The present study refers to the region of Bologna, where the availability of a 209-year-long daily rainfall series allows us to make a unique assessment of global climate models' reliability and their predicted changes in rainfall and multiyear droughts. Our results suggest carefully considering the impact of uncertainty when designing climate change adaptation policies for droughts. Rigorous use and comprehensive interpretation of the available information are needed to avoid mismanagement.

We investigated how stemflow (intercepted rainwater by the tree crown that travels down the stem) infiltrates within the soil. We simulated stemflow, applying coloured water along a tree trunk. Coloured patterns, observed when we excavated the soil after the experiment, were used to view and quantify preferential flow in the soil. We found that stemflow was mainly funnelled belowground along tree roots and macropores. Soil moisture near the trunk was affected both vertically and horizontally.

Mountains store and release water, serving as water towers for downstream regions and affecting global sediment and carbon fluxes. We use stream and rain chemistry to calculate how much streamflow comes from recent rainfall across seven sites in the Andes mountains and the nearby Amazon lowlands. We find that the type of rock and the intensity of rainfall control water retention and release, challenging assumptions that mountain topography exerts the primary effect on watershed hydrology.

Canopies change how rain reaches the soil: some spots receive more and others less water. It has long been debated whether this also leads to locally wetter and drier soil. We checked this using measurements of canopy drip and soil moisture. We found that the increase in soil water content after rain was aligned with canopy drip. Independently, the soil storage reaction was dampened in locations prone to drainage, like hig-macroporosity areas, suggesting that canopy drip enhances bypass flow.

This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.

Embedding input uncertainties in hydrological modelling naturally leads to stochastic models, which render parameter calibration an often computationally intractable problem. We use a case study from urban hydrology based on a stochastic rain model, and we employ a highly efficient Hamiltonian Monte Carlo inference algorithm with a timescale separation to demonstrate that fully fledged Bayesian inference with stochastic models is no longer off-limits for hydrological applications.

We present an automated, field-ready system that collects soil water vapor for stable isotope analysis. This system can be used to determine soil water evolution through time, which is helpful for understanding crop water use, water vapor fluxes to the atmosphere, and geologic proxy development. Our system can automatically collect soil water vapor and then store it for up to 30 d, which allows researchers to collect datasets from historically understudied, remote locations.

Mediterranean floods are causing major damage, and recent studies have shown that, despite the increase in intense rainfall, there has been no increase in river floods. This study reveals that the seasonality of floods changed in the Mediterranean Basin during 1959–2021. There was also an increased frequency of floods linked to short episodes of intense rain, associated with a decrease in soil moisture. These changes need to be taken into consideration to adapt flood warning systems.

We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.

This study used identified stormflow thresholds as a diagnostic tool to characterize abrupt variations in catchment emergent patterns pre- and post-earthquake. Earthquake-induced landslides with spatial heterogeneity and temporally undulating recovery increase the hydrologic nonstationary; thus, large post-earthquake floods are more likely to occur. This study contributes to mitigation and adaptive strategies for unpredictable hydrologic regimes triggered by abrupt natural disturbances.