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USGS2022

Incorporating antenna detections into abundance estimates of fish

Autonomous passive integrated transponder (PIT) tag antennas are commonly used to detect fish marked with PIT tags but cannot detect unmarked fish, creating challenges for abundance estimation. Here we describe an approach to estimate abundance from paired physical capture and antenna detection data in closed and open mark-recapture models. Additionally, for open models, we develop an approach that incorporates uncertainty in fish size, because fish size changes through time (as fish grow bigger) but is unknown if fish are not physically captured (e.g., only detected on antennas). Incorporation of size uncertainty allows for estimation of size-specific abundances and demonstrates a generally useful method for obtaining state-specific abundances estimates under state uncertainty. Simulation studies comparing models with and without antenna detections illustrate that the benefit of our approach increases as a larger proportion of the population is marked. When applied to two field data sets, our approach to incorporating antenna detections reduced uncertainty in abundance substantially. We conclude that PIT antennas hold great potential for improving abundance estimation, despite the challenges they present.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2012

Casual instrument corrections for short-period and broadband seismometers

Of all the filters applied to recordings of seismic waves, which include source, path, and site effects, the one we know most precisely is the instrument filter. Therefore, it behooves seismologists to accurately remove the effect of the instrument from raw seismograms. Applying instrument corrections allows analysis of the seismogram in terms of physical units (e.g., displacement or particle velocity of the Earth’s surface) instead of the output of the instrument (e.g., digital counts). The instrument correction can be considered the most fundamental processing step in seismology since it relates the raw data to an observable quantity of interest to seismologists. Complicating matters is the fact that, in practice, the term “instrument correction” refers to more than simply the seismometer. The instrument correction compensates for the complete recording system including the seismometer, telemetry, digitizer, and any anti‐alias filters. Knowledge of all these components is necessary to perform an accurate instrument correction. The subject of instrument corrections has been covered extensively in the literature (Seidl, 1980; Scherbaum, 1996). However, the prospect of applying instrument corrections still evokes angst among many seismologists—the authors of this paper included. There may be several reasons for this. For instance, the seminal paper by Seidl (1980) exists in a journal that is not currently available in electronic format and cannot be accessed online. Also, a standard method for applying instrument corrections involves the programs TRANSFER and EVALRESP in the Seismic Analysis Code (SAC) package (Goldstein et al. , 2003). The exact mathematical methods implemented in these codes are not thoroughly described in the documentation accompanying SAC.

Seismological Research Letters↗

USGS2009

Evaluation of trap capture in a geographically closed population of brown treesnakes on Guam

1. Open population mark-recapture analysis of unbounded populations accommodates some types of closure violations (e.g. emigration, immigration). In contrast, closed population analysis of such populations readily allows estimation of capture heterogeneity and behavioural response, but requires crucial assumptions about closure (e.g. no permanent emigration) that are suspect and rarely tested empirically. 2. In 2003, we erected a double-sided barrier to prevent movement of snakes in or out of a 5-ha semi-forested study site in northern Guam. This geographically closed population of >100 snakes was monitored using a series of transects for visual searches and a 13 ?? 13 trapping array, with the aim of marking all snakes within the site. Forty-five marked snakes were also supplemented into the resident population to quantify the efficacy of our sampling methods. We used the program mark to analyse trap captures (101 occasions), referenced to census data from visual surveys, and quantified heterogeneity, behavioural response, and size bias in trappability. Analytical inclusion of untrapped individuals greatly improved precision in the estimation of some covariate effects. 3. A novel discovery was that trap captures for individual snakes consisted of asynchronous bouts of high capture probability lasting about 7 days (ephemeral behavioural effect). There was modest behavioural response (trap happiness) and significant latent (unexplained) heterogeneity, with small influences on capture success of date, gender, residency status (translocated or not), and body condition. 4. Trapping was shown to be an effective tool for eradicating large brown treesnakes Boiga irregularis (>900 mm snout-vent length, SVL). 5. Synthesis and applications. Mark-recapture modelling is commonly used by ecological managers to estimate populations. However, existing models involve making assumptions about either closure violations or response to capture. Physical closure of our population on a landscape scale allowed us to determine the relative importance of covariates influencing capture probability (body size, trappability periods, and latent heterogeneity). This information was used to develop models in which different segments of the population could be assigned different probabilities of capture, and suggests that modelling of open populations should incorporate easily measured, but potentially overlooked, parameters such as body size or condition. ?? 2008 The Authors.

