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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 217 records · Page 12Linked to original sources
USGS2024

Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics

Invasive dreissenid mussels ( Dreissena polymorpha and Dreissena rostriformis bugensis ) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict Dreissena spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with Dreissena spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.

Lake Huron↗
USGS2001

USGS Mineral Resources Program; national maps and datasets for research and land planning

The U.S. Geological Survey, the Nation’s leader in producing and maintaining earth science data, serves as an advisor to Congress, the Department of the Interior, and many other Federal and State agencies. Nationwide datasets that are easily available and of high quality are critical for addressing a wide range of land-planning, resource, and environmental issues. Four types of digital databases (geological, geophysical, geochemical, and mineral occurrence) are being compiled and upgraded by the Mineral Resources Program on regional and national scales to meet these needs. Where existing data are incomplete, new data are being collected to ensure national coverage. Maps and analyses produced from these databases provide basic information essential for mineral resource assessments and environmental studies, as well as fundamental information for regional and national land-use studies. Maps and analyses produced from the databases are instrumental to ongoing basic research, such as the identification of mineral deposit origins, determination of regional background values of chemical elements with known environmental impact, and study of the relationships between toxic elements or mining practices to human health. As datasets are completed or revised, the information is made available through a variety of media, including the Internet. Much of the available information is the result of cooperative activities with State and other Federal agencies. The upgraded Mineral Resources Program datasets make geologic, geophysical, geochemical, and mineral occurrence information at the state, regional, and national scales available to members of Congress, State and Federal government agencies, researchers in academia, and the general public. The status of the Mineral Resources Program datasets is outlined below.

Fact Sheet↗
USGS2017

The Upper Mississippi River System—Topobathy

The Upper Mississippi River System (UMRS), the navigable part of the Upper Mississippi and Illinois Rivers, is a diverse ecosystem that contains river channels, tributaries, shallow-water wetlands, backwater lakes, and flood-plain forests. Approximately 10,000 years of geologic and hydrographic history exist within the UMRS. Because it maintains crucial wildlife and fish habitats, the dynamic ecosystems of the Upper Mississippi River Basin and its tributaries are contingent on the adjacent flood plains and water-level fluctuations of the Mississippi River. Separate data for flood-plain elevation (lidar) and riverbed elevation (bathymetry) were collected on the UMRS by the U.S. Army Corps of Engineers’ (USACE) Upper Mississippi River Restoration (UMRR) Program. Using the two elevation datasets, the U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) developed a systemic topobathy dataset.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2003

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Journal of Geophysical Research E: Planets↗
USGS2019

Toxicokinetics of imidacloprid-coated wheat seeds in Japanese quail (Coturnix japonica) and an evaluation of hazard

Birds are potentially exposed to neonicotinoid insecticides by ingestion of coated seeds during crop planting. Adult male Japanese quail were orally dosed with wheat seeds coated with an imidacloprid (IMI) formulation at either 0.9 mg/kg body weight (BW) or 2.7 mg/kg BW (~3 and 9% of IMI LD50 for Japanese quail, respectively) for 1 or 10 days. Quail were euthanized between 1 and 24 h post-exposure to assess toxicokinetics. Analysis revealed rapid absorption (1 h) into blood, and distribution to brain, muscle, kidney and liver. Clearance to below detection limits occurred at both dose levels and exposure durations in all tissues within 24 h. Metabolism was extensive, with 5-OH-IMI and IMI-olefin detected at greater concentrations than IMI in tissues and fecal samples. There was no lethality or overt signs of toxicity at either dose level. Furthermore, no evidence of enhanced expression of mRNA genes associated with hepatic xenobiotic metabolism, oxidative DNA damage or alterations in concentrations of corticosterone and thyroid hormones was observed. Application of the toxicokinetic data was used to predict IMI residue levels in liver with reasonable results for some field exposure and avian mortality events. It would appear that some affected species are either consuming larger quantities of seeds or exhibit differences in ADME or sensitivity than predicted by read-across from these data.

Environmental Science & Technology↗
USGS2015

Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km 2 ). LAGOS includes two modules: LAGOS GEO , with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOS LIMNO , with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.

