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Limited preservation of strike-slip surface displacement in the geomorphic record

Offset geomorphic markers are commonly used to interpret slip history of strike-slip faults and have played an important role in forming earthquake recurrence models. These data sets are typically analyzed using cumulative probability methods to interpret average amounts of slip in past earthquakes. However, interpretation of the geomorphic record to infer surface slip history is complicated by slip variability, measurement uncertainty, and modification of offset features in the landscape. To investigate how well geomorphic data record surface slip, we use offset measurements from recent strike-slip surface ruptures ( n = 39), faults with geomorphic evidence of multiple strike-slip earthquakes ( n = 29), and synthetic slip distributions with added noise ( n > 10,000) to examine the constraints of the geomorphic record and the underlying assumptions of the cumulative offset probability distribution analysis method. We find that the geomorphic record is unlikely to resolve more than two paleo-slip distributions, except in specific cases with low slip variability, high slip-per-event, and semiarid climate. In cases where site-specific conditions allow for interpretation of more than two earthquakes, lateral extrapolation along a fault is not straightforward because on-fault displacement and distributed deformation may be spatially variable in each earthquake. We also find that average slip in modern earthquakes is adequately recovered by probability methods, but the reported prevalence of strike-slip faults with characteristic slip history is not supported by geomorphic data. We also propose updated methods to interpret slip history and construct uncertainty bounds for paleo-slip distributions.

Journal of Geophysical Research: Solid Earth

Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed

Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.

Colorado

Uncertainty quantification of geologic energy storage in depleted gas reservoirs using material balance equations embedded in a hierarchical errors-in-variables model

The storage potential for gas in geologic settings, such as depleted hydrocarbon reservoirs and solution-mined salt caverns, is becoming salient to future energy infrastructure planning. Technologies such as carbon capture, utilization, and storage, carbon dioxide-enhanced oil recovery, and natural gas and hydrogen storage help meet growing energy demands, reduce carbon emissions to meet climate goals, and provide energy security amid geopolitical uncertainties. Therefore, estimates of underground gas storage capacity could be useful for efficiently navigating the energy transitions. Material balance is a fundamental method in reservoir engineering for estimating original gas in place and potential storage capacity at the scale necessary for national assessments of subsurface pore space resources. However, the deterministic method cannot accommodate multiple data sources or quantify uncertainty in predictions. In this study, a method that embeds material balance equations within a hierarchical errors-in-variables model is proposed which allows the estimation of the distributions of reservoir properties needed for assessments. Uncertainties associated with these reservoir properties have traditionally been expert-elicited, whereas the uncertainty estimates from the proposed models are data-driven. Capacity and uncertainty estimates can be used in a probabilistic resource assessment, supplementing information traditionally used by assessors or even replacing this expert elicitation step when data are unavailable. Various regression models are compared in a case study of the Michigan Basin, a large contributor to the United States’ current natural gas storage capacity. In particular, errors-in-variables models help ameliorate regression dilution and can quantify uncertainty in predictions of pressure in addition to storage capacity. Overfitting is addressed by quantifying generalization error and model averaging in simple and stratified cross-validation against reported working gas capacity, representing the varying quality and quantity of available data. Incorporating a statistical framework into existing numerical methods in reservoir engineering can improve the quality of estimation, and in particular, this method brings rigor to uncertainty quantification as part of a larger effort by the U.S. Geological Survey to assess domestic energy gas storage resources in depleted hydrocarbon reservoirs.

