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At least 919 records · Page 51Linked to original sources

The 2020 Westmorland, California earthquake swarm as aftershocks of a slow slip event sustained by fluid flow

Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high-quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow M w 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non-interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress-driven model based on the rate-and-state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en-echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter-earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.

California

Microgravity change during the 2008-2018 Kı̄lauea summit eruption: Nearly a decade of subsurface mass accumulation

Results from nine microgravity campaigns from Kı̄lauea, Hawaiʻi, spanning most of the volcano's 2008–2018 summit eruption, indicate persistent mass accumulation at shallow levels. A weighted least squares approach is used to recover microgravity results from a network of benchmarks around Kı̄lauea's summit, eliminate instrumental drift, and restore suspected data tares. A total mass of 1.9 × 10 11 kg was determined from these microgravity campaigns to have accumulated below Kı̄lauea Caldera during 2009–2015 at an estimated depth of 1.3 km below sea level. Only a fraction of this mass is reflected in surface deformation, and this is consistent with previously reported discrepancies between subsurface mass accumulation and observed surface deformation. The discrepancy, amongst other independent evidence from gas emissions, seismicity, and continuous gravimetry, indicate densification of magma in the reservoirs below the volcano summit. This densification may have been driven by degassing through the summit vent. It is hypothesized that during the final years of the summit eruption, magma densification resulted in a buildup of pressure in the reservoirs that may have contributed to the lower East Rift Zone outbreak of 2018. The observed mass accumulation beneath Kı̄lauea could not have been detected through other techniques and illustrates the importance of microgravity measurements in volcano monitoring.

Hawai'i

Slow slip detectability in seafloor pressure records offshore Alaska

In subduction zones worldwide, seafloor pressure data are used to observe tectonic deformation, particularly from megathrust earthquakes and slow slip events (SSEs). However, such measurements are also sensitive to oceanographic circulation-generated pressures over a range of frequencies that conflate with tectonic signals of interest. Using seafloor pressure and temperature data from the Alaska Amphibious Community Seismic Experiment, and sea surface height data from satellite altimetry, we evaluate the efficacy of various seasonal and oceanographic pressure signal proxy corrections and conduct synthetic tests to determine their impact on the timing and amplitude prediction of ramp-like signals typical of SSEs. We find that subtracting out the first mode of the complex empirical orthogonal functions of the pressure records on either the shelf or slope yields signal root-mean-square error (RMS) reductions up to 73% or 80%, respectively. Additional correction with proxies that exploit the depth-dependent spatial coherence of pressure records provides cumulative variance reductions up to 83% and 93%, respectively. Our detectability tests show that the timing and amplitude of synthetic SSE-like ramps can be well constrained for ramp amplitudes ≥4 cm on the shelf and ≥2 cm on the slope, using a fully automated detector. The principal limits on detectability are residual abrupt changes in pressure that occur as part of the transition to and from summer to winter conditions but are not adequately characterized by our seasonal corrections, as well as the inability to properly account for instrumental drift, which is not readily separated from the seasonal signal.

Alaska

Spatial and temporal analysis of geologic slip rates, Cucamonga Fault, California, USA: Implications for along-strike applications and multi-fault rupture

To constrain fault processes and hazard, fault slip rates may be extrapolated over different fault lengths or time intervals. Here, we investigate slip rates for the Cucamonga Fault (CF). The CF is located at the junction of the Transverse Range fault system with the San Andreas and San Jacinto Faults, and it is hypothesized to connect with these faults, promoting the propagation of large, multi-fault earthquakes. Previous work has shown that CF displacements on late Quaternary alluvial fan surfaces are highly variable along strike. We present two new 10 Be surface exposure ages from depth profiles on the alluvial fans. Slip rates are consistent with a rate of 1.4 ± 0.3 m/kyr over time intervals of ∼20, ∼30, and ∼40 kyr. If the CF participates in multi-fault ruptures, then these earthquakes occur either rarely or with sufficient regularity to maintain apparently steady rates over multiple intervals. We also explore along-strike fault displacement variability using a calibrated morphological model. The model successfully reproduces scarp profiles and indicates that fault displacement variability can be explained in part by scarp age but not uplift rate. We infer that both erosion by ephemeral gullying and distributed deformation contribute to fault displacement variability, although both are difficult to detect confidently without excavations across the scarp. These investigations show that better characterization of cumulative-slip variability along strike may improve accuracy and precision of slip rates. Slip rates that do not consider epistemic uncertainties may not be suitable for extrapolation over longer fault sections.

