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At least 1,765 records · Page 98Linked to original sources
USGS2019

Exploring silica stoichiometry on a large floodplain riverscape

Freshwater ecosystems are critical zones of nutrient and carbon (C) processing along the land-sea continuum. Relative to our understanding of C, nitrogen (N), and phosphorus (P) cycling within the freshwater systems, the controls on silicon (Si) cycling and export are less understood. Understanding Si biogeochemistry and its coupled biogeochemical processing with N and P has direct implications for both freshwater and coastal ecosystems, as the amount of Si in relation to N and P exported by rivers to coastal receiving waters can determine phytoplankton species assemblages, which in turn affects C cycling and food web structure. Here we examine the relationships between dissolved Si (DSi), total nitrogen (TN), and total phosphorus (TP) concentrations, and how these relationships relate to basin land cover, lithology, and river hydrogeomorphology (i.e., among different ‘aquatic areas’) in the Upper Mississippi River System (UMRS) using two datasets (one from the tributaries and one from the mainstem) that span a nine-year period (2010-2018) representing >10,000 unique samples. We found significant declines in DSi concentrations, as well as Si:TP and Si:TN ratios along the north-south gradient of the mainstem UMRS across all six aquatic area types. This signal was driven partially by a corresponding decline in tributary DSi inputs along this latitudinal gradient. Contrary to findings from other regions of North America, basin land cover was not an important predictor of tributary DSi concentrations, especially compared to lithology. However, Si:TN and Si:TP ratios appear to be strongly controlled by basin land cover, likely due to excess N and P loading from row-crop agriculture. Si, and its ratio with N and P (i.e., Si stoichiometry), was similar across most aquatic area types, including run-of-river impoundments and the main channel, suggesting similar processes affecting Si, N, and P concentrations in these reaches. However, backwater lakes had lower DSi and TN concentrations and compared to the other aquatic area types, highlighting the importance of water residence time and nutrient uptake in controlling Si stoichiometry in inland waters. Together, our results show rivers are not simple pipes for Si, but rather the complexity in watershed characteristics, hydrology, and biological uptake results in dynamic Si stoichiometry along the river continuum.

Frontiers in Ecology and Evolution↗
USGS2016

Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region

Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI) Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-based model, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeochemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes on cropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC) change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxes uncertainties and the relationships between the uncertainties and the land cover characteristics. Results indicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formed multiple clusters within the MCI region. We investigated the impacts of three land cover characteristics on the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The results indicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but not on the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties with small cropland percentage than the counties with large cropland percentage. Cropland species richness and diversity also showed negative correlations with the model uncertainties. Our study demonstrated that the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates. The approaches we used in this study can be applied to other ecosystem models to identify the areas with high uncertainties and where models can be improved to reduce overall uncertainties for regional carbon flux estimates.

Mid-Continent Intensive Campaign region↗
USGS2026

Integrating climate and anthropogenic dynamics can inform multifaceted management for declining mule deer populations

Wildlife and their habitats face profound challenges from climate and landscape-scale changes that extend beyond the influence and time horizon of most biologists and land managers. In this changing environment, long-term datasets can enhance assessments of how demographic trends respond to interactions among local (e.g., habitat restoration decisions) and broad extent drivers, including energy development, to shape wildlife populations. Although many studies evaluate habitat selection or demographics for a single population, our multipopulation, multiscale study quantifies the influence of local management actions given broader environmental forces using both immediate and lagged effects. This approach may be particularly important for species with high site fidelity that may have less adaptive capacity, including mule deer ( Odocoileus hemionus ), which are experiencing widespread population declines. We analyzed a 40-year (1980–2019) dataset for 37 mule deer populations across Wyoming, USA, to test hypotheses about and quantify the relative influence of conditions within winter use areas on annual rates of juvenile recruitment. Recruitment has been strongly affected by multiple factors largely beyond the control of managers. Land cover (agriculture and shrubland) had the largest positive effects on recruitment, with estimates more than twice the magnitude of other variables, but also had limited presence in some winter use areas. The next strongest effect sizes were shared by energy developments (including oil/gas and wind energy) and climatic conditions, which, except for wind turbines, had broad distributions across winter use areas. Recruitment increased with higher mean winter temperatures and summer precipitation, but declined with wind, oil and gas developments, cumulative drought, and wildfire. Expected increases in drought and decreases in summer precipitation may constrain options to sustain mule deer populations. Although mule deer recruitment may sometimes be enhanced through habitat restoration, effects varied with treatment type, habitat type, and time since treatment. Given large constraining effects of temperature and drought, supporting drought resiliency for important habitat may be useful. Our results can be used to weigh the relative strength of threats and the value of restoration actions, interpret historic demographic change, prioritize populations for conservation, and optimize options for wildlife habitat management.

