Investigating seasonal drought severity-area-frequency (SAF) curve over Indian region: incorporating GCM and scenario uncertainties
Autor: | Jew Das, Umamahesh V. Nanduri, Subhadarsini Das |
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Rok vydání: | 2021 |
Předmět: |
Environmental Engineering
Atmospheric circulation Kharif crop fungi Magnitude (mathematics) GCM transcription factors Monsoon Climatology Evapotranspiration Environmental Chemistry Environmental science Precipitation Safety Risk Reliability and Quality General Environmental Science Water Science and Technology |
Zdroj: | Stochastic Environmental Research and Risk Assessment. 36:1597-1614 |
ISSN: | 1436-3259 1436-3240 |
DOI: | 10.1007/s00477-021-02073-2 |
Popis: | Understanding the devastating nature of drought, this work has assessed the variability in the Severity-Area-Frequency (SAF) curve using Standardised Precipitation Evapotranspiration Index (SPEI) as meteorological drought indicator over Maharashtra, India. The future meteorological outputs from 19 Global Circulation Models (GCMs) of the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) under two Representative Concentration Pathway (RCP) 4.5 and 8.5 are used. The SAF curves are developed for five different seasons namely pre-monsoon, monsoon, post-monsoon, Kharif and Rabi. The uncertainty associated with GCMs and scenarios is assessed using possibility theory. The results reveal that the precipitation magnitude is expected to increase in pre-monsoon, monsoon, and Kharif seasons over most of the areas in Maharashtra. However, the temperature is likely to increase during all the seasons in future. The frequency of extreme drought condition during post-monsoon, pre-monsoon, and Rabi seasons shows an increment as compared to historical period. The Rabi season drought is noticed to be most pronounced and likely to affect significant portions of Maharashtra during all return periods. The SAF curve reveals that, in most of the cases, the percentage of drought affected area is expected to increase for high magnitude of severity. |
Databáze: | OpenAIRE |
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