Trend analysis and change-point detection of monsoon rainfall in Uttarakhand and its impact on vegetation productivity


  • PRIYANKA SWAMI Department of Agronomy, Agriculture University Jodhpur, Rajasthan, India



Mann-Kendall (MK) test, Pettitt test, rainfall trend, Gross primary productivity, forest and crop lands


This study analyzes the long-term spatio-temporal changes and trend analysis in rainfall using the data from 1901 to 2020 and its impact on vegetation from 2000 to 2020 across districts of Uttarakhand. The Pettitt test was employed to detect the abrupt change point in time frame, while the Mann-Kendall (MK) test was performed to analyze the rainfall trend. Results show that the most of the districts exhibited significant negative trend of rainfall in monsoon, except two districts. Out of 13 districts, 4 districts recorded noteworthy rainfall declining trend for the monsoon season at 0.05% significance level, while the insignificant negative trend of rainfall was detected for 7 districts of Uttarakhand. Furthermore, the significant negative trend (-2.23) was recorded for overall monsoon rainfall of Uttarakhand. Based on the findings of change detection, the most probable year of change detection was occurred primarily after 1960 for most of the districts of Uttarakhand. A significant decline rainfall was detected after 1960 while after 1970 interannual variability of rainfall was recorded to be increased.  The analysis of month wise cumulative gross primary productivity (GPP) for 13 districts with rainfall trends shows that there is significant impact of rainfall trend on GPP during month of June and it gradually reduces for subsequent monsoon months. It was observed that the GPP of region is increasing at rate of 9.1 gCm-2d-1 in the region since 2000. Based on sensitivity analysis, the GPP of cropped area of region is more sensitive towards rainfall than forest area of Uttarakhand.


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How to Cite

SWAMI, P. (2024). Trend analysis and change-point detection of monsoon rainfall in Uttarakhand and its impact on vegetation productivity. Journal of Agrometeorology, 26(1), 103–108.



Research Paper