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Results for “Advances in Water Resources”

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At least 55 records · Page 3Linked to original sources
USGS2014

Analytical solutions for benchmarking cold regions subsurface water flow and energy transport models: one-dimensional soil thaw with conduction and advection

Numerous cold regions water flow and energy transport models have emerged in recent years. Dissimilarities often exist in their mathematical formulations and/or numerical solution techniques, but few analytical solutions exist for benchmarking flow and energy transport models that include pore water phase change. This paper presents a detailed derivation of the Lunardini solution, an approximate analytical solution for predicting soil thawing subject to conduction, advection, and phase change. Fifteen thawing scenarios are examined by considering differences in porosity, surface temperature, Darcy velocity, and initial temperature. The accuracy of the Lunardini solution is shown to be proportional to the Stefan number. The analytical solution results obtained for soil thawing scenarios with water flow and advection are compared to those obtained from the finite element model SUTRA. Three problems, two involving the Lunardini solution and one involving the classic Neumann solution, are recommended as standard benchmarks for future model development and testing.

Advances in Water Resources↗
USGS2015

Development of a new semi-analytical model for cross-borehole flow experiments in fractured media

Analysis of borehole flow logs is a valuable technique for identifying the presence of fractures in the subsurface and estimating properties such as fracture connectivity, transmissivity and storativity. However, such estimation requires the development of analytical and/or numerical modeling tools that are well adapted to the complexity of the problem. In this paper, we present a new semi-analytical formulation for cross-borehole flow in fractured media that links transient vertical-flow velocities measured in one or a series of observation wells during hydraulic forcing to the transmissivity and storativity of the fractures intersected by these wells. In comparison with existing models, our approach presents major improvements in terms of computational expense and potential adaptation to a variety of fracture and experimental configurations. After derivation of the formulation, we demonstrate its application in the context of sensitivity analysis for a relatively simple two-fracture synthetic problem, as well as for field-data analysis to investigate fracture connectivity and estimate fracture hydraulic properties. These applications provide important insights regarding (i) the strong sensitivity of fracture property estimates to the overall connectivity of the system; and (ii) the non-uniqueness of the corresponding inverse problem for realistic fracture configurations.

Advances in Water Resources↗
USGS2016

Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth

In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

Advances in Water Resources↗
USGS2016

The international river interface cooperative: Public domain flow and morphodynamics software for education and applications

This paper describes a new, public-domain interface for modeling flow, sediment transport and morphodynamics in rivers and other geophysical flows. The interface is named after the International River Interface Cooperative (iRIC), the group that constructed the interface and many of the current solvers included in iRIC. The interface is entirely free to any user and currently houses thirteen models ranging from simple one-dimensional models through three-dimensional large-eddy simulation models. Solvers are only loosely coupled to the interface so it is straightforward to modify existing solvers or to introduce other solvers into the system. Six of the most widely-used solvers are described in detail including example calculations to serve as an aid for users choosing what approach might be most appropriate for their own applications. The example calculations range from practical computations of bed evolution in natural rivers to highly detailed predictions of the development of small-scale bedforms on an initially flat bed. The remaining solvers are also briefly described. Although the focus of most solvers is coupled flow and morphodynamics, several of the solvers are also specifically aimed at providing flood inundation predictions over large spatial domains. Potential users can download the application, solvers, manuals, and educational materials including detailed tutorials at www.-i-ric.org . The iRIC development group encourages scientists and engineers to use the tool and to consider adding their own methods to the iRIC suite of tools.

Advances in Water Resources↗
USGS2016

Seasonal flows of international British Columbia-Alaska rivers: The nonlinear influence of ocean-atmosphere circulation patterns

The northern portion of the Pacific coastal temperate rainforest (PCTR) is one of the least anthropogenically modified regions on earth and remains in many respects a frontier area to science. Rivers crossing the northern PCTR, which is also an international boundary region between British Columbia, Canada and Alaska, USA, deliver large freshwater and biogeochemical fluxes to the Gulf of Alaska and establish linkages between coastal and continental ecosystems. We evaluate interannual flow variability in three transboundary PCTR watersheds in response to El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and North Pacific Gyre Oscillation (NPGO). Historical hydroclimatic datasets from both Canada and the USA are analyzed using an up-to-date methodological suite accommodating both seasonally transient and highly nonlinear teleconnections. We find that streamflow teleconnections occur over particular seasonal windows reflecting the intersection of specific atmospheric and terrestrial hydrologic processes. The strongest signal is a snowmelt-driven flow timing shift resulting from ENSO- and PDO-associated temperature anomalies. Autumn rainfall runoff is also modulated by these climate modes, and a glacier-mediated teleconnection contributes to a late-summer ENSO-flow association. Teleconnections between AO and freshet flows reflect corresponding temperature and precipitation anomalies. A coherent NPGO signal is not clearly evident in streamflow. Linear and monotonically nonlinear teleconnections were widely identified, with less evidence for the parabolic effects that can play an important role elsewhere. The streamflow teleconnections did not vary greatly between hydrometric stations, presumably reflecting broad similarities in watershed characteristics. These results establish a regional foundation for both transboundary water management and studies of long-term hydroclimatic and environmental change.

