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At least 613 records · Page 34Linked to original sources
USGS2019

A parametric numerical analysis of factors controlling ground ruptures caused by groundwater pumping

A modeling analysis is used to investigate the relative susceptibility of various hydrogeologic configurations to aseismic rupture generation due to deformation of aquifer systems accompanying groundwater pumping. An advanced numerical model (GEPS3D) is used to simulate rupture generation and propagation for three typical processes: (i) reactivation of a preexisting fault, (ii) differential compaction due to variations in thickness of aquifer/aquitard layers constituting the aquifer system, and (iii) tensile fracturing above a bedrock ridge that forms the base of the aquifer system. A sensitivity analysis is developed to address the relative importance of various factors, including aquifer depletion, aquifer thickness, the possible uneven distribution and depth below land surface of the aquifer/aquitard layers susceptible to aquifer-system compaction, and the height of bedrock ridges beneath the aquifer system which contributes to thinning of the aquifer system. The rupture evolution is classified in two occurrences. In one, the rupture develops at the top of the aquifer or at land surface and does not propagate. In the other, the developed rupture propagates from the aquifer top toward the land surface and/or from the land surface downward. The aquifer depth is the most important factor controlling rupture evolution. Specifically, the probability of a significant rupture propagation is higher when the aquifer top is near land surface. The numerical results are processed by a statistical regression analysis to provide a general methodology for a preliminary evaluation of possible ruptures development in exploited aquifer systems susceptible to aquifer-system compaction and accompanying land subsidence. A comparison with a few representative case studies in Arizona, USA, China, and Mexico supports the study outcomes.

Arizona↗
USGS2019

Advances in quantifying streamflow variability across continental scales: 2. Improved model regionalization and prediction uncertainties using hierarchical Bayesian methods

The precise estimation of process effects in hydrological models requires applying models to large scales with extensive spatial variability in controlling factors. Despite progress in large‐scale applications of hydrological models in conterminous United States (CONUS) river basins, spatial constraints in model parameters have prevented the interbasin sharing of data, complicating quantification of process effects and limiting the accuracy of model predictions and uncertainties. Hierarchical Bayesian methods enable data sharing between basins and the identification of the causes of model uncertainties, which can improve model accuracy and interpretability; however, computational inefficiencies have been an obstacle to their large‐scale application. We used a new generation of Bayesian methods to develop a hierarchical version of a previous hybrid (statistical‐mechanistic) SPAtially Referenced Regression On Watershed attributes model of long‐term mean annual streamflow in the CONUS. We identified hierarchical (regional) variations in model coefficients and uncertainties and evaluated their effects on model accuracy and interpretability across diverse environments in 16 major CONUS regions. Hierarchical coefficients significantly improved spatial accuracy of model predictions, with the largest improvements in humid eastern regions, where uncertainties were approximately one third of those in arid western regions. Half of the coefficients varied regionally, with the largest variations in coefficients associated with water losses in streams and reservoirs. Our unraveling of the causes of model uncertainties identified a small latent process component of runoff that varies inversely with river size in most CONUS regions. Our study advances the use of hierarchical Bayesian methods to improve the predictive capabilities of hydrological models.

Water Resources Research↗
USGS2019

Copula theory as a generalized framework for flow-duration curve-based streamflow estimates in ungaged and partially gaged catchments

Flow‐duration curve (FDC) based streamflow estimation methods involve estimating an FDC at an ungaged or partially gaged location and using the time series of nonexceedance probabilities estimated from donor streamgage sites to generate estimates of streamflow. We develop a mathematical framework to illustrate the connection between copulas and prior FDC‐based approaches. The performance of copula methods is compared to several other streamflow estimation methods using a decade of daily streamflow data from 74 sites located within two river basins in the southeast United States with different climate characteristics and physiographic properties. We show that copula approaches: (1) outperform other methods in the limiting case of perfect information with regard to the rank‐based correlation structure and FDCs across the gaging network; (2) provide a hedge against poor performance when donor information becomes sparser and less informative; (3) outperform other methods when used for partially gaged sites with several years of available data; and (4) remain a competitive albeit nondominating method for ungaged sites and partially gaged sites with limited data when realistic error is introduced in the estimation of FDCs and correlations across the gaging network.

