Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India
Globally, there has been a lot of focus on climate variability, especially variability in annual precipitation and temperatures. Depending on the area, different climate variables have different degrees of variation. Therefore, analyzing the temporal and spatial changes or dynamics of meteorological...
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2024-12-01
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author | Netrananda Sahu Rajiv Nayan Arpita Panda Ayush Varun Ravi Kesharwani Pritiranjan Das Anil Kumar Suraj Kumar Mallick Martand Mani Mishra Atul Saini Sumat Prakash Aggarwal Sridhara Nayak |
author_facet | Netrananda Sahu Rajiv Nayan Arpita Panda Ayush Varun Ravi Kesharwani Pritiranjan Das Anil Kumar Suraj Kumar Mallick Martand Mani Mishra Atul Saini Sumat Prakash Aggarwal Sridhara Nayak |
author_sort | Netrananda Sahu |
collection | DOAJ |
description | Globally, there has been a lot of focus on climate variability, especially variability in annual precipitation and temperatures. Depending on the area, different climate variables have different degrees of variation. Therefore, analyzing the temporal and spatial changes or dynamics of meteorological or climatic variables in light of climate change is crucial to identifying the changes induced by climate and providing workable adaptation solutions. This study examined how climate variability affects tea production in Darjeeling, West Bengal, India. It also looked at trends in temperature and rainfall between 1991 and 2023. In order to identify significant trends in these climatic factors and their relationship to tea productivity, the study used a variety of statistical tests, including the Sen’s Slope Estimator test, the Mann–Kendall’s test, and regression tests. The study revealed a positive growth trend in rainfall (Sen’s slope = 0.25, <i>p</i> = 0.001, R<sup>2</sup> = 0.032), maximum temperature (Sen’s slope = 1.02, <i>p</i> = 0.026, R<sup>2</sup> = 0.095), and minimum temperature (Sen’s slope = 4.38, <i>p</i> = 0.006, R<sup>2</sup> = 0.556). Even with the rise in rainfall, there has been a decline in tea productivity, as seen by the sharp decline in both the tea cultivated area and the production of tea. The results obtained from the regression analysis showed an inverse relationship between temperature anomalies and tea yield (R = −0.45, <i>p</i> = 0.02, R<sup>2</sup> = 0.49), indicating that the growing temperatures were not favorable for the production of tea. Rainfall anomalies, on the other hand, positively correlated with tea yield (R = 0.56, <i>p</i> = 0.01, R<sup>2</sup> = 0.68), demonstrating that fluctuations in rainfall have the potential to affect production but not enough to offset the detrimental effects of rising temperatures. These results underline how susceptible the tea sector in Darjeeling is to climate change adversities and the necessity of adopting adaptive methods to lessen these negative consequences. The results carry significance not only for regional stakeholders but also for the global tea industry, which encounters comparable obstacles in other areas. |
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spelling | doaj-art-c9de9addd25e4b8f947b29fefc2321a42025-01-24T13:21:39ZengMDPI AGAtmosphere2073-44332024-12-01161110.3390/atmos16010001Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in IndiaNetrananda Sahu0Rajiv Nayan1Arpita Panda2Ayush Varun3Ravi Kesharwani4Pritiranjan Das5Anil Kumar6Suraj Kumar Mallick7Martand Mani Mishra8Atul Saini9Sumat Prakash Aggarwal10Sridhara Nayak11Department of Geography, Delhi School of Economics, University of Delhi, New Delhi 110007, IndiaDepartment of Commerce, Ramanujan College, University of Delhi, New Delhi 110019, IndiaDepartment of Geography, Central University of Jharkhand, Raatu-Lohardaga Road Brambe, Ranchi 835205, IndiaDepartment of Geography, Delhi School of Economics, University of Delhi, New Delhi 110007, IndiaDepartment of Geography, Delhi School of Economics, University of Delhi, New Delhi 110007, IndiaDepartment of Geography, Delhi School of Economics, University of Delhi, New Delhi 110007, IndiaDepartment of Geography, Delhi School of Economics, University of Delhi, New Delhi 110007, IndiaDepartment of Geography, Shaheed Bhagat Singh College, University of Delhi, New Delhi 110017, IndiaDepartment of Geography, Shyama Prasad Mukherji College for Women, University of Delhi, New Delhi 110033, IndiaDepartment of Geography, B.G.R Campus, Hemvati Nandan Bahuguna Garhwal University (Central University), Pauri, Srinagar 246001, IndiaDepartment of Commerce, Ramanujan College, University of Delhi, New Delhi 110019, IndiaResearch and Development Center, Japan Meteorological Corporation Limited, Osaka 530-0011, JapanGlobally, there has been a lot of focus on climate variability, especially variability in annual precipitation and temperatures. Depending on the area, different climate variables have different degrees of variation. Therefore, analyzing the temporal and spatial changes or dynamics of meteorological or climatic variables in light of climate change is crucial to identifying the changes induced by climate and providing workable adaptation solutions. This study examined how climate variability affects tea production in Darjeeling, West Bengal, India. It also looked at trends in temperature and rainfall between 1991 and 2023. In order to identify significant trends in these climatic factors and their relationship to tea productivity, the study used a variety of statistical tests, including the Sen’s Slope Estimator test, the Mann–Kendall’s test, and regression tests. The study revealed a positive growth trend in rainfall (Sen’s slope = 0.25, <i>p</i> = 0.001, R<sup>2</sup> = 0.032), maximum temperature (Sen’s slope = 1.02, <i>p</i> = 0.026, R<sup>2</sup> = 0.095), and minimum temperature (Sen’s slope = 4.38, <i>p</i> = 0.006, R<sup>2</sup> = 0.556). Even with the rise in rainfall, there has been a decline in tea productivity, as seen by the sharp decline in both the tea cultivated area and the production of tea. The results obtained from the regression analysis showed an inverse relationship between temperature anomalies and tea yield (R = −0.45, <i>p</i> = 0.02, R<sup>2</sup> = 0.49), indicating that the growing temperatures were not favorable for the production of tea. Rainfall anomalies, on the other hand, positively correlated with tea yield (R = 0.56, <i>p</i> = 0.01, R<sup>2</sup> = 0.68), demonstrating that fluctuations in rainfall have the potential to affect production but not enough to offset the detrimental effects of rising temperatures. These results underline how susceptible the tea sector in Darjeeling is to climate change adversities and the necessity of adopting adaptive methods to lessen these negative consequences. The results carry significance not only for regional stakeholders but also for the global tea industry, which encounters comparable obstacles in other areas.https://www.mdpi.com/2073-4433/16/1/1climate variabilityclimate changetemperature anomalytrend analysisMann–Kendall’s testSen’s slope estimator test |
spellingShingle | Netrananda Sahu Rajiv Nayan Arpita Panda Ayush Varun Ravi Kesharwani Pritiranjan Das Anil Kumar Suraj Kumar Mallick Martand Mani Mishra Atul Saini Sumat Prakash Aggarwal Sridhara Nayak Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India Atmosphere climate variability climate change temperature anomaly trend analysis Mann–Kendall’s test Sen’s slope estimator test |
title | Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India |
title_full | Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India |
title_fullStr | Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India |
title_full_unstemmed | Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India |
title_short | Impact of Changes in Rainfall and Temperature on Production of Darjeeling Tea in India |
title_sort | impact of changes in rainfall and temperature on production of darjeeling tea in india |
topic | climate variability climate change temperature anomaly trend analysis Mann–Kendall’s test Sen’s slope estimator test |
url | https://www.mdpi.com/2073-4433/16/1/1 |
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