Journal of Applied Ecology↗

USGS2011

Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

Journal of Agricultural, Biological, and Environme↗

USGS1998

Evaluation of transmitter attachment techniques on growth of wild turkey poults

We compared the effects on growth of backpack-mounted and surgically implanted radiotransmitters used as marking techniques in studies of wild turkey ( Meleagris gallopavo ) poult survival. We applied repeated-measures analysis of variance (ANOVA) and Bayesian analysis to evaluate the null hypothesis that marking technique did not affect growth. Growth in body mass was similar among treatment groups. We did, however, find differences in wing-growth rates among treatment groups. The control group had the highest wing-growth rate, the backpack group had the lowest growth rate, and the surgical implant group was intermediate. Latex backpack harnesses also caused physical developmental problems that would have negatively biased wild poult survival estimates in the field. Surgically implanted transmitters affected wing growth less than the backpack harnesses and are therefore recommended for attaching transmitters to wild turkey poults.

Journal of Wildlife Management↗

USGS2003

Modeling radium and radon transport through soil and vegetation

A one-dimensional flow and transport model was developed to describe the movement of two fluid phases, gas and water, within a porous medium and the transport of 226Ra and 222Rn within and between these two phases. Included in this model is the vegetative uptake of water and aqueous 226Ra and 222Rn that can be extracted from the soil via the transpiration stream. The mathematical model is formulated through a set of phase balance equations and a set of species balance equations. Mass exchange, sink terms and the dependence of physical properties upon phase composition couple the two sets of equations. Numerical solution of each set, with iteration between the sets, is carried out leading to a set-iterative compositional model. The Petrov-Galerkin finite element approach is used to allow for upstream weighting if required for a given simulation. Mass lumping improves solution convergence and stability behavior. The resulting numerical model was applied to four problems and was found to produce accurate, mass conservative solutions when compared to published experimental and numerical results and theoretical column experiments. Preliminary results suggest that the model can be used as an investigative tool to determine the feasibility of phytoremediating radium and radon-contaminated soil. ?? 2003 Elsevier Science B.V. All rights reserved.

Journal of Contaminant Hydrology↗

USGS2020

An efficient Bayesian framework for updating PAGER loss estimates

We introduce a Bayesian framework for incorporating time-varying noisy reported data on damage and loss information to update near real-time loss estimates/alerts for the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) system. Initial loss estimation by PAGER immediately following an earthquake includes several uncertainties. Historically, the PAGER’s alerting on fatality and economic losses has not incorporated location-specific reported data on physical damage or casualties for a given earthquake. The proposed framework provides the ability to include early reports on fatalities at any given time and improve the overall impact forecast for the earthquake. The reported data on fatalities or damage are generally incomplete and noisy, especially in the early hours of the disaster. To address these challenges, we develop a recursive Bayesian updating framework that takes into account the loss projection model and the measurement and model uncertainties. The framework is applied to loss data for three example earthquakes, and the results show that the proposed updating improves the loss estimates and alert level to the correct level within the first day of the earthquake.

Earthquake Spectra Journal↗

USGS2020

Influence of grain size and shape on volcanic ash electrical conductivity

Few studies have examined the electrical properties of volcanic ash or considered the effects of physical characteristics, such as grain size and shape on its electrification. This study measures the resistivity of eight volcanic ash samples, three milled-samples and five natural ashfall samples from Alaska, U.S.A., using a current amplifier and examines the influence of particle size and particle shape on calculated grain conductivity. Grain conductivities are calculated by applying spherical, oblate, and prolate ellipsoidal shape parameters within a general effective media equation. Volcanic ash is an electrically insulating material with average resistivity values ranging from 1.732E 7 to 1.606E 12 Ωm. Results show that grain size has a limited impact on resistivity. Calculated grain conductivities remained within the same order of magnitude between the three different shape calculations ranging between 1.367E − 7 and 2.196E − 12 S/m using the spherical shape parameter. Electrical measurements of heterogeneous powders are complex and challenging. This study aims to expand the community's dataset and understanding of the electrical properties of volcanic ash and the impact of different physical characteristics. This has implication for understanding ash hazards to electrical infrastructure and volcanic lightning.

