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At least 991 records · Page 55Linked to original sources
USGS2019

Multi-country willingness to pay for transborder migratory species conservation: A case study of Northern Pintails

Using contingent valuation, we estimated willingness to pay (WTP) in Canada, Mexico, and the United States to protect habitat for Northern Pintails (hereafter pintails), a migratory waterfowl species that provides benefits to and requires habitat in the three countries. Our study contributes to research on spatial subsidies by measuring the value of migratory species habitat. While WTP to protect pintail habitat is highest in the household's own country, there also is substantial WTP to protect pintail habitat in the other two countries. Canadian households' annual WTP is US$12 (all dollar values are in 2016 US dollars) to stabilize the pintail population in Canada, US$4 in Mexico, and US$5 in the U.S. Mexican households would pay US$8 in Mexico, US$5 in the U.S., and US$5 in Canada. U.S. households would pay US$28 in the U.S., US$18 in Canada, and US$16 in Mexico. WTP is statistically significantly higher in all three countries to increase the pintail population. WTP as a percentage of household income is statistically significantly higher for respondents in Mexico. WTP is logically related to explanatory variables such as respondent income, interest in hunting waterfowl, and financial support of wildlife conservation organizations. This study has important implications for conducting economic analyses of habitat issues of transboundary migratory species' conservation and to more effectively and equitably achieve conservation goals.

Ecological Economics↗
USGS2001

Use of thematic mapper imagery to assess water quality, trophic state, and macrophyte distributions in Massachusetts lakes

During the spring and summer of 1996, 1997, and 1998, measurements of phytoplankton- chlorophyll concentration, Secchi disk transparency, and color were made at 97 Massachusetts lakes within 24 hours of Landsat Thematic Mapper imaging of the lakes in an effort to assess water quality and trophic state. Spatial distributions of floating, emergent, and submerged macrophytes were mapped in 49 of the lakes at least once during the 3-year period. The maps were digitized and used to assign pixels in the thematic mapper images to one of four vegetation cover classes-open water, 1-50 percent floating-and-emergent-vegetation cover, 51-100 percent floating-and-emergent-vegetation cover, and submerged vegetation at any density. The field data were collected by teams of U.S. Geological Survey and Massachusetts Department of Environmental Management staff and by 76 volunteers. Side-by-side sampling by U.S. Geological Survey and volunteer field teams resulted in statistically similar chlorophyll determinations, Secchi disk readings, and temperature measurements, but concurrent color determinations were not similar, possibly due to contamination of sample bottles issued to the volunteers.Attempts to develop predictive relations between phytoplankton-chlorophyll concentration, Secchi disk transparency, lake color, dissolved organic carbon, and various combinations of thematic mapper bands 1, 2, 3, and 4 digital numbers were unsuccessful, primarily because of the extremely low concentrations of chlorophyll in the lakes studied, and also because of the highly variable dissolved organic carbon concentrations.Predictive relations were developed between Secchi disk transparency and phytoplankton-chlorophyll concentration, and between color and dissolved organic carbon concentration. Phytoplankton-chlorophyll concentration was inversely correlated with Secchi disk transparency during all three sampling periods. The relations were very similar in 1996 and 1997 and indicated that 62 to 67 percent of the variability in Secchi disk transparency could be explained by the chlorophyll concentration. Analysis of color and dissolved organic carbon concentrations in water samples collected by U.S. Geological Survey field teams in 1996-98 indicated that 91 percent of the variance in color in Massachusetts lakes can be explained by variations in dissolved organic carbon.Areas of open-water, submerged vegetation, and two surface-vegetation-cover classes predicted from Thematic Mapper images acquired in the summer of 1996 closely matched the areas observed in a set of field observations. However, the same analysis applied to a set of data acquired in the summer of 1997 resulted in somewhat less reliable predictions, and an attempt to predict 1996 vegetation-cover areas using the relations developed in the 1997 analysis was unsuccessful.

