Some streams respond to rainfall with flow that peaks twice: a sharp first peak followed by a broad second peak. We analyzed data from a catchment in Luxembourg to better understand the processes behind this phenomenon. Our results show that the first peak is mostly driven directly by rainfall, and the second peak is mostly driven by rain that infiltrates to groundwater. We also show that the relative importance of these two processes depends on how wet the landscape is before the rain falls.

We introduce GAMCR (Generalized Additive Models for Catchment Responses), a data-driven model that estimates how catchments respond to individual precipitation events. We validate GAMCR on synthetic data and demonstrate its ability to investigate the characteristic runoff responses from real-world hydrologic series. GAMCR provides new data-driven opportunities to understand and compare hydrological behavior across different catchments.

We study how Arctic rivers respond to rainfall in a warming climate. We show that runoff response can increase more than 5x under wetter conditions, and Active Layer Detachments amplify water and material runoff response to rainfall. Increasing subsurface storage can reduce runoff sensitivity to rainfall. Our results inform the flashiness of rainfall-runoff predictions based on expected weather and erosion conditions.

We used a new method to measure how streamflow responds to precipitation across a network of watersheds in Iran. Our analysis shows that streamflow is more sensitive to precipitation when groundwater levels are shallower, climates are more humid, topography is steeper, and drainage basins are smaller. These results are a step toward more sustainable water resource management and more effective flood risk mitigation.

This study explores how streams react to rain and how water travels through the landscape to reach them, two processes rarely studied together. Using detailed data from two temperate areas, we show that streams respond to rain much faster than rainwater travels to them. Wetter conditions lead to stronger runoff by releasing older stored water, while heavy rainfall moves newer rainwater to streams faster. These findings offer new insights into how water moves through the environment.

This study provides the first event-scale observational evidence that runoff sensitivity to precipitation decreases significantly in degrading permafrost regions of the Tibetan Plateau. Data-driven analysis reveals that permafrost thaw enhances infiltration and subsurface storage, reducing peak runoff and runoff coefficients, especially during heavy rainfall. These results are important for drought and flood risk management under climate change.

Here, I present a new way to quantify how streamflow responds to rainfall across a range of timescales. This approach can estimate how different rainfall intensities affect streamflow.  It can also quantify how runoff response to rainfall varies, depending on how wet the landscape already is before the rain falls. This may help us to understand processes and landscape properties that regulate streamflow and to assess the susceptibility of different landscapes to flooding.

We use a 3-year time series of tracer data of streamflow and soils to show how water moves through the subsurface to become streamflow. Less than 50% of soil water consists of rainfall from the last 3 weeks. Most annual streamflow is older than 3 months, and waters in deep subsurface layers are even older; thus deep layers are not the only source of streamflow. After wet periods more rainfall was found in the subsurface and the stream, suggesting that water moves quicker through wet landscapes.

The Alps are a key water resource for central Europe, providing water for drinking, agriculture, and hydropower production. To assess water availability in streams, we need to understand how much streamflow is derived from old water stored in the subsurface versus more recent precipitation. We use tracer data from 32 Alpine streams and statistical tools to assess how much recent precipitation can be found in Alpine rivers and how this amount is related to catchment properties and climate.

We study the seasonal and spatial patterns of soil moisture in 0–500 cm soil using 89 monitoring sites in a loess catchment with monsoonal climate. Soil moisture is highest during the months of least precipitation and vice versa. Soil moisture patterns at the hillslope scale are dominated by the aspect-controlled evapotranspiration variations (a local control), not by the hillslope convergence-controlled downslope flow (a nonlocal control), under both dry and wet conditions.

Monitoring sediment transport is relevant for flood safety and river restoration. However, the spatial and temporal variability of sediment transport processes makes their prediction challenging. We investigate the feasibility of a general calibration relationship between sediment transport rates and the impact signals recorded by metal plates installed in the channel bed. We present a new calibration method based on flume experiments and apply it to an extensive dataset of field measurements.

We present a new way to detect snowmelt using daily cycles in streamflow driven by solar radiation. Results show that warmer sites have earlier and more intermittent snowmelt than colder sites, and the timing of early snowmelt events is strongly correlated with the timing of streamflow volume. A space-for-time substitution shows greater sensitivity of streamflow timing to climate change in colder rather than in warmer places, which is then contrasted with land surface simulations.