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The objective of this study was to assess trends in maximum and minimum temperatures and total monthly rainfall in the Punjab province of Pakistan. Non parametric Mann-Kendall and Sen's slope techniques were employed to find trend strength and magnitude. Serial correlation in data was removed by using TFPW (Trend Free Pre-Whitening) approach. Monthly data of maximum and minimum temperatures and total rainfall was obtained from Regional Meteorological Office (Lahore) for nine districts of Punjab for the period 1961- 2014. The maximum temperature showed a significant increasing trend at Rawalpindi and Faisalabad with a Sen Slope of 0.010°C/year, while significant increasing trends at eight stations were observed in minimum temperature on annual basis. All stations have experienced increasing trends in rainfall out of which only two stations have shown significant trend annually. Overall in Punjab, maximum temperature has shown a significant upward trend in spring (0.028°C/year) and downward trend in summer season (-0.013°C/year). While in minimum temperature, significant increasing trends were observed in all seasons excluding summer. A significant increasing trend in rainfall was observed in summer (1.79 mm/year), autumn and on annual basis (3.23mm/year). The results indicate that spring season is warming and the decreasing trend in summer temperature is caused by increasing trend of rainfall in the province. [ABSTRACT FROM AUTHOR]

This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen's slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p < 0.05 to be statistically significant. We observed significant (p < 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p < 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan. [ABSTRACT FROM AUTHOR]

An increase in the human population, urbanization, industrialization, infrastructural development, and current agricultural practices acts as major factors leading to the decline of the groundwater table in the region. The present study analyzes the noticeable effect of anthropogenic pressure on the groundwater table in the Bist-Doab region in Punjab, India, from 1996 to 2016. Statistical techniques, viz., Mann-Kendall Z statistics and Sen's slope, were used to estimate the water table decline in the area. The results indicate that there was a slight increase in the groundwater table in the Kandi belt of Siwalik foothills and south-western parts of the region. In the rest of the areas, a significant declining trend was observed in the groundwater table. The decline in the water table ranged from 56 to 149 cm per year in the pre- and post-monsoon seasons due to increasing in rice cultivated area, which is an alarming situation in the aquifer system of the region. Hence, to reduce the further decline of the groundwater table, water management practices need to be encouraged in the region. There is requiring immediate attention to change the present land-use/cover practices and to grow less water-consuming crops instead of high water-consuming crops to reduce the pressure on groundwater. [ABSTRACT FROM AUTHOR]