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Climatic Change

, Volume 147, Issue 3–4, pp 601–615 | Cite as

Probabilistic assessment of projected climatological drought characteristics over the Southeast USA

  • Subhasis Mitra
  • Puneet Srivastava
  • Jasmeet Lamba
Article

Abstract

The study makes a probabilistic assessment of drought risks due to climate change over the southeast USA based on 15 Global Circulation Model (GCM) simulations and two emission scenarios. The effects of climate change on drought characteristics such as drought intensity, frequency, areal extent, and duration are investigated using the seasonal and continuous standard precipitation index (SPI) and the standard evapotranspiration index (SPEI). The GCM data are divided into four time periods namely Historical (1961–1990), Near (2010–2039), Mid (2040–2069), and Late (2070–2099), and significant differences between historical and future time periods are quantified using the mapping model agreement technique. Further, the kernel density estimation approach is used to derive a novel probability-based severity-area-frequency (PBS) curve for the study domain. Analysis suggests that future increases in temperature and evapotranspiration will outstrip increases in precipitation and significantly affect future droughts over the study domain. Seasonal drought analysis suggest that the summer season will be impacted the most based on SPI and SPEI. Projections based on SPI follow precipitation patterns and fewer GCMs agree on SPI and the direction of change compared to the SPEI. Long-term and extreme drought events are projected to be affected more than short-term and moderate ones. Based on an analysis of PBS curves, especially based on SPEI, droughts are projected to become more severe in the future. The development of PBS curves is a novel feature in this study and will provide policymakers with important tools for analyzing future drought risks, vulnerabilities and help build drought resilience. The PBS curves can be replicated for studies around the world for drought assessment under climate change.

Keywords

Droughts GCM Kernel density estimator Probability-based SAF curves Southeast USA 

Notes

Acknowledgements

The authors wish to acknowledge the funding provided by the National Integrated Drought Information System (NIDIS) and the Alabama Agricultural Experiment Station for this study.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10584_2018_2161_MOESM1_ESM.docx (32 kb)
ESM 1 (DOCX 32.4 kb)
10584_2018_2161_MOESM2_ESM.docx (5.3 mb)
ESM 2 (DOCX 5.27 mb)
10584_2018_2161_MOESM3_ESM.docx (37 kb)
ESM 3 (DOCX 37.4 kb)

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Civil Engineering DepartmentIndian Institute of Technology PalakkadKozhiparaIndia
  2. 2.Biosystems EngineeringAuburn UniversityAuburnUSA

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