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At least 649 records · Page 36Linked to original sources
USGS2021

Using turbulence to identify preferential areas for grass carp (Ctenopharyngodon idella) larvae in streams: A laboratory study

In this experimental series, we studied the swimming capabilities and response of grass carp ( Ctenopharyngodon idella ) larvae to flow turbulence in a laboratory flume. We compared three different experimental configurations, representing in‐stream obstructions commonly found in natural streams (e.g., a gravel bump, a single vertical cylinder, and patches of submerged rigid vegetation). Grass carp larvae (postgas bladder emergence) were introduced to each experimental configuration and subjected to a variety of hydrodynamic forces of different magnitudes and scales. We varied the flow velocities and water depths and found ranges of turbulent kinetic energy and Reynolds stresses that triggered a response in larval trajectories, identified by measured horizontal and vertical swimming speeds for each flow condition. Larvae apparently actively avoided areas with increased levels of turbulence by swimming away, moving faster in short bursts, and expending more energy. In addition to the magnitude of turbulent kinetic energy, the length scale and time scale of turbulent eddies also influenced the larvae response. These findings support the development of new strategies for controlling the spread of grass carp larvae in rivers, as well as the development of numerical tools incorporating active swimming capabilities to predict larval transport in streams.

Water Resources Research↗
USGS2020

Baseflow age distributions and depth of active groundwater flow in a snow‐dominated mountain headwater basin

Deeper flows through bedrock in mountain watersheds could be important, but lack of data to characterize bedrock properties limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow‐dominated, headwater basin of the Colorado River with a new method for dating baseflow age using dissolved gas tracers SF 6 , CFC‐113, N 2 , and Ar. The original flow model predicts the majority of groundwater flow through shallow alluvium (<8 m) sitting on top of less permeable bedrock. The water moves too quickly and is unable to reproduce observed SF 6 concentrations. To match gas data, bedrock permeability is increased to allow a larger fraction of deeper and older groundwater flow (median 112 m). The updated hydrologic model indicates interannual variability in baseflow age (3–12 years) is controlled by the volume of seasonal interflow and tightly coupled to snow accumulation and monsoon rain. Deeper groundwater flow remains stable (11.7 ± 0.7 years) as a function mean historical recharge to bedrock hydraulic conductivity (R/K). A sensitivity analysis suggests that increasing bedrock K effectively moves this alpine basin away from its original conceptualization of hyperlocalized groundwater flow (high R/K) with groundwater age insensitive to changes in water inputs. Instead, this basin is situated close to the precipitation threshold defining recharge controlled groundwater flow conditions (low R/K) in which groundwater age increases with small reductions in precipitation. Work stresses the need to explore alternative methods characterizing bedrock properties in mountain basins to better quantify deeper groundwater flow and predict their hydrologic response to change.

Colorado↗
USGS2021

Measuring and interpreting multilayer aquifer-system compactions for a sustainable groundwater-system development

Ever decreasing water resources and climate change have driven the increasing use of groundwater causing land subsidence in many countries. Geodetic sensors such as InSAR, GPS and leveling can detect surface deformation but cannot measure subsurface deformation. A single‐well, single‐depth extensometer can be used to measure subsurface deformation, but it cannot delineate the depths of major compaction and provide insight about the deformation mechanism throughout a complex aquifer system, unless man extensometers at different depths are used. We present a multilayer compaction well (MLCW), installed in a borehole, that uses magnetic rings to detect stratum compaction at 25 depths as deep as 300 m below land surface. Our laboratory and field assessments indicate 1 mm precision and accuracy for one single‐depth magnetic reading. We tested the performance of MLCW by measuring aquifer‐system compaction over the proximal, middle, and distal fans of the Choushui River Alluvial Fan (CRAF) that has long experienced severe land subsidence. The MLCW measurements were used to create time‐depth diagrams of compaction, showing different compaction rates at different layers of aquifers and aquitards to identify the depths of major compactions. The elastic (reversible) and inelastic (irreversible) compactions from MLCW were used in stress‐strain analyses to estimate skeletal specific storages and the safe groundwater levels, below which groundwater extractions have caused irreversible compactions. The hydrogeological parameters derived from MLCW measurements can help governmental agencies to determine effective land‐use and water‐use policies, and ascertain the best strategy for utilizing artificial recharge to prevent land subsidence and achieve sustainable groundwater management.