Water Resources Research↗
USGS2019

River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model

Accurate quantification of riverine water‐quality concentration and flux is challenging because monitoring programs typically collect concentration data at lower frequencies than discharge data. Statistical methods are often used to estimate concentration and flux on days without observations. One recently developed approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS), which has been shown to provide among the most accurate estimates compared to other common methods. The main objective of this work was to improve WRTDS estimation by accounting for the autocorrelation structure of model residuals using the first‐order autoregressive model (AR1). This modified approach, called WRTDS‐Kalman Filter (WRTDS‐K), was compared with WRTDS for six constituents including nitrate‐plus‐nitrite (NO x ), total phosphorus, total Kjeldahl nitrogen, soluble reactive phosphorus, suspended sediment, and chloride. Near‐daily concentration records at nine sites were used to generate subsets through Monte Carlo sampling for five different sampling scenarios. Results show that WRTDS‐K provided generally better daily estimates of concentration and flux than WRTDS under these sampling scenarios for all constituents, especially NO x . The degree of improvement is strongly affected by the underlying sampling scenario, with WRTDS‐K gaining more advantage when more samples are available, and hence more residuals can be exploited. The performance of WRTDS‐K depends on the AR1 coefficient (ρ) and that relationship varies with constituents and sampling scenarios. These results provided recommendations on the optimal ρ for each constituent and sampling scenario. Overall, WRTDS‐K has the potential for broad applications to monitoring records elsewhere, as demonstrated by a pilot application to Chesapeake Bay tributaries.

Ohio↗
USGS2020

An experimental study of longitudinal incisional grooves in a mixed bedrock-alluvial channel

Natural bedrock rivers have various bedforms created by erosion. Flow‐parallel incisional grooves formed longitudinally in bedrock are one common example of such bedforms. Although several studies have been conducted regarding these grooves, their formation processes are not well understood. In this study, we conducted a flume experiment to investigate the relationship between the flow structure and longitudinal grooves. The experimental results strongly suggest that longitudinal grooves are formed by moving sediment concentrated in multiple longitudinal pathways by turbulence‐driven secondary flows. The sediment preferentially abrades the bedrock along these flow‐parallel pathways resulting in longitudinal grooves in the bedrock. Measurements of the flow velocity distribution show that the positions of secondary flow cells producing the initial formation of the grooves are altered by the formation of those grooves. Because displaced secondary flows tend to make the sediment collide with the sidewalls of the longitudinal grooves, the grooves grow wider over time and some grooves partially combine with other adjacent grooves. The initial maximum number of longitudinal grooves N max strongly depends on the river width‐depth ratio B / D , which defines the number of secondary flow cells, and can be expressed as N max = 0.5 B / D . However, because some grooves coalesce with other grooves due to the effects of the displacement of secondary flows, the average number of grooves showed a relationship that can be expressed as N = 0.41 B / D . Based on this relationship, we inversely estimated the flow discharge of the Abashiri River using the number of longitudinal grooves observed in the river. The result was consistent with the observed annual maximum flow discharge of the river. This suggests that the number of longitudinal grooves can be used as an indicator for estimation of the formative flow discharge in bedrock rivers.

Water Resources Research↗
USGS2019

Assessing the feasibility of satellite-based thresholds for hydrologically driven landsliding