Wyoming↗
USGS2026

Tracking decadal changes in frequent fire activity across the southeastern U.S. (2000-2019): Insights from Southeast FireMap

Background The dominant natural habitats in the southeastern United States depend on frequent fire ignited by humans or lightning. However, fire activity has sharply declined in the region since the early 1900s, and reduced fire activity has degraded natural habitats and increased wildfire risk. Identifying changes in fire use during recent decades is necessary to guide the conservation of fire-dependent wildlife, management of hazardous fuels, and identify areas where increased fire use could improve ecosystem resilience. To address this need, we created the Southeast FireMap dataset by fine-tuning the United States Geological Survey’s Landsat Burned Area product to track burned area, and provide a fire history across the southeastern United States. We used the Southeast FireMap data to quantify changes in areas frequently burned, as measured by areas with multiple burns within a decade. We compared the periods 2000–2009 and 2010–2019 to identify where frequently burned area is increasing or declining. We examined patterns of change across ownership, land cover, and soil orders to provide geographic context, and we considered future implications of these changes for land use categories of ecological interest. Results Frequently burned area increased between decades across the region. This increase occurred on both private and public lands, in upland vegetation types, and on upland soils, though these increases were moderately offset by decreased wetland burning and its associated soil orders. However, changes varied among states, with burned area decreasing in some states. Conclusions The overall increase in frequently burned area across the region reflects a summation of positive and negative shifts associated with specific combinations of physiography, ownership class, and government jurisdiction. Southeast FireMap marks a significant advancement in our ability to identify changes in prescribed burning within the geographic and cultural contexts that will likely influence the complex future of fire in the region.

southeastern United States↗
USGS2015

Getting out of harm's way - evacuation from tsunamis

Scientists at the U.S. Geological Survey (USGS) have developed a new mapping tool, the Pedestrian Evacuation Analyst , for use by researchers and emergency managers to estimate how long it would take for someone to travel on foot out of a tsunami-hazard zone. The ArcGIS software extension, released in September 2014, allows the user to create maps showing travel times out of hazard zones and to determine the number of people that may or may not have enough time to evacuate. The maps take into account the elevation changes and the different types of land cover that a person would encounter along the way. Maps of travel time can be used by emergency managers and community planners to identify where to focus evacuation training and tsunami education. The tool can also be used to examine the potential benefits of vertical-evacuation structures, which are buildings or berms designed to provide a local high ground in low-lying areas of the hazard zone.

Sound Waves: Coastal science and research news fro↗
USGS2000

Assessing habitat selection in Spring by male American Woodcock in Maine with a geographic information system

Geographic information system (GIS) technology was used to identify habitats available to and used by male American woodcock (Scolopax minor) equipped with radio transmitters--54 in 1987, 51 in 1988, 46 in 1989 at Moosehorn National Wildlife Refuge, Maine. Woodcock were monitored from time of capture (25 March-15 April) to 15 June each year. To determine habitat selection by male woodcock, the following habitat characteristics were measured: land cover, age and stocking density of the forest overstory, soil drainage and texture, aspect, and percent slope. Habitat selection was examined as affected by the covariates weather and age-class of woodcock, and among years for diurnal and crepuscular periods of the breeding period. Multivariate techniques that compare use and availability of habitats were not available, so a statistical model was developed to rate importance of multiple habitat characteristics selected by woodcock. The most critical period for woodcock in terms of survival was from arrival to: mid-April. Second-year and after-second-year woodcock did not select different (P > 0.05) habitat types, but they did select different types among years and within breeding intervals (P < 0.05). In years when weather was moderate, woodcock selected young, dense stands of speckled alder (Alnus rugosa) and hardwoods, interspersed with forest openings. Suitable habitat can be maintained by creating an uneven-aged forest managed in even-aged blocks composed of several hardwood species. Managers can now quantify suitable woodcock habitat in a GIS and plan large-scale forest-harvesting strategies using data on several habitat characteristics (e.g., land cover, stand age, stocking density, soil drainage and texture, and aspect).