Water-Resources Investigations Report↗
USGS1999

Relation of arsenic, iron, and manganese in ground water to aquifer type, bedrock lithogeochemistry, and land use in the New England coastal basins

In a study of arsenic concentrations in public-supply wells in the New England Coastal Basins, concentrations at or above 0.005 mg/L (milligrams per liter) were detected in more samples of water from wells completed in bedrock (25 percent of all samples) than in water from wells completed in stratified drift (7.5 percent of all samples). Iron and manganese were detected (at concentrations of 0.05 and 0.03 mg/L, respectively) at approximately the same frequency in water from wells in both types of aquifers. Concentrations of arsenic in public-supply wells drilled in bedrock (in the National Water-Quality Assessment Program New England Coastal Basins study unit) vary with the bedrock lithology. Broad groups of lithogeochemical units generalized from bedrock lithologic units shown on state geologic maps were used in the statistical analyses. Concentrations of arsenic in water from public-supply wells in metasedimentary bedrock units that contain slightly to moderately calcareous and calcsilicate rocks (lithogeochemical group M c ) were significantly higher than the concentrations in five other groups of bedrock units in the study unit. Arsenic was detected, at or above 0.005 mg/L, in water from 44 percent of the wells in the lithogeochemical group M c and in water from less than 28 percent of wells in the five other groups. Additionally, arsenic concentrations in ground water were the lowest in the metasedimentary rocks that are characterized as variably sulfidic (group M s ). Generally, concentrations of arsenic were low in water from bedrock wells in the felsic igneous rocks (group I f ) though locally some bedrock wells in granitic rocks are known to have ground water with high arsenic concentrations, especially in New Hampshire. The concentrations of arsenic in ground water also correlate with land-use data; significantly higher concentrations are found in areas identified as agricultural land use than in undeveloped areas. There is, however, more agricultural land in areas overlying the metasedimentary rocks of lithogeochemical groups M c and the minimally-deformed clastic sediments of group M md than in areas overlying other lithogeochemical groups. This correlation complicates the interpretation of sources of arsenic to ground water in bedrock. A test of this association revealed that relations between arsenic concentrations and the metasedimentary rocks of group M c are not weakened when data associated with agricultural land use is removed; the reverse is true, however, if the data associated with the group M c are removed from the analysis. The occurrence and variability of arsenic in water from bedrock supply wells could be related to several factors. These include (1) the distribution and chemical form of arsenic in soils and rocks that are part of the ground-water-flow system, (2) the characteristics that influence the solubility and transport of arsenic in ground water, (3) the differing degrees of vulnerability of ground-water supplies to surface contamination, and (4) the spatial associations between land use, geology, and ground-water-flow patterns. Strong relations between agricultural land use and the metasedimentary rocks of group M c complicate the interpretation of arsenic source to water in these bedrock aquifers. This is due in part to the past use of arsenical pesticides; additionally, few whole-rock geochemical data are available for the rock types in the lithogeochemical groups of aquifers that contain ground water with elevated concentrations of arsenic. Without such data, identifying specific bedrock types as arsenic sources is not possible. In southern Maine and south-central New Hampshire, and in northern Massachusetts, the few available whole-rock analyses suggest, at least for these local areas, a connection between known bedrock chemistry and ground-water arsenic levels. Although the lithogeochemical group and land-use category variables individually describe much of the variance in the concentrations of arsenic in ground water, the lithogeochemical relation is statistically stronger than the land-use relation. Low concentrations of arsenic in water from bedrock public-supply wells are associated with the metasedimentary rocks of group M s (characterized as variably sulfidic). This association could reflect a variety of factors and suggests that simple dissolution of arsenic-bearing iron phases, such as sulfides, may not explain concentrations of arsenic in water in this bedrock aquifer group. Whole-rock geochemical data and more complete water-chemistry data, as well as studies of historical variation of arsenic concentrations (time-line studies), and site-specific studies, will be critical in addressing the arsenic source issue.

