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Trend and Change Point Detection of Precipitation in Urbanizing Districts of Uttarakhand in India


Affiliations
1 Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
 

Precipitation is the one of the prime indicators of climate change and its aberration causes many extreme events such as floods and droughts. Long-term trends were analyzed as monthly, seasonal and annual rainfall of Haridwar, Dehradun,Udham Singh Nagar, Almora and Nainital using Mann-Kendall and linear regression tests and change point was detected using cumulative deviation and Worsley likelihood statistic. Mann Kendall test revealed that there is significant increase in rainfall only for Haridwar district which has more urbanizing area compared to other districts. Haridwar is the holy place attracting significant floating population from all over the world, especially during festivals and fairs. Anthropogenic activity and industrialization is also the major cause of rainfall trend fluctuation in the Haridwar city. The monthly trend tests show that July rainfall is increasing whereas the December rainfall is decreasing which could be due to the seasonal shift. The start of change in the rainfall trend for the above mentioned districts is observed with distinct difference from 2009 onwards. From this it can be concluded that the stations to the west show significant trends compared to station which is towards east. Monsoon especially in July month a trend of increasing rainfall is observed in the studied Indian cities. The spatial and temporal trends of precipitation are pertinent for the future development and sustainable management of water resources of a given region.

Keywords

Change Point, Mann Kendall Trend, Rainfall, Uttarakhand, Worsely Likelihood Test
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  • Trend and Change Point Detection of Precipitation in Urbanizing Districts of Uttarakhand in India

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Authors

G. Pranuthi
Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
S. K. Dubey
Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
S. K. Tripathi
Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
S. K. Chandniha
Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India

Abstract


Precipitation is the one of the prime indicators of climate change and its aberration causes many extreme events such as floods and droughts. Long-term trends were analyzed as monthly, seasonal and annual rainfall of Haridwar, Dehradun,Udham Singh Nagar, Almora and Nainital using Mann-Kendall and linear regression tests and change point was detected using cumulative deviation and Worsley likelihood statistic. Mann Kendall test revealed that there is significant increase in rainfall only for Haridwar district which has more urbanizing area compared to other districts. Haridwar is the holy place attracting significant floating population from all over the world, especially during festivals and fairs. Anthropogenic activity and industrialization is also the major cause of rainfall trend fluctuation in the Haridwar city. The monthly trend tests show that July rainfall is increasing whereas the December rainfall is decreasing which could be due to the seasonal shift. The start of change in the rainfall trend for the above mentioned districts is observed with distinct difference from 2009 onwards. From this it can be concluded that the stations to the west show significant trends compared to station which is towards east. Monsoon especially in July month a trend of increasing rainfall is observed in the studied Indian cities. The spatial and temporal trends of precipitation are pertinent for the future development and sustainable management of water resources of a given region.

Keywords


Change Point, Mann Kendall Trend, Rainfall, Uttarakhand, Worsely Likelihood Test



DOI: https://doi.org/10.17485/ijst%2F2014%2Fv7i10%2F59375