Water Resources Research↗
USGS2021

Machine learning predicted redox conditions in the glacial aquifer system, northern continental United States

Groundwater supplies 50% of drinking water worldwide and 30% in the United States. Geogenic and anthropogenic contaminants can, however, compromise water quality, thus limiting groundwater availability. Reduction/oxidation (redox) processes and redox conditions affect groundwater quality by influencing the mobility and transport of common geogenic and anthropogenic contaminants. In the glacial aquifer system, northern United States (GLAC, 1.87 million km 2 ), groundwater with high arsenic or manganese concentration is associated with reducing conditions and high nitrate with oxidizing conditions. This study uses machine learning to identify the relative influence of drivers of redox conditions (e.g., residence time vs. reactivity) across the glacial landscape. We developed three‐dimensional boosted regression tree models to predict redox conditions using the likelihood of low dissolved oxygen or high iron as indicators of anoxic conditions. Results indicate that variation in redox condition is controlled primarily by residence time (e.g., groundwater age and relative depth) and to a lesser extent by geochemical reactivity (e.g., subsurface contact time, soil carbon). Older water and deeper wells, along with more water storage or slower water movement was associated with higher probability of anoxic conditions. Mapped model results illustrate regions where anoxic redox conditions may mobilize geogenic contaminants or oxic conditions may limit denitrification potential. Results may also provide simplified redox input for process or predictive models of, for example, arsenic, manganese, or nitrate. Machine learning modeling methods can lead to improved understanding of contaminant occurrence and what drives redox conditions, and the methods may be transferable to other settings.

Northern Continental United States↗
USGS2021

Identification of seasonal streamflow regimes and streamflow drivers for daily and peak flows in Alaska

Alaska is among northern high‐latitude regions where accelerated climate change is expected to impact streamflow properties, including seasonality and primary flow drivers. Evaluating changes to streamflow, including flood characteristics, across this large and diverse environment can be improved by identifying the distribution and influence of flow drivers. Using metrics of mean monthly streamflow data from 253 streamgages, seasonal flow regimes were clustered to guide identification of seasonal‐flow drivers and form hydrologic groups for identification of peak‐flow populations. Nine seasonally distinct subclasses described variability within three classes dominated by (mostly fall) rainfall, (spring) snowmelt, and (summer) high‐elevation melt. The most glacierized basins exclusively grouped into high‐elevation melt subclasses, and less glacierized basins sometimes exhibited seasonal patterns aligned with rainfall‐ and snowmelt‐dominated regimes. Peak‐flow populations varied by subclass from dominant rainfall or dominant snowmelt to mixed rainfall‐snowmelt or mixed rainfall, snowmelt, and high‐elevation melt. Within subclasses, rainfall generated higher mean peak flows (relative to mean annual flow) than snowmelt or high‐elevation melt. Seasonal flow regimes showed clear but complex associations with basin characteristics, primarily elevation and winter temperature, and with geographic location. These dependencies provided elevation‐based analogies for changes associated with warming and insights for seasonal flow regime prediction and hydrologic region delineation. These results provide a spatially comprehensive perspective on seasonal streamflow drivers across Alaska from historical data and serve as an important historical basis for analysis.

Alaska↗
USGS2021

Characterization of groundwater recharge and flow in California's San Joaquin Valley from InSAR-observed surface deformation