New England coastal basins↗
USGS2025

Automated generation of an urban synthetic elevation checkpoint network across the North Carolina coastline, USA

Lidar and structure from motion-derived digital elevation and surface models have widespread application. Consideration of a topographic model's vertical root mean squared error (RMSEz) and systematic directional bias is important for many of these applications, particularly landscape change detection and measurement. Due to logistic, resource, and time constraints, wide area remotely sensed topographic surveys are not always accompanied by an in situ checkpoint network for validating and characterizing survey error. Here we describe and test a method for automatically generating synthetic elevation checkpoints in bulk across hundreds of kilometers using a publicly available lidar-derived DEM time-series, road vector network, and landcover classification map. Our method produced 6000–10,000 synthetic checkpoints across the developed barrier island coastline of North Carolina. These checkpoints characterized vertical error metrics in a statistically similar way as in situ checkpoints when assessing the vertical accuracy of a contemporary lidar-derived DEM and produced RMSEz metrics an average of 0.018 m from the RMSEz of historical lidar DEMs published with tested accuracy metrics. This new method has the potential to A) lower the cost and time required to validate new remotely sensed topographic surveys by reducing or eliminating the field work associated with in situ checkpoint surveys, B) provide a means of retroactively assessing the absolute vertical accuracy and systematic bias of historical topographic datasets that were not published with tested accuracy metrics, and C) generate reference networks to assess and correct spatially variable patterns of vertical bias in topographic datasets.

North Carolina↗
USGS2010

On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake

Most models of lower crust/mantle viscosity inferred from postearthquake relaxation assume one or two uniform-viscosity layers. A few existing models possess apparently significant radially variable viscosity structure in the shallow mantle (e.g., the upper 200 km), but the resolution of such variations is not clear. We use a geophysical inverse procedure to address the resolving power of inferred shallow mantle viscosity structure using postearthquake relaxation data. We apply this methodology to 9 years of GPS-constrained crustal motions after the 16 October 1999 M = 7.1 Hector Mine earthquake. After application of a differencing method to isolate the postearthquake signal from the “background” crustal velocity field, we find that surface velocities diminish from ∼20 mm/yr in the first few months to ≲2 mm/yr after 2 years. Viscoelastic relaxation of the mantle, with a time-dependent effective viscosity prescribed by a Burgers body, provides a good explanation for the postseismic crustal deformation, capturing both the spatial and temporal pattern. In the context of the Burgers body model (which involves a transient viscosity and steady state viscosity), a resolution analysis based on the singular value decomposition reveals that at most, two constraints on depth-dependent steady state mantle viscosity are provided by the present data set. Uppermost mantle viscosity (depth ≲ 60 km) is moderately resolved, but deeper viscosity structure is poorly resolved. The simplest model that explains the data better than that of uniform steady state mantle viscosity involves a linear gradient in logarithmic viscosity with depth, with a small increase from the Moho to 220 km depth. However, the viscosity increase is not statistically significant. This suggests that the depth-dependent steady state viscosity is not resolvably different from uniformity in the uppermost mantle.

California↗
USGS2020

Identifying areas of degrading and improving groundwater-quality conditions in the State of California, USA, 1974-2014

Areas of improving and degrading groundwater-quality conditions in the State of California were assessed using spatial weighting of a new metric for scoring wells based on constituent concentrations and the direction and magnitude of a trend slope (Sen). Individual well scores were aggregated across 2135 equal-area grid cells covering the entire groundwater resource used for public supply in the state. Spatial weighting allows results to be aggregated locally (well or grid cell), regionally (groundwater basin), provincially, or statewide. Results differentiate degrading (increasing concentration trends) areas with low to moderate concentrations (unimpaired) from degrading areas with moderate to high concentrations (impaired). Results also differentiate improving areas (decreasing concentration trends) in the same manner. Multi-year to decadal groundwater-quality trends were computed from periodic, inorganic water-quality data for 38 constituents collected between 1974 and 2014 for compliance monitoring of nearly 13,000 public-supply wells (PSWs) in the State of California. Mann-Kendall (MK) rank correlations and Sen’s slope estimator were used to detect statistically significant trends for the entire period of recorded data (long-term trend), for the period since 2000 (recent trend), for different pumping seasons (seasonal trend), and for reversals of trends. Statewide, the most frequently detected trends since 2000 were for nitrate (36%), gross alpha/uranium (10%), arsenic (14%), total dissolved solids (TDS) (23%), and the major ions that contribute to TDS (19–28%). The Transverse and Selected Peninsular Ranges (TSPR) and the San Joaquin Valley (SJV) hydrogeologic provinces had the largest percentage of areas with moderate to high nitrate concentrations and groundwater quality trends. Improving nitrate concentrations in parts of the TSPR is associated with long-term managed aquifer recharge that has replaced historical, agriculturally affected groundwater with low-nitrate recharge in parts of the TSPR. This example suggests that application of dilute, excess surface water to agricultural fields during the winter could improve groundwater-quality in the SJV over the long term.