Elevated soil moisture and heavy precipitation contribute to landslides worldwide. These environmental variables are now being resolved with satellites at spatiotemporal scales that could offer new perspectives on the development of landslide warning systems. However, the application of these data to hydro-meteorological thresholds (which account for antecedent soil moisture and rainfall) first need to be evaluated with respect to proven, direct measurement-based thresholds that use rain gauges and in situ soil moisture sensors. Here, we compare ground-based hydrologic data to overlapping satellite-based data before, during, and after a recent season of widespread shallow landsliding in the San Francisco Bay Area (California, USA). We then explore how the remotely sensed information could be used to empirically define hypothetical thresholds for shallow landsliding. We find that the ground-based thresholds developed with a single monitoring station show superior performance because the in situ soil saturation data better reflect the gravity-dominated subsurface flow conditions that are characteristic of hillslopes during the rainy season. Although the satellite-based thresholds can identify most of the landslide days, they include a greater number of false alarms due to overestimates of soil moisture between major storm events. To avoid the type of false alarms that are characteristic of our satellite-based thresholds, further post-processing of the near-surface hydrologic response data to better reflect gravity-dominated drainage should be integrated into satellite-based model outputs. Our results encourage further deployment of ground stations in landslide-prone terrain and cautious exploration of satellite-based hydro-meteorological thresholds where in situ networks are nonexistent.

California↗
USGS2020

Estimating bedload from suspended load and water discharge in sand bed rivers

Estimates of fluvial sediment discharge from in situ instruments are an important component of large‐scale sediment budgets that track long‐term geomorphic change. Suspended sediment load can be reliably estimated using acoustic or physical sampling techniques; however, bedload is difficult to measure directly and can consequently be one of the largest sources of uncertainty in estimates of total load. We propose a physically informed predictive empirical model for bedload sand flux as a function of variables that are measured using existing acoustic or physical sampling techniques. This model depends on the assumption that concentration and grain size in suspension are in equilibrium with reach‐averaged boundary conditions. Bayesian inference is used to fit model parameters to data from eight sand‐bed rivers and to simulate bedload flux over the available gage record at one site on the Colorado River in Grand Canyon National Park. We find that the cumulative bedload flux during the 9 year period from 2008 to 2016 was 5% of the cumulative suspended sand load; however, instantaneous bedload flux ranged from as little as 1% of instantaneous suspended sand load to as much as 75% of instantaneous suspended sand load due to fluctuations in flow strength and sediment supply. Changes in bedload flux at a constant discharge are indicative of short‐term sediment supply enrichment and depletion. Long‐term average bedload flux cannot be expected to remain constant in the future as the river adjusts to changes in sediment runoff and the dam‐regulated discharge regime.

Arizona↗
USGS2019

Multiorder hydrologic position in the conterminous United States: A set of metrics in support of groundwater mapping at regional and national scales

The location of a point on the landscape within a stream network (hydrologic position) can be an important predictive measure in hydrology. Hydrologic position is defined here by two metrics: lateral position and distance from stream to divide, both measured horizontally. Lateral position (dimensionless) is the relative position of a point between the stream and its watershed divide. Distance from stream to divide (units of length) is an indicator of position within a watershed: generally small near a confluence and generally large in headwater areas. Watersheds and watershed divides are defined here by Thiessen polygons rather than topographic divides. Lateral position and distance from stream to divide are also defined in the context of hydrologic order. Hydrologic order “ n ” is defined as the network of streams, and associated divides, of order n and higher. And given that a point can have different positions in different hydrologic orders the term multiorder hydrologic position (MOHP) is used to describe the ensemble of hydrologic positions. MOHP was mapped across the conterminous United States for nine hydrologic orders at a spatial resolution of 30 m (about 8.7 billion pixels). There are 18 metrics for each pixel. Four case studies are presented that use MOHP metrics as explanatory factors in random forest machine learning models. The case studies show that lower order MOHP metrics can serve as indicators of hydrologic process while higher‐order metrics serve as indicators of location. MOHP is shown to have utility as a predictor variable across a large range of scales (50,000 to 8,000,000 km 2 ).

Water Resources Research↗
USGS2020

Formation criteria for hyporheic anoxic microzones: Assessing interactions of hydraulics, nutrients and biofilms

