Abstract
In this study, the trend of annual and monthly rainfall; and trend of maximum and minimum temperature of the month have been detected. The presence of trends in annual rainfall time series are detected and evaluated using linear regression (LR), Mann-Kendall(M-K) test with Sen's slope estimator, and Innovative Trend analysis (ITA). Results of trend analysis by LR, M-K and ITA methods show close agreement. An inverse distance weighting (IDW) method in Arc GIS is used for developing spatial distribution of the trends over the entire study area of Sabarmati River basin, India. Result of the monthly rainfall shows reducing trend in the June month and shows increasing trend for the month of September in the study area. This is indicative of tendency of late starting and late vanishing of the monsoon season. Maximum temperature in the basin, in winter months show reducing trend, while in summer months, temperature show increasing trends. Results shown shifting of summer season (March to May) extending to the monsoon months. The Land Use Land cover is examined for regional influential linkages to climate change. The change in the seasonal climate bears significance for its inferences in agriculture field and water resources field for fulfilling the demand from available water resources in the river basin.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Atmospheric and Solar-Terrestrial Physics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
