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Results for “Journal of Computational Physics”

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At least 37 records · Page 2Linked to original sources
USGS2009

Numerical models of caldera deformation: Effects of multiphase and multicomponent hydrothermal fluid flow

Ground surface displacement (GSD) in large calderas is often interpreted as resulting from magma intrusion at depth. Recent advances in geodetic measurements of GSD, notably interferometric synthetic aperture radar, reveal complex and multifaceted deformation patterns that often require complex source models to explain the observed GSD. Although hydrothermal fluids have been discussed as a possible deformation agent, very few quantitative studies addressing the effects of multiphase flow on crustal mechanics have been attempted. Recent increases in the power and availability of computing resources allow robust quantitative assessment of the complex time-variant thermal interplay between aqueous fluid flow and crustal deformation. We carry out numerical simulations of multiphase (liquid-gas), multicomponent (H 2O-CO2) hydrothermal fluid flow and poroelastic deformation using a range of realistic physical parameters and processes. Hydrothermal fluid injection, circulation, and gas formation can generate complex, temporally and spatially varying patterns of GSD, with deformation rates, magnitudes, and geometries (including subsidence) similar to those observed in several large calderas. The potential for both rapid and gradual deformation resulting from magma-derived fluids suggests that hydrothermal fluid circulation may help explain deformation episodes at calderas that have not culminated in magmatic eruption.

Journal of Geophysical Research B: Solid Earth↗
USGS2016

A glacier runoff extension to the Precipitation Runoff Modeling System

A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.

Journal of Geophysical Research F: Earth Surface↗
USGS2013

2D IR spectra of cyanide in water investigated by molecular dynamics simulations

Using classical molecular dynamics simulations, the 2D infrared (IR) spectroscopy of CN − solvated in D 2 O is investigated. Depending on the force field parametrizations, most of which are based on multipolar interactions for the CN − molecule, the frequency-frequency correlation function and observables computed from it differ. Most notably, models based on multipoles for CN − and TIP3P for water yield quantitatively correct results when compared with experiments. Furthermore, the recent finding that T 1 times are sensitive to the van der Waals ranges on the CN − is confirmed in the present study. For the linear IR spectrum, the best model reproduces the full widths at half maximum almost quantitatively (13.0 cm −1 vs. 14.9 cm −1 ) if the rotational contribution to the linewidth is included. Without the rotational contribution, the lines are too narrow by about a factor of two, which agrees with Raman and IR experiments. The computed and experimental tilt angles (or nodal slopes) α as a function of the 2D IR waiting time compare favorably with the measured ones and the frequency fluctuation correlation function is invariably found to contain three time scales: a sub-ps, 1 ps, and one on the 10-ps time scale. These time scales are discussed in terms of the structural dynamics of the surrounding solvent and it is found that the longest time scale (≈10 ps) most likely corresponds to solvent exchange between the first and second solvation shell, in agreement with interpretations from nuclear magnetic resonance measurements.

Journal of Chemical Physics↗
USGS2025

Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning

As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.

Nankai subduction zone↗
USGS1997

Regionalized loads of sediment and phosphorus to lakes Michigan and Superior—high flow and long-term average

Daily loads of suspended sediment and total phosphorus for the 10-year, 1-day design high flow and average of the 16-year period (1975 to 1990) were computed for 18 well-monitored tributaries to Lake Michigan and Lake Superior by use of constituent-transport models. The loads from these 18 reference tributaries were used to estimate the loads from all the United States tributaries (with drainage basins greater than 325 km 2 ) to Lake Michigan and Lake Superior by selection of a reference tributary with the most similar physical characteristics and use of a unit-area yield. Statistical comparisons between computed yields and environmental factors were used to determine the physical characteristics that were most influential in selecting a reference tributary. Suspended sediment yields were affected primarily by river gradient and secondarily by the texture of surficial deposits, whereas total phosphorus yields were affected primarily by the texture of surficial deposits and secondarily by river gradient. Average total phosphorus loads were greatest in rivers entering the middle to southern part of Lake Michigan, especially those draining clayey surficial deposits in agricultural areas. During high flow, loads of phosphorus and suspended sediment from tributaries entering the southwestern part of Lake Superior dominate the total input of these constituents because of the steep gradients of the rivers and the clayey surficial deposits that they drain. These loads were used to compute regional loads and to rank the tributaries on the basis of their respective loads during a specified high flow and over extended periods.

