摘要：The overall objective of this paper is to analyze the long-term spatio-temporal patterns of precipitation and temperature especially under changing climatic conditions. A comprehensive study of different non-parametric trend techniques for serially correlated data were performed. Four variants of Mann Kendall, Spearmen’s rho and Theil Sen’s approach were utilized to quantify the significance of precipitation and temperature trends and their magnitude. Furthermore, to investigate the non-stationary behavior of these trends, Sequential Mann Kendall technique has been used. Besides, inter-annual and seasonal variations in the precipitation and temperature patterns were analyzed to understand the climatic conditions of the study area along with their spatial fluctuating characteristics. Abrupt changes in precipitation and temperature patterns were also illustrated to understand the hydrological behaviors.It is concluded that the Modified Mann Kendall technique is more reliable for trend detection of serially correlated data. The results indicated that generally no significance trend in annual and seasonal precipitation data series exist. However, for temperature except during summer, a significant increasing trend in annual and seasonal data series has been observed with a change up to 0.17 oC/ decade. Results of Sequential Mann Kendall indicated that change in trend for annual and seasonal precipitation except for autumn season began in 1955-1965, whereas it started in 1965-1975 for annual and seasonal temperature for majority of the study regions.
关键词：Seasonal and annual trends;Modified Mann Kendall;Trend Change;Abrupt change
