Abstract
Drought depends upon many factors such as lack of precipitation, sunshine duration, and altitude. In this study, future rainfall trend pattern was studied, and an attempt was made to quantify the amount of rainfall deficit to cause drought occurrence and corresponding required water for the recovery of future drought. The non-standardized anomaly index (AI) was used to quantify the water deficit for future drought event, which is based on CMIP 6 climatic model generated rainfall data under the four different shared socioeconomic pathways’ (SSPs) scenarios (SSP 1–2.6, SSP 2–4.5, SSP 3–7.0, and SSP 5–8.5) for the chosen study area (the upper Tapti River basin in central India). Our study found out that the future rainfall pattern would be an increasing trend for all the SSPs scenarios up to the end of the twenty-first century. Particularly, SSP 5–8.5 scenario projected increasing rainfall pattern and more number of drought events than other SSPs. In specific season, the future monsoon season showed more number of drought events. The water required for drought recovery was found increased from SSP 1–2.6 to SSP 5–8.5 scenario. The results presented in this study are helpful to adopt drought management activity in response to changing rainfall pattern under climate change aspect.
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Data availability
The raw GCM data available in online on the World Climate Research Programme (WCRP) climate data portal (https://esgf-node.llnl.gov/search/cmip6/) and bias corrected future rainfall data obtained from the website (https://zenodo.org/record/3874046#.YOQWg0kzZPa). The observed data was procured from IMD in grid format.
Code availability
The authors have used MATLAB program which has been written by Simone Fatichi (https://www.mathworks.com/matlabcentral/fileexchange/25533-mann-kendall-modified-test) for trend analysis. Besides, customized MATLAB scripts were used for generation of figures and copula analysis.
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Acknowledgements
The authors are grateful to the Indian Agricultural Research Institute, New Delhi, for needful funding on the research work and also to the Professor and Director, ICAR-Central Institute of Agricultural Engineering, Bhopal for facilitating the software requirement such as ArcGIS and MATLAB, besides other infrastructural facilities. Further, we acknowledge the India Meteorological Department (IMD), World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6 and Mishra et al. (2020) for data availability.
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This manuscript is a part of the PhD research work of the 1st author (P.Kanthavel). The conceptualization, planning, and development of methodology as well has initial framing of this paper were made by the first author. The second author (Dr. Chandra Kant Saxena) and the third author (Dr. Ranjay Kumar Singh) are the guide (promoter) and co-guide (co-promoter), respectively. Both of them have supervised the work right from conceptualization till the writing of this reply of review. All authors have discussed the results and edited the manuscript.
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Kanthavel, P., Saxena, C.K. & Singh, R.K. Identification of water requirement to ameliorate future drought events: approach with CMIP6 climatic models. Theor Appl Climatol 155, 105–116 (2024). https://doi.org/10.1007/s00704-023-04594-y
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DOI: https://doi.org/10.1007/s00704-023-04594-y