Michigan, Illinois, Wisconsin↗
USGS2007

Calculation of nonlinear confidence and prediction intervals for ground-water flow models

A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that inclusion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.

Journal of the American Water Resources Associatio↗
USGS2023

In-stream laser diffraction for measuring suspended sediment concentration and particle size distribution in rivers: Insights from field campaigns

This study evaluates the laser in situ scattering and transmissometry (LISST) instrument LISST-SL2, a laser diffraction instrument for suspended sediment sampling in rivers, with concurrent physical measurements of suspended sediment concentration (SSC) and particle size distribution (PSD) as well as velocity measurements by an acoustic Doppler current profiler (ADCP). We collected 136 LISST-SL2 samples along with 61 physical samples for SSC measurement, of which 24 physical samples included PSD measurement during 2018–2020 from 11 sites in Washington state and Virginia. An effective density is required to convert the measured volumetric SSC by the LISST-SL2 into a reported mass SSC, and by default the LISST-SL2 assumes a value of 2.65 g / mL . From our data set, we computed effective densities (mass SSC/volumetric SSC) that ranged from 0.5 to 5.4 g / mL , with a best-fit value of 2.05 g / mL . Additionally, the LISST-SL2 was not able to measure the finest sediment sizes in suspension, which affects the resulting PSD. Therefore, we propose some adjustments of the LISST-SL2 data with a supporting physical sample to account for these effective density and PSD issues. When doing so, we were able to reduce the root-mean square relative error (RMSRE) to 18% from 117% for SSC, and to 26% from 78% for PSD. LISST-SL2 velocities were generally higher than ADCP velocities with a 21% RMSRE. Our results and guidance will allow for more accurate sampling by the LISST-SL2, which has potential for studying spatial and temporal variation of suspended sediment characteristics in rivers.

Virginia, Washington↗
USGS2017

Benchmarking computational fluid dynamics models of lava flow simulation for hazard assessment, forecasting, and risk management

Numerical simulations of lava flow emplacement are valuable for assessing lava flow hazards, forecasting active flows, designing flow mitigation measures, interpreting past eruptions, and understanding the controls on lava flow behavior. Existing lava flow models vary in simplifying assumptions, physics, dimensionality, and the degree to which they have been validated against analytical solutions, experiments, and natural observations. In order to assess existing models and guide the development of new codes, we conduct a benchmarking study of computational fluid dynamics (CFD) models for lava flow emplacement, including VolcFlow, OpenFOAM, FLOW-3D, COMSOL, and MOLASSES. We model viscous, cooling, and solidifying flows over horizontal planes, sloping surfaces, and into topographic obstacles. We compare model results to physical observations made during well-controlled analogue and molten basalt experiments, and to analytical theory when available. Overall, the models accurately simulate viscous flow with some variability in flow thickness where flows intersect obstacles. OpenFOAM, COMSOL, and FLOW-3D can each reproduce experimental measurements of cooling viscous flows, and OpenFOAM and FLOW-3D simulations with temperature-dependent rheology match results from molten basalt experiments. We assess the goodness-of-fit of the simulation results and the computational cost. Our results guide the selection of numerical simulation codes for different applications, including inferring emplacement conditions of past lava flows, modeling the temporal evolution of ongoing flows during eruption, and probabilistic assessment of lava flow hazard prior to eruption. Finally, we outline potential experiments and desired key observational data from future flows that would extend existing benchmarking data sets.

