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At least 433 records · Page 24Linked to original sources

Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River Valley, Washington

Lahars large enough to reach populated areas are a hazard at Mount Adams, a massive volcano in the southern Cascade Range of Washington State (fig. 1). It is considered to be still active and has the potential to erupt again. By definition, lahars are gravity-driven flows of water-saturated mixtures of mud and rock (plus or minus ice, wood, and other debris), which originate from volcanoes and have a variety of potential triggering mechanisms (Vallance, 2000; Vallance and Iverson, 2015). Flowing mixtures can range in fluid consistency from something like a milkshake to something more like wet concrete, and they behave like flash floods, in that they can appear suddenly in river channels with little warning and commonly have boulder- or log-choked flow fronts. Lahars are hazardous because they can flow rapidly in confined valleys (commonly 20–35 miles per hour [mph] or 9–16 meters per second [m/s]), can travel more than 100 miles (mi) (161 kilometers [km]) from a source volcano, and can move with incredible destructive force, carrying multi-ton boulders and logs that can act as battering rams (Pierson, 1998). The biggest threats from lahars to downstream communities are present during eruptive activity, and impacts to communities can be dire. For example, a very large eruption-triggered lahar in Colombia in 1985 surprised and killed more than 20,000 people in a large town located about 45 mi (72 km) downstream and out of sight of the volcano that produced it (Pierson and others, 1990). Mount Adams, one of the largest volcanoes in the Cascade Range, is a composite stratocone composed primarily of andesite lava flows. It has been the most continuously active volcano within the 480-mi 2 Mount Adams volcanic field—a region covering parts of Klickitat, Skamania, Yakima, andLewis Counties and part of the Yakama Nation Reservation in Washington State (Hildreth and Fierstein,1995, 1997). About 500,000 years in age, Mount Adams reached its present size by about 15,000 years ago, primarily through the episodic effusion of lava flows; it has not had a history of major explosive eruptions like Mount St. Helens, its neighbor to the west. Timing of the most recent eruptive activity (recorded by four thin tephra layers) is on the order of 1,000 years ago; the tephras are bracketed by 2,500-year-old and 500-year-old ash layers from Mount St. Helens (Hildreth and Fierstein, 1995, 1997). Mount Adams currently shows no signs of renewed unrest. Eruptive history does not tell us everything we need to know about hazards at Mount Adams, however, which are fully addressed in the volcano hazard assessment for Mount Adams (W.E. Scott and others, 1995). This volcano has had a long-active hydrothermal system that circulated acidic hydrothermal fluids, formed by the solution of volcanic gases in heated groundwater, through fractures and permeable zones into upper parts of the volcanic cone. Acid sulfate leaching of rocks in the summit area may still be occurring, but chemical and thermal evidence suggests that the main hydrothermal system is no longer active at Mount Adams (Nathenson and Mariner, 2013). However, these rock-weakening chemical reactions have operated long enough to change about 0.4 cubic miles (mi 3 ) (1.7 cubic kilometers [km 3 ]) of the hard lava rock in the volcano’s upper cone to a much weaker clay-rich rock, thus significantly reducing rock strength and thereby slope stability in parts of the cone (Finn and others, 2007). The two largest previous lahars from Mount Adams were triggered by landslides of hydrothermally altered rock from the upper southwestern flank of the cone, and any future large lahars are likely to be triggered by the same mechanism. Mount Rainier also has had extensive hydrothermal alteration of rock in its upper edifice, and it also has a history of large landslides that transform into lahars (K.M. Scott and others, 1995; Vallance and Scott, 1997; Reid and others, 2001). The spatial depiction of modeled lahar inundation zones accompanying this report, shown in two different map perspectives, is intended to augment (not replace) the existing hazard maps for Mount Adams (W.E. Scott and others, 1995; Vallance, 1999). The maps in this report show potential areas of inundation by lahars of different initial volumes, which are determined by a computer model, LAHARZ (Iverson and others, 1998; Schilling, 1998). One map sheet presents LAHARZ-determined inundation areas on a normal plan-view shaded-relief map of the study area; the other gives an oblique perspective of the landscape with raised topography, as if one were viewing the landscape at an angle from an aircraft (Jenny and Patterson, 2007). LAHARZ was developed after the original hazard maps (based only on mapping of geologic deposits) were made. Predicted inundation zones on these maps provide an alternative approach to estimation of areas that could be inundated as lahars of different volumes pass through the valley. However, there is considerable uncertainty in the exact location of the hazard-zone boundaries shown on these maps, as well as on earlier maps.

