Assessment of long-term climatic variability of Uttarakhand

Sujeet Kumar, Shakti Suryavanshi

Article ID: 744
Vol 3, Issue 1, 2020

VIEWS - 2118 (Abstract) 1458 (PDF)

Abstract


A trend analysis was performed for historic (1901-2002) climatic variables (Rainfall, Maximum Temperature and Minimum Temperature) of Uttarakhand State located in Northern India. In the serially independent climatic variables, Mann-Kendall test (MK test) was applied to the original sample data. However, in the serially correlated series, prewhitening is utilized before employing the MK test. The results of this study indicated a declining trend of rainfall in monsoon season for seven out of thirteen districts of Uttarakhand state. However, an increasing trend was observed in Haridwar and Udhamsingh Nagar districts for summer season rainfall. For maximum and minimum temperature, a few districts exhibited a declining trend in monsoon season whereas many districts exhibited an increasing trend in winter and summer season. Mountain dominated areas (as Uttarakhand state) are specific ecosystems, distinguished by their diversity, sensitivity and intricacy. Thus the variability of rainfall and temperature has a severe and rapid impact on mountainous ecosystems. Nevertheless, mountains have significant impacts on hydrology, which may further threaten populations living in the mountain areas as well as in adjacent, lowland regions.


Keywords


Trend Analysis; Mann-Kendall Test; Climate Change; Uttarakhand State

Full Text:

PDF


References


1. Pal I, Al-Tabbaa. Assessing seasonal precipitation trends in India using Parametric and non-parametric statistical techniques. Theoretical and Applied Climatology 2011; 103(1): 1–11.

2. Suryavanshi S, Pandey A, Chaube UC, et al. Long-term historic changes in climatic variables of Betwa basin, India. Theoretical and Applied Climatology 2014; 117(34): 403418.

3. Cruz RVH, Harasawa M, Lal S, et al. Climate change 2007: Impacts, adaptation and vulnerability, contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. UK, Cambridge: Cambridge University Press; 2006.

4. WCDMP-45. World climate programme—Water, detecting trend and other changes in hydrological data. In: Kundzewicz ZW, Robson A (editors). Genva, United Nations Educational Scientific and Cultural Organization, World Meteorological Organization; 2006.

5. Mann HB. Non-parametric tests against trend. Econometrica 1945; 13: 245259.

6. Kendall MG. Rank correlation methods. London: Charles Griffin; 1955.

7. Basistha A, Arya DS, Goel NK. Analysis of historical changes in rainfall in the Indian Himalayas. International Journal of Climatology 2009; 29(4): 555572.

8. WMO. Climatic change. WMO Technical Note 79, World Meteorological Organization, Geneva; 1966.

9. Matalas NC. Time series analysis. Water Resources Research 1967; 3: 817829.

10. Rodhe H, Virji H. Trends and periodicities in East African rainfall data. Monthly Weather Review 1976; 104: 307–315.

11. Granger OE. Secular fluctuations of seasonal precipitation in lowland California. Monthly Weather Review 1977; 105: 386–397.

12. Ogallo L. Rainfall variability in Africa. Monthly Weather Review 1979; 107: 1133–1139.

13. Anyadike RNC. Seasonal and annual rainfall variations over Nigeria. International Journal Climathology 1993; 13: 567–580.

14. Drosdowsky W. An analysis of Australian seasonal rainfall anomalies: 1950–1987, II: Temporal variability and teleconnection patterns, International. Climatology 1993; 119(1): 51–65.

15. Nicholson, Palao IM. A re-evaluation of rainfall variability in the Sahel, Part I, Characteristics of rainfall fluctuations, International. Climatology 1993; 13: 371–389.

16. Türkes Sümer UM, Kiliç G. Persistence and periodicity in the precipitation series of Turkey and associations with 500 hPa geopotential heights. Climatic Research 2002; 21: 59–81.

17. Yevjevich V. Stochastic Processes in Hydrology, Water Resources Publications, Fort Collins, CO; 1971.

18. Burn DH and Hag Elnur MA. Detection of hydrologic trends and variability. Journal of Hydrology 2002; 255(14): 107122.

19. Yue S, Pilon P, Cavadias G. Power of the Mann-Kendall and Spearman’s rho test for detecting monotonic trends. Hydrology 2002; 259: 254271.

20. Theil H. A rank invariant method of linear and polynomial regression analysis, Part 3. Netherlands Akademie van Wettenschappen 1950; 53: 13971412.

21. Sen PK. Estimates of the regression coefficient based on Kendall’s tau. American Statistical Association 1968; 63: 13791389.

22. Hirsch RM, Slack JR, Smith RA. Techniques of trend analysis for monthly water quality data. Water Resources Research 1982; 18(1): 107–121.




DOI: https://doi.org/10.24294/nrcr.v3i1.744

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Sujeet Kumar, Shakti Suryavanshi

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

This site is licensed under a Creative Commons Attribution 4.0 International License.