Surface deformation in California's Central Valley (CV) has long been linked to changes in groundwater storage. Recent advances in remote sensing have enabled the mapping of CV deformation and associated changes in groundwater resources at increasingly higher spatiotemporal resolution. Here, we use interferometric synthetic aperture radar (InSAR) from the Sentinel‐1 missions, augmented by continuous Global Positioning System (cGPS) positioning, to characterize the surface deformation of the San Joaquin Valley (SJV, southern two‐thirds of the CV) for consecutive dry (2016) and wet (2017) water years. We separate trends and seasonal oscillations in deformation time series and interpret them in the context of surface and groundwater hydrology. We find that subsidence rates in 2016 (mean −42.0 mm/yr; peak −345 mm/yr) are twice that in 2017 (mean −20.4 mm/yr; peak −177 mm/yr), consistent with increased groundwater pumping in 2016 to offset the loss of surface‐water deliveries. Locations of greatest subsidence migrated outwards from the valley axis in the wetter 2017 water year, possibly reflecting a surplus of surface‐water supplies in the lowest portions of the SJV. Patterns in the amplitude of seasonal deformation and the timing of peak seasonal uplift reveal entry points and potential pathways for groundwater recharge into the SJV and subsequent groundwater flow within the aquifer. This study provides novel insight into the SJV aquifer system that can be used to constrain groundwater flow and subsidence models, which has relevance to groundwater management in the context of California's 2014 Sustainable Groundwater Management Act (SGMA).

California↗
USGS2021

Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates

The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters ( e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.

Water Resources Research↗
USGS2021

Direct observation of the depth of active groundwater circulation in an alpine watershed

The depth of active groundwater circulation is a fundamental control on stream flows and chemistry in mountain watersheds, yet it remains challenging to characterize and is rarely well constrained. We collected hydraulic conductivity, hydraulic head, temperature, chemical, noble gas, and 3 H/ 3 He groundwater age data from discrete levels in two boreholes 46 and 81 m deep in an alpine watershed, in combination with chemical and age data from shallow groundwater discharge, to discern groundwater flow rates at different depths and directly observe active and inactive groundwater. Vertical head gradients are steep (average of 0.4) and thermal profiles are consistent with typical linear conductive continental geotherms. Groundwater deeper than ∼20 m is distinct from shallow groundwater and creek water in its chemistry, noble gas signature, and age (dominantly >65 years compared to <9 years). Together these results suggest low vertical groundwater flow velocities and a relatively shallow active circulation depth of ∼20 m. This hypothesis is tested with a simple 2‐D numerical fluid flow and heat transport model representing a hillslope transect through the two boreholes. The modeling indicates that the subhorizontally bedded sedimentary rocks underlying the basin are highly anisotropic with low vertical hydraulic conductivity, and at most ∼10% of bedrock recharge (equivalent to <2% of stream baseflow) flows below a depth of 20 m. The study demonstrates the considerable value of discrete‐depth hydrogeologic, chemical, and age data for determining active circulation depth, and illustrates an approach for maximizing the utility of individual boreholes drilled for mountain bedrock aquifer characterization.

Colorado↗
USGS2021

Substantial declines in salinity observed across the Upper Colorado River Basin during the 20th century, 1929 to 2019

Salinity in the Colorado River Basin causes an estimated $300 to $400 million per year in economic damages in the U.S. To inform and improve salinity‐control efforts, this study quantifies long‐term trends in salinity (dissolved solids) across the Upper Colorado River Basin (UCRB), including time periods prior to the construction of large dams and preceding the implementation of salinity‐control projects. Weighted Regressions on Time, Discharge, and Season was used with datasets of dissolved‐solids and specific‐conductance measurements, collected as early as 1929, to evaluate long‐term trends in dissolved‐solids loads and concentrations in streams from 1929 to 2019 ( n =14). Results indicate that large, widespread, and sustained downward trends in dissolved‐solids concentrations and loads occurred over the last 50 to 90 years. For 12 of the 14 stream sites with significant downward change, median declines of ‐38% (range of ‐14 to ‐57%) and ‐40% (range of ‐9 to ‐65%) were observed for flow‐normalized concentration and load, respectively. Steepest rates of decline occurred from 1980 to 2000, coincident with the initiation of salinity‐control efforts in the 1980s. However, there was a consistent slowing or reversing of downward trends after 2000 even though salinity‐control efforts continued. Significant decreases in salinity occurred as early as the 1940s at some streams, indicating that, in addition to salinity‐control projects, changes in land cover, land use, and/or climate substantially affect salinity transport in the UCRB. Observed dissolved‐solids trends are likely the result of changes to watershed‐related processes, not due to changes in the streamflow regime.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2021

Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system

We present a field study combining measurements of vegetation density, vegetative drag, and reduction of suspended-sediment concentration (SSC) within patches of the invasive submerged aquatic plant Egeria densa . Our study was motivated by concern that sediment trapping by E. densa , which has proliferated in the Sacramento–San Joaquin Delta, is impacting marsh accretion and reducing turbidity. In the freshwater tidal Delta, E. densa occupies shallow regions, frequently along channel margins. We investigated two sites: Lindsey Slough, a muddy low-energy backwater, and the lower Mokelumne River, with stronger currents and sandy bed sediments. At the two sites biomass density, frontal area, and areal density of the submerged aquatic vegetation (SAV) were similar. Current attenuation within E. densa exceeded 90% and the vegetative drag coefficient followed , where is stem Reynolds number. The SAV reduced SSC by an average of 18% in Lindsey Slough. At Mokelumne River the reduction ranged 0–40%, with greatest trapping when discharge and SSC were elevated. This depletion of SSC decreases the transport of sediment to marshes by the same percentage, as the rising tide must pass through fringing SAV before reaching marshes. Sediment trapping in E. densa in the Delta is limited by low flux through the canopy and low settling velocity of suspended sediment (mostly flocculated mud). Sediment trapping by SAV has the potential to reduce channel SSC, but the magnitude and sign of the effect can vary with local factors including vegetative coverage and the depositional or erosional nature of the setting.

California↗
USGS2021

Estimating and forecasting time-varying groundwater recharge in fractured rock: A state-space formulation with preferential and diffuse flow to the water table

Rapid infiltration following precipitation may result in groundwater contamination from surface contaminants or pathogens. In fractured rock, contaminants can migrate rapidly to points of groundwater withdrawals. In contrast to the temporal availability of groundwater quality chemical indicators, meteorological and groundwater level observations are available in real-time to estimate time-varying recharge, which can act as a surrogate to identify periods of rapid infiltration that may indicate contamination susceptibility. Estimating recharge using methods, such as base-flow recession, unsaturated infiltration models, or Water-Table Fluctuations (WTF), cannot capitalize on currently available technologies and telecommunication infrastructure to conduct real-time recharge estimation at scales relevant to characterizing rapid infiltration. We present a linear, physics-based State-Space (SS) model of one-dimensional infiltration to estimate recharge, which includes preferential and diffuse-flow to the water table. The model can take advantage of real-time data for water-table altitude, precipitation, and evapotranspiration. Model parameters are calibrated over an observation period, and the Kalman Filter (KF) is subsequently applied to continuously update the observed (water-table altitude) and unobserved (groundwater recharge) system states and predict future states as new data become available. The SS/KF algorithm is demonstrated at the Masser Groundwater Recharge Site in Pennsylvania, USA and comparisons are made with recharge estimates from WTF methods. Model results indicate that the frequency of observations (daily versus sub-daily) dictates the allocation between preferential and diffuse flow. Additionally, because infiltration processes encompass many nonlinearities, model parameters estimated from observation periods need to be updated at least seasonally to account for changing recharge conditions.

Water Resources Research↗
USGS2021

Climate impacts on source contributions and evaporation to flow in the Snake River Basin using surface water isoscapes (δ2H and δ18O)

Rising global temperatures are expected to decrease the precipitation amount that falls as snow, causing greater risk of water scarcity, groundwater overdraft, and fire in areas that rely on mountain snowpack for their water supply. Streamflow in large river basins varies with the amount, timing, and type of precipitation, evapotranspiration, and drainage properties of watersheds; however, these controls vary in time and space making it difficult to identify the areas contributing most to flow and when. In this study, we separate the evaporative influences from source values of water isotopes from the Snake River Basin in the western United States (US) to relate source area to flow dynamics. We developed isoscapes (δ 2 H and δ 18 O) for the basin and found that isotopic composition of surface water in small watersheds is primarily controlled by longitude, latitude, and elevation. To examine temporal variability in source contributions to flow, we present a six-year record of Snake River water isotopes from King Hill, Idaho after removing evaporative influences. During periods of low flow, source water values were isotopically lighter indicating a larger contribution to flow from surface waters in the highest elevation, eastern portion of the basin. River evaporation increases were evident during summer likely reflecting climate, changing water availability, and management strategies within the basin. Our findings present a potential tool for identifying critical portions of basins contributing to river flow as climate fluctuations alter flow dynamics. This tool can be applied in other continental-interior basins where evaporation may obscure source water isotopic signatures.

