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Results for “Nonlinear Processes in Geophysics”

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At least 19 recordsLinked to original sources

Multifractal magnetic susceptibility distribution models of hydrothermally altered rocks in the Needle Creek Igneous Center of the Absaroka Mountains, Wyoming

Magnetic susceptibility was measured for 700 samples of drill core from thirteen drill holes in the porphyry copper-molybdenum deposit of the Stinkingwater mining district in the Absaroka Mountains, Wyoming. The magnetic susceptibility measurements, chemical analyses, and alteration class provided a database for study of magnetic susceptibility in these altered rocks. The distribution of the magnetic susceptibilities for all samples is multi-modal, with overlapping peaked distributions for samples in the propylitic and phyllic alteration class, a tail of higher susceptibilities for potassic alteration, and an approximately uniform distribution over a narrow range at the highest susceptibilities for unaltered rocks. Samples from all alteration and mineralization classes show susceptibilities across a wide range of values. Samples with secondary (supergene) alteration due to oxidation or enrichment show lower susceptibilities than primary (hypogene) alteration rock. Observed magnetic susceptibility variations and the monolithological character of the host rock suggest that the variations are due to varying degrees of alteration of blocks of rock between fractures that conducted hydrothermal fluids. Alteration of rock from the fractures inward progressively reduces the bulk magnetic susceptibility of the rock. The model introduced in this paper consists of a simulation of the fracture pattern and a simulation of the alteration of the rock between fractures. A multifractal model generated from multiplicative cascades with unequal ratios produces distributions statistically similar to the observed distributions. The reduction in susceptibility in the altered rocks was modelled as a diffusion process operating on the fracture distribution support. The average magnetic susceptibility was then computed for each block. For the purpose of comparing the model results with observation, the simulated magnetic susceptibilities were then averaged over the same interval as the measured data. Comparisons of the model and data from drillholes show good but not perfect agreement.

Wyoming↗

Scaling of peak flows with constant flow velocity in random self-similar networks

A methodology is presented to understand the role of the statistical self-similar topology of real river networks on scaling, or power law, in peak flows for rainfall-runoff events. We created Monte Carlo generated sets of ensembles of 1000 random self-similar networks (RSNs) with geometrically distributed interior and exterior generators having parameters p i and p e , respectively. The parameter values were chosen to replicate the observed topology of real river networks. We calculated flow hydrographs in each of these networks by numerically solving the link-based mass and momentum conservation equation under the assumption of constant flow velocity. From these simulated RSNs and hydrographs, the scaling exponents β and φ characterizing power laws with respect to drainage area, and corresponding to the width functions and flow hydrographs respectively, were estimated. We found that, in general, φ > β, which supports a similar finding first reported for simulations in the river network of the Walnut Gulch basin, Arizona. Theoretical estimation of β and φ in RSNs is a complex open problem. Therefore, using results for a simpler problem associated with the expected width function and expected hydrograph for an ensemble of RSNs, we give heuristic arguments for theoretical derivations of the scaling exponents β (E) and φ (E) that depend on the Horton ratios for stream lengths and areas. These ratios in turn have a known dependence on the parameters of the geometric distributions of RSN generators. Good agreement was found between the analytically conjectured values of β (E) and φ (E) and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ (E) and φ with respect to the value of flow velocity and runoff intensity implies an interesting connection between unit hydrograph theory and flow dynamics. Our results provide a reference framework to study scaling exponents under more complex scenarios of flow dynamics and runoff generation processes using ensembles of RSNs.

