Abstract
The study of temperature trends and its impact on agricultural crop is critically important for evaluating the effects of climate change on food security. Spatiotemporal trends of the monthly, seasonal, and annual average temperature of 36 districts of Maharashtra, located in west India, were analyzed using 68 years of gridded temperature data of India Meteorological Department Mann-Kendall, modified Mann-Kendall, and Spearman’s rank correlation tests were used to analyze the trends of temperature, whereas Sen’s slope, Spearman’s Rho, and simple linear regression were used to quantify the magnitude of trends at 1% and 5% levels of significance. Correlation and regression analysis were performed between temperature and detrended yield for sugarcane. Results revealed that only increasing trends of monthly, seasonal, and annual average temperatures were significant in districts of Maharashtra. Significantly rising temperature trends of up to 2.58 °C, 1.78 °C and 1.05°C per 100 year were observed in monthly, seasonal, and annual temperatures, respectively. The magnitude of increasing temperature trends was more in the second half of the year. November and post-monsoon season had the highest increasing magnitude of trend for monthly and seasonal temperatures, respectively. Our analysis reveals increasing trends of average temperature in the region, which has significant negative impacts on Sugarcane (Saccharum officinarum L.). District-wise correlations of yield and monthly temperature anomalies showed 63.9% negative correlations, with significant negative correlations in 7.3% combinations. Overall the state has significant negative correlations of yield and monthly temperature, with Pearson’s correlation coefficient varying from −0.1(September) to −0.32 (July). The study confirms the adverse impacts of climate change on agricultural crop, and the results along with the district-wise temperature trend maps will be helpful for policy planners for agricultural resource management in west India.
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Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
AghaKouchak A, Chiang F, Huning LS, Love CA, Mallakpour I, Mazdiyasni O, Moftakhari H, Papalexiou SM, Ragno E, Sadegh M (2020) Climate extremes and compound hazards in a warming world. Annu Rev Earth Planet Sci 48:519–548. https://doi.org/10.1146/annurev-earth-071719-055228
Akbar H, Gheewala SH (2020) Effect of climate change on cash crops yield in Pakistan. Arab J Geosci 13. https://doi.org/10.1007/s12517-020-05333-7
Almeida CT, Oliveira-Júnior JF, Delgado RC, Cubo P, Ramos MC (2017) Spatiotemporal rainfall and temperature trends throughout the Brazilian Legal Amazon, 1973-2013. Int J Climatol 37:2013–2026. https://doi.org/10.1002/joc.4831
Anderson RL (1942) Distribution of the serial correlation coefficient. Ann Math Stat 13:1–13. https://doi.org/10.1007/s11269-007-9228-2
Atta-ur-Rahman, Dawood M (2017) Spatio-statistical analysis of temperature fluctuation using Mann–Kendall and Sen's slope approach. Clim Dyn 48:783–797. https://doi.org/10.1007/s00382-016-3110-y
Beacham AM, Hand P, Barker GC, Denby KJ, Teakle GR, Walley PG, Monaghan JM (2018) Addressing the threat of climate change to agriculture requires improving crop resilience to short-term abiotic stress. Outlook Agric 47:270–276. https://doi.org/10.1177/0030727018807722
Benzater B, Elouissi A, Benaricha B, Habi M (2019) Spatio-temporal trends in daily maximum rainfall in northwestern Algeria (Macta watershed case, Algeria). Arab J Geosci 12:370. https://doi.org/10.1007/s12517-019-4488-8
Bindi M, Olesen JE (2011) The responses of agriculture in Europe to climate change. Reg Environ Chang 11:151–158. https://doi.org/10.1007/s10113-010-0173-x
Byjesh K, Kumar SN, Aggarwal PK (2010) Simulating impacts, potential adaptation and vulnerability of maize to climate change in India. Mitig Adapt Strateg Glob Chang 15:413–431. https://doi.org/10.1007/s11027-010-9224-3
Chandiposha M (2013) Potential impact of climate change in sugarcane and mitigation strategies in Zimbabwe. African J Agric Res 8:2814–2818. https://doi.org/10.5897/AJAR2013.7083
Datta P, Das S (2019) Analysis of long-term seasonal and annual temperature trends in North Bengal, India. Spat Inf Res 27:475–496. https://doi.org/10.1007/s41324-019-00250-8