Mathematical Geosciences

Patterns and drivers of cliff erosion in Big Sur, California, USA using repeat photogrammetry, 2017–2023

Seacliff erosion in steep terrain poses major risks to transportation and critical infrastructure. In Big Sur, California, USA, seacliff erosion threatens the sustainability of the central coast stretch of California State Route 1, a transportation corridor that is critical to the region's economy. Published cliff retreat rates for the region range from 1 to 40 cm yr −1 , highlighting that high-resolution, process-based studies could enhance understanding of the causes of spatial and temporal variability. We quantified cliff erosion and investigated its drivers along ∼13 km of the Big Sur coastline at week–month timescales during the late fall to early spring wet seasons between January 2017 and June 2023 by analyzing 3D point clouds developed from aerial imagery using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. We calculated cliff face retreat rates of 2.23 ± 3.06 cm yr −1 (mean ±1 σ ), an order of magnitude lower than long-term estimated rates for the region (which included large deep-seated landslides), but in line with short-term rates reported across California. Change detection imagery comparison, cliff profiles through time, and statistical analysis reveal a cyclical cliff evolution process in which erosion by wave action at the cliff base destabilizes the cliff and primes it for subsequent failure during precipitation events. Although more erosion by volume could be attributed to precipitation-induced increases in soil moisture (784 m 3 km −1 yr −1 ) compared with erosion attributed to wave power (282 m 3 km −1 yr −1 ), our observations underscore the coupled nature of these processes in driving cliff evolution, consistent with established theory and observations.

California

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and translational slides derived solely from high-resolution (≤3 m) elevation data and globally available estimates of the diffusion coefficient for sediment flux. The method applies a linear diffusion model to the roughest landslide deposits until they reach a representative non-landslide roughness distribution. This estimates the time for a landslide deposit to be unrecognizable in high-resolution digital elevation data, which we term the mean lifetime of the landslide. Using the mean lifetime and number of landslides within an area of interest, we can estimate the mean occurrence rate of landslides over that domain. We validate this approach using a comprehensive temporal inventory of landslides in western Oregon created using age-roughness curves that are calibrated with high-resolution elevation data and radiocarbon data. We find good agreement between our diffusion method and the existing age-roughness-derived estimates, producing mean lifetimes of 4500 and 5200 years (4% difference), respectively. Hazard maps produced using the two methodologies generally agree, with the maximum differences in landslide probability reaching 0.1. Due to the relative abundance of high-resolution elevation data compared with age-dated landslides, our method could help constrain landslide occurrence rates in areas previously considered unfeasible.

Oregon

A regional model comparison between MODPATH and MT3D of groundwater travel time distributions

Groundwater quality changes in wells and streams lag behind changes to land use due to groundwater travel times. Two contaminant transport methods were compared to assess differences in their simulated travel time distributions (TTDs) to streams and wells in the Wisconsin Central Sands. MODPATH simulates advective groundwater flow with particle tracking, while MT3D simulates age-mass using a finite difference solution without dispersion to allow for direct comparison of the two methods. MODPATH appropriately simulates groundwater TTDs from the water table to surface discharge but is subject to inaccuracies at weak-sink well cells due to the flow-model grid discretization and imprecise location of well discharge within well cells. MT3D better represents weak-sink well cells since it removes mass in proportion to the prescribed pumping rate, although travel time within well cells is neglected. Conversely, MT3D's treatment of surface water boundary cells is not as accurate as MODPATH because mass should be removed from the water table rather than the full cell volume. MT3D simulations of TTDs can also be confounded by the instantaneous vertical distribution of mass introduced throughout recharge cells instead of at the water table, which initiates mass along deeper flow paths. We evaluated 9 MODPATH and 13 MT3D implementations, generating differences in median travel times of up to 18 years. Both methods have strengths and weaknesses, with MT3D better representing weak-sink well cell behavior and MODPATH better representing surficial recharge and discharge. The effect of these characteristics on simulated TTDs, along with ideas for ameliorating method weaknesses, is discussed.

Wisconsin

Landsliding follows signatures of wildfire history and vegetative regrowth in a steep coastal shrubland

Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km 2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.