Nonlinear Processes in Geophysics↗

Multifractal model of magnetic susceptibility distributions in some igneous rocks

Measurements of in-situ magnetic susceptibility were compiled from mainly Precambrian crystalline basement rocks beneath the Colorado Plateau and ranges in Arizona, Colorado, and New Mexico. The susceptibility meter used measures about 30 cm 3 of rock and measures variations in the modal distribution of magnetic minerals that form a minor component volumetrically in these coarsely crystalline granitic to granodioritic rocks. Recent measurements include 50–150 measurements on each outcrop, and show that the distribution of magnetic susceptibilities is highly variable, multimodal and strongly non-Gaussian. Although the distribution of magnetic susceptibility is well known to be multifractal, the small number of data points at an outcrop precludes calculation of the multifractal spectrum by conventional methods. Instead, a brute force approach was adopted using multiplicative cascade models to fit the outcrop scale variability of magnetic minerals. Model segment proportion and length parameters resulted in 26 676 models to span parameter space. Distributions at each outcrop were normalized to unity magnetic susceptibility and added to compare all data for a rock body accounting for variations in petrology and alteration. Once the best-fitting model was found, the equation relating the segment proportion and length parameters was solved numerically to yield the multifractal spectrum estimate. For the best fits, the relative density (the proportion divided by the segment length) of one segment tends to be dominant and the other two densities are smaller and nearly equal. No other consistent relationships between the best fit parameters were identified. The multifractal spectrum estimates appear to distinguish between metamorphic gneiss sites and sites on plutons, even if the plutons have been metamorphosed. In particular, rocks that have undergone multiple tectonic events tend to have a larger range of scaling exponents.

Nonlinear Processes in Geophysics↗

Sediment transport under wave groups: Relative importance between nonlinear waveshape and nonlinear boundary layer streaming

Sediment transport under nonlinear waves in a predominately sheet flow condition is investigated using a two-phase model. Specifically, we study the relative importance between the nonlinear waveshape and nonlinear boundary layer streaming on cross-shore sand transport. Terms in the governing equations because of the nonlinear boundary layer process are included in this one-dimensional vertical (1DV) model by simplifying the two-dimensional vertical (2DV) ensemble-averaged two-phase equations with the assumption that waves propagate without changing their form. The model is first driven by measured time series of near-bed flow velocity because of a wave group during the SISTEX99 large wave flume experiment and validated with the measured sand concentration in the sheet flow layer. Additional studies are then carried out by including and excluding the nonlinear boundary layer terms. It is found that for the grain diameter (0.24 mm) and high-velocity skewness wave condition considered here, nonlinear waveshape (e.g., skewness) is the dominant mechanism causing net onshore transport and nonlinear boundary layer streaming effect only causes an additional 36% onshore transport. However, for conditions of relatively low-wave skewness and a stronger offshore directed current, nonlinear boundary layer streaming plays a more critical role in determining the net transport. Numerical experiments further suggest that the nonlinear boundary layer streaming effect becomes increasingly important for finer grain. When the numerical model is driven by measured near-bed flow velocity in a more realistic surf zone setting, model results suggest nonlinear boundary layer processes may nearly double the onshore transport purely because of nonlinear waveshape. Copyright 2010 by the American Geophysical Union.

Journal of Geophysical Research C: Oceans↗

Statistical approach to neural network imaging of karst systems in 3D seismic reflection data

The current lack of a robust, standardized technique for geophysical mapping of karst systems can be attributed to both the complexity of the environment and prior technological limitations. Abrupt lateral variations in physical properties that are inherent to karst systems generate significant geophysical noise, challenging conventional seismic signal processing and interpretation. Modern application of neural networks to multi-attribute seismic interpretation now provide a semiautomated method for identifying and leveraging the nonlinear relationships exhibited among seismic attributes. The ambiguity generally associated with designing neural networks for seismic object detection can be reduced via statistical analysis of the extracted attribute data. A data-driven approach to selecting the appropriate set of input seismic attributes, as well as the locations and minimum number of training examples, provides a more objective and computationally efficient method for identifying karst systems using reflection seismology. This statistically optimized neural network technique is thoroughly demonstrated using three-dimensional seismic reflection data collected from the southeastern portion of the Florida carbonate platform. Several dimensionality reduction methods are applied and the resulting karst probability models are evaluated relative to one another based on both quantitative and qualitative criteria. Comparing the preferred model, using quadratic discriminant analysis, to previously available seismic object detection workflows demonstrates the karst-specific nature of the tool. Results suggest that the karst multi-attribute workflow presented is capable of approximating the structural boundaries of karst systems with more accuracy and efficiency than a human counterpart or previously presented seismic interpretation schemes. This objective technique, using solely three-dimensional seismic reflection data, likely represents the most practical approach to mapping karst systems for subsequent hydrogeological modeling.