Dawood M, Rahman A, Ullah S, Rahman G, Azam K (2018) Spatio-temporal analysis of temperature variability, trend, and magnitude in the Hindu Kush region using Monte Carlo and Sen's slope approaches. Arab J Geosci 11:471. https://doi.org/10.1007/s12517-018-3823-9
Dua VK, Singh BP, Govindakrishnan PM et al (2013) Impact of climate change on potato productivity in Punjab – a simulation study. Curr Sci 105:787–794
Dubey SK, Sharma D (2018) Assessment of climate change impact on yield of major crops in the Banas River Basin, India. Sci Total Environ 635:10–19. https://doi.org/10.1016/j.scitotenv.2018.03.343
Gadedjisso-Tossou A, Adjegan KI, Kablan AKM (2020) Rainfall and temperature trend analysis by Mann–Kendall Test and significance for rainfed cereal yields in Northern Togo. Sci 2:74. https://doi.org/10.3390/sci2040074
Gajbhiye S, Meshram C, Mirabbasi R, Sharma SK (2016) Trend analysis of rainfall time series for Sindh river basin in India. Theor Appl Climatol 125:593–608. https://doi.org/10.1007/s00704-015-1529-4
Guntukula R (2020) Assessing the impact of climate change on Indian agriculture: Evidence from major crop yields. J Public Aff 20. https://doi.org/10.1002/pa.2040
Hamed KH, Ramachandra Rao A (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196. https://doi.org/10.1016/S0022-1694(97)00125-X
Haan CT (2002) Statistical methods in hydrology, 2nd edn. The Iowa State University Press, Iowa
Hansen J, Sato M, Ruedy R, Lo K, Lea DW, Medina-Elizade M (2006) Global temperature change. Proc Natl Acad Sci 103:14288–14293. https://doi.org/10.1073/pnas.0606291103
Hereher ME (2016) Recent trends of temperature and precipitation proxies in Saudi Arabia: implications for climate change. Arab J Geosci 9:575. https://doi.org/10.1007/s12517-016-2605-5
IPCC. 2014. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, CB Field, VR Barros, DJ Dokken, et al. White (eds). Cambridge University Press: Cambridge, UK and New York, NY, 1– 32.
Israel E, David AK, Omolara EG (2021) Spatio-temporal variation and trends of long-term meteorological variables in Nigeria. Arab J Geosci 13:1290. https://doi.org/10.1007/s12517-020-06392-6
Jain SK, Kumar V (2012) Trend analysis of rainfall and temperature data for India. Curr Sci 102:37–49
Kahlown MA, Azam M (2002) Individual and combined effect of waterlogging and salinity on crop yields in the Indus basin. Irrig Drain 51:329–338. https://doi.org/10.1002/ird.62
Kendall MG (1975) Rank Correlation Methods. England, Griffin London
Kim J, Sang W, Shin P, Cho H, Seo M, Yoo B, Kim KS (2015) Evaluation of regional climate scenario data for impact assessment of climate change on rice productivity in Korea. J Crop Sci Biotechnol 18:257–264. https://doi.org/10.1007/s12892-015-0103-z
Kumar S, Machiwal D, Dayal D (2017) Spatial modelling of rainfall trends using satellite datasets and geographic information system. Hydrol Sci J 62:1636–1653. https://doi.org/10.1080/02626667.2017.1304643
Lamaoui M, Jemo M, Datla R, Bekkaoui F (2018) Heat and Drought Stresses in Crops and Approaches for Their Mitigation. Front Chem 6. https://doi.org/10.3389/fchem.2018.00026
Lehmann EL, D'Abrera HJ (1975) Nonparametrics: Statistical methods based on ranks. Nonparametrics Stat. methods based Rank. xvi, 457–xvi, 457
Li X, Wang X, Babovic V (2018) Analysis of variability and trends of precipitation extremes in Singapore during 1980-2013. Int J Climatol 38:125–141. https://doi.org/10.1002/joc.5165
Li Y, Guan K, Schnitkey GD, DeLucia E, Peng B (2019) Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Glob Chang Biol gcb.14628. https://doi.org/10.1111/gcb.14628
Lobell DB, Schlenker W, Costa-Roberts J (2011) Climate Trends and Global Crop Production Since 1980. Science (80- ) 333:616–620. https://doi.org/10.1126/science.1204531
Machiwal D, Gupta A, Jha MK, Kamble T (2019) Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques. Theor Appl Climatol 136:301–320. https://doi.org/10.1007/s00704-018-2487-4
MAFW (2019) Commodity profile for rice-July, 2019. Annu Report www.agricoop.nic.in 1–9
Malik A, Kumar A, Guhathakurta P, Kisi O (2019) Spatial-temporal trend analysis of seasonal and annual rainfall (1966–2015) using innovative trend analysis method with significance test. Arab J Geosci 12. https://doi.org/10.1007/s12517-019-4454-5
Mall RK, Gupta A, Sonkar G (2017) Effect of Climate Change on Agricultural Crops. Elsevier B.V.