Connecticut, Delaware, Illinois, Indiana, Iowa, Ma↗
USGS2007

Invasive species management and research using GIS

Geographical Information Systems (GIS) are powerful tools in the field of invasive species management. GIS can be used to create potential distribution maps for all manner of taxa, including plants, animals, and diseases. GIS also performs well in the early detection and rapid assessment of invasive species. Here, we used GIS applications to investigate species richness and invasion patterns in fish in the United States (US) at the 6-digit Hydrologic Unit Code (HUC) level. We also created maps of potential spread of the cane toad (Bufo marinus) in the southeastern US at the 8-digit HUC level using regression and environmental envelope techniques. Equipped with this potential map, resource managers can target their field surveys to areas most vulnerable to invasion. Advances in GIS technology, maps, data, and many of these techniques can be found on websites such as the National Institute of Invasive Species Science (www.NIISS.org). Such websites provide a forum for data sharing and analysis that is an invaluable service to the invasive species community.

Conference Paper↗
USGS2010

Great Basin Integrated Landscape Monitoring Pilot Summary Report

The Great Basin Integrated Landscape Monitoring Pilot project (GBILM) was one of four regional pilots to implement the U.S. Geological Survey (USGS) Science Thrust on Integrated Landscape Monitoring (ILM) whose goal was to observe, understand, and predict landscape change and its implications on natural resources at multiple spatial and temporal scales and address priority natural resource management and policy issues. The Great Basin is undergoing rapid environmental change stemming from interactions among global climate trends, increasing human populations, expanding and accelerating land and water uses, invasive species, and altered fire regimes. GBLIM tested concepts and developed tools to store and analyze monitoring data, understand change at multiple scales, and forecast landscape change. The GBILM endeavored to develop and test a landscape-level monitoring approach in the Great Basin that integrates USGS disciplines, addresses priority management questions, catalogs and uses existing monitoring data, evaluates change at multiple scales, and contributes to development of regional monitoring strategies. GBILM functioned as an integrative team from 2005 to 2010, producing more than 35 science and data management products that addressed pressing ecosystem drivers and resource management agency needs in the region. This report summarizes the approaches and methods of this interdisciplinary effort, identifies and describes the products generated, and provides lessons learned during the project.

Open-File Report↗
USGS2003

Modeling precipitation and sorption of elements during mixing of river water and porewater in the Coeur d'Alene River basin

Reddish brown flocs form along the edge of the Coeur d'Alene River when porewater drains into river water during the annual lowering of water level in the basin. The precipitates are efficient scavengers of dissolved elements and have characteristics that may make metals associated with them bioavailable. This work characterizes the geochemistry of the porewater and models the formation and composition of the flocs. Porewater is slightly acidic, has suboxic to anoxic characteristics, tends to have higher alkalinity, and contains elevated concentrations of many constituents relative to river water. Laboratory mixing experiments involving porewater and river water were done to produce the precipitates. Thermodynamic predictions using PHREEQC indicate that predicted amounts of ferrihydrite and gibbsite agree with removal of Fe and Al. Predictions of element removal by adsorption onto ferrihydrite are consistent with observed removal using a combination of surface complexation constants for the generalized two-layer model (As and Se), alternative surface constants derived from experiments at high sorbate-to-sorbent ratios (Cd, Co, Cu, Ni, Pb, and Zn), and adjusted surface constants to fit experimental data (Cr, Mo, and Sb). This new set of surface complexation constants needs further testing in other contaminated systems.

Idaho↗
USGS2024

Informative priors can account for location uncertainty in stop-level analyses of the North American Breeding Bird Survey (BBS), allowing fine-scale ecological analyses

Ecological inferences are often based on the locations at which species are present, but many species records have substantial uncertainty in spatial metadata, limiting their utility for fine-scale analyses. This is especially prevalent in historical records such as museum specimens, and in some citizen-science data. For example, the North American Breeding Bird Survey (BBS) has 55+ years of bird data from regular transects (“routes”) across the continent but was not designed to capture the spatial component of point count events, limiting analyses of species-habitat relationships for which it would otherwise be well suited. We present a new methodology for quantifying location uncertainty in BBS records using digitized estimated stop locations, deriving the corresponding environmental covariate uncertainty distributions, and incorporating this information into hierarchical species distribution models using informative Bayesian priors. This approach allows for estimation of species–environment relationships in a way that fully accounts for underlying spatial uncertainty. We quantify stop-location uncertainty in BBS data across the central United States, model bird–land cover relationships in the upper Midwest, and validate our method by comparing posterior land cover estimates to known covariate values for a subset of GPS-digitized stop locations. We provide code for implementing this method in R. Posterior land cover estimates (forest, grass/hay, and developed land cover), based on our informative priors, were highly correlated with known land cover values from GPS-digitized stop locations. Our approach thus makes it possible to responsibly leverage large historic and citizen science databases, such as the BBS, for fine-scale ecological analyses.