Alaska, British Columbia↗
USGS2016

Regional flow duration curves: Geostatistical techniques versus multivariate regression

A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.

Advances in Water Resources↗
USGS2018

Groundwater flow and heat transport for systems undergoing freeze-thaw: Intercomparison of numerical simulators for 2D test cases

In high-elevation, boreal and arctic regions, hydrological processes and associated water bodies can be strongly influenced by the distribution of permafrost. Recent field and modeling studies indicate that a fully-coupled multidimensional thermo-hydraulic approach is required to accurately model the evolution of these permafrost-impacted landscapes and groundwater systems. However, the relatively new and complex numerical codes being developed for coupled non-linear freeze-thaw systems require verification. This issue is addressed by means of an intercomparison of thirteen numerical codes for two-dimensional test cases with several performance metrics (PMs). These codes comprise a wide range of numerical approaches, spatial and temporal discretization strategies, and computational efficiencies. Results suggest that the codes provide robust results for the test cases considered and that minor discrepancies are explained by computational precision. However, larger discrepancies are observed for some PMs resulting from differences in the governing equations, discretization issues, or in the freezing curve used by some codes.

Advances in Water Resources↗
USGS2018

Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model

One important component of continental-scale hydrologic modeling is quantifying the level of uncertainty in long-term hydrologic simulations and providing a range of possible simulated streamflow and/or runoff values for gaged and ungaged locations. In this paper, uncertainty was quantified for simulated streamflow and runoff generated from a monthly water balance model (MWBM) at 1575 streamgages and 109,951 hydrologic response units (HRUs), which span the conterminous United States (CONUS). A stochastic-approach, which incorporated the properties of modeled streamflow residuals back into the simulated model output, was used to create time series of upper and lower uncertainty intervals (UIs) around the simulated monthly time series. This approach was applied to an existing hydrologic regionalization implementation. Metrics used to evaluate the UIs across the CONUS (the coverage ratio, average width index, and interval skill score) indicated that on average the UIs were reliable, skillful, and sharp in being able to both contain measured streamflow observations and reduce estimates of uncertainty based on expected model predictions. These uncertainty evaluation metrics can complement each other in characterizing model skill and uncertainty over large-scale domains.

Advances in Water Resources↗
USGS2019

UAV-based measurements of spatio-temporal concentration distributions of fluorescent tracers in open channel flows

A new method of unmanned aerial vehicle (UAV)-based tracer tests using RGB (red, green, blue) images was developed in order to acquire the spatio-temporal concentration distribution of tracer clouds in open channel flows. Tracer tests using Rhodamine WT were conducted to collect the RGB images using a commercial digital camera mounted on a UAV, and the concentration of Rhodamine WT using in-situ fluorometric probes. The correlation analysis showed that the in-situ measured concentrations of Rhodamine WT were strongly correlated with the digital number ( DN ) of the RGB images, even though the response of DN to the concentration was spatially heterogeneous. The empirical relationship between the DN values and the Rhodamine WT concentration data was estimated using artificial neural network (ANN) models. The trained ANN models, which consider the effect of water depth and river bed, accurately retrieved the detailed spatio-temporal concentration distributions of all study areas that had an R 2 higher than 0.9. The acquired spatio-temporal concentration distributions by the proposed method based on the UAV images gave general as well as detailed views of the tracer cloud moving dynamically in open channel flows that cannot be easily observed using conventional in-situ measurements.