California↗
USGS2022

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire behavior and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns would support better policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. High severity patch simulations was comparable between the coarse and fine resolution vegetation datasets. Improving our ability to simulate burn severity will help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps can support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

California↗
USGS2015

Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions

Triggered seismicity arising from dynamic stresses is often explained by the Mohr-Coulomb failure criterion, where elevated pore pressures reduce the effective strength of faults in fluid-saturated rock. The seismic response of a fluid-rock system naturally depends on its hydro-mechanical properties, but accurately assessing how pore-fluid pressure responds to applied stress over large scales in situ remains a challenging task; hence, spatial variations in response are not well understood, especially around active faults. Here I analyze previously unutilized records of dynamic strain and pore-pressure from regional and teleseismic earthquakes at Plate Boundary Observatory (PBO) stations from 2006 through 2012 to investigate variations in response along the Pacific/North American tectonic plate boundary. I find robust scaling-response coefficients between excess pore pressure and dynamic strain at each station that are spatially correlated: around the San Andreas and San Jacinto fault systems, the response is lowest in regions of the crust undergoing the highest rates of secular shear strain. PBO stations in the Parkfield instrument cluster are at comparable distances to the San Andreas fault (SAF), and spatial variations there follow patterns in dextral creep rates along the fault, with the highest response in the actively creeping section, which is consistent with a narrowing zone of strain accumulation seen in geodetic velocity profiles. At stations in the San Juan Bautista (SJB) and Anza instrument clusters, the response depends non-linearly on the inverse fault-perpendicular distance, with the response decreasing towards the fault; the SJB cluster is at the northern transition from creeping-to-locked behavior along the SAF, where creep rates are at moderate to low levels, and the Anza cluster is around the San Jacinto fault, where to date there have been no statistically significant creep rates observed at the surface. These results suggest that the strength of the pore pressure response in fluid-saturated rock near active faults is controlled by shear strain accumulation associated with tectonic loading, which implies a strong feedback between fault strength and permeability: dynamic triggering susceptibilities may vary in space and also in time.

Journal of Geophysical Research B: Solid Earth↗
USGS2002

Spatio-temporal dynamics of species richness in coastal fish communities

Determining patterns of change in species richness and the processes underlying the dynamics of biodiversity are of key interest within the field of ecology, but few studies have investigated the dynamics of vertebrate communities at a decadal temporal scale. Here, we report findings on the spado-temporal variability in the richness and composition of fish communities along the Norwegian Skagerrak coast having been surveyed for more than half a century. Using statistical models incorporating non-detection and associated sampling variance, we estimate local species richness and changes in species composition allowing us to compute temporal variability in species richness. We tested whether temporal variation could be related to distance to the open sea and to local levels of pollution. Clear differences in mean species richness and temporal variability are observed between fjords that were and were not exposed to the effects of pollution. Altogether this indicates that the fjord is an appropriate scale for studying changes in coastal fish communities in space and time. The year-to-year rates of local extinction and turnover were found to be smaller than spatial differences in community composition. At the regional level, exposure to the open sea plays a homogenizing role, possibly due to coastal currents and advection.

Proceedings of the Royal Society B: Biological Sci↗
USGS2017

Is “morphodynamic equilibrium” an oxymoron?