Interpretation↗

Thinking outside the rocks: Subsurface water storage, topography, and land cover are key modulators of large-scale riverine dissolved silicon dynamics

Riverine dissolved silicon (DSi) dynamics reflect integrated geologic, hydrologic, climatic, and ecological controls. We compiled annual DSi data for 337 rivers across four continents and trained interpretable machine-learning models to predict concentrations and yields from 28 watershed variables. Both models reproduced testing data ( R 2 = 0.85 for concentration and 0.96 for yield) and withheld-site validation ( R 2 = 0.91 and 0.93). Lithology, especially volcanic rock fraction, strongly controlled DSi while subsurface storage, topography, and land cover further shaped DSi dynamics. DSi concentrations and yields exhibited nonlinear responses to basin slope, recession-curve slope, proportion of open-water cover, and nutrient availability. Concentrations showed sharper threshold responses to hydrologic and biotic variables, whereas yields varied more gradually with climate and lithology. These results provide a framework for forecasting DSi under land cover and climate change and for embedding realistic, nonlinear processes in mechanistic models.

Geophysical Research Letters↗

Characteristics of frequent dynamic triggering of microearthquakes in Southern California

Dynamic triggering of earthquakes has been reported at various fault systems. The triggered earthquakes are thought to be caused either directly by dynamic stress changes due to the passing seismic waves, or indirectly by other nonlinear processes that are initiated by the passing waves. Distinguishing these physical mechanisms is difficult because of the general lack of high‐resolution earthquake catalogs and robust means to quantitatively evaluate triggering responses, particularly, delayed responses. Here we use the high‐resolution Quake Template Matching catalog in Southern California to systematically evaluate teleseismic dynamic triggering patterns in the San Jacinto Fault Zone and the Salton Sea Geothermal Field from 2008 to 2017. We develop a new statistical approach to identify triggered cases, finding that approximately 1 out of every 5 global M w ≥ 6 earthquakes dynamically trigger microearthquakes in Southern California. The triggering responses include both instantaneous and delayed triggering, showing a highly heterogeneous pattern and indicating possible evolving triggering thresholds. We do not observe a clear peak ground velocity triggering threshold that can differentiate triggering earthquakes from non‐triggering events, but there are subtle differences in the frequency content that may possibly differentiate the earthquakes. In contrast to the depth distribution of background seismicity, the identified triggered earthquakes tend to concentrate at the edges of the seismogenic zones. Although instantaneously triggered earthquakes are likely a result of dynamic Coulomb stress changes, the cases of delayed dynamic triggering are best explained by nonlinear triggering processes, including cyclic material fatigue, accelerated transient creep, and stochastic frictional heterogeneities.

California↗

Resolving terrestrial ecosystem processes along a subgrid topographic gradient for an earth-system model

Soil moisture is a crucial control on surface water and energy fluxes, vegetation, and soil carbon cycling. Earth-system models (ESMs) generally represent an areal-average soil-moisture state in gridcells at scales of 50–200 km and as a result are not able to capture the nonlinear effects of topographically-controlled subgrid heterogeneity in soil moisture, in particular where wetlands are present. We addressed this deficiency by building a subgrid representation of hillslope-scale topographic gradients, TiHy (Tiled-hillslope Hydrology), into the Geophysical Fluid Dynamics Laboratory (GFDL) land model (LM3). LM3-TiHy models one or more representative hillslope geometries for each gridcell by discretizing them into land model tiles hydrologically coupled along an upland-to-lowland gradient. Each tile has its own surface fluxes, vegetation, and vertically-resolved state variables for soil physics and biogeochemistry. LM3-TiHy simulates a gradient in soil moisture and water-table depth between uplands and lowlands in each gridcell. Three hillslope hydrological regimes appear in non-permafrost regions in the model: wet and poorly-drained, wet and well-drained, and dry; with large, small, and zero wetland area predicted, respectively. Compared to the untiled LM3 in stand-alone experiments, LM3-TiHy simulates similar surface energy and water fluxes in the gridcell-mean. However, in marginally wet regions around the globe, LM3-TiHy simulates shallow groundwater in lowlands, leading to higher evapotranspiration, lower surface temperature, and higher leaf area compared to uplands in the same gridcells. Moreover, more than four-fold larger soil carbon concentrations are simulated globally in lowlands as compared with uplands. We compared water-table depths to those simulated by a recent global model-observational synthesis, and we compared wetland and inundated areas diagnosed from the model to observational datasets. The comparisons demonstrate that LM3-TiHy has the capability to represent some of the controls of these hydrological variables, but also that improvement in parameterization and input datasets are needed for more realistic simulations. We found large sensitivity in model-diagnosed wetland and inundated area to the depth of conductive soil and the parameterization of macroporosity. With improved parameterization and inclusion of peatland biogeochemical processes, the model could provide a new approach to investigating the vulnerability of Boreal peatland carbon to climate change in ESMs.

