Open AccessTrend Detection in Rainfall and Temperature Data [1960-2014] of Anand, Gujrat, India
Author(s) -
S. S. Chinchorkar,
G. J. Kamani
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-949
Subject(s) - monsoon , climate change , trend analysis , agriculture , environmental science , kharif crop , wet season , geography , cropping , climatology , livelihood , ecology , biology , meteorology , mathematics , cartography , archaeology , geology , statistics
The temperature and rainfall trends are analyzed for meteorological data of Anand in Gujarat, India over approximately last three decades stretching between years 1960 to 2014. The long–term change in temperature and rainfall has been assessed by linear trend analysis. Due to their biophysical characteristics, dry lands ecosystems are most Vulnerable the Climate risks. Climate variability has serious implications on major livelihoods of the region i.e. Agriculture and livestock. In this paper, attempts have been made to study variations in temperature and rainfall in Anand of Gujarat, India. Data at annual, seasonal and monthly time scales for the period of 1960-2014 (Temperature) and 1960-2014 (Rainfall) were examined. Study of monthly variations revealed rise in the temperatures in the month of September. Rainfall and Rainy days have also increased in past 4 decades. Annual and Monsoon rainfall have been observed to increase, where the month of August shows a statistically significant increasing trend. Any variability in monsoon season will have implications on agricultural activities as the season overlaps with Kharif, a major cropping season for the country. The variations of temperature and rainfall during monsoons may have impacts on the various growth stages of the crops. Changing weather conditions may lead to increase in pest infestations. Macro level studies may or may not be relevant at village level and therefore the advisories generated may not benefit the locals. Trends in temperature, rainfall and rainy days have been assessed by Non-parametric tests (Mann-Kendall or Pre Whitened Mann-Kendall test for trend detection and Theil and Sen's Slope for magnitude of trend). Temperature and Rainfall variations, Climate Change, Mann-Kendall Test.