California

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

On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments ( 2 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs.

Journal of Geophysical Research--Solid Earth

Using corrected and imputed polarity measurements to improve focal mechanisms in a regional earthquake catalog near the Mt. Lewis Fault Zone, California

We utilized relative polarity measurements and machine learning techniques to better resolve focal mechanisms and stress orientations considering a catalog of ∼29,000 relocated earthquakes that occurred during 1984–2021 in the southeastern San Francisco Bay Area. Earthquake focal mechanisms are commonly produced using P wave first motion polarities, which traditionally requires events to be well-recorded across a seismic network with good focal sphere coverage. We adapted recently developed approaches that are less dependent on high signal-to-noise records and exploit similar waveforms to produce relative polarity and amplitude measurements between earthquake pairs. These techniques were previously only applied on localized earthquake sequences, and we further developed these approaches so that they can be utilized for regional catalogs. We validated or corrected manually identified polarities by performing polarity consensuses using earthquake pairs. Missing and unreliable polarity measurements were imputed using iterative random forests, an unsupervised ensemble machine learning method. Relative P and S wave amplitude measurements were made between earthquakes, constraining S / P ratios for low signal-to-noise waveforms. Using these techniques, we were able to reduce focal mechanism uncertainties by an average of ∼13° and produced well-constrained focal mechanisms for ∼6 times as many earthquakes than those produced using only the traditionally derived polarities. We performed stress inversions using the focal mechanisms by grouping the focal mechanism results into a quadtree structure. Our stress results are consistent with previous work, albeit at a higher spatial resolution, and demonstrate these techniques can aid our understanding of fault structures and kinematics in more detail than was previously possible.

California

Strength recovery in quartzite is controlled by changes in friction in experiments at hydrothermal conditions up to 200°C

The rate of fault zone restrengthening between earthquakes can be influenced by both frictional and cohesive healing processes. Friction is dependent on effective normal stress while cohesion is independent of normal stress, potentially explaining—in part—the lack of depth dependence of earthquake stress drops. Although amenable to laboratory testing, few studies have systematically addressed the normal stress dependence of restrengthening rate. This is partially due to difficulty in separating relative contributions of friction and cohesion in recovery of fault strength. We present results from a series of slide-hold-slide tests on thin layers (≤10 𝜇m) of ultrafine quartz gouge that develop during shearing of initially bare-surface quartzite. Tests were conducted at 10 MPa constant pore pressure, 20–200 MPa constant effective normal stress, and temperatures of 22°–200°C. Restrengthening, defined as the difference between peak shear stress measured after resumption of sliding and steady-state sliding shear stress, increases with the log of hold duration. The 200°C healing rate, 0.014 per e-fold increase in time, is comparable to that determined from seismological observations along the Calaveras Fault, California. Construction of Mohr-Coulomb failure envelopes shows that changes in cohesion are small (<1 MPa) and independent of hold durations to 10 5 s, indicating that the increased strength is due to changes in the friction coefficient. These experimental results are inconsistent with the hypothesis that cohesive healing explains the depth independence of earthquake stress drop, but higher temperatures, longer time-scales, and more complex mineralogy could facilitate cohesive healing in natural fault systems.

Journal of Geophysical Research - Solid Earth

High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia

During a volcanic crisis, high-rate, localized deformation can indicate magma close to the surface, with important implications for eruption forecasting. However, only a few such examples have been reported, because frequent, dense monitoring is needed. High-resolution Synthetic Aperture Radar (SAR) is capable of achieving <1 m spatial resolution and sub-weekly revisit times, but is under-used. Here we use high-resolution satellite SAR imagery from COSMO-SkyMed, TerraSAR-X, and Sentinel-1 to detect intra-crater uplift preceding the November 2017 onset of eruptive activity at Agung, Indonesia. Processing the SAR imagery with an up-to-date, accurate, high-resolution digital elevation model was crucial for preventing aliasing of the deformation signal and for accurate georeferencing. We show that >15 cm of line-of-sight shortening occurred over a 400-by-400 m area on the crater floor in September-October 2017, accompanying a deep seismic swarm and flank dyke intrusion. We attribute the deformation to the pressurization of a shallow (<200 m deep) hydrothermal system by the injection of magmatic gases and fluids. We also observe a second pulse of intra-crater deformation of 3–5 cm within 4 days to 11 hr prior to the first phreatomagmatic eruption, which is consistent with interaction between the hydrothermal system and the ascending magma. This phreatomagmatic eruption created the central pathway used during the final stages of magma ascent. Our observations have important implications for understanding unrest and eruption forecasting, and demonstrate the potential of monitoring with high-resolution SAR.