Idaho, Montana, Oregon, Wyoming↗
USGS2021

Assessing the feasibility of managed aquifer recharge in California

With aquifers around the world stressed by over-extraction, water managers are increasingly turning to managed aquifer recharge (MAR), directly replenishing groundwater resources through injection wells, recharge basins, or other approaches. While there has been progress in understanding the geological and infrastructure-related considerations to make MAR more effective, critical evaluations of its institutional design and implementation are limited. This study assesses MAR projects, using a case study of projects proposed by groundwater sustainability agencies (GSAs) in California to comply with the state's Sustainable Groundwater Management Act of 2014; these projects will almost double the number of MAR projects in the United States. We draw on content analysis of groundwater sustainability plans that propose these projects. We first assess the types of recharge projects proposed and the stated aims of the projects, to assess when and why agencies are turning to MAR as a solution. We find that recharge basins are by far the most common approach, and that GSAs hope these basins will improve water table levels, reduce subsidence, and improve water quality. We then analyze potential barriers to project implementation and assess the projects' ability to achieve the stated goals. Primary concerns identified include a potential lack of available water, a potentially challenging legal framework, and minimal consideration of funding and cumulative land needs. To conclude, we discuss broader considerations for ensuring that MAR is an effective water management tool.

California↗
USGS2021

Anomalous noble gas solubility in liquid cloud water: Possible implications for noble gas temperatures and cloud physics

The noble gas temperature climate proxy is an established tool that has previously been applied to determine the source of groundwater recharge, however, unanswered questions remain. In fractured media (e.g., volcanic islands) recharge can be so rapid that groundwater is significantly depleted in heavy noble gases, indicating that the water has retained noble gas concentrations from higher elevations. Previous studies of rain samples have confirmed a match to patterns seen in fractured-rock groundwater for heavy noble gases along with a significant helium excess. Snow has been shown to be a credible source for both the helium excess and the observed heavy noble gas pattern. Here, liquid cloud water samples were collected at two mountainous sites and analyzed for noble gas concentrations. A pattern like that of rainwater was found. However, an analysis of diffusive uptake of noble gases into cloud water demonstrates that droplets of 1 mm diameter and smaller should be in constant solubility equilibrium with the atmosphere. To explain this, we present a novel hypothesis that relies on the assumption that liquid water consists of two types of water molecule clusters bounded by hydrogen bonds: a low-density ice-like structure and a high-density condensed structure. In this model, the pressure gradient near the surface of a droplet resulting from surface tension could allow for the formation of a surface layer that is rich in ice-like low density clusters. This can explain both the helium excess and the heavy noble gas depletion seen in the samples.