Washington↗

A preliminary deposit model for lithium-cesium-tantalum (LCT) pegmatites

This report is part of an effort by the U.S. Geological Survey to update existing mineral deposit models and to develop new ones. We emphasize practical aspects of pegmatite geology that might directly or indirectly help in exploration for lithium-cesium-tantalum (LCT) pegmatites, or for assessing regions for pegmatite-related mineral resource potential. These deposits are an important link in the world’s supply chain of rare and strategic elements, accounting for about one-third of world lithium production, most of the tantalum, and all of the cesium.

Open-File Report↗

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

Model selection for the North American Breeding Bird Survey

The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale‐specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave‐one‐out cross‐validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large‐scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra‐Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra‐Poisson overdispersion effects are independent and t ‐distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.

Ecological Applications↗

Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the eastern United States

This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to conduct a comprehensive national assessment of storage and flux (flow) of carbon and the fluxes of other greenhouse gases in ecosystems of the Eastern United States. These carbon and greenhouse gas variables were examined for major terrestrial ecosystems (forests, grasslands/shrublands, agricultural lands, and wetlands) and aquatic ecosystems (rivers, streams, lakes, estuaries, and coastal waters) in the Eastern United States in two time periods: baseline (from 2001 through 2005) and future (projections from the end of the baseline through 2050). The Great Lakes were not included in this assessment due to a lack of input data. The assessment was based on measured and observed data collected by the U.S. Geological Survey and many other agencies and organizations and used remote sensing, statistical methods, and simulation models.

Professional Paper↗

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable. In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Scientific Investigations Report↗

Documentation of single-well aquifer tests and integrated borehole analyses, Pahute Mesa and Vicinity, Nevada

Single-well aquifer testing has been carried out at Pahute Mesa in southern Nevada since 1962. These tests include single-well pumping and slug tests to estimate geologic formation hydraulic properties. Initially, aquifer tests focused on identifying low-permeability rocks suitable for testing large-yield nuclear devices, whereas later hydrologic investigations focused on potential subsurface transport of radionuclides away from Pahute Mesa. The number of single-well aquifer tests analyzed for Pahute Mesa and vicinity was much greater than the number of actual tests because each response to a water-level displacement was interpreted multiple times using different analytical models by different investigators, which were reported as distinct, individual aquifer tests. Some aquifer tests also were reinterpreted multiple times because the wells had not been defined uniquely. Previous databases and reports identified wells by different borehole names, reported various depths to top and bottom of open intervals, and used inconsistent wetted-aquifer thicknesses, which were coupled with inappropriate analytical methods to interpret aquifer-test data. This work standardized the reporting of single-well aquifer-test results at Pahute Mesa and vicinity. A hydraulic-parameter database was created that uniquely identifies tested wells, reports all replicated aquifer tests in each well, and identifies the best transmissivity estimate for each well. Datasets, interpreted models, and results from 1,459 analyses are presented and evaluated for 360 unique wells. Integrated borehole analyses were used to estimate hydraulic conductivity by depth in Pahute Mesa because vertical variations in hydraulic conductivity greatly affect groundwater velocities, which directly affect subsurface transport rates and directions. The integrated analyses reconciled differences between transmissivity estimated from pumping tests and the summed transmissivity from straddle-packer slug tests done at different depth intervals in a borehole. An integration borehole database was created that presents integrated aquifer-test results from 17 boreholes.

Nevada↗

Model documentation for relations between continuous real-time and discrete water-quality constituents in Indian Creek, Johnson County, Kansas, June 2004 through May 2013