Mann HB (1945) Nonparametric Tests Against Trend. Econometrica 13:245. https://doi.org/10.2307/1907187
Meshram SG, Kahya E, Meshram C, Ghorbani MA, Ambade B, Mirabbasi R (2020) Long-term temperature trend analysis associated with agriculture crops. Theor Appl Climatol 140:1139–1159. https://doi.org/10.1007/s00704-020-03137-z
Misra V, Solomon S, Mall AK, Prajapati CP, Hashem A, EF Abd_Allah, Ansari MI (2020) Morphological assessment of water stressed sugarcane: A comparison of waterlogged and drought affected crop. Saudi J Biol Sci 27:1228–1236. https://doi.org/10.1016/j.sjbs.2020.02.007
Mullick MRA, Nur RM, Alam MJ, Islam KMA (2019) Observed trends in temperature and rainfall in Bangladesh using pre-whitening approach. Glob Planet Change 172:104–113. https://doi.org/10.1016/j.gloplacha.2018.10.001
Neumeister L (2010) Climate Change and Crop Protection. Pestic Action Netw 1–42
NFSM (2016), Brief Note on Sugarcane, Ministry of Agriculture and Farmers Welfare, Government of India. https://www.nfsm.gov.in/BriefNote/BN_Sugarcane.pdf. Accessed on 02 July 2021.
NITI Aayog (2020), Report of the Task Force on Sugarcane and Sugar Industry NITI Aayog, Government of India, New Delhi.
Novotny EV, Stefan HG (2007) Stream flow in Minnesota: Indicator of climate change. J Hydrol 334:319–333. https://doi.org/10.1016/j.jhydrol.2006.10.011
Pingale SM, Khare D, Jat MK, Adamowski J (2014) Spatial and temporal trends of mean and extreme rainfall and temperature for the 33 urban centers of the arid and semi-arid state of Rajasthan, India. Atmos Res 138:73–90. https://doi.org/10.1016/j.atmosres.2013.10.024
Prăvălie R, Bandoc G, Patriche C, Tomescu M (2017) Spatio-temporal trends of mean air temperature during 1961–2009 and impacts on crop (maize) yields in the most important agricultural region of Romania. Stoch Environ Res Risk Assess 31:1923–1939. https://doi.org/10.1007/s00477-016-1278-7
Praveen B, Sharma P (2020) Climate Change and its impacts on Indian agriculture: An Econometric analysis. J Public Aff 20. https://doi.org/10.1002/pa.1972
Radhakrishnan K, Sivaraman I, Jena SK, Sarkar S, Adhikari S (2017) A climate trend analysis of temperature and rainfall in India. Clim Chang Environ Sustain 5:146. https://doi.org/10.5958/2320-642x.2017.00014.x
Ram B (2018) Development of sugarcane varieties for abiotic stresses suitable for sub-tropical conditions
Rasheed R, Wahid A, Farooq M, Hussain I, Basra SMA (2011) Role of proline and glycinebetaine pretreatments in improving heat tolerance of sprouting sugarcane (Saccharum sp.) buds. Plant Growth Regul 65:35–45. https://doi.org/10.1007/s10725-011-9572-3
Reddy PP (2015) Climate Resilient Agriculture for Ensuring Food Security. Springer India, New Delhi
Sah S, Singh R, Chaturvedi G, Das B (2020) Trends, variability, and teleconnections of long-term rainfall in the Terai region of India. Theor Appl Climatol. 143:291–307. https://doi.org/10.1007/s00704-020-03421-y
Salman SA, Shahid S, Ismail T, Chung ES, al-Abadi AM (2017) Long-term trends in daily temperature extremes in Iraq. Atmos Res 198:97–107. https://doi.org/10.1016/j.atmosres.2017.08.011
Sen PK (1968) Estimates of the Regression Coefficient Based on Kendall's Tau. J Am Stat Assoc 63:1379–1389. https://doi.org/10.1080/01621459.1968.10480934
Shahin M, van Oorschot HJL, de Lange SJ (1993) Statistical analysis in water resources engineering. A.A. Balkema, Rotterdam
Sharma S, Mujumdar P (2017) Increasing frequency and spatial extent of concurrent meteorological droughts and heatwaves in India. Sci Rep 7:15582. https://doi.org/10.1038/s41598-017-15896-3