Book chapter↗
USGS2010

Multistate modeling of habitat dynamics: Factors affecting Florida scrub transition probabilities

Many ecosystems are influenced by disturbances that create specific successional states and habitat structures that species need to persist. Estimating transition probabilities between habitat states and modeling the factors that influence such transitions have many applications for investigating and managing disturbance-prone ecosystems. We identify the correspondence between multistate capture-recapture models and Markov models of habitat dynamics. We exploit this correspondence by fitting and comparing competing models of different ecological covariates affecting habitat transition probabilities in Florida scrub and flatwoods, a habitat important to many unique plants and animals. We subdivided a large scrub and flatwoods ecosystem along central Florida's Atlantic coast into 10-ha grid cells, which approximated average territory size of the threatened Florida Scrub-Jay (Aphelocoma coerulescens), a management indicator species. We used 1.0-m resolution aerial imagery for 1994, 1999, and 2004 to classify grid cells into four habitat quality states that were directly related to Florida Scrub-Jay source-sink dynamics and management decision making. Results showed that static site features related to fire propagation (vegetation type, edges) and temporally varying disturbances (fires, mechanical cutting) best explained transition probabilities. Results indicated that much of the scrub and flatwoods ecosystem was resistant to moving from a degraded state to a desired state without mechanical cutting, an expensive restoration tool. We used habitat models parameterized with the estimated transition probabilities to investigate the consequences of alternative management scenarios on future habitat dynamics. We recommend this multistate modeling approach as being broadly applicable for studying ecosystem, land cover, or habitat dynamics. The approach provides maximum-likelihood estimates of transition parameters, including precision measures, and can be used to assess evidence among competing ecological models that describe system dynamics. ?? 2010 by the Ecological Society of America.

Ecology↗
USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗
USGS2022

Development of the LCMAP annual land cover product across Hawai'i

Following the completion of land cover and change (LCC) products for the conterminous United States (CONUS), the U.S. Geological Survey's (USGS’s) Land Change Monitoring, Assessment, and Projection initiative has broadened the capability of characterizing continuous historical land change across the full Landsat records for Hawaiʻi at 30-meter resolution. One of the challenges of implementing the LCMAP framework to process annual land cover maps in Hawaiʻi is to collect sufficient high-quality training data. Although multiple datasets depicting land cover information are available in Hawaiʻi, they covered limited time frames and were produced from various remote sensing sources with different, classification categories, spatial resolution, and mapping accuracies. No solo product is suitable to provide LCMAP training data labels on its own. In this paper, we focused on enhancing the LCMAP training datasets to generate land cover products from 2000 to 2019 in Hawaiʻi. A total of 200 independent reference data plots were generated and manually interpreted for validating the mapping results produced by the training datasets. The results revealed that using the appropriate filter of multiple products as training data pools improved the classification model performance. The effect of training datasets (e.g., spatial coverage, quality) on accuracies for different land cover types were summarized. The LCMAP land surface change products for Hawaiʻi are available at https://doi.org/10.5066/P91E8M23 .