California

Near-surface geophysics: Environmental applications

The field of geophysics encompasses a broad and diverse compilation of methodologies that employs principles of physics to characterize properties of earth materials within the subsurface. While geophysical methods have a long history in resource exploration and studies of Earth’s interior, the subdiscipline of “near-surface geophysics” has evolved in recent decades for examination of the shallow, near-surface environment for a range of purposes ranging from archaeological or forensic investigations to assessment of geologic, hydrologic, biologic, and geochemical properties and processes. “Environmental geophysics” are near-surface geophysical studies and methods that focus on understanding natural systems (e.g., watershed hydrology, groundwater–surface water connections, biophysical processes) as well as research pertaining to anthropogenic impacts and land management, (e.g., contamination and remediation, saltwater intrusion, agricultural practices). This field can be further subdivided into subdisciplines focused on specific topics and applications, such as water resources and hydrology (hydrogeophysics) or biologic and microbial processes (biogeophysics). Studies in environmental geophysics span a range of scales, from pore-scale laboratory tests to watershed-scale or regional field experiments. Methods vary by the nature of physics employed, the specific measurement acquired, and how that data is ultimately processed and analyzed to produce interpretable results. There exists further diversity in the acquisition logistics, geometry, and timing of data collection. Geophysical data can be collected in boreholes (one-dimensional, 1-D, vertical profiles), along survey lines (two-dimensional, 2-D, cross-sections), or in dense sensor arrays or gridded profiles (three-dimensional, 3-D, models). Regarding the temporal aspect, studies can conduct one-time geophysical surveys to obtain detailed imaging of subsurface structure or use timelapse and continuous monitoring to investigate variations in subsurface properties over time. The cumulation of all possible permutations of these factors (method, acquisition geometry, survey design, and target application) results in an immense diversity among environmental geophysical studies. Nevertheless, this field remains unified in the pursuit of understanding natural and human-impacted near-surface environments through geophysical investigations. Here we highlight some key references within environmental geophysics. Resources on geophysical theory, acquisition logistics, processing and inversion workflows, and example case studies are categorized into the most common geophysical classes within Geophysical Methods. Lastly, example references for the dominant types of applications in environmental geophysical studies are catalogued in Environmental Applications.

Book chapter

Global performance of remote sensing-based and reanalysis-driven models to estimate open water evaporation

Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing-based models, 1 reanalysis-driven model and 1 ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. Our results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm day −1 , respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.

Water Resources Research

Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York

Nitrogen transported along groundwater flow paths in coastal aquifers can contribute substantially to nitrogen loading into surface water receptors, particularly in hydrologic systems dominated by groundwater discharge. Nitrogen entrained in the aquifer is a function of land use and associated nitrogen sources at the time of groundwater recharge, which may differ considerably from present-day sources. Legacy nitrogen can result in substantial discrepancies between observed present-day nitrogen loading to surface water receptors and loading estimated from present-day sources. Additionally, legacy nitrogen can continue to discharge into surface waters after nitrogen mitigation actions have been undertaken. Here, we use a numerical modeling framework to compare three methods of estimating time-varying historical nitrogen loads to four water bodies (receptors) on eastern Long Island, New York. The methods span a range of data requirements and process complexity, from instantaneous receptor loads calculated from steady-state groundwater contributing areas, to transient loads estimated by explicitly simulating legacy groundwater nitrogen transport over a century with large changes in nitrogen sources and hydrologic conditions. The effects of legacy nitrogen on estimated receptor loads varied temporally and spatially within the study area. Depending on antecedent nitrogen inputs and hydrologic conditions, historical annual nitrogen loads estimated from transient simulations accounting for legacy nitrogen can be quite similar (<10% difference) or substantially different (±100%) from those estimated from simpler instantaneous methods. Continued input of present-day nitrogen sources using methods that account for legacy nitrogen results in asymptotic increases in receptor nitrogen loads over time, indicating that simulated present-day receptor nitrogen loads are not in equilibrium with present-day inputs. For these receptors in disequilibrium, models simulating transient groundwater nitrogen transport could be used to account for legacy nitrogen lag times to help resource managers evaluate the potential effectiveness of proposed nitrogen mitigation actions.