Journal of Applied Volcanology↗
USGS2002

Adaptive moving mesh methods for simulating one-dimensional groundwater problems with sharp moving fronts

Accurate modelling of groundwater flow and transport with sharp moving fronts often involves high computational cost, when a fixed/uniform mesh is used. In this paper, we investigate the modelling of groundwater problems using a particular adaptive mesh method called the moving mesh partial differential equation approach. With this approach, the mesh is dynamically relocated through a partial differential equation to capture the evolving sharp fronts with a relatively small number of grid points. The mesh movement and physical system modelling are realized by solving the mesh movement and physical partial differential equations alternately. The method is applied to the modelling of a range of groundwater problems, including advection dominated chemical transport and reaction, non-linear infiltration in soil, and the coupling of density dependent flow and transport. Numerical results demonstrate that sharp moving fronts can be accurately and efficiently captured by the moving mesh approach. Also addressed are important implementation strategies, e.g. the construction of the monitor function based on the interpolation error, control of mesh concentration, and two-layer mesh movement. Copyright ?? 2002 John Wiley and Sons, Ltd.

International Journal for Numerical Methods in Eng↗
USGS2016

An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth’s system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty.

Journal of Hydrology↗
USGS2010

A universal approximation to grain size from images of non-cohesive sediment

The two-dimensional spectral decomposition of an image of sediment provides a direct statistical estimate, grid-by-number style, of the mean of all intermediate axes of all single particles within the image. We develop and test this new method which, unlike existing techniques, requires neither image processing algorithms for detection and measurement of individual grains, nor calibration. The only information required of the operator is the spatial resolution of the image. The method is tested with images of bed sediment from nine different sedimentary environments (five beaches, three rivers, and one continental shelf), across the range 0.1 mm to 150 mm, taken in air and underwater. Each population was photographed using a different camera and lighting conditions. We term it a “universal approximation” because it has produced accurate estimates for all populations we have tested it with, without calibration. We use three approaches (theory, computational experiments, and physical experiments) to both understand and explore the sensitivities and limits of this new method. Based on 443 samples, the root-mean-squared (RMS) error between size estimates from the new method and known mean grain size (obtained from point counts on the image) was found to be ±≈16%, with a 95% probability of estimates within ±31% of the true mean grain size (measured in a linear scale). The RMS error reduces to ≈11%, with a 95% probability of estimates within ±20% of the true mean grain size if point counts from a few images are used to correct bias for a specific population of sediment images. It thus appears it is transferable between sedimentary populations with different grain size, but factors such as particle shape and packing may introduce bias which may need to be calibrated for. For the first time, an attempt has been made to mathematically relate the spatial distribution of pixel intensity within the image of sediment to the grain size.

Journal of Geophysical Research F: Earth Surface↗
USGS2023

Using DC resistivity ring array surveys to resolve conductive structures around tunnels or mine-workings

In underground environments, conventional direct current (DC) resistivity surveys with a single linear array of electrodes produce fundamentally non-unique inversions. These non-uniqueness and model resolution issues stem from limitations placed on the location of transmitters (TXs) and receivers (RXs) by the geometry of existing tunnels and boreholes. Poor excitation and/or sampling of the region of interest (ROI) can create artifacts and reduce the resolution of the recovered model. To address these problems we propose the use of an ensemble of ring arrays, which are created by placing one or more electrodes in each face (sidewalls, floor, and ceiling) of the tunnel to form a ring of electrodes at each along-tunnel location. Using a series of increasingly complex synthetic models, we assess the benefits of ring arrays and show that they can be used to better constrain the location and shape of anomalous bodies around the tunnel. Although ring arrays significantly improve the resolution of the recovered model, the size of the comprehensive ring array survey increases rapidly with the number of electrodes used. To balance model resolution and survey size, we developed a physics-based survey design methodology. In this methodology, TXs are selected based upon secondary charge accumulations on a test block that is moved throughout the ROI. Although this survey design methodology does not produce a strictly optimal survey, it balances model resolution and survey size in a practical and computationally efficient manner. Since the ring array more accurately estimates the around-tunnel location of targets and ensures that targets on all sides of the tunnel are detected, it is ideally suited to tunnel-based environments. Our results show that only about 6 % "> 6% of the possible TXs and 0.5 % "> 0.5% of the RXs in the comprehensive ring array survey are needed to retain the improvements in resolution. Therefore, economical ring array surveys can be designed for both reconnaissance and target characterization. Following the inversion of the reconnaissance dataset, additional rings can be added to reduce the inter-ring spacing or off-tunnel boreholes can be added to the region around identified anomalies to increase resolution as required.