Johnson County is the fastest growing county in Kansas, with a population of about 560,000 people in 2012. Urban growth and development can have substantial effects on water quality, and streams in Johnson County are affected by nonpoint-source pollutants from stormwater runoff and point-source discharges such as municipal wastewater effluent. Understanding of current (2014) water-quality conditions and the effects of urbanization is critical for the protection and remediation of aquatic resources in Johnson County, Kansas and downstream reaches located elsewhere. The Indian Creek Basin is 194 square kilometers and includes parts of Johnson County, Kansas and Jackson County, Missouri. Approximately 86 percent of the Indian Creek Basin is located in Johnson County, Kansas. The U.S. Geological Survey, in cooperation with Johnson County Wastewater, operated a series of six continuous real-time water-quality monitoring stations in the Indian Creek Basin during June 2011 through May 2013; one of these sites has been operating since February 2004. Five monitoring sites were located on Indian Creek and one site was located on Tomahawk Creek. The purpose of this report is to document regression models that establish relations between continuously measured water-quality properties and discretely collected water-quality constituents. Continuously measured water-quality properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, turbidity, and nitrate. Discrete water-quality samples were collected during June 2011 through May 2013 at five new sites and June 2004 through May 2013 at a long-term site and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models for 28 water-quality constituents were developed and documented. The water-quality information in this report is important to Johnson County Wastewater because it allows the concentrations of many potential pollutants of interest, including nutrients and sediment, to be estimated in real time and characterized during conditions and time scales that would not be possible otherwise.

Kansas↗

A Streamflow Statistics (StreamStats) Web Application for Ohio

A StreamStats Web application was developed for Ohio that implements equations for estimating a variety of streamflow statistics including the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year peak streamflows, mean annual streamflow, mean monthly streamflows, harmonic mean streamflow, and 25th-, 50th-, and 75th-percentile streamflows. StreamStats is a Web-based geographic information system application designed to facilitate the estimation of streamflow statistics at ungaged locations on streams. StreamStats can also serve precomputed streamflow statistics determined from streamflow-gaging station data. The basic structure, use, and limitations of StreamStats are described in this report. To facilitate the level of automation required for Ohio's StreamStats application, the technique used by Koltun (2003)1 for computing main-channel slope was replaced with a new computationally robust technique. The new channel-slope characteristic, referred to as SL10-85, differed from the National Hydrography Data based channel slope values (SL) reported by Koltun (2003)1 by an average of -28.3 percent, with the median change being -13.2 percent. In spite of the differences, the two slope measures are strongly correlated. The change in channel slope values resulting from the change in computational method necessitated revision of the full-model equations for flood-peak discharges originally presented by Koltun (2003)1. Average standard errors of prediction for the revised full-model equations presented in this report increased by a small amount over those reported by Koltun (2003)1, with increases ranging from 0.7 to 0.9 percent. Mean percentage changes in the revised regression and weighted flood-frequency estimates relative to regression and weighted estimates reported by Koltun (2003)1 were small, ranging from -0.72 to -0.25 percent and -0.22 to 0.07 percent, respectively.

Scientific Investigations Report↗

Simulation of selected ground-water pumping scenarios at Fort Stewart and Hunter Army Airfield, Georgia

A regional MODFLOW ground-water flow model of parts of coastal Georgia, Florida, and South Carolina was used to evaluate the effects of current and hypothetical groundwater withdrawal, and the relative effects of pumping in specific areas on ground-water flow in the Upper Floridan aquifer near Fort Stewart and Hunter Army Airfield (HAAF), coastal Georgia. Simulation results for four steady-state pumping scenarios were compared to each other and to a Base Case condition. The Base Case represents year 2000 pumping rates throughout the model area, with the exception that permitted annual average pumping rates for the year 2005 were used for 26 production wells at Fort Stewart and HAAF. The four pumping scenarios focused on pumping increases at HAAF resulting from projected future demands and additional personnel stationed at the facility and on reductions in pumping at Fort Stewart. Scenarios A and B simulate 1- and 2-million-gallon-perday (Mgal/d) increases, respectively, at HAAF. Simulated water-level change maps for these scenarios indicate an area of influence that extends into parts of Bryan, Bulloch, Chatham, Effingham, and Liberty Counties, Ga., and Beaufort and Jasper Counties, S.C., with maximum drawdowns from 0.5 to 4 feet (ft) for scenario A and 1 to 8 ft for Scenario B. For scenarios C and D, increases in pumping at HAAF were offset by decreases in pumping at Fort Stewart. Scenario C represents a 1-Mgal/d increase at HAAF and a 1-Mgal/d decrease at Fort Stewart; simulated water-level changes range from 0.4 to -4 ft. Scenario D represents a 2-Mgal/d increase at HAAF and 2-Mgal/d decrease at Fort Stewart; simulated water-level changes range from 0.04 to -8 ft. The simulated water-level changes indicate an area of influence that extends into parts of Bryan, Bulloch, Chatham, Effingham, Liberty, and McIntosh Counties, Ga., and Jasper and Beaufort Counties, S.C. In general, decreasing pumping at Fort Stewart by an equivalent amount to pumping increases at HAAF reduced the magnitude and extent of drawdown resulting from the additional pumping. None of the scenarios resulted in large changes in the configuration of the simulated potentiometric surface and related ground-water flow directions. The scenarios simulated vary from the original model only by increasing pumpage less than 1 percent of the total calibrated model withdrawals. The changes in pumpage are located near the center of the original model area. Thus, the scenarios described in this report are considered to be reasonable with no less uncertainty than the original calibrated model.