Journal of Volcanology and Geothermal Research↗

USGS2024

A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands

Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well-suited to dryland ecosystems, such as high sensitivity of plant water-use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine-scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi-mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process-based models, and loosely constrains time-varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross-wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub-yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem-scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

New Mexico↗

USGS2023

Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate

Snow avalanches are a natural hazard in mountainous areas worldwide with severe impacts that include fatalities, damage to infrastructure, disruption to commerce, and landscape disturbance. Understanding long-term avalanche frequency patterns, and associated climate and weather influences, improves our understanding of how climate change may affect avalanche activity. We used dendrochronological techniques to evaluate the historical frequency of large magnitude avalanches (LMAs) in the high-latitude climate of southeast Alaska, United States. We collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between 1720 and 2018, which allowed us to reconstruct 82 years with LMA activity across three sub-regions. By combining this tree-ring-derived avalanche data set with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found that February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of LMA activity in the study area. Specifically, LMA activity occurred during winters with substantial February and March precipitation and neutral or negative (cold) ONI values, while years not characterized by LMAs occur more frequently during warm winters (positive ONI values). Our examination of the climate-avalanche relationship in southeast Alaska sheds light on important climate variables and physical processes associated with LMA years. These results can be used to inform long-term infrastructure planning and avalanche mitigation operations in an urban area, such as Juneau, where critical infrastructure is subject to substantial avalanche hazard.

Alaska↗

USGS2025

Ultraviolet and visible remote sensing of volcanic gases

As magma rises in volcanic systems, volatile species exsolve from the silicate melt and are emitted as gases into the atmosphere. Measuring the magnitude and composition of gas emissions from volcanoes provides insights into processes occurring deep within the Earth and helps constrain the impact of volcanic degassing on atmospheric chemistry. Optical remote sensing techniques allow volcanic gas emissions to be characterized without the need to access hazardous areas near active volcanic vents. This paper reviews the state of the art in ultraviolet and visible volcanic gas remote sensing from the ground, air, and space. Special attention is given to discussing the physics of atmospheric radiative transfer on which these techniques are based. The functionality and limitations of different remote sensing instruments are examined, making clear that the ideal choice of instrumentation will depend on the volcanic system to which it is applied and the sought measurement parameters. Common algorithms for determining trace gas column densities, gas burdens, and volcanic emission rates from measurements of spectral radiance are outlined and compared, showing how some algorithms attempt to model the physics of the measurement while others maximize sensitivity. Several examples demonstrate how remote sensing measurements continue to advance our understanding of volcanic systems and their impact on the atmosphere. Finally, a few promising directions of inquiry are suggested that could lead to improvements in remote sensing instrumentation and analysis techniques. By combining spectroscopic and imaging techniques, improving our understanding of atmospheric radiative transfer, expanding the suite of target gases, and increasing the coverage and frequency of observations, we stand to significantly improve our ability to detect and quantify volcanic gas emissions and gain new insights into important Earth-system processes.

Journal of Volcanology and Geothermal Research↗

USGS2007

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

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

Journal of the American Water Resources Associatio↗

USGS2009

A one-dimensional heat-transport model for conduit flow in karst aquifers

A one-dimensional heat-transport model for conduit flow in karst aquifers is presented as an alternative to two or three-dimensional distributed-parameter models, which are data intensive and require knowledge of conduit locations. This model can be applied for cases where water temperature in a well or spring receives all or part of its water from a phreatic conduit. Heat transport in the conduit is simulated by using a physically-based heat-transport equation that accounts for inflow of diffuse flow from smaller openings and fissures in the surrounding aquifer during periods of low recharge. Additional diffuse flow that is within the zone of influence of the well or spring but has not interacted with the conduit is accounted for with a binary mixing equation to proportion these different water sources. The estimation of this proportion through inverse modeling is useful for the assessment of contaminant vulnerability and well-head or spring protection. The model was applied to 7 months of continuous temperature data for a sinking stream that recharges a conduit and a pumped well open to the Madison aquifer in western South Dakota. The simulated conduit-flow fraction to the well ranged from 2% to 31% of total flow, and simulated conduit velocity ranged from 44 to 353 m/d.