Puerto Rico↗
USGS2021

Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity

Upscaling groundwater flow is a fundamental challenge in hydrogeology. This study proposed time-fractional flow equations (t-FFEs) for upscaling long-term, transient groundwater flow and propagation of pressure heads in heterogeneous media. Monte Carlo simulations showed that, with increasing variance and correlation of the hydraulic conductivity ( K ), flow dynamics gradually deviated from Darcian flow and exhibit sub-diffusive, time-dependent evolution which can be separated into three major stages. At the early stage, the interconnected high- K zones dominated flow, while at intermediate times, the transverse flow due to mixed high- and low- K zones caused delayed rise of the piezometric head. At late times when flow in the relatively high- K domains reached stability, cells with very low- K continued to block the entry of water and generate “islands” with low piezometric head, significantly extending the temporal evolution of the piezometric head. The elongated water breakthrough curve cannot be quantified by the flow equation with an effective K , the space-fractional flow equation, or the multi-rate mass transfer (MRMT) flow model with a few rates, motivating the development of t-FFEs assuming temporally non-Darcian flow. Model applications showed that both the early and intermediate stages of flow dynamics can be captured by a single-index t-FFE (whose index is the exponent of the power-law probability density function of the random operational time for water parcels), but the overall evolution of flow dynamics, especially the enhanced retention of flow at later times, required a distributed-order t-FFE with variable indexes for different flow phases that can dominate flow dynamics at different stages. Therefore, transient groundwater flow in aquifers with spatially stationary heterogeneity can be temporally non-Darcian and non-stationary, due to the time-sensitive, combined effects of interconnected high- K channels and isolated low- K deposits on flow dynamics (which is the hydrogeological mechanism for the temporally non-Darcian flow and sub-diffusive pressure propagation), whose long-term behavior can be quantified by multi-index stochastic models.

Water Resources Research↗
USGS2021

Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Water Resources Research↗
USGS2021

Accounting for fine-scale forest structure is necessary to model snowpack mass and energy budgets in montane forests

Accurately modeling the effects of variable forest structure and change on snow distribution and persistence is critical to water resource management. The resolution of many snow models is too coarse to represent heterogeneous canopy structure in forests, and therefore, most models simplify forest effects on snowpack mass and energy budgets. To quantify the loss of snowpack prediction from simplifications of forest canopy-mediated processes, we applied a high-resolution energy balance snowpack model at two forested sites at a fine (1 m 2 ) and coarse (100 m 2 ) spatial resolution. Simulating open and forested areas separately, as is done in many land surface models (LSMs), leads to biases between the coarse and fine-scale simulations because there is no representation of areas that are near (e.g., <15 m from) trees but with no overhead canopy, which are common in forests of low to medium tree density. Consistent with previous LSM intercomparisons, the coarser simulations predict greater under-canopy radiation (by 30%–80% at our sites), faster snow ablation (by almost 2×), and earlier snow disappearance (by 1–22 days). Many of these biases are reduced dramatically or eliminated when canopy edge environments are considered in the coarser simulations. Furthermore, remaining disagreement between the 100-m and 1-m models can be partially explained by using a combination of tree height, canopy cover, and canopy edginess (which together can explain 46%–96% of remaining model biases). The lack of information about canopy edges and other fine-scale forest structure characteristics in many current LSMs may limit their reliability for simulating forest disturbance.

California, New Mexico↗
USGS2021

Concentration-discharge relationships of dissolved rhenium in Alpine catchments reveal its use as a tracer of oxidative weathering

Oxidative weathering of sedimentary rocks plays an important role in the global carbon cycle. Rhenium (Re) has been proposed as a tracer of rock organic carbon (OC petro ) oxidation. However, the sources of Re and its mobilization by hydrological processes remain poorly constrained. Here we examine dissolved Re as a function of water discharge, using samples collected from three alpine catchments that drain sedimentary rocks in Switzerland (Erlenbach, Vogelbach) and Colorado, USA (East River). The Swiss catchments reveal a higher Re flux in the catchment with higher erosion rates, but have similar [Re]/[Na + ] and [Re]/[SO 4 2- ] ratios, which indicate a dominance of Re from OC petro . Despite differences in rock type and hydro-climatic setting, the three catchments have a positive correlation between river water [Re]/[Na + ] and [Re]/[SO 4 2- ] and water discharge. We propose that this reflects preferential routing of Re from a near-surface, oxidative weathering zone. The observations support the use of Re as a proxy to trace rock-organic carbon oxidation, and suggest it may be a hydrological tracer of vadose zone processes. We apply the Re proxy, and estimate CO 2 release by OC petro oxidation of 5.7 +6.6 / -2.0 tC km -2 yr -1 for the Erlenbach. The overall weathering intensity was ∼40%, meaning that the corresponding export of un-weathered OC petro in river sediments is large, and the findings call for more measurements of OC petro oxidation in mountains and rivers as thet cross floodplains.

Water Resources Research↗