Georgia↗

Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region

Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.

Great Lakes↗

Strontium isotope geochemistry of soil and playa deposits near Yucca Mountain, Nevada

The isotopic composition of strontium contained in the carbonate fractions of soils provides an excellent tracer which can be used to test models for their origin. This paper reports data on surface coatings and cements, eolian sediments, playas and alluvial fan soils which help to constrain a model for formation of the extensive calcretes and fault infillings in the Yucca Mountain region. The playas contain carbonate with a wide range of strontium compositions; further work will be required to fully understand their possible contributions to the pedogenic carbonate system. Soils from an alluvial fan to the west of Yucca Mountain show that only small amounts of strontium are derived from a fan draining a carbonate terrane have strontium component. Although much evidence points to an eolian source for at least some of the strontium in the pedogenic carbonates near Yucca Mountain, an additional component or past variation of strontium composition in the eolian source is required to model the pedogenic carbonate system

Nevada↗

Lidar estimation of storage capacity for managed water resources used by Desert Bighorn Sheep (Ovis canadensis mexicana) at Cabeza Prieta National Wildlife Refuge, Arizona

In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey Southwest Biological Science Center employed ground-based light detection and ranging (lidar) during February 2022 to help meet two resource management objectives at the Cabeza Prieta National Wildlife Refuge (CPNWR), Arizona. The two objectives are (1) characterize the water storage capacity for one developed and two modified tanks, which are bedrock catchments also referred to as tinajas, that are important water sources for desert bighorn sheep ( Ovis canadensis mexicana ) in designated wilderness at the CPNWR; and (2) develop a stage-storage model to estimate water volumes from monitoring observations of water surface levels in each tank. We measured storage capacity for the three tanks identified by refuge managers, Buckhorn, Senita, and Eagle, using ground-based lidar collected during February 2022. These data produced high-resolution (centimeter scale) topographic models that improved estimates of maximum water storage capacity over previous geometry-based estimates, permitting estimations of storage capacity at multiple water surface levels (stage heights). We found that the maximum water storage capacity for the Buckhorn, Senita, and Eagle tanks was 9,108.730, 8,623.308, and 6,039.603 US gallons (gal), respectively. For each tank we report a stage-storage model based on a polynomial function that best explained variability in water storage capacity as a function of water stage height. The results presented herein will permit the CPNWR managers to (1) easily estimate water available for wildlife at any point of time, (2) interpret tank recharge following rainstorms, and (3) decide whether and when to transport water via vehicles to mechanically refill the tanks in designated wilderness.

Arizona↗

A satellite model of Southwestern Willow Flycatcher ( Empidonax traillii extimus ) breeding habitat and a simulation of potential effects of tamarisk leaf beetles ( Diorhabda spp.), southwestern United States