Morphodynamic equilibrium is a widely adopted yet elusive concept in the field of geomorphology of coasts, rivers and estuaries. Based on the Exner equation, an expression of mass conservation of sediment, we distinguish three types of equilibrium defined as static and dynamic, of which two different types exist. Other expressions such as statistical and quasi-equilibrium which do not strictly satisfy the Exner conditions are also acknowledged for their practical use. The choice of a temporal scale is imperative to analyse the type of equilibrium. We discuss the difference between morphodynamic equilibrium in the “real world” (nature) and the “virtual world” (model). Modelling studies rely on simplifications of the real world and lead to understanding of process interactions. A variety of factors affect the use of virtual-world predictions in the real world (e.g., variability in environmental drivers and variability in the setting) so that the concept of morphodynamic equilibrium should be mathematically unequivocal in the virtual world and interpreted over the appropriate spatial and temporal scale in the real world. We draw examples from estuarine settings which are subject to various governing factors which broadly include hydrodynamics, sedimentology and landscape setting. Following the traditional “tide-wave-river” ternary diagram, we summarize studies to date that explore the “virtual world”, discuss the type of equilibrium reached and how it relates to the real world.

Earth-Science Reviews↗
USGS2023

Estimating lentic recreational fisheries catch and effort across the United States

Recreational fisheries represent a socially, ecologically, and economically significant component of global fisheries. The U.S. Inland Creel and Angler Survey Catalog (CreelCat) database includes inland recreational fisheries survey data across the United States to facilitate large-scale analyses. However, because survey methods differ, a statistical method capable of integrating these surveys is necessary to assess patterns and relationships across regions. Here, we developed a hierarchical generalized linear mixed modeling approach to estimate the relationship between daily recreational fisheries catch and effort based on waterbody, socio-economic, and ecological covariates. We applied this approach to CreelCat data on lentic waterbodies and found that recreational fisheries catch and effort were non-linearly related (i.e., catch per unit of effort declined as effort increased), where effort varied regionally and by waterbody area, median county age, and distance to nearest primary road. This modeling approach could be used to inform data-poor regions or waterbodies, make comparisons across spatial scales, and, with the inclusion of socio-economic and ecological factors, inform management techniques in an era of shifting demographics and landscapes.

Fisheries Management and Ecology↗
USGS2020

The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011. The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies. Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.

Florida↗
USGS2017

Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier

Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008 to 2013. In this investigation, we sought to contribute to the availability of consistent CONUS crop cover maps by extending temporal coverage of the NASS CDL archive back eight additional years to 2000 by creating annual NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million records to train a classification tree algorithm and develop a crop classification model (CCM). The model was used to create crop cover maps for the CONUS for years 2000–2013 at 250 m spatial resolution. The CCM and the maps for years 2008–2013 were assessed for accuracy relative to resampled NASS CDLs. The CCM performed well against a withheld test data set with a model prediction accuracy of over 90%. The assessment of the crop cover maps indicated that the model performed well spatially, placing crop cover pixels within their known domains; however, the model did show a bias towards the ‘Other’ crop cover class, which caused frequent misclassifications of pixels around the periphery of large crop cover patch clusters and of pixels that form small, sparsely dispersed crop cover patches.

Remote Sensing Letters↗
USGS2021

Assessment of water availability in the Osage Nation using an integrated hydrologic-flow model