Recent experimental studies have detected the presence of anoxic microzones in hyporheic sediments. These microzones are small‐scale anoxic pores, embedded within oxygen‐rich porous media and can act as anaerobic reaction sites producing reduction compounds such as nitrous oxide, a potent greenhouse gas. Microbes are a key control on nutrient transformation in hyporheic sediment, but their associated biomass growth is also capable of altering hydraulic flux, leading to potential bioclogging. Here, we developed one of the first computational modeling approaches that combined hydraulics and microbial conditions to explore the continuous evolution of microzones in stream sediments. The model assessed stream and sediment conditions with different hydraulic flux (0.1–1.0 m/day Darcy flux), nutrient concentrations (O 2 = 8 mg/L, OrgC = 20 mg/L, NO − 3 = 1.5–3 mg/L, and NH 3 = 0.5–1 mg/L), and biomass scenarios (with and without). The model domain is a pore network model with random sized pore‐throat radii creating heterogeneous and anisotropic flow that is representative of a natural streambed composed of medium sand with a hydraulic conductivity of 0.8 m/day. Results from 30 day simulations indicate that hyporheic microzone formation will occur and microzone distributions are not simply controlled by residence time alone, rather by the complex interactions of hydraulic flux, nutrient concentrations, and biomass, with bioclogging having strong feedbacks on both hydraulics and nutrients. Under all conditions with biomass growth, anoxic microzones were unstable, perishing a few days after formation, because bioclogging primarily occurs near the influent (downwelling) area of the hyporheic zone. In turn, this bioclogging shifts transport conditions from advection‐dominated to diffusion‐dominated transport, removing all oxic regions in the hyporheic zone. Overall, results from the modeling show that anoxic microzones are likely to form under many hyporheic zone conditions, and be dynamic through space and time as they are dependent on both hydraulic flux and nutrient transport.

Water Resources Research↗
USGS2020

Fundamental hydraulics of cross sections in natural rivers: Preliminary analysis of a large data set of acoustic doppler flow measurements

We have assembled a comprehensive and publicly accessible U.S. Geological Survey (USGS) streamflow measurement data set, called HYDRoSWOT, from a USGS National Water Information System archive of acoustic Doppler current profiler river discharge measurements collected from a wide range of rivers throughout the United States. The data set provides a wealth of information on the range of hydraulic characteristics of river cross sections in the United States. Preliminary exploration of the data set, filtered for quality control, indicates that rivers tend toward consistent and predictable forms as discharge increases. The ratio of maximum-to-mean depth is highly predictable and is remarkably consistent across all river sizes and discharges. Distributions of hydraulic characteristics provide a large-scale perspective on the general hydraulic characteristics of rivers. The data set affords the opportunity to analyze hydraulic relations for individual rivers as a function of stage, geomorphic setting, and energy environments and, combined with additional information contained in this data set, might yield predictive relations that could help constrain and parameterize river hydraulic models.

Water Resource Research↗
USGS2020

A classification of streamflow patterns across the coastal Gulf of Alaska

Streamflow controls many freshwater and marine processes, including salinity profiles, sediment composition, fluxes of nutrients, and the timing of animal migrations. Watersheds that border the Gulf of Alaska (GOA) comprise over 400,000 km 2 of largely pristine freshwater habitats and provide ecosystem services such as reliable fisheries for local and global food production. Yet no comprehensive watershed-scale description of current temporal and spatial patterns of streamflow exists within the coastal GOA. This is an immediate need because the spatial distribution of future streamflow patterns may shift dramatically due to warming air temperature, increased rainfall, diminishing snowpack, and rapid glacial recession. Our primary goal was to describe variation in streamflow patterns across the coastal GOA using an objective set of descriptors derived from flow predictions at the downstream-most point within each watershed. We leveraged an existing hydrologic runoff model and Bayesian mixture model to classify 4,140 watersheds into 13 classes based on seven streamflow statistics. Maximum discharge timing (annual phase shift) and magnitude relative to mean discharge (amplitude) were the most influential attributes. Seventy-six percent of watersheds by number showed patterns consistent with rain or snow as dominant runoff sources, while the remaining watersheds were driven by rain-snow, glacier, or low-elevation wetland runoff. Streamflow classes exhibited clear mechanistic links to elevation, ice coverage, and other landscape features. Our classification identifies watersheds that might shift streamflow patterns in the near future and, importantly, will help guide the design of studies that evaluate how hydrologic change will influence coastal GOA ecosystems.

