Heterogeneous climate effect on crop yield and associated risks to water security in India

ABSTRACT

This study uses the Just–Pope approach to investigate the effects of seasonal weather variables and extremes on the mean yield and yield variability of rice, bajra, chickpea, groundnut and sugarcane in India during the period 1990–2015. Results reveal that changes in rainfall and evapotranspiration across seasons largely affect mean yields for most crops, including bajra, chickpea and groundnut. However, high summer rainfall and low monsoon evapotranspiration extremes reduce groundnut and chickpea yield variability. Considering the importance of water availability to crop yields, this study suggests improving irrigation and water reallocation and management to reduce the severity of seasonal climate effects.

KEYWORDS:

• Stochastic frontier analysis
• climate change
• food security
• water management
• India

Acknowledgements

This paper was presented at the Conference on Water Resource Management in Agriculture for Achieving Food and Water Security Under Climate Change in Asia, organized by the Asian Development Bank Institute on October 26-27, 2022. We appreciate the feedback from the conference participants and session discussant Dr Wanglin Ma from Lincoln University. We thank the editor-in-chief and anonymous referees of the journal for their insightful comments. We are also grateful to Dr Saumya Verma from Delhi University, Prof Anuja Tigga from Andhra University, and Dr Dil Rahut and Dr Jeetendra Aryal from the Asian Development Bank Institute for their valuable suggestions that have enhanced the content of this paper. The views, information or opinions expressed in the paper are those of the authors, and the usual disclaimer applies.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

The data that support the findings of this study are available from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) (http://data.icrisat.org/dld/) and Mendeley Data (https://doi.org/10.17632/ywp3y5j9vv.1).

Supplementary material

Supplemental data for this article can be accessed at https://doi.org/10.1080/07900627.2023.2244086.