The Osage Nation of northeastern Oklahoma, conterminous with Osage County, covers about 2,900 square miles. The area is primarily rural with 62 percent of the land being native prairie grass, and much of the area is used for cattle ranching and extraction of petroleum and natural gas. Protection of water rights are important to the Osage Nation because of its reliance on cattle ranching and the potential for impairment of water quality by petroleum extraction. Additionally, the potential for future population increases, demands for water from neighboring areas such as the Tulsa metropolitan area, and expansion of petroleum and natural-gas extraction on water resources of this area further the need for the Osage Nation to better understand its water availability. Therefore, the U.S. Geological Survey, in cooperation with the Osage Nation, completed a hydrologic investigation to assess the status and availability of surface-water and groundwater resources in the Osage Nation. A transient integrated hydrologic-flow model was constructed using the U.S. Geological Survey fully integrated hydrologic-flow model called the MODFLOW One-Water Hydrologic Model. The integrated hydrologic-flow model, called the Osage Nation Integrated Hydrologic Model (ONIHM), was constructed and uses an orthogonal grid of 276 rows and 289 columns, and each grid cell measures 1,312.34 feet (ft; 400 meters) per side, with eight variably thick vertical layers that represented the alluvial and bedrock aquifers within the study area, including the alluvial aquifer, the Vamoosa-Ada aquifer, and the minor Pennsylvanian bedrock aquifers, and the confining units. Landscape and groundwater-flow processes were simulated for two periods: (1) the 1950–2014 period from January 1950 through September 2014 and (2) the forecast period from October 2014 through December 2099. The 1950–2014 period ONIHM simulated past conditions using measured or estimated inputs, and the forecast-period ONIHM simulated three separate potential forecast conditions under constant dry, average, or wet climate conditions using calibrated input values from the 1950–2014 period ONIHM. The 1950–2014 period ONIHM was calibrated by linking the Parameter Estimation software (PEST) with the MODFLOW One-Water Hydrologic Model. PEST uses statistical parameter estimation techniques to identify the best set of parameter values to minimize the difference between measured or estimated calibration targets and their simulated equivalent values (residuals). Tikhonov regularization and singular-value decomposition-assist features of PEST were used during the calibration process. The 1950–2014 period ONIHM was calibrated to 713 measured groundwater levels at 195 wells; 95,636 estimated monthly mean groundwater levels at 124 wells; 5,307 measured streamflows at 13 streamgages; and 8,679 simulated mean monthly streamflows at 10 streamgages extracted from a surface-water model by adjusting 231 parameters. The estimated groundwater-level observations and streamflows were included as observations to improve the spatial and temporal density of observation targets during calibration. The best set of parameter values obtained during the calibration process of the 1950–2014 model was then used as the input parameter values for the forecast model simulations. A comparison of the calibration targets to their corresponding simulated values indicated that the model adequately reproduced streamflows and groundwater levels for some streamgages and wells and underestimated streamflows and groundwater levels at other locations. Measured and simulated streamflows correlated adequately with a coefficient of determination of 0.938, as did water levels with a coefficient of determination of 0.795. The 1950–2014 period ONIHM underestimated certain groundwater levels and streamflows, but generally measured or estimated calibration targets correlated well with simulated equivalents, which indicated that the model can adequately simulate the response of the hydrologic system to stresses in the 1950–2014 and forecast periods. In the 1950–2014 period ONIHM, the calibrated mean horizontal hydraulic conductivity for layer 1 alluvial aquifer was 30.7 feet per day, and the seven lower layers had a calibrated mean horizontal hydraulic conductivity of less than 3.3 feet per day. The mean calibrated groundwater-level residual was 16.6 ft, and the mean calibrated streamflow residual of the Arkansas River at Ralston, Oklahoma, streamgage (U.S. Geological Survey station 07152500) was within 6 percent (373 cubic feet per second) of mean measured streamflow for the 1950–2014 period ONIHM. The ONIHM simulated landscape fluxes of precipitation; groundwater applied by irrigation wells; evapotranspiration from precipitation, groundwater, and irrigation; runoff from precipitation; and deep percolation from precipitation. The largest loss of water from the landscape was evapotranspiration from precipitation with a calibrated mean annual outflow of 32 inches (in.): mean annual precipitation was about 36 in. Calibrated mean annual runoff and deep percolation (recharge to the water table) rates were 4.7 inches per year (in/yr) and 0.70 in/yr, respectively, for the 1950–2014 period ONIHM. The calibrated 1950–2014 period ONIHM groundwater fluxes included net farm net recharge (calculated as the difference between the inflow of recharge to the water table and the outflow of evapotranspiration from the water table such that negative values indicate that evapotranspiration from the water table was greater than deep percolation [recharge to the water table] and vice versa). Net farm net recharge was the largest flux from the groundwater system with a mean annual net outflow of 153.4 cubic feet per second. Stream leakage was the largest flux to the groundwater system with a mean annual net inflow of 152.5 cubic feet per second, indicating that, on average, the groundwater/surface-water interaction was a “losing” system where stream water leaked into the subsurface and recharged the water table. Simulated monthly trends demonstrated that net stream leakage was the largest inflow to the groundwater-flow system for 10 of the 12 months; for the other 2 months (January and March), farm net recharge (January) and net storage (March) were the largest inflow to the groundwater-flow system. A saline groundwater interface map was created for the study and compared to the water levels from the final stress period of the 1950–2014 model to identify the presence of fresh/marginal groundwater throughout the study area. Fresh/marginal groundwater was characterized as groundwater with less than 1,500 milligrams per liter of total dissolved solids. Fresh/marginal groundwater thickness ranged from 0 to 438.2 ft within the study area. The thickest regions of fresh/marginal groundwater were in the eastern part of the study area near Sand Creek, Bird Creek, and Hominy Creek and in the Arkansas River alluvial aquifer in the region downstream from the Arkansas River at Ralston, Okla. Like the 1950–2014 model, forecast model results for the landscape indicated that transpiration from precipitation was the largest flux out of the landscape for all three forecasts, constituting 77, 73, and 58 percent of precipitation for the dry, average, and wet forecasts, respectively. The dry and average forecast landscape fluxes demonstrated similar trends and magnitudes, whereas the wet forecast landscape fluxes indicated the largest changes compared to the average forecast fluxes. Most notably, runoff increased from a mean of 1.1 and 1.6 in/yr for the dry and average forecasts, respectively, to 10 in/yr for the wet forecast. Similar changes occurred for the other wet forecast landscape fluxes. The calibrated 1950–2014 period ONIHM simulated three forecasts to assess the effects of potential climatic changes on the hydrologic system from October 2014 to December 2099. The three forecasts simulated theoretical dry, average, and wet conditions using precipitation and potential evapotranspiration datasets from selected years in the calibrated 1950–2014 period ONIHM. Annual precipitation amounts were 26.89, 35.47, and 50.73 in. for the dry, average, and wet forecasts, respectively. Groundwater-flow component forecast results indicated that stream leakage is always a net inflow to the groundwater-flow system for dry, average, and wet conditions, meaning the study area stream network is always predominantly a “losing” regime where stream water infiltrates into the underlying aquifer. Storage was only a net outflow from the groundwater-flow system and indicated a replenishment to groundwater storage that resulted in an increase in groundwater levels only during the wet forecast. Further, these gains in groundwater storage for the wet forecast occurred only during February through June. Mean fresh/marginal groundwater saturated thicknesses were 125 and 126 ft for the dry and average forecast conditions, respectively, and wet forecast average thickness was 145 ft and ranged from 0 to 443 ft. The spatial extents of fresh/marginal groundwater at the end of the dry, average, and wet forecast model periods (December 2099) did not change substantially from the end of the 1950–2014 model period (September 2014).