Journal of Applied Geophysics↗
USGS2024

RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale

Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research: Earth Surface↗
USGS2021

Temporal seismic velocity variations: Recovery following from the 2019 Mw 7.1 Ridgecrest, California earthquake

We investigated seismic velocity changes ( dv / v ) associated with the 2019 Ridgecrest earthquake sequence with high‐frequency autocorrelations of ambient seismic noise data. Daily autocorrelation functions were computed for the entirety of 2019 and the first quarter of 2020 for broadband stations within the region, including the temporary broadband stations installed during the aftershock deployment. Travel time shifts in the daily autocorrelation functions, relative to the mean autocorrelation waveform, were computed to produce dv / v time series, which are sensitive to the evolving material properties of the shallow crust surrounding the Ridgecrest fault zone (RFZ). A short‐term velocity drop follows the M w 7.1 earthquake at stations in the vicinity of the rupture surface, while those greater than 50 km away showed no such drop. The maximum, absolute changes in seismic velocity are proportional to the logarithm of distance from the fault rupture and to the peak dynamic strain experienced during the earthquake. Near the areas of the highest coseismic slip within the RFZ, seismic velocities recovered over 3 months. However, in the vicinity of the nearby Garlock fault, where triggered slip manifested, and north of the RFZ, seismic velocities recovered within a month. We interpret the seismic velocity changes and their recovery to be largely due to changes in the physical properties of the shallow crust, such as fault zone damage recovery caused by the earthquake rupture process and in response to the large dynamic stresses of passing seismic waves from the mainshock.

California↗
USGS2016

Debris flow runup on vertical barriers and adverse slopes

Runup of debris flows against obstacles in their paths is a complex process that involves profound flow deceleration and redirection. We investigate the dynamics and predictability of runup by comparing results from large-scale laboratory experiments, four simple analytical models, and a depth-integrated numerical model (D-Claw). The experiments and numerical simulations reveal the important influence of unsteady, multidimensional flow on runup, and the analytical models highlight key aspects of the underlying physics. Runup against a vertical barrier normal to the flow path is dominated by rapid development of a shock, or jump in flow height, associated with abrupt deceleration of the flow front. By contrast, runup on sloping obstacles is initially dominated by a smooth flux of mass and momentum from the flow body to the flow front, which precedes shock development and commonly increases the runup height. D-Claw simulations that account for the emergence of shocks show that predicted runup heights vary systematically with the adverse slope angle and also with the Froude number and degree of liquefaction (or effective basal friction) of incoming flows. They additionally clarify the strengths and limitations of simplified analytical models. Numerical simulations based on a priori knowledge of the evolving dynamics of incoming flows yield quite accurate runup predictions. Less predictive accuracy is attained in ab initio simulations that compute runup based solely on knowledge of static debris properties in a distant debris flow source area. Nevertheless, the paucity of inputs required in ab initio simulations enhances their prospective value in runup forecasting.