Hawaii↗
USGS2026

Invasion resistance varies by fuel break type in sagebrush ecosystems

Background Wildfire is an increasingly important driver of changes within sagebrush (Artemisia spp. L.) ecosystems of the western USA, often resulting in increased spread of exotic annual grasses, such as cheatgrass (Bromus tectorum L.), and subsequent losses of native vegetation and wildlife habitat. Fuel breaks— areas of land treated to reduce or redistribute fuel loads — are widely implemented to help prevent the spread of wildfires and provide areas to facilitate firefighting efforts. However, localized installation and maintenance of fuel breaks directly reduce or remove vegetation and may propagate the spread of exotic annual grasses into fuel break boundaries and surrounding areas, inadvertently weakening ecological resilience to disturbance. To investigate if exotic annual grass cover was associated with mowed or green strip fuel breaks across the sagebrush biome, we combined multiple data sources and methodologies. We used targeted field surveys and land-management agency monitoring data within a space-for-time substitution framework coupled with a progressive-change before-after control-impact (PC BACI) study design using historical remotely sensed vegetation cover data which allowed us to account for potential confounding effects of roads on annual grass cover. Results Models using both field collected and remotely sensed vegetation indices estimated increases in exotic annual grass cover over time following mowed fuel break installation, and higher exotic annual grass cover closer to mowed fuel breaks. These increases in exotic annual grass occurred within, at 500 m and at 1000 m from mowed fuel breaks. However, we found variable patterns of exotic annual grass after green strip fuel break installation depending on the data source. No increase in exotic annual grass were indicated by either analysis at distances greater than 500 m from green strip fuel breaks. However, our and field data analyses disagreed on the direction of the association of exotic annual grass cover and green strip fuel breaks. Conclusions Although fuel breaks are an important tool in managing wildland fire, our analysis underscores the importance of planting fire-resistant vegetation, rather than mowing alone, to reduce invasion by annual grasses within and around fuel breaks in sagebrush ecosystems. In addition, site characteristics that hinder the proliferation of exotic annual grasses could be evaluated when installing fuel breaks to minimize unintended effects of exotic annual grass on surrounding sagebrush habitat.

California, Idaho, Nevada, Oregon, Utah↗
USGS2020

Non-crop habitat use by wild bees (Hymenoptera: Apoidea) in a mixed-use agricultural landscape

Homogeneous, agriculturally intense landscapes have abundant records of pollinator community research, though similar studies in the forest-dominated, heterogeneous mixed-use landscape that dominates the northeastern United States are sparse. Trends of landscape effects on wild bees are consistent across homogeneous agricultural landscapes, whereas reported studies in the northeastern United States have not found this consistency. Additionally, the role of noncrop habitat in mixed-use landscapes is understudied. We assessed wild bee communities in the mixed-use lowbush blueberry ( Vaccinium angustifolium Ait.) production landscape of Maine, United States at 56 sites in eight land cover types across two regional landscapes and analyzed effects of floral resources, landscape pattern, and spatial scale on bee abundance and species richness. Within survey sites, cover types with abundant floral resources, including lowbush blueberry fields and urban areas, promoted wild bee abundance and diversity. Cover types with few floral resources such as coniferous and deciduous/mixed forest reduced bee abundance and species richness. In the surrounding landscape, lowbush blueberry promoted bee abundance and diversity, while emergent wetland and forested land cover strongly decreased these measures. Our analysis of landscape configuration revealed that patch mixing can promote wild bee abundance and diversity; however, this was influenced by strong variation across our study landscape. More surveys at intra-regional scales may lead to better understanding of the influence of mixed-use landscapes on bee communities.

Environmental Entomology↗
USGS2017

Multi-scale 46-year remote sensing change detection of diamond mining and land cover in a conflict and post-conflict setting

