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In the present study, long-term rainfall trend was analyzed using the traditional Mann–Kendall (MK) test and innovative trend analysis (ITA) method for annual and seasonal rainfall series for 20 districts of Punjab state for the period of 1951–2021. The autocorrelation test was performed to detect the presence or absence of serial correlation in the rainfall series. Based on the autocorrelation test, MK or modified Mann–Kendall (MMK) test and Sen's slope test were applied to determine the direction and magnitude of the rainfall trend, respectively. The ITA which revealed the presence of a trend graphically was compared with the traditional MK/MMK test. The autocorrelation test showed that all the annual rainfall series are serially independent, except for the Hoshiarpur. The MK/MMK test revealed the presence of a decreasing trend in annual rainfall series of all districts, except for Fatehgarh Sahib, Kapurthala, Patiala, and Tarn Taran of the central zone and Muktsar of the south west zone. The computed probable change point year was 1998. The innovative trend slope revealed the presence of a significant decreasing trend for the districts of Punjab missed by the traditional MK/MMK test. The highest decrease (− 4.5 mm/year) in annual rainfall was observed at Gurdaspur of the north zone and Faridkot of the south west zone. The ITA showed the statistically significant decreasing trend in annual rainfall for all the districts of the south west zone at 1% significance level. The analysis using ITA determined the presence of hidden trends missed by the traditional MK/MMK test. The decreasing pattern in rainfall over most of the districts and high irrigation requirement for largely growing paddy crop of Punjab indicated the urgent need of efficient planning of water resources. The study may guide planners and policy makers for effective implementation of the rainwater harvesting and groundwater recharge strategies to improve the status of water resources in the entire Punjab. [ABSTRACT FROM AUTHOR]

This study explores the spatio-temporal distribution and trends on monthly, seasonal, and annual scales of rainfall in the central Punjab districts of Punjab province in Pakistan by using observation and satellite data products. The daily observed data was acquired from the Pakistan Metrological Department (PMD) between 1983 and 2020, along with one reanalysis, namely the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and one satellite-based daily Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks climate data record (PERSIANN-CDR) using the Google Earth Engine (GEE) web-based API platform to investigate the spatio-temporal fluctuations and inter-annual variability of rainfall in the study domain. Several statistical indices were employed to check the data similarity between observed and remotely sensed data products and applied to each district. Moreover, non-parametric techniques, i.e., Mann–Kendall (MK) and Sen's slope estimator were applied to measure the long-term spatio-temporal trends. Remotely sensed data products reveal 422.50 mm (CHIRPS) and 571.08 mm (PERSIANN-CDR) mean annual rainfall in central Punjab. Maximum mean rainfall was witnessed during the monsoon season (70.5%), followed by pre-monsoon (15.2%) and winter (10.2%). Monthly exploration divulges that maximum mean rainfall was noticed in July (26.5%), and the minimum was in November (0.84%). The district-wise rainfall estimation shows maximum rainfall in Sialkot (931.4 mm) and minimum in Pakpattan (289.2 mm). Phase-wise analysis of annual, seasonal, and monthly trends demonstrated a sharp decreasing trend in Phase-1, averaging 3.4 mm/decade and an increasing tendency in Phase-2, averaging 9.1 mm/decade. Maximum seasonal rainfall decreased in phase-1 and increased Phase-2 during monsoon season, averaging 2.1 and 4.7 mm/decade, whereas monthly investigation showed similar phase-wise tendencies in July (1.1 mm/decade) and August (2.3 mm/decade). In addition, as district-wise analyses of annual, seasonal, and monthly trends in the last four decades reveal, the maximum declined trend was in Sialkot (18.5 mm/decade), whereas other districts witnessed an overall increasing trend throughout the years. Out of them, Gujrat district experienced the maximum increasing trend in annual terns (50.81 mm/decade), and Faisalabad (25.45 mm/decade) witnessed this during the monsoon season. The uneven variability and trends have had a crucial imprint on the local environment, mainly in the primary activities. [ABSTRACT FROM AUTHOR]

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]

Recent improvements in time series studies of hydro-climatological variables have led to the belief that the effects of nonstationarity are substantial enough to call the idea of traditional stationary approaches into doubt. The mean and variability of annual and seasonal rainfall in Pakistan are changing due to anthropogenic climate change. With the use of stationary and nonstationary frequency analysis techniques, this study set out to assess the impacts of nonstationarity in Southern Punjab, Pakistan, over the historical period of 1970–2015 and the future periods of 2020–2060 and 2060–2100. Four frequency distributions, namely Generalized Extreme Value (GEV), Gumbel, normal, and lognormal, were used. The findings of the nonstationarity impact across Southern Punjab showed different kinds of impacts, such as an increase or reduction in the return level of extreme precipitation. In comparison to other distributions, GEV provided the finest fit. In Bahawalnagar, Bahawalpur, Multan, Rahim Yar Khan and DG. Khan, the annual nonstationarity impacts for the 100-year return level were increased up to 15.2%, 8.7%, 58.3%, 18.7%, and 20%, respectively. Moreover, extreme precipitation was found to be increasing during the historical and projected periods, which may increase floods, while less water availability appeared at a seasonal scale (summer) during 2061–2100. The increased nonstationarity effects emphasized adapting these nonstationarities induced by climate change into the design of water resource structures. [ABSTRACT FROM AUTHOR]