EarthArXiv

Introduction to the special section on improving measurements of earthquake source parameters

Earthquake source parameters such as magnitude, seismic moment, source dimension, stress drop, and radiated energy are fundamental to understanding earthquake physics, and are also key ingredients in earthquake ground‐motion modeling, rupture simulation, and statistical seismology. However, the uncertainties in these parameters estimated from the radiated seismic wavefield are large due to variability in approaches, including site and attenuation characterizations, and so estimates for an individual earthquake made by different studies can vary greatly. Estimating spectral source parameters remains a popular topic, due to a combination of their intrinsic importance and their apparent ease of measurement, but also a controversial one, due to many sources of variability and large uncertainty. The available methods coupled with necessary parameter choices and assumptions in the analysis make it challenging for researchers to apply methods or understand the reliability in results or reported source parameters. This Special Section on Improving Measurements of Earthquake Source Parameters showcasing comparisons between methods and studies seeks to alleviate some of these difficulties to help the community identify the important components and trade‐offs of decomposing recorded seismograms into their source, path, and site components.

Bulletin of the Seismological Society of America

A journey to the center of the USGS National Strong-motion Project processing and beyond

The United States Geological Survey (USGS) National Strong Motion Project (NSMP) has the primary U.S. government responsibility to acquire, process, and disseminate significant strong-motion earthquake ground motion records measured at surficial free-field stations, structures (buildings, dams, and bridges, and geotechnical arrays to the earthquake engineering community. As a result of the deployment of modern seismic instrumentation and growth of tools such as web-services, earthquake data from U.S. and international seismic networks are more accessible than ever. Our mission is to provide raw and processed strong-motion waveforms with PGA values greater than 0.1%g for M3.0 earthquakes and larger in California and M4.0 and larger within the conterminous US, Hawaii, Puerto Rico, and Alaska. Datasets of interest to the engineering and geophysics communities, such as event sequences in areas of induced seismicity and significant global events, are also processed and posted at the Center for Engineering Strong Motion Data (CESMD) at strongmotioncenter.org when available through collaboration with the international strong-motion data community. Here we outline (1) the NSMP’s current workflow to acquire, process, and distribute data at CESMD; (2) our new endeavours and collaborations focusing on comparison and integration of waveform processing software, development of techniques for metadata quality checks before and after earthquakes, and construction of a dynamic site characterization repository; and (3) our topics for possible collaboration topics across the global strong-motion community.

Conference Paper

Subduction zone earthquake catalog separation tool: Implementation in the USGS 2025 Puerto Rico and U.S. Virgin Islands National Seismic Hazard Model

The U.S. Geological Survey (USGS) periodically releases updates to National Seismic Hazard Model (NSHM) for the United States and its territories leveraging current scientific knowledge and methodologies to guide public policy, building codes, and risk assessments regarding potential ground shaking due to earthquakes that may result in infrastructure damage. In subduction zones, there is a need to separate the earthquake catalog into tectonic regimes to create specific seismicity models for which the most appropriate ground‐motion models are then applied. Here, we describe newly developed methods and software, called CatSep, that classifies subduction zone events into three primary tectonic regimes: crustal, interface, and intraslab. This method incorporates information about the location of the earthquake relative to the subducting slab, the depth of the Mohorovičić discontinuity, and the earthquake’s moment tensor. Applying this method is a first step in the NSHM workflow for regions covering U.S. subduction zones. Results using this subduction zone earthquake catalog separation tool for the 2025 Puerto Rico and U.S. Virgin Islands NSHM earthquake catalog are presented and analyzed.

