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.

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.

We examine stream-power incision and linear diffusion landscape evolution models with and without incision thresholds. We present a steady-state relationship between curvature and the steepness index, which plots as a straight line. We view this line as a counterpart to the slope–area relationship for the case of landscapes with hillslope diffusion. We show that simple shifts and rotations of this line graphically express the topographic response of landscapes to changes in model parameters.

Extracting water from plant stems can introduce analytical errors in isotope analyses. We demonstrate that sensitivities to suspected errors can be evaluated and that conclusions drawn from extracted plant water isotope ratios are neither generally valid nor generally invalid. Ultimately, imperfect measurements of plant and soil water isotope ratios can continue to support useful inferences if study designs are appropriately matched to their likely biases and uncertainties.

Automated water samplers are often used to collect precipitation and streamwater samples for subsequent isotope analysis, but the isotopic signal of these samples may be altered due to evaporative fractionation occurring during the storage inside the autosamplers in the field. In this article we present and evaluate a cost-efficient modification to the Teledyne ISCO automated water sampler that prevents isotopic enrichment through evaporative fractionation of the water samples.

This paper presents a new distributed hydrological model: the distributed simple dynamical systems (dS2) model. The model is built with a focus on computational efficiency and is therefore able to simulate basins at high spatial and temporal resolution at a low computational cost. Despite the simplicity of the model concept, it is able to correctly simulate discharge in both small and mesoscale basins.

Low river flows affect societies and ecosystems. Here we study how precipitation and potential evapotranspiration shape low flows across a network of 380 Swiss catchments. Low flows in these rivers typically result from below-average precipitation and above-average potential evapotranspiration. Extreme low flows result from long periods of the combined effects of both drivers.

Streams and groundwaters often show daily cycles in response to snowmelt and evapotranspiration. These typically have a roughly 6 h time lag, which is often interpreted as a travel-time lag. Here we show that it is instead primarily a phase lag that arises because aquifers integrate their inputs over time. We further show how these cycles shift seasonally, mirroring the springtime retreat of snow cover to higher elevations and the seasonal advance and retreat of photosynthetic activity.

Evapotranspiration (ET) is the largest flux from the land to the atmosphere and thus contributes to Earth's energy and water balance. Due to its impact on atmospheric dynamics, ET is a key driver of droughts and heatwaves. In this paper, we demonstrate how averaging over land surface heterogeneity contributes to substantial overestimates of ET fluxes. We also demonstrate how one can correct for the effects of small-scale heterogeneity without explicitly representing it in land surface models.