The Indus River, which flows through China, India, and Pakistan, is mainly fed by melting snow and glaciers that are spread across the Hindukush–Karakoram–Himalaya Mountains. The downstream population of the Indus Plain heavily relies on this water resource for drinking, irrigation, and hydropower generation. Therefore, its river runoff variability must be properly monitored. Gilgit Basin, the northwestern part of the Upper Indus Basin, is selected for studying cryosphere dynamics and its implications on river runoff. In this study, 8-day snow products (MOD10A2) of moderate resolution imaging spectroradiometer, from 2001 to 2015 are selected to access the snow-covered area (SCA) in the catchment. A non-parametric Mann–Kendall test and Sen’s slope are calculated to assess whether a significant trend exists in the SCA time series data. Then, data from ground observatories for 1995–2013 are analyzed to demonstrate annual and seasonal signals in air temperature and precipitation. Results indicate that the annual and seasonal mean of SCA show a non-significant decreasing trend, but the autumn season shows a statistically significant decreasing SCA with a slope of −198.36 km²/year. The annual mean temperature and precipitation show an increasing trend with highest values of slope 0.05 °C/year and 14.98 mm/year, respectively. Furthermore, Pearson correlation coefficients are calculated for the hydro-meteorological data to demonstrate any possible relationship. The SCA is affirmed to have a highly negative correlation with mean temperature and runoff. Meanwhile, SCA has a very weak relation with precipitation data. The Pearson correlation coefficient between SCA and runoff is −0.82, which confirms that the Gilgit River runoff largely depends on the melting of snow cover rather than direct precipitation. The study indicates that the SCA slightly decreased for the study period, which depicts a possible impact of global warming on this mountainous region.

Dengue fever (DF) is a national health problem in Pakistan. It has become endemic in Lahore after its recent reemergence in 2016. This study investigates the impacts of climatic factors (temperature and rainfall) on DF transmission in the district of Lahore through statistical approaches. Initially, the climatic variability was explored using a time series analysis on climatic factors from 1970 to 2012. Furthermore, ordinary and multiple linear regression analyses were used to measure the simulating effect of climatic factors on dengue incidence from 2007 to 2012. The time series analysis revealed significant annual and monthly variability in climatic factors, which shaped a dengue-supporting environment. It also showed a positive temporal relationship between climatic factors and DF. Moreover, the regression analyses revealed a substantial monthly relationship between climatic factors and dengue incidence. The ordinary linear regression of rainfall versus dengue showed monthly R² = 34.2%, whereas temperature versus dengue presented R² = 38.0%. The multiple regression analysis showed a monthly significance of R² = 44.6%. Consequently, our study shows a substantial synergism between dengue and climatic factors in Lahore. The present study could help in unveiling new ways for health prediction modeling of dengue and might be applicable in other subtropical and temperate climates.

It is known that the rainfall is one of the major aspects of the climate change and hydrological processes. Its impact on the resources of water has always been considered very essential. In the countries like Pakistan having severe weather conditions the effect of rainfall can be more crucial. Due to the geographical differences, the impact of sudden rainfall can be more disastrous in Pakistan as in 2011 and 2022 only the few days' extreme rainfall in summer monsoon disturbed many regions of Pakistan especially southern region of Pakistan and lost hundreds of lives and homes. In addition, there are two methods applied for this study (1) trend analysis and (2) probability distribution functions. Our results revealed that only three cities i.e. Chitral, Skardu and Gilgit having increasing as well as the station Sialkot have increasing trend pattern in only summer rainfall, and other all have shown decreasing trend overall. Furthermore, key extreme weather events over Pakistan have changed in frequency and intensity during the past decades due to significant increase in global warming. The methods and results will be useful to study the historical rainfall data for projecting future rainfall variations impact on hydrological processes due to climate change.•The Data, methods and results of this study can be useful to government officials for protective measures and future developments.•Detecting trend analysis was applied to point out how strong the trend in the rainfall is and whether it is increasing or decreasing.•Additionally, the probability distribution was applied to indicate changed in frequency and intensity during the past decades due to significant variations in rainfall data.