Puerto Rico, U.S. Virgin Islands

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen

Event classification, seismicity, and eruption forecasting at Great Sitkin Volcano, Alaska: 1999–2023

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Alaska

Monitoring marine eruptions

Introduction Submarine volcanoes produce much of the same seismicity and eruptive activity as subaerial volcanoes and can pose hazards to society. Although they can be monitored with similar techniques and methods as described in other chapters of this volume, their submerged location brings unique challenges. This chapter addresses these challenges and provides recommendations for monitoring volcanoes fully or partly in marine environments to meet the capabilities described in other chapters of this volume. The United States and its territories host dozens of submarine volcanoes with most (around 60) in the Commonwealth of the Northern Mariana Islands. Approximately 20 of the Northern Mariana Islands submarine volcanoes are known to be hydrothermally active, and 10 have confirmed eruptions since the 1950s (for example, Baker and others, 2008; Tepp and others, 2019a). Nine of those volcanoes were considered by the National Volcanic Threat Assessment (Ewert and others, 2018) to have a combination of eruptive type and summit depth that poses a higher risk of hazardous eruptions, although only one was listed as a moderate (level 3) threat. Other notable submarine volcanoes of interest to the United States that have historically erupted are Axial Seamount off the Washington State coast, Kamaʻehuakanaloa in Hawaiʻi, and Vailuluʻu seamount in American Samoa. All of these, however, have a low risk of hazards because of their depth (greater than 600 meters below sea level) and eruptive type and so are not included in the National Volcanic Threat Assessment. In addition to submarine volcanoes, the submerged flanks of island volcanoes can also be a source of hazardous submarine eruptions—for example, the 1877 eruption of Mauna Loa, Hawai‘i, in Kealakekua Bay (Wanless and others, 2006). The most notable submarine eruption in recent times was the 2022 eruption of Hunga Tonga–Hunga Haʻapai in Tonga, which was one of the largest eruptions on Earth in the past 100 years. It created a massive volcanic plume, unprecedented shock waves, and far-reaching tsunami (Lynett and others, 2022). Other recent submarine eruptions in the Pacific Ocean Basin have produced subaerial plumes that reached aircraft heights (Carey and others, 2014) and large pumice rafts that can affect marine traffic and harbors (for example, Jutzeler and others, 2014; Kornei, 2019). These examples illustrate the potential hazards of major submarine eruptions. Yet, submarine volcanoes are largely unmonitored, and many eruptions occur that are unnoticed or only identified hours or days afterward. Within U.S. territory, submarine volcanoes in the Northern Mariana Islands have been known to produce eruptive activity that can affect society. Reports from fishermen and other marine vessels in the Northern Mariana Islands have noted underwater explosions, sea-surface discoloration, and bubbling water, all of which are known to be signs of submarine volcanic activity. South Sarigan seamount, located about 160 kilometers (km) north of Saipan, erupted in 2010 from greater than 150 meters below the sea surface, resulting in a gas and ash plume that reached more than 11.9 km into the atmosphere (for example, Searcy, 2013; Embley and others, 2014), high enough to affect international air traffic. Precursory and co-eruptive seismicity was detected on the regional Northern Mariana Islands seismic network (Searcy, 2013) and on global monitoring instruments (Green and others, 2013). Monitoring of submarine volcanoes is best accomplished with marine-based instrumentation, which is also useful for monitoring small island volcanoes that may not have the land area necessary for comprehensive subaerial monitoring. The primary marine-based instrumentation used for submarine volcanoes includes ocean-bottom pressure sensors to assess sea-floor deformation, ocean-bottom seismometers (OBSs) to detect seismicity, and both moored and ocean-bottom hydrophones to detect submarine explosions. Other sensors offer important monitoring data, such as turbidity, temperature, and chemistry of hydrothermal emissions. Marine-based instruments are typically deployed in campaign-style networks with no real-time telemetry owing to cost considerations and technical limitations. However, when necessary, marine instruments can be operated in real time using cables to transmit data to land-based facilities; other technologies for this purpose are in use or in development, such as acoustic transmission from the instrument to a moored buoy (Matsumoto and others, 2016) and a winch-based system with a satellite antenna that is part of the instrument mooring (Matsumoto and others, 2019). Emerging technologies for marine-based monitoring may be considered as part of a future monitoring plan. These technologies include ocean gliders and floats with on-board hydrophones that have been used to record earthquakes and submarine eruptions (for example, Matsumoto and others, 2013; Sukhovich and others, 2015) and fiber-optic cables that have been used as strainmeters to detect earthquakes (for example, Marra and others, 2018; Lindsey and others, 2019). Land-based instruments and satellites can also provide some capability for monitoring submarine volcanoes, but they provide more limited observations than marine-based instrumentation.