Journal of Hydrology↗

USGS2016

Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico

We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.

Journal of Geophysical Research C: Oceans↗

USGS1993

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level.

Journal of Hydrology↗

USGS2013

Economic vulnerability to sea-level rise along the northern U.S. Gulf Coast

The northern Gulf of Mexico coast of the United States has been identified as highly vulnerable to sea-level rise, based on a combination of physical and societal factors. Vulnerability of human populations and infrastructure to projected increases in sea level is a critical area of uncertainty for communities in the extremely low-lying and flat northern gulf coastal zone. A rapidly growing population along some parts of the northern Gulf of Mexico coastline is further increasing the potential societal and economic impacts of projected sea-level rise in the region, where observed relative rise rates range from 0.75 to 9.95 mm per year on the Gulf coasts of Texas, Louisiana, Mississippi, Alabama, and Florida. A 1-m elevation threshold was chosen as an inclusive designation of the coastal zone vulnerable to relative sea-level rise, because of uncertainty associated with sea-level rise projections. This study applies a Coastal Economic Vulnerability Index (CEVI) to the northern Gulf of Mexico region, which includes both physical and economic factors that contribute to societal risk of impacts from rising sea level. The economic variables incorporated in the CEVI include human population, urban land cover, economic value of key types of infrastructure, and residential and commercial building values. The variables are standardized and combined to produce a quantitative index value for each 1-km coastal segment, highlighting areas where human populations and the built environment are most at risk. This information can be used by coastal managers as they allocate limited resources for ecosystem restoration, beach nourishment, and coastal-protection infrastructure. The study indicates a large amount of variability in index values along the northern Gulf of Mexico coastline, and highlights areas where long-term planning to enhance resiliency is particularly needed.

Alabama;Florida;Louisiana;Mississippi;Texas↗

USGS2010

Modeling downstream fining in sand-bed rivers. II: Application

In this paper the model presented in the companion paper, Wright and Parker (2005) is applied to a generic river reach typical of a large, sand-bed river flowing into the ocean in order to investigate the mechanisms controlling longitudinal profile development and downstream fining. Three mechanisms which drive downstream fining are studied: a delta prograding into standing water, sea-level rise, and tectonic subsidence. Various rates of sea-level rise (typical of the late Holocene) and tectonic subsidence are modeled in order to quantify their effects on the degree of profile concavity and downstream fining. Also, several other physical mechanisms which may affect fining are studied, including the relative importance of the suspended versus bed load, the effect of the loss of sediment overbank, and the influence of the delta bottom slope. Finally, sensitivity analysis is used to show that the grain-size distribution at the interface between the active layer and substrate has a significant effect on downstream fining.

Journal of Hydraulic Research↗

USGS2024

Debris-flow monitoring on volcanoes via a novel usage of a laser rangefinder

Mount Rainier has had at least 11 large lahars over the last 6,000 years, including one occurring without evidence of eruptive activity. This prompted the creation of a lahar detection system that uses a combination of seismic, infrasound, and tripwires. We test a laser rangefinder placed on a river channel bank for detecting and confirming mass movements flowing past a station as an alternative to the physical tripwires. After testing the device at an experimental debris-flow flume, the laser rangefinder successfully captured a small debris flow on Mount Rainier in 2023, confirming its effectiveness as a lahar detection and monitoring tool. Over the 2-month deployment at Mount Rainier, we find that spurious recordings in the laser rangefinder data (noise) tend to correlate with high humidity, and that periods of noise do not correlate with increased co-located seismic amplitude. Therefore, the impact of the noise on future alarms can be mitigated by coupling a laser rangefinder alarm with that of independent datasets.

Journal of Applied Volcanology↗