Journal of Geophysical Research F: Earth Surface↗
USGS2022

Toward next-generation lava flow forecasting: Development of a fast, physics-based lava propagation model

During effusive volcanic crises, the eruption and propagation of lava flows pose a significant hazard to nearby populations, homes, and infrastructure. Consequently, timely lava flow forecasts are a critical need for volcano observatory and emergency management operations. Previous lava flow modeling tools are typically either too slow to produce timely forecasts, or are fast, but lack critical aspects of lava physics or important forecasting outputs. In particular, the strong thermal stratification present in laminar, high-Prandtl number flows has generally been neglected. Bulk rheological changes have previously been computed from cell-averaged temperatures, assuming that the flow is thermally mixed. Here, we detail the development and initial testing of Lava2d, a new two-dimensional depth-averaged finite volume model of lava flow propagation over natural terrain which accounts for bulk rheological changes due to thermorheological stratification. We use a novel approach to energy conservation based on tracking cooling and solidifying at the flow base and at the moving flow surface, allowing for the estimation of more realistic vertical thermorheological profiles, while maintaining computational efficiency, producing very timely model runs. We validate our approach with three examples: comparison with theoretical propagation of crust-dominated lava flows, comparison with a large-scale molten basalt experiment from the Syracuse University Lava Project, and efficiency testing and comparison with the initial phase of the 1984 Mauna Loa lava flows. Our model is shown to produce rapid, realistic forecasts, making it a good candidate for operationalization in active volcanic regions such as in Hawai'i.

Journal of Geophysical Research - Solid Earth↗
USGS2012

Testing alternative conceptual models of seawater intrusion in a coastal aquifer using computer simulation, southern California, USA

Two alternative conceptual models of the physical processes controlling seawater intrusion in a coastal basin in California, USA, were tested to identify a likely principal pathway for seawater intrusion. The conceptual models were tested by using a two-dimensional, finite-element groundwater flow and transport model. This pathway was identified by the conceptual model that best replicated the historical data. The numerical model was applied in cross section to a submarine canyon that is a main avenue for seawater to enter the aquifer system underlying the study area. Both models are characterized by a heterogeneous, layered, water-bearing aquifer. However, the first model is characterized by flat-lying aquifer layers and by a high value of hydraulic conductivity in the basal aquifer layer, which is thought to be a principal conduit for seawater intrusion. The second model is characterized by offshore folding, which was modeled as a very nearshore outcrop, thereby providing a shorter path for seawater to intrude. General conclusions are that: 1) the aquifer system is best modeled as a flat, heterogeneous, layered system; 2) relatively thin basal layers with relatively high values of hydraulic conductivity are the principal pathways for seawater intrusion; and 3) continuous clay layers of low hydraulic conductivity play an important role in controlling the movement of seawater.

Hydrogeology Journal↗
USGS2024

Improved efficient physics-based computational modeling of regional wave-driven coastal flooding for reef-lined coastlines

Coastal flooding affects low-lying communities worldwide and is expected to increase with climate change, especially along reef-lined coasts, where wave-driven flooding is particularly prevalent. However, current regional modeling approaches are either insufficient or too computationally expensive to accurately assess risks in these complex environments. This study introduces and validates an improved computationally efficient and physics-based approach to compute dynamic wave-driven regional flooding on reef-lined coasts. We coupled a simplified-physics flood model (SFINCS) with a one-dimensional wave transformation model (XBeach-1D). To assess the performance of the proposed approach, we compared its results with results from a fully resolving two-dimensional wave transformation model (XBeach-2D). We applied this approach for a range of storms and sea-level rise scenarios for two contrasting reef-lined coastal geomorphologies: one low relief area and one high relief area. Our findings reveal that SFINCS coupled with XBeach-1D generates flood extents comparable to those produced by XBeach-2D, with a hit rate of 92%. However, this method tends to underpredict the flood extent of weaker, high-frequency storms and overpredict stronger, low-frequency storms. Across scenarios, our approach overpredicted the mean flood water depth, with a positive bias of 7 cm and root mean square difference of 15 cm. Offering approximately 100 times greater computational efficiency than its two-dimensional XBeach counterpart, this flood modeling technique is recommended for wave-driven flood modeling in scenarios with high computational demands, such as modeling numerous scenarios or undertaking detailed regional-scale modeling.

Journal of Marine Science & Engineering↗