The changing climate is expected to affect the frequency and severity of climate-driven natural disasters throughout much of the world. Floods are a significant driver of damage to property and will be directly affected by a changing climate. To establish flood risk management strategies and make informed policy decisions, it is crucial to understand how the characteristics of significant floods may change due to climate change. In our study, we looked at the spatial distribution of trends from observed hydrometeorological variables in Italy between 1979 and 2018. For meteorological trends, we analyzed trends in Mean Spring Temperature (MST), as well as in the Annual Maximum Precipitation (AMP) accumulation at different durations, 24, 72, 120, and 168 hrs, both taken from a downscaled ERA5 gridded (8 × 8 km) dataset. For streamflow trends, we used Annual Maximum Flows (AMF) from 157 river gauges that are not influenced by the anthropogenic factors like reservoir regulation. We observed that (i) for MST, 88% showed significant positive and no negative significant, (ii) trends for AMP, 13 and 3% of grids show statistically significant positive and negative trends respectively, and (iii) for AMF, 6% of gauges show significant negative trends and 3% significant positive trends. Additionally, we explored the sensitivity of the MST, AMP, and AMF trends for different time periods of the data through multitemporal analysis. We will also discuss impacts on flood quantile at high return periods after detrending of Precipitation and AMF data to near-present climate, an important aspect for assessing the tail risk in the flood (re)insurance and industry.