Agung Volcano, Bali

Identification of seismo-volcanic regimes at Whakaari/White Island (New Zealand) via systematic tuning of an unsupervised classifier

We present an algorithm based on Self-Organizing Maps (SOM) and k-means clustering to recognize patterns in a continuous 12.5-year tremor time series recorded at Whakaari/White Island volcano, New Zealand (hereafter referred to as Whakaari). The approach is extendable to a variety of volcanic settings through systematic tuning of the classifier. Hyperparameters are evaluated by statistical means, yielding a combination of “ideal” SOM parameters for the given data set. Extending from this, we applied a Kernel Density Estimation approach to automatically detect changes within the observed seismicity. We categorize the Whakaari seismic time series into regimes representing distinct volcano-seismic states during recent unrest episodes at Whakaari (2012/2013, 2016, and 2019). There is a clear separation in classification results between background regimes and those representing elevated levels of unrest. Onset of unrest is detected by the classifier 6 weeks before the August 2012 eruption, and ca. 3.5 months before the December 2019 eruption, respectively. Regime changes are corroborated by changes in commonly monitored tremor proxies as well as with reported volcanic activity. The regimes are hypothesized to represent diverse mechanisms including: system pressurization and depressurization, degassing, and elevated surface activity. Labeling these regimes improves visualization of the 2012/2013 and 2019 unrest and eruptive episodes. The pre-eruptive 2016 unrest showed a contrasting shape and nature of seismic regimes, suggesting differing onset and driving processes. The 2016 episode is proposed to result from rapid destabilization of the shallow hydrothermal system, while rising magmatic gases from new injections of magma better explain the 2012/2013 and 2019 episodes.

Whakaari, White Island

Observations of flocs in an estuary and implications for computation of settling velocity

The settling velocity ( w s ) in estuarine environments can impact whether a region is eroding or accreting sediment on the bed, yet determining this rate can be an indirect process requiring a number of assumptions. Accurate determination of w s is especially needed for numerical models to reproduce observed sediment concentrations at the appropriate timescale. We collected information on suspended sediment flocculation at a channel site (13 m deep) and a shallows site (4 m deep) within South San Francisco Estuary, alongside timeseries of flow, wave statistics, turbulent shear, and bottle samples analyzed for both w s and particle size. Using the measurements of floc size and settling velocity, we performed a sensitivity analysis on the unknown parameters in the general explicit formula for settling velocity. The collected particle size distribution data show that multiple classes of flocs are present; these are characterized as flocculi, microflocs, and macroflocs. We show that w s of flocculi is closest to w s for the full distribution. The determined parameter values lead to near-bed mass-weighted settling velocities (standard deviation) of 1.18 (0.55) and 0.22 (0.15) mm/s at the channel and shallows sites, respectively. Modeling efforts can use this work to help select an appropriate sediment model and parameter values.

California

Flow development and entrainment in turbulent particle-laden jets

Explosive eruptions expel volcanic gases and particles at high pressures and velocities. Within this multiphase fluid, small ash particles affect the flow dynamics, impacting mixing, entrainment, turbulence, and aggregation. To examine the role of turbulent particle behavior, we conducted an analogue experiment using a particle-laden jet. We used compressed air as the carrier fluid, considering turbulent conditions at Reynolds numbers from approximately 5,000 to 20,000. Two different particles were examined: 14-μm diameter solid nickel spheres and 13-μm diameter hollow glass spheres. These resulted in Stokes numbers between 1 and 35 based on the convective scale. The particle mass percentage in the mixture is varied from 0.3% to more than 20%. Based on a 1-D volcanic plume model, these Stokes numbers and mass loadings corresponded to millimeter-scale particle diameters at heights of 4–8 km above the vent during large, sustained eruptions. Through particle image velocimetry, we measured the mean flow behavior and the turbulence statistics in the near-exit region, primarily focusing on the dispersed phase. We show that the flow behavior is dominated by the particle inertia, with high Stokes numbers reducing the entrainment by more than 40%. When applied to volcanic plumes, these results suggest that high-density particles can greatly increase the probability of column collapse.