The town of Tortiya was created in the rural northern region of Côte d′Ivoire in the late 1940s to house workers for a new diamond mine. Nearly three decades later, the closure of the industrial-scale diamond mine in 1975 did not diminish the importance of diamond profits to the region's economy, and resulted in the growth of artisanal and small-scale diamond mining (ASM) within the abandoned industrial-scale mining concession. In the early 2000s, the violent conflict that arose in Côte d′Ivoire highlighted the importance of ASM land use to the local economy, but also brought about international concerns that diamond profits were being used to fund the rebellion. In recent years, cashew plantations have expanded exponentially in the region, diversifying economic activity, but also creating the potential for conflict between diamond mining and agricultural land uses. As the government looks to address the future of Tortiya and this potential conflict, a detailed spatio-temporal understanding of the changes in these two land uses over time may assist in informing policymaking. Remotely sensed imagery presents an objective and detailed spatial record of land use/land cover (LULC), and change detection methods can provide quantitative insight regarding regional land cover trends. However, the vastly different scales of ASM and cashew orchards present a unique challenge to comprehensive understanding of land use change in the region. In this study, moderate-scale categories of LULC, including cashew orchards, uncultivated forest, urban space, mining/ bare, and mixed vegetation, were produced through supervised classification of Landsat multispectral imagery from 1984, 1991, 2000, 2007, and 2014. The fine-scale ASM land use was identified through manual interpretation of annually acquired high resolution satellite imagery. Corona imagery was also integrated into the study to extend the temporal duration of the remote sensing record back to the period of industrial-scale mining. These different-scale analyses were then integrated to create a record of 46 years of mining activity and land cover change in Tortiya. While similar in spatial extent, the mining/ bare class in the integrated analysis exhibits a substantially different spatial distribution than in the original classifications. This additional information regarding the locations of ASM activity in the Tortiya area is important from a policy and planning perspective. The results of this study also suggest that LULC classifications of Landsat imagery do not consistently capture areas of ASM in the Côte d′Ivoire landscape.

Remote Sensing Applications: Society and Environme↗
USGS2001

A strategy for estimating tree canopy density using Landsat 7 ETM+ and high resolution images over large areas

Forest cover is of great interest to a variety of scientific and land management applications, many of which require not only information on forest categories, but also tree canopy density. In previous studies, large area tree canopy density had been estimated at spatial resolutions of 1km or coarser using coarse resolution satellite images. In this study, a strategy is developed for estimating tree canopy density at a spatial resolution of 30 m. This strategy is based on empirical relationships between tree canopy density and Landsat data, established using linear regression and regression tree techniques. One-meter digital orthophoto quadrangles were used to derive reference tree canopy density data needed for calibrating the relationships between canopy density and Landsat spectral data. This strategy was tested over three areas of the United States. In general, models derived using both linear regression and regression tree techniques were statistically significant. The regression tree was found more robust than linear regression, primary due to its capability of approximating complex non-linear relationships using a set of linear equations. This strategy will be recommended for use in developing a nation wide tree canopy density data set at a 30 m resolution as part of the Multi-Resolution Land Characteristics 2000 project.

Conference Paper↗
USGS2025

U.S. national park units as breeding bird habitat: A comparison of species prevalence and land cover across the midwestern and central United States

The value of national parks as bird habitat depends not only on local conditions within the parks, but also on the landscape habitat matrices in which they are located. However, the influences of local and landscape habitat matrices on birds vary by species and have not been quantified. Similarly, the trends of land cover types through time have not been systematically quantified for Midwest Region national parks and the landscapes around them, despite evidence of ongoing habitat loss exacerbated by climate change and human population growth. Managers and policy makers can use this information to understand and sustain the contribution of parks to our Nation’s avifauna. We developed models using North American Breeding Bird Survey (BBS) data collected on routes from across the central United States. The models were used to predict occupancy of bird species of concern in 32 national park units across nine Bird Conservation Regions in the Midwest based on land cover in and around those parks. We then compared these predictions with data collected through National Park Service (NPS) bird surveys at each park to determine if bird species of concern were more or less prevalent than expected. In each park, the mean difference between observed species detections and mean predicted detections indicates that most species are less frequently detected in the parks than predicted. However, when the range of uncertainty of predictions is considered, only 21% of park-bird combinations showed strong evidence (95%) of differing from expectation. Of these, species were less common than expected in the park in all but two cases. These results indicate that some bird species of concern occupy sites in Midwest Region national park units at a rate roughly comparable to sites with similar land cover in the Bird Conservation Region (BCR) in which they occur. However, for one in five species-park combinations, parks appear to be less occupied than comparable sites elsewhere.