Hydrology and Earth System Sciences↗

Shoaling of nonlinear internal waves in Massachusetts Bay

The shoaling of the nonlinear internal tide in Massachusetts Bay is studied with a fully nonlinear and nonhydrostatic model. The results are compared with current and temperature observations obtained during the August 1998 Massachusetts Bay Internal Wave Experiment and observations from a shorter experiment which took place in September 2001. The model shows how the approaching nonlinear undular bore interacts strongly with a shoaling bottom, offshore of where KdV theory predicts polarity switching should occur. It is shown that the shoaling process is dominated by nonlinearity, and the model results are interpreted with the aid of a two-layer nonlinear but hydrostatic model. After interacting with the shoaling bottom, the undular bore emerges on the shallow shelf inshore of the 30-m isobath as a nonlinear internal tide with a range of possible shapes, all of which are found in the available observational record. Copyright 2008 by the American Geophysical Union.

Masschusetts↗

Process-based, morphodynamic hindcast of decadal deposition patterns in San Pablo Bay, California, 1856-1887

This study investigates the possibility of hindcasting-observed decadal-scale morphologic change in San Pablo Bay, a subembayment of the San Francisco Estuary, California, USA, by means of a 3-D numerical model (Delft3D). The hindcast period, 1856-1887, is characterized by upstream hydraulic mining that resulted in a high sediment input to the estuary. The model includes wind waves, salt water and fresh water interactions, and graded sediment transport, among others. Simplified initial conditions and hydrodynamic forcing were necessary because detailed historic descriptions were lacking. Model results show significant skill. The river discharge and sediment concentration have a strong positive influence on deposition volumes. Waves decrease deposition rates and have, together with tidal movement, the greatest effect on sediment distribution within San Pablo Bay. The applied process-based (or reductionist) modeling approach is valuable once reasonable values for model parameters and hydrodynamic forcing are obtained. Sensitivity analysis reveals the dominant forcing of the system and suggests that the model planform plays a dominant role in the morphodynamic development. A detailed physical explanation of the model outcomes is difficult because of the high nonlinearity of the processes. Process formulation refinement, a more detailed description of the forcing, or further model parameter variations may lead to an enhanced model performance, albeit to a limited extent. The approach potentially provides a sound basis for prediction of future developments. Parallel use of highly schematized box models and a process-based approach as described in the present work is probably the most valuable method to assess decadal morphodynamic development. Copyright ?? 2011 by the American Geophysical Union.

California↗

Inversion of multichannel geophysical data with projected kernels

Statistical de‐noising methods such as Principal Component Analysis modify data in a way not constrained by physics. In much the same way as frequency‐filtered data must incorporate altered frequency content into numerical interpretation, so must statistically rotated data include the rotation operator in inversion processes. We propose a method of accounting for statistical reduction of data in non‐linear inversions (such as for electromagnetic data) through an incorporation of the rotation operator into the kernels and sensitivity matrix. We show a generalized linear inversion to demonstrate the necessity of rotating the inversion kernels in this abstract and will present a nonlinear parametric example from an unexploded ordnance application.

