Rainfall and Temperature Trends in Jagtial District of Telangana State

Aims: To investigate and assess the significance of the potential trend of two variables viz. rainfall, temperature in Jagtial district of Telangana state.

Place and Duration of Study: Data of Daily rainfall and temperature data of 39 years (1980-2019) collected from the meteorological observatory at Regional Agricultural Research Station, Polasa, Jagtial.

Methodology: In this study, trend analysis has been carried out on monthly, seasonal and annual basis using the data period between 1980 to 2019 for rainfall and temperature. Mann-Kendall test and Sen’s slope estimate test were applied to identify the existing trend direction and magnitude of change over time.

Results: The rainfall seasonal trend analysis indicates that pre-monsoon, monsoon and post-monsoon and winter period showed a negative rainfall trend with z statistics of-1.47, -2.51, -0.55 and-1.38 respectively. However, the annual rainfall showed a negative trend with a z value of -2.53. In the case of Sen’s slope shows that negative trend in monthly, seasonal and annual rainfall. But the significant rising trend of monthly, seasonal average temperature is noticed from 1980 onwards. The annual average maximum temperature in the Jagtial showed an increasing trend (Z value +5.03). An increasing trend in the all seasons will lead to increase in annual mean temperature. The results of minimum temperature shows a rising trend and falling trend observed Monthly. However annual mean minimum temperature in the Jagtial District showed an increasing trend (Z value 0.10). In the case of maximum temperature for the observed period, it showed rising trend (Sen's slope = 0.63) while the minimum temperature trend showed no trend (Sen's slope = 0.02).

Conclusion: Time series was carried out using nonparametric M–K test and Sen's slope estimator, which are widely used tests for conducting trend analysis. Therefore, its take into think about the rainfall variability in particular and temperature variability in general of the area into their climate change adaptation approach.