Journal of Geophysical Research: Atmospheres

Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California

Wildfire can impact soil-hydraulic properties by reducing saturated hydraulic conductivity and sorptivity, making recently burned landscapes prone to debris flows and flash floods. The post-fire hazard window can range from years to decades. In Northern California, where wildfire frequency is steadily increasing, the impact and soil-hydraulic recovery from wildfires is unknown. Following the October 2017 Nuns and Tubbs fires in the Northern Bay Area of California, we established 41 monitoring sites for repeat tension-disc infiltrometer measurements of field-saturated hydraulic conductivity ( K fs ) over 3.5 years. Our site arrays, which encompass grasslands, chaparral, and oak and conifer forests across a range in lithology, show a marked decrease in K fs following the wildfires and a swift partial recovery following the initial post-fire rainy season. Our time series reveals a complex path to soil-hydraulic recovery marked by distinct seasonal stages. Analysis of changing K fs , sorptivity, and infiltration model residuals collectively suggests that these stages are related to transitions between soil-hydraulic processes like structural soil sealing from rainsplash, thermal cracking of bare soil, and vegetation regrowth. While soil infiltration rates were strongly impacted by the 2017 fires, dry ravel estimates are an order of magnitude less for similar slopes than the 2009 Station fire in the San Gabriel mountains of Southern California, suggesting that limited ravel flux may insufficiently load channels for debris flows that initiate from within-channel failure. Our analysis suggests that burned landscapes in the Northern Bay Area of California may experience rapid soil-hydraulic recovery and limited pathways toward post-fire debris flow initiation.

California

Can lava flow like water? Assessing applications of critical flow theory to channelized basaltic lava flows

Flowing lava and water have dramatically different physical properties but can form similar hydraulic structures, including undular hydraulic jumps, or standing wave trains. In water flows, undular hydraulic jumps are evidence of critical flow (Froude number ∼1) and open-channel hydraulic theory provides a powerful tool for estimating flow depth and velocity. Monitoring these parameters in an active lava channel is inherently challenging, but essential for calculating lava discharge (effusion rate), a primary control on the rate of flow front advance and ultimate flow runout distance. We analyze undular hydraulic jumps in both water and lava flows to assess the conditions under which they form and, by extension, the potential use of critical flow theory to estimate, in real time, lava flow velocity, depth, and discharge. Experimental data for water flows show that these structures mark the transition from supercritical to subcritical flow. Undular hydraulic jumps in the near-vent lava channel of the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi also reflect critical flow conditions; their wavelengths scale with flow depth and velocity, consistent with hydraulic theory. Calculated lava effusion rates are similar to estimates made using more traditional approaches (Jeffreys', 1925, https://doi.org/10.1080/14786442508634662 , equation based on lava viscosity, density, and channel slope) and with lava volumes derived from topographic-change mapping. From this we conclude that critical flow phenomena show great potential to track flow dynamics and inform hazard assessment for a wide range of geophysical fluids.

Journal of Geophysical Research - Earth Surface

Time-lapse seafloor surveys reveal how turbidity currents and internal tides in Monterey Canyon interact with the seabed at centimeter-scale

Here we show how ultra-high resolution seabed mapping using new technology can help to understand processes that sculpt submarine canyons. Time-lapse seafloor surveys were conducted in the axis of Monterey Canyon, ∼50 km from the canyon head (∼1,840 m water depth) over an 18-month period. These surveys comprised 5-cm resolution multibeam bathymetry, 1-cm resolution lidar bathymetry, and 2-mm resolution stereophotographic imagery. Bathymetry data reveal centimeter-scale textures that would be undetectable by more traditional survey methods. Upward-looking Acoustic Doppler Current Profilers at the site recorded the flow character of internal tides and the passage of three turbidity currents, while sediment cores collected from the site record flow deposits. Combined with flow and core data, the bathymetry shows how turbidity currents and internal tides modify the seabed. The turbidity currents drape sediment across the site, infilling bedform troughs and smoothing erosional features carved by the internal tides (e.g., rippled scours). Turbidity currents with speeds of 0.9–3.3 m/s failed to cause notable bedform movement, which is surprising given that flows with similar speeds produced rapid bedform migration elsewhere, including the upper Monterey Canyon. The lack of migration may be related to the character of the underlying substrate or indicate that turbidity currents at the site lack dense, near-bed layers. The scale of scours produced by the internal tides (≤0.7 m/s) approaches the scale of features recorded in the ancient rock record. Thus, these results illustrate how the scale gap between seabed mapping technology and the rock record may eventually be bridged.

