Abstract
Crop yield has been analyzed under different hydrological conditions by many researchers. However, little information is available about the behavior of rice yield for different conditions during its growth. This study investigated the behavior of rice yield under varying hydrological conditions in two regions of India, one rainfed and the other irrigated, for the period 2000–2018. Additionally, it examined how individual, coincidental, and sequential compound extremes, such as rainfall, temperature, and soil moisture, affected rice yield. Four individual, two coincidental, and two sequential compound extremes regression models were developed. These models were designed with yield as a function of individual and compound extremes. Individual extreme models focused on heat and water metrics independently, while compound extremes occurred when heat and water stress coincided or followed each other closely. Linear panel models were used to assess the dependency of rice yield on hydrological parameters. Results indicate that excessive heat negatively affects rice yield, particularly when coupled with low soil moisture. However, excess soil moisture mitigates heat-related damage, highlighting the significance of controlling soil moisture levels. Additionally, coincidental compound extremes pose greater threats to rice yield than sequential ones. The study underscores the importance of considering geographical variations and hydrological variables in understanding crop yield behaviour. Overall, the findings suggest the potential for optimizing soil moisture management to enhance rice yield amidst changing climatic conditions.
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Abbreviations
- CCE :
-
Compound coincidental extremes
- CCM :
-
Compound coincidental extremes model
- CSE :
-
Compound sequential extremes
- CSM :
-
Compound sequential extremes model
- CSMD :
-
Cumulative soil moisture below normal levels
- CSMN :
-
Cumulative soil moisture above normal levels
- DS :
-
Different stages
- IEM :
-
Individual extremes model
- M :
-
Seasonal mean soil moisture content
- M 2 :
-
Square of season mean soil moisture content
- NDD :
-
Number of days when soil moisture is below normal levels
- NDS :
-
Number of days when soil moisture is above normal levels
- R :
-
Cumulative growing season rainfall
- R 2 :
-
Square of cumulative growing season rainfall
- T max :
-
Daily maximum temperature
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Acknowledgements
The authors would like to thank Swati Kumari for her help in data visualisation and Aditi Babanrao Palve and Swagat Patra for their support in data extraction.
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Anshuman Mishra: Conceptualization, Methodology, Software, Data Curation, Formal analysis, Writing -Original Draft, Visualization.
Litan Kumar Ray: Conceptualisation, Methodology, Supervision, Writing-Reviewing & Editing, Visualization.
V. Manohar Reddy: Conceptualization, Software, Data Curation, Formal analysis, Visualization.
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Key points
1. Developed statistical models for analysing the effect of the individual as well as coincidental and sequential compound extremes on rice yield.
2. Sequential hot and dry days are more damaging to rice yields than simply hot days.
3. Temperature above 35 °C are found to be negatively correlating with the rice yield.
4. Rice yield favours abundant soil moisture above normal soil moisture in the growing season.
5. Damage due to extreme heat on rice yield can be controlled by keeping the soil moisture above the normal soil moisture conditions.
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Mishra, A., Ray, L.K. & Reddy, V.M. Effects of compound hydro-meteorological extremes on rice yield in different cultivation practices in India. Theor Appl Climatol (2024). https://doi.org/10.1007/s00704-024-04894-x
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DOI: https://doi.org/10.1007/s00704-024-04894-x