Investigation of trends in basin-scale temperature variables



Published Aug 18, 2023
Harsh Upadhyay
P.K. Singh M. Kothari S.R. Bhakar K.K. Yadav


This research paper presents an analysis of temperature variables over the West Banas basin in order to detect the presence of underlying trends employing historical temperature data for three points viz., Abu Road, Mount Abu and Pindwara obtained for a period of 40 years (1981 – 2020) from MERRA-2 database. The study aims to investigate the long-term changes in temperature trends and identify any significant patterns or anomalies in mean, maximum and minimum temperatures at monthly, seasonal and annual timescales at the three locations amounting to a total of 162 series. The trends were evaluated using the Mann-Kendall test, a popular and powerful statistical technique formulated for analysing abnormal distributions. Prior to the application of the trend test, autocorrelated time series were identified and the trend test was modified using a variance correction approach to incorporate the influence of autocorrelations upon the resultant trends. The findings of autocorrelation analysis revealed that 11 of the 162 series were autocorrelated, a majority of which were associated with the temperature series at Abu Road. The results of the trend test showed that 27 out of the 162 series possessed significant trends with the mean and maximum monsoon temperatures in most of the series exhibiting a reducing trend while the minimum temperature appeared to be rising. Overall, the research highlights the importance of monitoring temperature trends, particularly in regions that may be more vulnerable to the impacts of climate change. The findings of this study can inform future climate adaptation strategies and support decision-making processes aimed at mitigating the effects of global warming on the natural and built environment.

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Upadhyay, H., Singh, P., Kothari, M., Bhakar, S., & Yadav, K. (2023). Investigation of trends in basin-scale temperature variables. Environment Conservation Journal.


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Autocorrelation, Climate change, Mann-Kendall test, Temperature, Trend analysis

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