Sharma S, Saha AK (2017) Statistical analysis of rainfall trends over Damodar River basin, India. Arab J Geosci 10:319. https://doi.org/10.1007/s12517-017-3096-8
Shifteh Some'e B, Ezani A, Tabari H (2012) Spatiotemporal trends and change point of precipitation in Iran. Atmos Res 113:1–12. https://doi.org/10.1016/j.atmosres.2012.04.016
Singh R, Mukherjee J, Sehgal VK, Krishnan P, Das DK, Dhakar RK, Bhatia A (2021a) Interactive effect of elevated tropospheric ozone and carbon dioxide on radiation utilisation, growth and yield of chickpea (Cicer arietinum L.). Int J Biometeorol. https://doi.org/10.1007/s00484-021-02150-9
Singh R, Sah S, Chaturvedi G, et al (2021b) Innovative trend analysis of rainfall in relation to soybean productivity over western Maharashtra. 23:228–235
Singh R, Sah S, Das B, Potekar S, Chaudhary A, Pathak H (2021c) Innovative trend analysis of spatio-temporal variations of rainfall in India during 1901–2019. Theor Appl Climatol 145:821–838. https://doi.org/10.1007/s00704-021-03657-2
Singh R, Sah S, Das B, Vishnoi L, Pathak H (2020) Spatio-temporal trends and variability of rainfall in Maharashtra, India: Analysis of 118 years. Theor Appl Climatol. 143:883–900. https://doi.org/10.1007/s00704-020-03452-5
Sneyers, R. (1990). On the statistical analysis of series of observations. WMO Technical Note (143). World Meteorological Organization, Geneve.
Srivastava AK, Rajeevan M, Kshirsagar SR (2009) Development of a high resolution daily gridded temperature data set (1969-2005) for the Indian region. Atmos Sci Lett n/a-n/a. https://doi.org/10.1002/asl.232
Srivastava AK (2012) Sugarcane production: Impact of climate change and its mitigation. Biodiversitas, J Biol Divers 13:214–227. 10.13057/biodiv/d130408
Suryavanshi S, Pandey A, Chaube UC, Joshi N (2014) Long-term historic changes in climatic variables of Betwa Basin, India. Theor Appl Climatol 117:403–418. https://doi.org/10.1007/s00704-013-1013-y
Theil H (1950) A rank-invariant method of linear and polynomial. Mathematics 392:387–392
Vashisht BB, Mulla DJ, Jalota SK, Kaur S, Kaur H, Singh S (2013) Productivity of rainfed wheat as affected by climate change scenario in northeastern Punjab, India. Reg Environ Chang 13:989–998. https://doi.org/10.1007/s10113-013-0412-z
Wagholikar NK, Sinha Ray KC, Sen PN, Pradeep Kumar P (2014) Trends in seasonal temperatures over the Indian region. J Earth Syst Sci 123:673–687. https://doi.org/10.1007/s12040-014-0433-0
Xiong W, Holman IP, You L, Yang J, Wu W (2014) Impacts of observed growing-season warming trends since 1980 on crop yields in China. Reg Environ Chang 14:7–16. https://doi.org/10.1007/s10113-013-0418-6
Zhao C, Liu B, Piao S, Wang X, Lobell DB, Huang Y, Huang M, Yao Y, Bassu S, Ciais P, Durand JL, Elliott J, Ewert F, Janssens IA, Li T, Lin E, Liu Q, Martre P, Müller C et al (2017) Temperature increase reduces global yields of major crops in four independent estimates. Proc Natl Acad Sci 114:9326–9331. https://doi.org/10.1073/pnas.1701762114
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The author(s) would like to thank the India Meteorological Department (IMD), Pune for providing the daily temperature time series data for this study.
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Singh, R., Sah, S., Das, B. et al. Long-term spatiotemporal trends of temperature associated with sugarcane in west India. Arab J Geosci 14, 1955 (2021). https://doi.org/10.1007/s12517-021-08315-5
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DOI: https://doi.org/10.1007/s12517-021-08315-5