Kansas, Oklahoma↗
USGS2004

Spatial and temporal changes in microbial community structure associated with recharge-influenced chemical gradients in a contaminated aquifer

In a contaminated water‐table aquifer, we related microbial community structure on aquifer sediments to gradients in 24 geochemical and contaminant variables at five depths, under three recharge conditions. Community amplified ribsosomal DNA restriction analysis (ARDRA) using universal 16S rDNA primers and denaturing gradient gel electrophoresis (DGGE) using bacterial 16S rDNA primers indicated: (i) communities in the anoxic, contaminated central zone were similar regardless of recharge; (ii) after recharge, communities at greatest depth were similar to those in uncontaminated zones; and (iii) after extended lack of recharge, communities at upper and lower aquifer margins differed from communities at the same depths on other dates. General aquifer geochemistry was as important as contaminant or terminal electron accepting process (TEAP) chemistry in discriminant analysis of community groups. The Shannon index of diversity ( H ) and the evenness index ( E ), based on DGGE operational taxonomic units (OTUs), were statistically different across community groups and aquifer depths. Archaea or sulphate‐reducing bacteria 16S rRNA abundance was not clearly correlated with TEAP chemistry indicative of methanogenesis or sulphate reduction. Eukarya rRNA abundance varied by depth and date from 0 to 13% of the microbial community. This contaminated aquifer is a dynamic ecosystem, with complex interactions between physical, chemical and biotic components, which should be considered in the interpretation of aquifer geochemistry and in the development of conceptual or predictive models for natural attenuation or remediation.