Executive Summary The study described in this report represents the first time that a satellite model has been used to identify potential Southwestern Willow Flycatcher ( Empidonax traillii extimus ) (hereinafter referred to as “flycatcher”) breeding habitat rangewide for 2013–15. Fifty-seven Landsat scenes were required to map the entire range of the flycatcher, encompassing parts of six States and more than 1 billion 30-meter pixels. Predicted flycatcher habitat was summarized in a hierarchical fashion from largest to smallest: regionwide, State, U.S. Fish and Wildlife Service (FWS) management unit, 7.5-minute quadrangle, and critical-habitat reach. The term “predicted habitat” is used throughout this report to distinguish areas the satellite model predicts as suitable flycatcher habitat from what may actually exist on the ground. A rangewide accuracy assessment was done with 758 territories collected in 2014, and change detection was done with yearly habitat maps to identify how and where habitat changed over time. Additionally, effects of tamarisk leaf beetles ( Diorhabda spp.) on flycatcher habitat were summarized for the lower Virgin River from 2010 to 2015, and simulations of how tamarisk leaf beetles may affect flycatcher habitat in the lower Colorado and upper Gila Rivers were done for 2015. Model results indicated that the largest areas of predicted flycatcher habitat at elevations below 1,524 meters were in New Mexico and Arizona, areas followed in descending order by California, Texas, Nevada, Utah, and Colorado. By FWS management unit, the largest area of flycatcher habitat during all 3 years were the Middle Rio Grande (New Mexico), followed by the Upper Gila (Arizona and New Mexico) and Middle Gila/San Pedro (Arizona) management units. The area of predicted flycatcher habitat varied considerably in 7.5-minute quadrangles, ranging from 0 to1,398 hectares (ha). Averaged across 3 years, the top three producing quadrangles were Paraje Well (New Mexico), San Marcial (New Mexico), and San Carlos Reservoir (Arizona). The top three FWS critical-habitat reaches in 2015 were Rio Grande-middle (9,544 ha), San Pedro River (1,779 ha), and Gila River-mid San Carlos (1,356 ha); this ranking did not change in 2013 or 2014. Change detection among years showed a large shift in predicted flycatcher habitat influenced by drought patterns, with California habitat decreasing and New Mexico habitat increasing. An accuracy assessment indicated that 88 percent of territories were correctly classified at a 40 percent probability threshold, with an exponential relationship between territory densities and five probability classes. A spatially explicit analysis indicated that beetles decreased predicted flycatcher habitat 94.2 percent from 2010 to 2015 along the lower Virgin River, with only 5.8 percent persisting. In contrast, beetle simulations indicated that 64.1 percent of habitat will persist along the lower Colorado River and 45 percent will persist along the upper Gila River. This project shows that the satellite model adequately predicts flycatcher habitat rangewide, but it lacks the ability to predict which patches will be occupied in a given year. The next logical step is the development of an occupancy model that ties the habitat predictions of the satellite model to patch occupancy so managers can better allocate their resources for survey and restoration activities. Finally, the methods presented in this report seem well suited for automated mapping applications and cloud-based resources.

Open-File Report↗

Upscaling of U (VI) desorption and transport from decimeter‐scale heterogeneity to plume‐scale modeling

Scientifically defensible predictions of field scale U(VI) transport in groundwater requires an understanding of key processes at multiple scales. These scales range from smaller than the sediment grain scale (less than 10 μm) to as large as the field scale which can extend over several kilometers. The key processes that need to be considered include both geochemical reactions in solution and at sediment surfaces as well as physical transport processes including advection, dispersion, and pore-scale diffusion. The research summarized in this report includes both experimental and modeling results in batch, column and tracer tests. The objectives of this research were to: (1) quantify the rates of U(VI) desorption from sediments acquired from a uranium contaminated aquifer in batch experiments;(2) quantify rates of U(VI) desorption in column experiments with variable chemical conditions, and(3) quantify nonreactive tracer and U(VI) transport in field tests.

Colorado↗

Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington

In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass ( Zostera marina L.) and surf smelt ( Hypomesus pretiosus ) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.

Washington↗

A-DROP: A predictive model for the formation of oil particle aggregates (OPAs)

Oil–particle interactions play a major role in removal of free oil from the water column. We present a new conceptual–numerical model, A-DROP, to predict oil amount trapped in oil–particle aggregates. A new conceptual formulation of oil–particle coagulation efficiency is introduced to account for the effects of oil stabilization by particles, particle hydrophobicity, and oil–particle size ratio on OPA formation. A-DROP was able to closely reproduce the oil trapping efficiency reported in experimental studies. The model was then used to simulate the OPA formation in a typical nearshore environment. Modeling results indicate that the increase of particle concentration in the swash zone would speed up the oil–particle interaction process; but the oil amount trapped in OPAs did not correspond to the increase of particle concentration. The developed A-DROP model could become an important tool in understanding the natural removal of oil and developing oil spill countermeasures by means of oil–particle aggregation.

