Abstract
Wheat is an important food security crop supporting the livelihood of a large population across the world. Though climatic change has been affecting wheat yields globally, the detailed study on the historical climatic impacts on wheat yield in India is mostly missing. There are two approaches to assess the climatic impacts on crop yields: process-based models, and statistical models. The present manuscript investigates the historical climatic impacts on wheat yield in India using a statistical modeling approach. Fifty years of wheat yield and climate data (panel data comprising 175 Indian districts) were fitted in the six statistical models over the periods 1966–2015, 1966–75, 1976–85, 1986–95, 1996–05, and 2006–15. We found that (1) minimum and maximum temperatures have impacted wheat yield negatively in almost all the periods (except during 1966–75 and 1996–05 for maximum temperature). The estimated regression coefficients demonstrating the effect of minimum and maximum temperatures on wheat yield were − 43.74 kg/ha per °C (p < 0.001) and − 101.80 kg/ha per °C (p < 0.001) during 1966–15. (2) Precipitation and wet days did not impact wheat yield significantly during 1966–2015, but affected wheat yields negatively during 1996–05, and positively during 1976–85 and 1986–95. (3) Potential evapotranspiration and vapor pressure have impacted wheat yield negatively in almost all the periods (except during 1966–75 and 1996–05 for potential evapotranspiration). The estimated regression coefficients demonstrating the effect of potential evapotranspiration and vapor pressure on wheat yield were − 75.12 kg/ha per cm/day (p < 0.001) and − 49.98 kg/ha per hPa (p < 0.001) during 1966–2015. Our research findings highlight that temperatures, potential evapotranspiration, and vapor pressure have a more profound negative impact on wheat yield as compared to precipitation and wet days. This detailed analysis of historical climatic impacts on wheat yield is the first step towards achieving the bigger goal of identifying and recommending appropriate mitigation strategies. The results of this study are highly relevant for planners and policymakers in India and globally.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aggarwal PK (2008) Global climate change and Indian agriculture: impacts, adaptation and mitigation. Indian J Agric Sci 78(11):0019–5022
Asseng S, Foster I, Turner NC (2011) The impact of temperature variability on wheat yields. Glob Change Biol 17:997–1012. https://doi.org/10.1111/j.1365-2486.2010.02262.x
Asseng S, Zhu Y, Wang E, Zhang W (2015) Chapter 20—crop modeling for climate change impact and adaptation. In: Sadras VO, Calderini DF (eds) Crop physiology, 2nd edn. Elsevier, pp 505–546. https://doi.org/10.1016/B978-0-12-417104-6.00020-0
Auffhammer M, Schlenker W (2014) Empirical studies on agricultural impacts and adaptation. Energy Econ 46:555–561
Basha G, Kishore P, Ratnam MV et al (2017) Historical and projected surface temperature over India during the 20th and 21st century. Sci Rep 7:2987. https://doi.org/10.1038/s41598-017-02130-3
De Wit CT (1965) Photosynthesis of leaf canopies. Agric Res Rep. https://doi.org/10.2172/4289474
Dell M, Jones BF, Olken BA (2014) What do we learn from the weather? The new climate-economy literature. J Econ Lit 52:740–798. https://doi.org/10.1257/jel.52.3.740
Duncan JMA, Saikia SD, Gupta N, Biggs EM (2016) Observing climate impacts on tea yield in Assam, India. Appl Geogr 77:64–71. https://doi.org/10.1016/j.apgeog.2016.10.004
FAOSTAT (2018) FAOSTAT agricultural data. https://www.fao.org/faostat/en. Accessed 5 Mar 2020
Hsiang SM (2016) Climate econometrics. National bureau of economic research, 1050 Massachusetts Avenue, Cambridge, MA 02138. https://www.nber.org/papers/w22181. Accessed 25 Apr 2018
Islam MN, Kitazawa D, Mannan MA et al (2015) Modeling alternative mitigation strategies of salinity intrusion on food production by integrating SWOT and TEAM decision models. Model Earth Syst Environ 1:12. https://doi.org/10.1007/s40808-015-0012-7
Islam R, Islam MM, Islam MN et al (2020) Climate change adaptation strategies: a prospect toward crop modelling and food security management. Model Earth Syst Environ 6:769–777. https://doi.org/10.1007/s40808-019-00708-6
Jakariya M, Islam MN (2017) Evaluation of climate change induced vulnerability and adaptation strategies at Haor areas in Bangladesh by integrating GIS and DIVA model. Model Earth Syst Environ 3:1303–1321. https://doi.org/10.1007/s40808-017-0378-9
Kirkegaard JA, Lilley JM, Howe GN, Graham JM (2007) Impact of subsoil water use on wheat yield. Aust J Agric Res 58(4):303–315. https://doi.org/10.1071/ar06285