Conference Paper↗

Factors affecting suspended-solids concentrations in South San Francisco Bay, California

Measurements of suspended-solids concentration (SSC) were made at two depths at three sites in South San Francisco Bay (South Bay) to determine the factors that affect SSC. Twenty-eight segments of reliable and continuous SSC time series data longer than 14 days were collected from late 1991 or 1992 through September 1993. Spectral analysis and singular spectrum analysis were used to relate these data segments to time series of several potential forcing factors, including diurnal and semidiurnal tides, the spring-neap tidal cycle, wind shear, freshwater runoff, and longitudinal density differences. SSC is greatest during summer, when a landward wind shear is applied to South Bay by the afternoon sea breeze. About one half the variance of SSC is caused by the spring-neap cycle, and SSC lags the spring-neap cycle by about 2 days. Relatively short duration of slack water limits the duration of deposition of suspended solids and consolidation of newly deposited bed sediment during the tidal cycle, so suspended solids accumulate in the water column as a spring tide is approached and slowly deposit as a neap tide is approached. Perturbations in SSC caused by wind and local runoff from winter storms during the study period were usually much smaller than SSC variations caused by the spring-neap cycle. Variations of SSC at the study sites at tidal timescales are tidally forced, and nonlinear physical processes are significant. Advective transport dominates during spring tides, when water with higher SSC due to wind wave resuspension is advected to the main channel from shallow water, but, during neap tides, advective transport is less significant. The findings of this and other studies indicate that the tidally averaged transport of suspended solids responds to seasonal variations of wind shear in South Bay.

Journal of Geophysical Research C: Oceans↗

Non-perturbational surface-wave inversion: A Dix-type relation for surface waves

We extend the approach underlying the well-known Dix equation in reflection seismology to surface waves. Within the context of surface wave inversion, the Dix-type relation we derive for surface waves allows accurate depth profiles of shear-wave velocity to be constructed directly from phase velocity data, in contrast to perturbational methods. The depth profiles can subsequently be used as an initial model for nonlinear inversion. We provide examples of the Dix-type relation for under-parameterized and over-parameterized cases. In the under-parameterized case, we use the theory to estimate crustal thickness, crustal shear-wave velocity, and mantle shear-wave velocity across the Western U.S. from phase velocity maps measured at 8-, 20-, and 40-s periods. By adopting a thin-layer formalism and an over-parameterized model, we show how a regularized inversion based on the Dix-type relation yields smooth depth profiles of shear-wave velocity. In the process, we quantitatively demonstrate the depth sensitivity of surface-wave phase velocity as a function of frequency and the accuracy of the Dix-type relation. We apply the over-parameterized approach to a near-surface data set within the frequency band from 5 to 40 Hz and find overall agreement between the inverted model and the result of full nonlinear inversion.

Geophysics↗

Low-frequency electrical properties

In the interpretation of induced polarization data, it is commonly assumed that metallic mineral polarization dominantly or solely causes the observed response. However, at low frequencies, there is a variety of active chemical processes which involve the movement or transfer of electrical charge. Measurements of electrical properties at low frequencies (such as induced polarization) observe such movement of charge and thus monitor many geochemical processes at a distance. Examples in which this has been done include oxidation-reduction of metallic minerals such as sulfides, cation exchange on clays, and a variety of clay-organic reactions relevant to problems in toxic waste disposal and petroleum exploration. By using both the frequency dependence and nonlinear character of the complex resistivity spectrum, these reactions may be distinguished from each other and from barren or reactionless materials.

Geophysics↗

Generalizing a nonlinear geophysical flood theory to medium-sized river networks

The central hypothesis of a nonlinear geophysical flood theory postulates that, given space-time rainfall intensity for a rainfall-runoff event, solutions of coupled mass and momentum conservation differential equations governing runoff generation and transport in a self-similar river network produce spatial scaling, or a power law, relation between peak discharge and drainage area in the limit of large area. The excellent fit of a power law for the destructive flood event of June 2008 in the 32,400-km 2 Iowa River basin over four orders of magnitude variation in drainage areas supports the central hypothesis. The challenge of predicting observed scaling exponent and intercept from physical processes is explained. We show scaling in mean annual peak discharges, and briefly discuss that it is physically connected with scaling in multiple rainfall-runoff events. Scaling in peak discharges would hold in a non-stationary climate due to global warming but its slope and intercept would change.

