Understanding streamflow generation at the catchment scale requires quantifying how different components of the system are linked, and how they respond to meteorological forcing. Here we use a data-driven nonlinear deconvolution and demixing approach, Ensemble Rainfall-Runoff Analysis (ERRA), to characterize and quantify dynamic linkages between precipitation, groundwater recharge, and streamflow in a mesoscale intensively farmed catchment. Streamflow in this catchment is flashy, but occurs at time lags that are too long to be plausibly attributed to overland flow runoff. Instead, the impulse responses of groundwater recharge to precipitation, and of streamflow to groundwater recharge, imply that this intermittent runoff is primarily driven by precipitation infiltrating to recharge groundwater, followed by linear-reservoir discharge of groundwater to streamflow. Streamflow increases nonlinearly with increasing precipitation intensity or groundwater recharge, and exhibits almost no runoff response to precipitation or recharge rates of less than 10 mm d−1. Groundwater recharge is both nonlinear, increasing more-than-proportionally with precipitation intensity, and nonstationary, increasing with antecedent wetness. Simulations with the infiltration model Hydrus-1D reproduce the observed water table time series reasonably well (NSE=0.70). However, the model’s impulse response is inconsistent with the observed impulse response estimated from measured precipitation and groundwater recharge, illustrating that goodness-of-fit statistics can be weak tests of model realism. Our analysis demonstrates how impulse responses estimated by ERRA can help quantify nonlinearity and nonstationarity in hydrologic processes, and can help clarify the mechanistic linkages between precipitation and streamflow at the catchment scale.

The forest-floor litter layer can retain substantial volumes of water, thus affecting evaporation and soil-moisture dynamics. However, litter layer wetting/drying dynamics are often overlooked when estimating forest water budgets. Here, we present field and laboratory experiments characterizing water cycling in the forest-floor litter layer and outline its implications for subcanopy microclimatic conditions and for estimates of transpiration and recharge. Storage capacities of spruce needle litter and beech broadleaf litter averaged 3.1 and 1.9 mm, respectively, with drainage/evaporation timescales exceeding 2 days. Litter-removal experiments showed that litter reduced soil water recharge, reduced soil evaporation rates, and insulated against ground heat fluxes that impacted snowmelt. Deadwood stored ~0.7 mm of water, increasing with more advanced states of decomposition, and retained water for >7 days. Observed daily cycles in deadwood weight revealed decreasing water storage during daytime as evaporation progressed and increasing storage at night from condensation or absorption. Water evaporating from the forest-floor litter layer modulates the subcanopy microclimate by increasing humidity, decreasing temperature, and reducing VPD. Despite the relatively small litter storage capacity (<3.1 mm in comparison to ~102 mm for typical forest soil rooting zones), the litter layer alone retained and cycled 18% of annual precipitation, or 1/3 of annual evapotranspiration. These results suggest that overlooking litter interception may lead to substantial overestimates of recharge and transpiration in many forest ecosystems.

Stream networks are highly abundant across Earth’s surface, reflecting the tectonic and climatic history under which they have developed. Recent studies suggest that branching angles are strongly correlated with climatic aridity. However, the impact of tectonic forcing, especially in tectonically active regions, remains ambiguous. Here we analyze the branching angles of major stream networks on the eastern Tibetan Plateau, a region with complex tectonics, variable climate, and diverse landscapes. We find that spatial variations in tectonic uplift (as reflected in channel gradients) shape the branching geometry of stream networks on the steep eastern margin while in the flat interior of the eastern Tibetan Plateau, branching angles are mainly controlled by climatic aridity. This leads to the conclusion that, in the steep margin of the eastern Tibetan Plateau, climatic impacts on branching angles are overprinted by stronger tectonic controls.

The spatio-temporal variability of bedload transport processes poses considerable challenges for bedload monitoring systems. One such system, the Swiss plate geophone (SPG), has been calibrated in several gravel-bed streams using direct sampling techniques. The linear calibration coefficients linking the signal recorded by the SPG system to the transported bedload can vary between different monitoring stations by about a factor of six, for reasons that remain unclear. Recent controlled flume experiments allowed us to identify the grain-size distribution of the transported bedload as a further site-specific factor influencing the signal response of the SPG system, along with the flow velocity and the bed roughness. Additionally, impact tests performed at various field sites suggested that seismic waves generated by impacting particles can propagate over several plates of an SPG array, and thus potentially bias the bedload estimates. To gain an understanding of this phenomenon, we adapted a test flume by installing a partition wall to shield individual sensor plates from impacting particles. We show that the SPG system is sensitive to seismic waves that propagate from particle impacts on neighboring plates or on the concrete bed close to the sensors. Based on this knowledge, we designed a filter method that uses time-frequency information to identify and eliminate these “apparent” impacts. Finally, we apply the filter to four field calibration datasets and show that it significantly reduces site-to-site differences between calibration coefficients and enables the derivation of a single calibration curve for total bedload at all four sites.

Trees in seasonal climates may use water originating from both winter and summer precipitation. However, the seasonal origins of water used by trees have not been systematically studied. We used stable isotopes of water to compare the seasonal origins of water found in three common tree species across 24 Swiss forest sites sampled in two different years. Water from winter precipitation was observed in trees at most sites, even at the peak of summer, although the relative representation of seasonal sources differed by species. However, the representation of winter precipitation in trees decreased with site mean annual precipitation in both years; additionally, it was generally lower in the cooler and wetter year. Together, these relationships show that precipitation amount influenced the seasonal origin water taken up by trees across both time and space. These results suggest higher turnover of the plant-available soil-water pool in wetter sites and wetter years.

Hydrological analyses and their associated uncertainties are a function of their supporting observational datasets. Publicly available large-sample hydrology datasets covering a range of climates, times, and locations can be used to support inter-watershed comparisons, pattern identification, and watershed regionalization studies. However, most of the large-sample datasets are limited to a series of basic measurements such as precipitation, air temperature, and streamflow. Here we synthesized data from 30 intensively monitored catchments with soil moisture, snowmelt, and other hydrometeorological observations at daily scale across the US. This data synthesis product, CHOSEN (CONUS/Comprehensive Hydrologic Observatory SEnsor Network), includes watersheds from the Long-Term Ecological Research (LTER) and Critical Zone Observatory (CZO) networks, and several other ecological and hydrological observatories. Catchments span diverse climate gradients and encompass multiple biomes and ecosystems. To achieve a consistent and standardized data product, we first implemented data cleaning and control procedures with strict variable naming conventions and unit conversions. Following data quality control, data processing methods, including gap filling by interpolation, linear regression, and climate catalog-based techniques, were implemented to produce alternative level-2 products. The data and metadata were written into self-describing NetCDF files, facilitating ease of access by multiple computer platforms. All python coding scripts, ranging from processing to accessing the NetCDF files, are publicly available, along with a user-friendly tutorial. The standardizations adopted here, and the availability of the data-processing pipeline, will facilitate future additions of new observations to this database. We anticipate that this synthesis will support comparative long-term hydrological studies and contribute to a growing body of open-source research in watershed and ecosystem science.