Alaska↗
USGS2020

Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy

Modelling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small-scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium-complexity energy-balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in RMSE). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned, and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parametrizations and canopy metrics can be applied for high-resolution simulations of the sub-canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub-grid parametrizations without necessitating complex high-resolution models.

Water Resources Research↗
USGS2020

The future of sediment transport and streamflow under a changing climate and the implications for long-term resilience of the San Francisco Bay-Delta

Sedimentation and turbidity have effects on habitat suitability in the San Francisco Bay‐Delta (Bay‐Delta), concerning key species in the bay as well as the ability of the delta marshes to keep pace with sea level rise. A daily rainfall runoff and transport model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the Bay‐Delta for the next century (water years, WY2010–2099). The model was calibrated to historical streamflow and sediment data and applied using 10 Global Climate Models with two representative concentration pathways (RCP) each for WY1980–2099 from the IPCC 5th Assessment Report. Results indicate average increases in peak streamflow of +58% and +66% for the RCP 4.5 and 8.5 ensembles, respectively, by mid‐century and +62 and +96% by end‐of‐century. Sediment loads increased by +39% and +69% by end‐of‐century. Suspended sediment concentrations (SSC) increased on average by +4.6% and +6.7% for RCP 4.5 and 8.5, respectively, by end‐of‐century. Individual scenario results varied, and statistically significant increasing trends of sediment loads to the Bay‐Delta were found for the RCP 4.5 and 8.5 ensembles and five individual scenarios. Increased suspended sediment loads may have negative effects such as contaminant transport but also have positive effects that help protect against sea level rise, increase turbidity and fish habitat, and sustain wetland habitats in the Bay‐Delta.

California↗
USGS2020

Probabilistic categorical groundwater salinity mapping from airborne electromagnetic data adjacent to California’s Lost Hills and Belridge oil fields

Growing water stress has led to emerging interest in protecting fresh and brackish groundwater as a potential supplement to water supplies and raised questions about factors that could affect the future quality of fresh and brackish aquifers. Limited well infrastructure, particularly in regions where elevated salinity has led to limited historical groundwater development, hinders traditional mapping of salinity distributions through groundwater sampling. This paper presents a quantitative salinity mapping approach of the upper 300 m using high‐resolution, regionally comprehensive resistivity models derived from Bayesian inversion of an airborne electromagnetic survey adjacent to the Lost Hills and Belridge oil fields in the southwestern San Joaquin Valley of California. Using local water quality observations as an interpretational foundation, a probabilistic approach yields maps of fresh, saline, and brackish groundwater while quantifying joint uncertainty inherited from the geophysical data and interpretational relations. Saline and fresh regions are mapped with relatively high confidence in many locations, while areas of lower confidence, particularly at depth, can be mapped as their most probable salinity category while reflecting the relative uncertainty in the interpretation. These maps identify a stratified salinity structure, where saline water commonly occurs in the surficial aquifer overlying fresher groundwater in the Tulare aquifer, separated by regional confining clay layers. Downgradient of unlined surface water diversions, recharge of imported surface water results in relatively fresh groundwater throughout the depth of investigation.

California↗
USGS2021

Signatures of hydrologic function across the critical zone observatory network

Despite a multitude of small catchment studies, we lack a deep understanding of how variations in critical zone architecture lead to variations in hydrologic states and fluxes. This study characterizes hydrologic dynamics of 15 catchments of the U.S. Critical Zone Observatory (CZO) network where we hypothesized that our understanding of subsurface structure would illuminate patterns of hydrologic partitioning. The CZOs collect data sets that characterize the physical, chemical, and biological architecture of the subsurface, while also monitoring hydrologic fluxes such as streamflow, precipitation, and evapotranspiration. For the first time, we collate time series of hydrologic variables across the CZO network and begin the process of examining hydrologic signatures across sites. We find that catchments with low baseflow indices and high runoff sensitivity to storage receive most of their precipitation as rain and contain clay‐rich regolith profiles, prominent argillic horizons, and/or anthropogenic modifications. In contrast, sites with high baseflow indices and low runoff sensitivity to storage receive the majority of precipitation as snow and have more permeable regolith profiles. The seasonal variability of water balance components is a key control on the dynamic range of hydraulically connected water in the critical zone. These findings lead us to posit that water balance partitioning and streamflow hydraulics are linked through the coevolution of critical zone architecture but that much work remains to parse these controls out quantitatively.