Geophysical Research Letters↗

Multichannel analysis of surface waves

The frequency‐dependent properties of Rayleigh‐type surface waves can be utilized for imaging and characterizing the shallow subsurface. Most surface‐wave analysis relies on the accurate calculation of phase velocities for the horizontally traveling fundamental‐mode Rayleigh wave acquired by stepping out a pair of receivers at intervals based on calculated ground roll wavelengths. Interference by coherent source‐generated noise inhibits the reliability of shear‐wave velocities determined through inversion of the whole wave field. Among these nonplanar, nonfundamental‐mode Rayleigh waves (noise) are body waves, scattered and nonsource‐generated surface waves, and higher‐mode surface waves. The degree to which each of these types of noise contaminates the dispersion curve and, ultimately, the inverted shear‐wave velocity profile is dependent on frequency as well as distance from the source. Multichannel recording permits effective identification and isolation of noise according to distinctive trace‐to‐trace coherency in arrival time and amplitude. An added advantage is the speed and redundancy of the measurement process. Decomposition of a multichannel record into a time variable‐frequency format, similar to an uncorrelated Vibroseis record, permits analysis and display of each frequency component in a unique and continuous format. Coherent noise contamination can then be examined and its effects appraised in both frequency and offset space. Separation of frequency components permits real‐time maximization of the S/N ratio during acquisition and subsequent processing steps. Linear separation of each ground roll frequency component allows calculation of phase velocities by simply measuring the linear slope of each frequency component. Breaks in coherent surface‐wave arrivals, observable on the decomposed record, can be compensated for during acquisition and processing. Multichannel recording permits single‐measurement surveying of a broad depth range, high levels of redundancy with a single field configuration, and the ability to adjust the offset, effectively reducing random or nonlinear noise introduced during recording. A multichannel shot gather decomposed into a swept‐frequency record allows the fast generation of an accurate dispersion curve. The accuracy of dispersion curves determined using this method is proven through field comparisons of the inverted shear‐wave velocity ( υ s ">

Geophysics↗

Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm

Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant result is that final solution is determined by the average model derived from multiple trials instead of one computation due to the randomness in a genetic algorithm procedure. These advantages were demonstrated by synthetic and real-world examples of inversion of potential-field data. ?? 2005 Elsevier Ltd. All rights reserved.

Computers & Geosciences↗

Constraining the permeability and outer-rise hydration at the Central America margin

Subduction zones are important drivers of Earth's geochemical evolution; the presence of water within the subduction system has substantial implications for geohazards, including the style of seismicity and the volume of magma generated at arc volcanoes. We utilize estimates of pore fluid distributions in the outer-rise region of the Central American margin imaged using controlled-source electro-magnetic surveys and novel two-dimensional forward models simulating poro-elastic deformation of slab bending to constrain the background permeability structure of the Cocos Plate and within outer-rise fault damage zones. The model results suggest that a relatively low background permeability structure is required to match the observed porosity at depths greater than 3 km (less than ~10 −21 m 2 . Similarly, increasing the permeability within the damage zones of outer-rise faults by more than a factor of 10 also over-predicts observed porosity distributions at depths greater than 3 km. However, the simulations consistently underpredict pore fluid distributions between depths of 1–3 km, which may reflect nonlinear elastic or anelastic deformation processes not included in the simulations or inherent uncertainty in the conversion of resistivity measurements to porosity distributions. The best-fitting depth-permeability relationship is relatively low, which has important implications for the timing of pore fluid release down-dip of the trench, as it restricts shallow fluid release, likely leading to higher pore fluid pressures, more widespread hydraulic fracturing, and deeper release of pore fluid along the plate interface.

Journal of Geophysical Research, Solid Earth↗