Advances in Water Resources↗
USGS2019

Changes in hydrodynamics and wave energy as a result of seagrass decline along the shoreline of a microtidal back-barrier estuary

Seagrasses are marine flowering plants that provide key ecological services. In recent decades, multiple stressors have caused a worldwide decline in seagrass beds. Changes in bottom friction associated with seagrass loss are expected to influence the ability of estuarine systems to trap sediment inputs through local and regional changes in hydrodynamics. Herein, we conduct a numerical study using six historical maps of seagrass distribution in Barnegat Bay, USA, to demonstrate that reductions in seagrass coverage destabilize estuarine systems, decreasing their flood-dominance in the areas interested by seagrass disappearance and increasing bed-shear stress values across the entire back-barrier basin. Furthermore, we reveal how seagrass decline has considerably increased the impact of wind-waves on marsh edges between 1968 and 2009. From a comparison with a numerical experiment without submerged aquatic vegetation, we estimate that up to 40% of the computed wave thrust on marsh boundaries can be reduced by seagrass beds and we find that the location of a seagrass patch in addition to its aerial extent plays a crucial role in this attenuation process. This study highlights the benefits of seagrass meadows in enhancing estuarine resilience and reducing marsh-edge retreat by wind-wave attack, which is recognized as a chief agent in lateral marsh loss.

Advances in Water Resources↗
USGS2021

Simulating water and heat transport with freezing and cryosuction in unsaturated soil: Comparing an empirical, semi-empirical and physically-based approach

Freezing of unsaturated soil is an important process that influences runoff and infiltration in cold-climate regions. We used a simple numerical model to simulate water and heat transport with phase change in unsaturated soil via three different approaches: empirical, semi-empirical and physically based. We compared the performance and parameterization of each approach through testing on three experimental datasets. All approaches reproduced the observed unsaturated freezing process satisfactorily. The empirical cryosuction equation used in this study managed to capture observed cryosuction with a fixed empirical parameter value. The semi-empirical version therefore does not require calibration of a specific frozen soil related parameter. In view of simplicity, small computational demand and accurate performance, all three approaches are suitable for implementation in land-use schemes, catchment scale hydrological models, or multi-dimensional thermo-hydrological models.

Advances in Water Resources↗
USGS2023

Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach

Prediction of short- (i.e., aquifer is near or at saturated conditions) and long-time (i.e., aquifer is not near or at saturated conditions) baseflow recession characteristics at ungauged stream locations is a current challenge that has been primarily addressed by empirical approaches that relate these characteristics to basin attributes. However, the performance of these models is often only fair with coefficient of determination values ranging from 0.5 to 0.7. In this study, we propose a hybrid physical and machine learning approach to predict the long- and short-time baseflow recession characteristics at ungauged stream locations. This approach is compared to a machine learning method, random forest regression, that relates baseflow recession characteristics to basin attributes in 582 basins across the western and eastern United States. The new approach resulted in lower median and inner quartile ranges (IQR) of absolute normalized errors in predicting long-time baseflow recession characteristics (western: 23%, IQR=32%; eastern: 30%, IQR=39%) compared to estimates of those properties based on random forest regressions (western: 27%, IQR=34%; eastern: 38%, IQR=50%). For the short-time baseflow recession characteristics, the hybrid approach resulted in substantially lower median errors and IQR values (western: 79%, IQR=143%; eastern: 83%, IQR=140%) compared to estimates from random forest regressions (western: 1,577%, IQR=8,887%; eastern: 341%, IQR=2,154%). In addition, this approach identified four major regions in the western United States and three in the eastern United States where the baseflow recession characteristics are mostly constant, and these characteristics only vary based on the geometric properties of aquifers. Lastly, the inter-basin variability of the baseflow recession characteristics was not found to be strongly related to metrics measuring interstorm arrival periods, average number of storms, and average length of storms.

Advances in Water Resources↗
USGS2024

Precipitation uncertainty estimation and rainfall-runoff model calibration using iterative ensemble smoothers

The introduction of iterative ensemble smoothers (IES) for parameter calibration opens avenues for expanding parameter space in surface water hydrologic modeling. Here, we have introduced independent parameters into a model calibration experiment to estimate errors in rainfall forcing data. This approach has the potential to estimate rainfall errors using other hydrological observations and to improve model calibration. Using high-resolution rain gauge data, we estimated “real” rainfall errors across the Turkey River watershed at storm and daily scales. Tests on synthetic and real-world scenarios successfully estimated errors correlated with observed values – even at daily scales. However, a bias remained from model parameter compensation, and identifying errors was challenging for low precipitation and snowfall. Despite synthetic results showing good error correlation, the biases in parameter identification masked potential improvements in hydrological calibration. This study highlights the potential of IES to provide additional information on rainfall errors, even only using streamflow observations.