Water Resources Research↗
USGS2020

Land use effects on sediment nutrient processes in a heavily modified watershed using structural equation models

Contemporary land use can affect sediment nutrient processes in rivers draining heavily modified watersheds; however, studies linking land use to sediment nutrient processes in large river networks are limited. In this study, we developed and evaluated structural equation models (SE models) for denitrification and phosphorus retention capacity to determine direct and indirect linkages between current land use and sediment nutrient processes during baseflow in the Fox River watershed, Wisconsin USA. A large spatial-scale dataset used for this study included sediment nitrogen and phosphorus retention measurements and land use information for 106 sites. The SE models for the Fox River watershed identified direct links between current land use and in-stream sediment nutrient processes. Sub-watersheds with agricultural land consisting of more natural land cover had lower surface water nitrate concentrations and higher denitrification enzyme activity than sub-watersheds with less alternative cover. This suggests that best management practices implemented in the Fox River watershed that restore natural land cover can improve water quality through nitrogen removal on the agricultural landscape and in the river network. Best management practices are not having the same measurable affect on phosphorus in the river network, most likely due to legacy phosphorus stored in the sediment.

Wisconsin↗
USGS2020

Calibrated simulation of the long-term average surficial groundwater system and derived spatial distributions of its characteristics for the contiguous United States

While the physical processes governing groundwater flow are well understood, and the computational resources now exist for solving the governing equations in three dimensions over continental-scale domains, there remains substantial uncertainty about the subsurface distribution of the properties that control groundwater flow and transport for much of the contiguous United States (CONUS). The transmissivity of the shallow subsurface is a key parameter for the simulation of water table position, shallow groundwater flow, and base-flow discharge, but is not well-characterized at large regional to continental scales. We used a process-based inversion of CONUS-extent groundwater information to generate national data sets of (a) the transmissivity of the shallow groundwater system, (b) the depth to the water table, (c) groundwater discharge as base-flow, and (d) long-term average water content in the unsaturated zone. CONUS-extent coverage was developed in the form of 75 subdomain models, with the spatial distribution of long-term average transmissivity for each subdomain model calibrated against water-levels derived from U.S. Geological Survey (USGS) observation wells, NHDPlusV2 first-order perennial streams, and National Wetlands Inventory (NWI) freshwater wetlands. Estimated transmissivities were lower in the western CONUS than the eastern CONUS, and across the CONUS both transmissivity and depth to water correlate with recharge, elevation, and topographic slope. These generated data sets provide spatially distributed, long-term average estimates of subsurface properties and hydrological states that we anticipate will complement other environmental modeling efforts as explanatory variables, boundary conditions, or transport pathways.

contiguous United States↗
USGS2020

A one‐dimensional model for turbulent mixing in the benthic biolayer of stream and coastal sediments

In this paper, we develop and validate a rigorous modeling framework, based on Duhamel's Theorem, for the unsteady one-dimensional vertical transport of a solute across a flat sediment-water interface (SWI) and through the benthic biolayer of a turbulent stream. The modeling framework is novel in capturing the two-way coupling between evolving solute concentrations above and below the SWI and in allowing for a depth-varying diffusivity. Three diffusivity profiles within the sediment (constant, exponentially decaying, and a hybrid model) are evaluated against an extensive set of previously published laboratory measurements of turbulent mass transfer across the SWI. The exponential diffusivity profile best represents experimental observations and its reference diffusivity scales with the permeability Reynolds number, a dimensionless measure of turbulence at the SWI. The depth over which turbulence-enhanced diffusivity decays is of the order of centimeters and comparable to the thickness of the benthic biolayer. Thus, turbulent mixing across the SWI may serve as a universal transport mechanism, supplying the nutrient and energy fluxes needed to sustain microbial growth, and nutrient processing, in the benthic biolayer of stream and coastal sediments.

Water Resources Research↗