher risk than other regions because of high water consumption levels. The contributions analysis indicates that agricultural land use is the largest contributor to drought risk, except for Africa, where the population makes the largest contribution. Model uncertainty of the General Circulation Models (GCMs) and Hydrological Models (HMs) is dominant compared to the RCP and SSP scenarios, with uncertainty from the GCMs the most dominant. This study provides possible depictions and their uncertainties of future drought risks and can assist decision-makers in developing better adaptation and mitigation strategies for climatic, environmental, and socioeconomic changes.
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