Evaluation of climate change study is vital for appropriate management of hydrological resources and future planning. South Xinjiang is comprising various sort of climatic conditions. The focal point of this study is to assess the dissemination and pattern of temperature for as far back as 39 years in south Xinjiang China. The time series data recorded as maximum, minimum and mean monthly temperature at different metrological stations. For trend detection Mann-Kendall tests and Sen's slope estimation model were applied for appropriate results. The statistical analysis of the study indicates a significant upward trend in three types mean max. min. and average temperature on seasonal & monthly scale. Change points find out in the four decades show an increasing trend of temperature. Results found from Sen's slope magnitudes vary from 0.010ºC to 0.070ºC in Tmax per annum. Further, Sen's slope from − 0.150ºC to 0.080ºC and − 0.080ºC to 0.060ºC every year for both Tmin and Tmean. So for the increasing trend in all temperature is a get way to a dangerous atmospheric devastation and environmental change. Seasonal evaluation of temperature (JJA) June, July and August detected upward trend of temperature while the rainfall occurring months (NDJF), November, December, January and February found significantly dry. The seasonal changeability of temperature is straightforwardly responsible for desertification in the area. The conclusion of the research study that southern Xinjiang facing severe dry conditions are essential to highlight this burning issue for further development and sustainability of water resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.