California

Mapping landslide susceptibility over large regions with limited data

Landslide susceptibility maps indicate the spatial distribution of landslide likelihood. Modeling susceptibility over large or diverse terrains remains a challenge due to the sparsity of landslide data (mapped extent of known landslides) and the variability in triggering conditions. Several different data sampling strategies of landslide locations used to train a susceptibility model are used to mitigate this challenge. However, to our knowledge, no study has systematically evaluated how different sampling strategies alter a model's predictor effects (i.e., how a predictor value influences the susceptibility output) critical to explaining differences in model outputs. Here, we introduce a statistical framework that examines the variation in predictor effects and the model accuracy (measured using receiver operator characteristics) to highlight why certain sampling strategies are more effective than others. Specifically, we apply our framework to an array of logistic regression models trained on landslide inventories collected at sub-regional scales over four terrains across the United States. Results show significant variations in predictor effects depending on the inventory used to train the models. The inconsistent predictor effects cause low accuracies when testing models on inventories outside the domain of the training data. Grouping test and training sets according to physiographic and ecological characteristics, which are thought to share similar triggering mechanisms, does not improve model accuracy. We also show that using limited landslide data distributed uniformly over the entire modeling domain is better than using dense but spatially isolated data to train a model for applications over large regions.

California, Kentucky, North Carolina, West Virgini

The influence of drying on the aeolian transport of river-sourced sand

Transgression and regression of water levels (stages) have impacted the evolution of aeolian landforms and sedimentary deposits throughout geologic history. We studied this phenomenon over a five-day period of reduced flow on the Colorado River in Grand Canyon National Park, AZ, USA, in March 2021. These transient low flows exposed river-channel sand deposits to the air, causing progressive desiccation (drying) and thereby making these deposits susceptible to aeolian transport. We measured aeolian threshold friction velocities ( u *t ) for sand saltation and PM10 dust emissions, as well as other characteristics, on a subaerially exposed sandbar and downwind aeolian dunefield during each day of the low river flow. The sandbar transitioned from supply-limited to transport-limited aeolian sediment transport conditions during the regression in river water stage. A possible tipping point between the two transport conditions occurred approximately 48 hours after the drop in river flow. The empirically measured u *t decreased as the sandbar sediment dried with increased subaerial exposure time. Theoretical estimates and empirical measurements of u *t corresponded closely on the aeolian dunefield and on the sandbar when it was drier during the third and fourth day of the experiment. Eighty-seven percent of the variability in u *t was explained by empirical models that provide practical estimates of aeolian transport potential of subaerial river sediment deposits using monitoring data that are commonly available in this and other river systems. The work provides theoretical insight into the response of aeolian processes to sediment supply changes driven by periods of anthropogenic activity, drought, and climate change.

Arizona

Impacts of spontaneous waterfall development on bedrock river longitudinal profile morphology

River profiles are shaped by climatic and tectonic history, lithology, and internal feedbacks between flow hydraulics, sediment transport and erosion. In steep channels, waterfalls may self-form without changes in external forcing (i.e., autogenic formation) and erode at rates faster or slower than an equivalent channel without waterfalls. We use a 1-D numerical model to investigate how self-formed waterfalls alter the morphology of bedrock river longitudinal profiles. We modify the standard stream power model to include a slope threshold above which waterfalls spontaneously form and a rate constant allowing waterfalls to erode faster or slower than other fluvial processes. Using this model, we explore how waterfall formation alters both steady state and transient longitudinal profile forms. Our model predicts that fast waterfalls create km-scale reaches in a dynamic equilibrium with channel slope held approximately constant at the threshold slope for waterfall formation, while slow waterfalls can create local channel slope maxima at the location of slow waterfall development. Furthermore, slow waterfall profiles integrate past base level histories, leading to multiple possible profile forms, even at steady-state. Consistency between our model predictions and field observations of waterfall-rich rivers in the Kings and Kaweah drainages in the southern Sierra Nevada, California, supports the hypothesis that waterfall formation can modulate river profiles in nature. Our findings may help identify how bedrock channels are influenced by waterfall erosion and aid in distinguishing between signatures of external and internal perturbations, thereby strengthening our ability to interpret past climate and tectonic changes from river longitudinal profiles.

Journal of Geophysical Research - Earth Surface