Future global concurrent droughts and their effects on maize yield

Droughts are one of the most devastating natural disasters. Droughts can co-exist in different forms (e.g. meteorological, hydrological, and agricultural) as concurrent droughts. Such concurrent droughts can have far reaching implications for crop yield and global food security. The present study ai...

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Vydané v:The Science of the total environment Ročník 855; s. 158860
Hlavní autori: Muthuvel, Dineshkumar, Sivakumar, Bellie, Mahesha, Amai
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 10.01.2023
Predmet:
basins
Brazil
Central America
Climate change
CMIP6
Compound drought
Copula
corn
crop yield
drought
environment
food security
France
Mexico
Multivariate standardized drought index
runoff
soil water
Southern Africa
time series analysis
Brazil
Central America
Mexico
France
Southern Africa
Climate change
CMIP6
Compound drought
Copula
Multivariate standardized drought index
ISSN:0048-9697, 1879-1026, 1879-1026
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Shrnutí:Droughts are one of the most devastating natural disasters. Droughts can co-exist in different forms (e.g. meteorological, hydrological, and agricultural) as concurrent droughts. Such concurrent droughts can have far reaching implications for crop yield and global food security. The present study aims to assess global concurrent drought traits and their effects on maize yield under climate change. The standardized indices of precipitation, runoff, and soil moisture incorporated as multivariate standardized drought index (MSDI) using copula functions are used to quantify the concurrent droughts. The ensemble data of several General Circulation Models (GCMs) considering the high emission scenario of Coupled Model Intercomparison Project phase 6 (CMIP6) are utilized. Applying run theory on a time series (1950–2100) of MSDI values, the duration, severity, areal coverage, and average areal intensity of concurrent droughts are computed. The temporal evolution of drought duration and severity are compared among historical (1950–2014), near future (2021–2060), and far future (2061–2100) timeframes. The results indicate that the most vulnerable regions in the late 21st century are Central America, the Mediterranean, Southern Africa, and the Amazon basin. The indices and spatial extent of the individual droughts are used as predictor variables to predict the country-level crop index of the top seven producers of maize. The historical dynamics between maize yield and different drought forms are projected using XGBoost (Extreme Gradient Boosting) algorithms. The future temporal changes in drought-crop yield dynamics are tracked using probabilities of various drought forms under yield-loss conditions. The conditional concurrent drought probabilities are as high as 84 %, 64 %, and 37 % in France, Mexico, and Brazil, revealing that concurrent drought affects the maize yield tremendously in the far future. This approach of applying statistical and soft-computing techniques could aid in drought mitigation under changing climatic conditions. [Display omitted] •A copula-based approach is adopted to quantify global future concurrent droughts.•Concurrent drought duration, severity, spatial extent, and intensity are measured.•The Amazon, Central America, and the Mediterranean regions will be the most affected.•The XGBoost algorithm performs well in forecasting drought-maize yield dynamics.•Severe concurrent droughts could hamper maize yield in Mexico, France, and Brazil.
Bibliografia:ObjectType-Article-1
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ISSN:0048-9697
1879-1026
1879-1026
DOI:10.1016/j.scitotenv.2022.158860