Environmental Microbiology↗
USGS2008

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

Ecological Modelling↗
USGS2022

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

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

Journal of Geophysical Research--Solid Earth↗
USGS2006

Water-quality characteristics, including sodium-adsorption ratios, for four sites in the Powder River drainage basin, Wyoming and Montana, water years 2001-2004

The U.S. Geological Survey, in cooperation with the Wyoming Department of Environmental Quality, monitors streams throughout the Powder River structural basin in Wyoming and parts of Montana for potential effects of coalbed natural gas development. Specific conductance and sodium-adsorption ratios may be larger in coalbed waters than in stream waters that may receive the discharge waters. Therefore, continuous water-quality instruments for specific conductance were installed and discrete water-quality samples were collected to characterize water quality during water years 2001-2004 at four sites in the Powder River drainage basin: Powder River at Sussex, Wyoming; Crazy Woman Creek near Arvada, Wyoming; Clear Creek near Arvada, Wyoming; and Powder River at Moorhead, Montana. During water years 2001-2004, the median specific conductance of 2,270 microsiemens per centimeter at 25 degrees Celsius (?S/cm) in discrete samples from the Powder River at Sussex, Wyoming, was larger than the median specific conductance of 1,930 ?S/cm in discrete samples collected downstream from the Powder River at Moorhead, Montana. The median specific conductance was smallest in discrete samples from Clear Creek (1,180 ?S/cm), which has a dilution effect on the specific conductance for the Powder River at Moorhead, Montana. The daily mean specific conductance from continuous water-quality instruments during the irrigation season showed the same spatial pattern as specific conductance values for the discrete samples. Dissolved sodium, sodium-adsorption ratios, and dissolved solids generally showed the same spatial pattern as specific conductance. The largest median sodium concentration (274 milligrams per liter) and the largest range of sodium-adsorption ratios (3.7 to 21) were measured in discrete samples from the Powder River at Sussex, Wyoming. Median concentrations of sodium and sodium-adsorption ratios were substantially smaller in Crazy Woman Creek and Clear Creek, which tend to decrease sodium concentrations and sodium-adsorption ratios at the Powder River at Moorhead, Montana. Dissolved-solids concentrations in discrete samples were closely correlated with specific conductance values; Pearson's correlation coefficients were 0.98 or greater for all four sites. Regression equations for discrete values of specific conductance and sodium-adsorption ratios were statistically significant (p-values <0.001) at all four sites. The strongest relation (R2=0.92) was at the Powder River at Sussex, Wyoming. Relations on Crazy Woman Creek (R2=0.91) and Clear Creek (R2=0.83) also were strong. The relation between specific conductance and sodium-adsorption ratios was weakest (R2=0.65) at the Powder River at Moorhead, Montana; however, the relation was still significant. These data indicate that values of specific conductance are useful for estimating sodium-adsorption ratios. A regression model called LOADEST was used to estimate dissolved-solids loads for the four sites. The average daily mean dissolved-solids loads varied among the sites during water year 2004. The largest average daily mean dissolved-solids load was calculated for the Powder River at Moorhead, Montana. Although the smallest concentrations of dissolved solids were in samples from Clear Creek, the smallest average daily mean dissolved-solids load was calculated for Crazy Woman Creek. The largest loads occurred during spring runoff, and the smallest loads occurred in late summer, when streamflows typically were smallest. Dissolved-solids loads may be smaller than average during water years 2001-2004 because of smaller than average streamflow as a result of drought conditions.

Scientific Investigations Report↗