Marine Pollution Bulletin↗

Environmental systems and management activities on the Kennedy Space Center, Merritt Island, Florida: results of a modeling workshop

In the early 1960's, the National Aeronautics and Space Administration (NASA) began purchasing 140,000 acres on Merritt Island, Florida, in order to develop a center for space exploration. Most of this land was acquired to provide a safety and security buffer around NASA facilities. NASA, as the managing agency for the Kennedy Space Center (KSC), is responsible for preventing or controlling environmental pollution from the Federal facilities and activities at the Space Center and is committed to use all practicable means to protect and enhance the quality of the surrounding environment. The Merritt Island National Wildlife Refuge was established in 1963 when management authority for undeveloped lands at KSC was transferred to the U.S. Fish and Wildlife Service. In addition to manage for 11 Federally-listed threatened and endangered species and other resident and migratory fish and wildlife populations, the Refuge has comanagement responsibility for 19,000 acres of mosquito control impoundments and 2,500 acres of citrus groves. The Canaveral National Seashore was developed in 1975 when management of a portion of the coastal lands was transferred from NASA to the National Park Service. This multiagency jurisdiction on Merritt Island has resulted in a complex management environment. The modeling workshop described in this report was conducted May 21-25, 1984, at the Kennedy Space Center to: (1) enhance communication among the agencies with management responsibilities on Merritt Island; (2) integrate available information concerning the development, management, and ecology of Merritt Island; and (3) identify key research and monitoring needs associated with the management and use of the island's resources. The workshop was structured around the formulation of a model that would simulate primary management and use activities on Merritt Island and their effects on upland, impoundment, and estuarine vegetation and associated wildlife. The simulation model is composed of four connected submodels. The Uplands submodel calculates changes in acres and structural components of vegetation communities resulting from succession, fire, facilities development, and shuttle launch depositions, as well as the quantity and quality of surface runoff and aquifer input to an impoundment and an estuary. The Impoundment submodel next determines water quality and quantity and changes in vegetation resulting from water level manipulation and prescribed burning. The Estuary submodel than determines water quality parameters and acres of seagrass beds. Finally, the Wildlife submodel calculates habitat suitability indices for key species of interest, based on vegetation conditions in the uplands and impoundments and on several hydrologic parameters. The model represents a hypothetical management unit with 2,500 acres of uplands, a 600-acre impoundment, and a 1,500-acre section of estuary. Two management scenarios were run to analyze model behavior. The scenarios differ in the frequency of shuttle launches and prescribed burning, the extent of facilities development, the amount of land disposed waste material applied, and the nature and timing of impoundment water level control. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. Open communication occurs among the Federal, State, and local agencies involved with activities on Merritt Island and the agencies have a cooperative working relationship. The workshop provided an opportunity for all of these agencies to meet at one time and have focused discussions on the key environmental and multiagency resource management issues. The workshop framework helped to integrate information and assumptions from a number of disciplines and agencies. This integration occurred in the computer simulation model and among workshop participants as submodel linkages were developed and scenario results discussed. A number of research needs were identified at the workshop during the model building and testing exercises and associated discussions. These needs were based on the informed judgement of researchers and managers familiar with Merritt Island or similar areas, rather than on a comprehensive literature review of sensitivity analysis of the preliminary model developed at the workshop. Some of the needs can be addressed by interpreting the results of completed studies from similar geographic areas as they relate to Merritt Island, while other will require additional research studies on Merritt Island. Major research needs associated with the Upland submodel include behavior of the near-surface aquifer, factors limiting slash pine regeneration, frequency and effects of natural fire on various cover types, cumulative effects of shuttle launches, and fate in upland soils of nitrogen and phosphorous from land applied waste material. Key Impoundment submodel needs include documentation of vegetation changes in response to altered water depth, salinity, and nutrient concentrations and better specification of the functional characteristics of impoundments as chemical filters. Important information gaps identified in the Estuary submodel include a more complete analysis of factors contributing to phytoplankton abundance, evaluation of sources of turbidity other than phytoplankton, and identification and quantification of factors limiting seagrass distribution. Primary research needs associated with the Wildlife submodel include a survey of breeding habitat, production data, and harvest data for mottled ducks; data on the emigration and immigration of juvenile mullet (and other transient fish) in the impoundment; the contribution of various seagrasses to habitat requirements of sea trout; and the effects of dissolved oxygen on survival of juvenile sea trout. Ideally, the modeling workshop process is iterative in nature. Periods between workshops are used for research, data collection, and model refinement. Each workshop integrates information collected since the last workshop and produces a more credible model that is more useful in evaluating management alternatives. Participants felt that continued application of this process would help provide ongoing integration and communication among agencies and would allow each agency's planning and management activities to be viewed within the context of an overall assessment.

Report↗