Liu B, Asseng S, Müller C, Ewert F et al (2016) Similar estimates of temperature impacts on global wheat yield by three independent methods. Nat Clim Change 6:1130–1136. https://doi.org/10.1038/nclimate3115
Lobell DB (2014) Climate change adaptation in crop production: beware of illusions. Glob Food Secur 3(2):72–76. https://doi.org/10.1016/j.gfs.2014.05.002
Lobell DB, Asseng S (2017) Comparing estimates of climate change impacts from process-based and statistical crop models. Environ Res Lett 12:015001. https://doi.org/10.1088/1748-9326/aa518a
Lobell DB, Burke MB (2009) Climate change and food security: adapting agriculture to a warmer world. Springer, Cornell University, New York
Lobell DB, Burke MB (2010) On the use of statistical models to predict crop yield responses to climate change. Agric For Meteorol 150:1443–1452. https://doi.org/10.1016/j.agrformet.2010.07.008
Lu W, Atkinson DE, Newlands NK (2017) ENSO climate risk: predicting crop yield variability and coherence using cluster-based PCA. Model Earth Syst Environ 3:1343–1359. https://doi.org/10.1007/s40808-017-0382-0
Madhukar A, Kumar V, Dashora K (2019) Spatial and temporal trends in the yields of three major crops: wheat, rice and maize in India. Int J Plant Prod. https://doi.org/10.1007/s42106-019-00078-0
Meza FJ, Silva D (2009) Dynamic adaptation of maize and wheat production to climate change. Clim Change 94:143–156. https://doi.org/10.1007/s10584-009-9544-z
Moore FC, Baldos ULC, Hertel T (2017) Economic impacts of climate change on agriculture: a comparison of process-based and statistical yield models. Environ Res Lett 12:065008. https://doi.org/10.1088/1748-9326/aa6eb2
Paymard P, Bannayan M, Haghighi RS (2018) Analysis of the climate change effect on wheat production systems and investigate the potential of management strategies. Nat Hazards 91:1237–1255. https://doi.org/10.1007/s11069-018-3180-8
Rao BB, Chowdary PS, Sandeep VM et al (2015) Spatial analysis of the sensitivity of wheat yields to temperature in India. Agric For Meteorol 200:192–202. https://doi.org/10.1016/j.agrformet.2014.09.023
Ray DK, West PC, Clark M et al (2019) Climate change has likely already affected global food production. PLoS ONE 14(5):e0217148. https://doi.org/10.1371/journal.pone.0217148
Roberts MJ, Braun NO, Sinclair TR et al (2017) Comparing and combining process-based crop models and statistical models with some implications for climate change. Environ Res Lett 12:095010. https://doi.org/10.1088/1748-9326/aa7f33
Sloat LL, Davis SJ, Gerber JS et al (2020) Climate adaptation by crop migration. Nat Commun 11:1243. https://doi.org/10.1038/s41467-020-15076-4
Tanaka A, Takahashi K, Masutomi Y et al (2015) Adaptation pathways of global wheat production: importance of strategic adaptation to climate change. Sci Rep 5:14312. https://doi.org/10.1038/srep14312
Toros H, Mokari M, Abbasnia M (2019) Regional variability of temperature extremes in the maritime climate of Turkey: a case study to develop agricultural adaptation strategies under climate change. Model Earth Syst Environ 5:857–865. https://doi.org/10.1007/s40808-019-00572-4
Van Oort PAJ, Zhang T, de Vries ME et al (2011) Correlation between temperature and phenology prediction error in rice (Oryza sativa L.). Agric For Meteorol 151:1545–1555. https://doi.org/10.1016/j.agrformet.2011.06.012
White JW, Hoogenboom G, Kimball BA, Wall GW (2011) Methodologies for simulating impacts of climate change on crop production. Field Crops Res 124:357–368
Wooldridge JM (2013) Introductory econometrics: a modern approach. South Western Cengage Learning, Nelson Education, Mason
Yu Q, Li L, Luo Q et al (2013) Year patterns of climate impact on wheat yields. Int J Climatol. https://doi.org/10.1002/joc.3704
Zaveri EB, Lobell D (2019) The role of irrigation in changing wheat yields and heat sensitivity in India. Nat Commun 10:4144. https://doi.org/10.1038/s41467-019-12183-9
Acknowledgements
Anand Madhukar sincerely thank the Indian Institute of Technology (IIT) Delhi for providing a research fellowship. Authors declare no conflict of interest or finance.
Funding
Anand Madhukar sincerely thank the Indian Institute of Technology (IIT) Delhi for providing a research fellowship.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Madhukar, A., Dashora, K. & Kumar, V. Investigating historical climatic impacts on wheat yield in India using a statistical modeling approach. Model. Earth Syst. Environ. 7, 1019–1027 (2021). https://doi.org/10.1007/s40808-020-00932-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-020-00932-5