Advances in Water Resources↗
USGS2025

Karhunen–Loève deep learning method for surrogate modeling and approximate Bayesian parameter estimation

We evaluate the performance of the Karhunen–Loève Deep Neural Network (KL-DNN) framework for surrogate modeling and approximate Bayesian parameter estimation in partial differential equation models. In the surrogate model, the Karhunen–Loève (KL) expansions are used for the dimensionality reduction of the number of unknown parameters and variables, and a deep neural network is employed to relate the reduced space of parameters to that of the state variables. The KL-DNN surrogate model is used to formulate a maximum-a-posteriori-like least-squares problem, which is randomized to draw samples of the posterior distribution of the parameters. We test the proposed framework for a hypothetical unconfined aquifer via comparison with the forward MODFLOW and inverse PEST++ iterative ensemble smoother (IES) solutions as well as the state-of-the-art Fourier neural operator (FNO) and deep operator networks (DeepONets) operator learning surrogate models. Our results show that the KL-DNN surrogate model outperforms FNO and DeepONet for forward predictions. For solving inverse problems, the randomized algorithm provides the same or more accurate Bayesian predictions of the parameters than IES as evidenced by the higher log predictive probability of both the estimated parameter field and the forecast hydraulic head. The posterior mean obtained from the randomized algorithm is closer to the reference parameter field than that obtained with FNO as the maximum a posteriori estimate.

Advances in Water Resources↗
USGS2025

The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics

This paper introduces the use of acoustic Doppler current profiler (ADCP) measurements as input for the Acoustic Mapping Velocimetry (AMV) method, a technique for characterizing the dynamics of riverine bedforms. The performance of this new approach, ADCP-AMV, is compared with input from a multibeam echosounder through a field study conducted on the Mississippi River (USA). A virtual ADCP tool has been created to support the ADCP-AMV measurements with optimal data density predictions. To the authors’ knowledge, this is the first time ADCP measurements have been used in conjunction with the AMV dune-tracking method. Subsequently, the paper discusses the coupling of ADCP-AMV measurements with ancillary data extracted from the ADCP. These ancillary data are processed using previously developed protocols to characterize hydrodynamics and the suspended sediment distribution in the water column. This paper emphasizes the capability of ADCPs to characterize open-channel river hydromorphodynamic parameters with high spatiotemporal resolution. Recommendations to accurately and efficiently acquire these multi-variable measurements and derived datasets are discussed.

Tennessee↗
USGS2002

Putting aquifers into atmospheric simulation models: An example from the Mill Creek Watershed, Northeastern Kansas

Aquifer-atmosphere interactions can be important in regions where the water table is shallow (<2 m). A shallow water table provides moisture for the soil and vegetation and thus acts as a source term for evapotranspiration to the atmosphere. A coupled aquifer-land surface-atmosphere model has been developed to study aquifer-atmosphere interactions in watersheds, on decadal timescales. A single column vertically discretized atmospheric model is linked to a distributed soil-vegetation-aquifer model. This physically based model was able to reproduce monthly and yearly trends in precipitation, stream discharge, and evapotranspiration, for a catchment in northeastern Kansas. However, the calculated soil moisture tended to drop to levels lower than were observed in drier years. The evapotranspiration varies spatially and seasonally and was highest in cells situated in topographic depressions where the water table is in the root zone. Annually, simulation results indicate that from 5-20% of groundwater supported evapotranspiration is drawn from the aquifer. The groundwater supported fraction of evapotranspiration is higher in drier years, when evapotranspiration exceeds precipitation. A long-term (40 year) simulation of extended drought conditions indicated that water table position is a function of groundwater hydrodynamics and cannot be predicted solely on the basis of topography. The response time of the aquifer to drought conditions was on the order of 200 years indicating that feedbacks between these two water reservoirs act on disparate time scales. With recent advances in the computational power of massively parallel supercomputers, it may soon become possible to incorporate physically based representations of aquifer hydrodynamics into general circulation models (GCM) land surface parameterization schemes. ?? 2002 Elsevier Science Ltd. All rights reserved.

Advances in Water Resources↗
USGS2001

River flow mass exponents with fractal channel networks and rainfall

An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable. ?? 2001 Elsevier Science Ltd. All rights reserved.

Advances in Water Resources↗
USGS2001

Tests of peak flow scaling in simulated self-similar river networks

The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.

Advances in Water Resources↗