Scientific Investigations Report

Regional evaluation of evapotranspiration in the Everglades

Nine sites in the Florida Everglades were selected and instrumented for collection of data necessary for evapotranspiration-determination using the Bowen-ratio energy-budget method. The sites were selected to represent the sawgrass or cattail marshes, wet prairie, and open-water areas that constitute most of the natural Everglades system. At each site, measurements necessary for evapotranspiration (ET) calculation and modeling were automatically made and stored on-site at 15- or 30-minute intervals. Data collected included air temperature and humidity at two heights, wind speed and direction, incoming solar radiation, net solar radiation, water level and temperature, soil moisture content, soil temperature, soil heat flux, and rainfall. Data summarized in this report were collected from January 1996 through December 1997, and the development of site-specific and regional models of ET for this period is described. Latent heat flux is the energy flux density equivalent of the ET rate. Modified Priestley-Taylor models of latent heat flux as a function of selected independent variables were developed at each site. These models were used to fill in periods of missing latent heat flux measurement, and to develop regional models of the entire Everglades region. The regional models may be used to estimate ET in wet prairie, sawgrass or cattail marsh, and open-water portions of the natural Everglades system. The models are not applicable to forested areas or to the brackish areas adjacent to Florida Bay. Two types of regional models were developed. One type of model uses measurements of available energy at a site, together with incoming solar energy and water depth, to estimate hourly ET. This available-energy model requires site data for net radiation, water heat storage, and soil heat flux, as well as data for incoming solar radiation and water depth. The other type of model requires only incoming solar energy, air temperature, and water depth data to provide estimates of hourly ET. The second model thus uses data that are more readily available than the data required for the available-energy model. Computed ET mean annual totals for all nine sites for the 1996-97 period ranged from 42.4 inches per year at a site where the water level is below land surface for several months each year to 57.4 inches per year at an open-water site with no emergent vegetation. Although the density of photosynthetically-active plant leaves has been shown to relate directly to ET in some studies, it does not appear to relate directly to ET in the Everglades, based on comparison of annual ET data with leaf-area index, defined as the Normalized Difference Vegetation Index (NDVI), data from satellite imagery. NDVI and ET appear to be inversely related in the Everglades. The greatest ET rates occurred at open-water sites where the NDVI data indicated the lowest leaf-area index. Among the remaining vegetated sites, there is no clear relation between ET and NDVI, though the highest ET rate corresponded to the lowest NDVI and one of the lowest ET rates corresponded to the highest NDVI value. The variation in ET follows a seasonal pattern, with lowest monthly ET totals occurring in December through February, and highest ET occurring in May through August. The greatest range in monthly ET among all nine sites for the 2-year period occurred at site 3: from 1.81 inches in December 1997 to 6.84 inches in July 1996. A study to compare the Bowen-ratio/energy balance method of ET measurement with the eddy-correlation method was done at one site from June 22, 1998, through September 28, 1998. This comparison indicated that both methods gave comparable values of the Bowen ratio, but there was a considerable difference in available energy measured by the two methods. The mean of all 30-minute measured turbulent heat fluxes from the eddy-correlation apparatus for June 22 through September 29, 1998, was 137.4 watts per square meter, and the mean of the corresponding measured energy was 163.6 watts per square meter, or about 20 percent greater. The disagreement in mean energy fluxes measured by the two methods is problematical and is not fully understood. Although the difference seems to be related to friction velocity, and is practically non-existent at values of friction velocity greater than 0.3 meter per second, the "correctness" of either method cannot be determined with the data available.

Florida