Midwest region↗
USGS1993

"Relative CIR": an image enhancement and visualization technique

Many techniques exist to spectrally and spatially enhance digital multispectral scanner data. One technique enhances an image while keeping the colors as they would appear in a color-infrared (CIR) image. This "relative CIR" technique generates an image that is both spectrally and spatially enhanced, while displaying a maximum range of colors. The technique enables an interpreter to visualize either spectral or land cover classes by their relative CIR characteristics. A relative CIR image is generated by developed spectral statistics for each class in the classifications and then, using a nonparametric approach for spectral enhancement, the means of the classes for each band are ranked. A 3 by 3 pixel smoothing filter is applied to the classification for spatial enhancement and the classes are mapped to the representative rank for each band. Practical applications of the technique include displaying an image classification product as a CIR image that was not derived directly from a spectral image, visualizing how a land cover classification would look as a CIR image, and displaying a spectral classification or intermediate product that will be used to label spectral classes.

Pecora 12 Symposium↗
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↗
USGS2011

Evaluation of an index of biotic integrity approach used to assess biological condition in western U.S. streams and rivers at varying spatial scales

Consistent assessments of biological condition are needed across multiple ecoregions to provide a greater understanding of the spatial extent of environmental degradation. However, consistent assessments at large geographic scales are often hampered by lack of uniformity in data collection, analyses, and interpretation. The index of biotic integrity (IBI) has been widely used in eastern and central North America, where fish assemblages are complex and largely composed of native species, but IBI development has been hindered in the western United States because of relatively low fish species richness and greater relative abundance of alien fishes. Approaches to developing IBIs rarely provide a consistent means of assessing biological condition across multiple ecoregions. We conducted an evaluation of IBIs recently proposed for three ecoregions of the western United States using an independent data set covering a large geographic scale. We standardized the regional IBIs and developed biological condition criteria, assessed the responsiveness of IBIs to basin-level land uses, and assessed their precision and concordance with basin-scale IBIs. Standardized IBI scores from 318 sites in the western United States comprising mountain, plains, and xeric ecoregions were significantly related to combined urban and agricultural land uses. Standard deviations and coefficients of variation revealed relatively low variation in IBI scores based on multiple sampling reaches at sites. A relatively high degree of corroboration with independent, locally developed IBIs indicates that the regional IBIs are robust across large geographic scales, providing precise and accurate assessments of biological condition for western U.S. streams. ?? Copyright by the American Fisheries Society 2008.

Transactions of the American Fisheries Society↗
USGS2008

Wide-area estimates of saltcedar (Tamarix spp.) evapotranspiration on the lower Colorado River measured by heat balance and remote sensing methods

In many places along the lower Colorado River, saltcedar ( Tamarix spp) has replaced the native shrubs and trees, including arrowweed, mesquite, cottonwood and willows. Some have advocated that by removing saltcedar, we could save water and create environments more favourable to these native species. To test these assumptions we compared sap flux measurements of water used by native species in contrast to saltcedar, and compared soil salinity, ground water depth and soil moisture across a gradient of 200–1500 m from the river's edge on a floodplain terrace at Cibola National Wildlife Refuge (CNWR). We found that the fraction of land covered ( f c ) with vegetation in 2005–2007 was similar to that occupied by native vegetation in 1938 using satellite-derived estimates and reprocessed aerial photographs scaled to comparable spatial resolutions (3–4 m). We converted f c to estimates of leaf area index (LAI) through point sampling and destructive analyses ( r 2 = 0·82). Saltcedar LAI averaged 2·54 with an f c of 0·80, and reached a maximum of 3·7 with an f c of 0·95. The ranges in f c and LAI are similar to those reported for native vegetation elsewhere and from the 1938 photographs over the study site. On-site measurements of water use and soil and aquifer properties confirmed that although saltcedar grows in areas where salinity has increased much better than native shrubs and trees, rates of transpiration are similar. Annual water use over CNWR was about 1·15 m year −1 .

Arizona, California↗