While assessing the effects of climate change at global or regional scales, local factors responsible for climate change are generalized, which results in the averaging of effects. However, climate change assessment is required at a micro-scale to determine the severity of climate change. To ascertain the impact of spatial scales on climate change assessments, trends and shifts in annual and seasonal (monsoon and non-monsoon), rainfall and temperature (minimum, average and maximum) were determined at three different spatial resolutions in India (Ajmer city, Ajmer District and Rajasthan State). The Mann–Kendall (MK), MK test with pre-whitening of series (MK–PW), and Modified Mann–Kendall (MMK) test, along with other statistical techniques were used for the trend analysis. The Pettitt–Mann–Whitney (PMW) test was applied to detect the temporal shift in climatic parameters. The Sen’s slope and % change in rainfall and temperature were also estimated over the study period (35 years). The annual and seasonal average temperature indicates significant warming trends, when assessed at a fine spatial resolution (Ajmer city) compared to a coarser spatial resolution (Ajmer District and Rajasthan State resolutions). Increasing trend was observed in minimum, mean and maximum temperature at all spatial scales; however, trends were more pronounced at a finer spatial resolution (Ajmer city). The PMW test indicates only the significant shift in non-monsoon season rainfall, which shows an increase in rainfall after 1995 in Ajmer city. The Kurtosis and coefficient of variation also revealed significant climate change, when assessed at a finer spatial resolution (Ajmer city) compared to a coarser resolution. This shows the contribution of land use/land cover change and several other local anthropogenic activities on climate change. The results of this study can be useful for the identification of optimum climate change adaptation and mitigation strategies based on the severity of climate change at different spatial scales.

The conservation of rainwater and augmentation of groundwater reserve is necessary to meet the increased water de-mands. Precipitation occurring in the smart cities need to be understood for a better water management action plan. There-fore, monotonic precipitation trend analysis was performed for eight smart cities drawn from six monsoon homogeneous regions across India. The precipitation data were investigated for trends using the modified Mann–Kendall (MMK) test and Sen’s slope estimator at annual, seasonal and monthly scales. The trend analysis was carried out over 118 years (from 1901 to 2018) at 95% significance level. The Dehradun city (Northern Himalayan region) showed a significant increasing annual precipitation trend (Z = +3.22). Indore and Bhopal cities from West Central region showed significant increasing annual trend (Z = +2.01) and non-significant decreasing annual trend respectively. Although, Vadodara and Jaipur are lying in the same Northwest region, the trends are opposite in nature. Jaipur city showed a significant increasing annual pre-monsoon trend (Z = +2.44). The winter rainfall in the city of Vadodara is showing a significant decreasing trend (Z = –2.16). The pre-monsoon rainfall in Bhubaneswar (Central Northeast region) and monsoon precipitation in Trivandrum (Peninsular region) are showing significant increasing (Z = +2.56) and decreasing (Z = –2.71) trends, respectively. A non-significant decreasing trend was seen in Guwahati city (Northeast region). The eight smart cities selected for investigation are not truly representing the entire country. However, the study is clearly pointing towards the regional disparity existing in the coun-try. These findings will be helpful for water managers and policymakers in these regions for better water management.