Ornithological Applications↗
USGS2005

Topographic, bioclimatic, and vegetation characteristics of three ecoregion classification systems in North America: Comparisons along continent-wide transects

Ecoregion classification systems are increasingly used for policy and management decisions, particularly among conservation and natural resource managers. A number of ecoregion classification systems are currently available, with each system defining ecoregions using different classification methods and different types of data. As a result, each classification system describes a unique set of ecoregions. To help potential users choose the most appropriate ecoregion system for their particular application, we used three latitudinal transects across North America to compare the boundaries and environmental characteristics of three ecoregion classification systems [Ku??chler, World Wildlife Fund (WWF), and Bailey]. A variety of variables were used to evaluate the three systems, including woody plant species richness, normalized difference in vegetation index (NDVI), and bioclimatic variables (e.g., mean temperature of the coldest month) along each transect. Our results are dominated by geographic patterns in temperature, which are generally aligned north-south, and in moisture, which are generally aligned east-west. In the west, the dramatic changes in physiography, climate, and vegetation impose stronger controls on ecoregion boundaries than in the east. The Ku??chler system has the greatest number of ecoregions on all three transects, but does not necessarily have the highest degree of internal consistency within its ecoregions with regard to the bioclimatic and species richness data. In general, the WWF system appears to track climatic and floristic variables the best of the three systems, but not in all regions on all transects. ?? 2005 Springer Science+Business Media, Inc.

Environmental Management↗
USGS2003

Geographic analysis and monitoring at the United States Geological Survey

The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey assesses the Nation's land surface at a variety of spatial and temporal scales to understand the rates, causes, and consequences of natural and human-induced processes and their interactions that affect the landscape over time. The program plays an important role in developing National Map tools and application. The GAM is a science and synthesis program that not only assesses the rates of changes to the Earth's land surface, but also provides reports on the status and trends of the Nation's land resources on a periodic basis, produces a land-use and land- cover database for the periodically updated map and data set-the Geographic Face of the Nation, and conducts research leading to improved understanding and knowledge about geographic processes. Scientific investigations provide comprehensive information needed to understand the environmental, resource, and economic consequences of landscape change. These analyses responds to the needs of resource managers and offers the American public baseline information to help them understand the dynamic nature of our national landscape and to anticipate the opportunities and consequences of our actions.

Cartography and Geographic Information Science↗
USGS2021

Current activity on the Martian surface: A key subject for future exploration

One of the fundamental discoveries in Mars science in the last decade has been the extent and importance of current surface activity. Recent results have shifted our view of Mars from a world where the most interesting geologic events were in the distant past (similar to the Moon) to a world that undergoes active evolution and one where understanding the present is key to deciphering the planet’s history. When input was requested for the last Planetary Science Decadal Survey, some observations of surface changes had been published, but the number of detections was small and their significance not fully appreciated. Since that time, detections have proliferated, driven primarily by the long-term operation of the Mars Reconnaissance Orbiter (MRO) and the High Resolution Imaging Science Experiment (HiRISE) as well as landed observations of aeolian activity. In addition to observed changes, theory suggests that additional important surface processes are likely active but not yet observed because orbital data are limited in space and time and landed studies are rare. Understanding current Martian surface processes is a fundamental science question in itself, as it provides a test for physical and terrestrial analog-based models of specific geological processes acting under non-Earth planetary and environmental conditions. It is also an essential step for reading Mars’ geologic history and providing input to climate models: without understanding current dynamic processes, we cannot understand how they have varied during recent climate cycles, nor how they are reflected in ancient rock or modern ice records. Understanding the rates and types of current surface activity is also highly relevant to selecting geological samples, setting Planetary Protection rules, and understanding the hazards and environment that would be experienced by future human explorers.

Bulletin of the AAS↗
USGS2010

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

International Journal of Remote Sensing↗
USGS2022

Ungulate migration in a changing climate—An initial assessment of climate impacts, management priorities, and science needs

Executive Summary Migratory behavior among ungulates in the Western United States occurs in response to changing forage quality and quantity, weather patterns, and predation risk. As snow melts and vegetation green-up begins in late spring and early summer, many migratory ungulates leave their winter range and move to higher elevation summer ranges to access high-quality forage and areas with vegetative cover for protection during fawning. Ungulates remain on these ranges until the fall when increasing snowfall and decreasing temperatures trigger them to migrate back to their lower elevation winter ranges. While researchers have begun to assess the effects of physical barriers such as roads and energy infrastructure on migration, less attention has been paid to understanding how changing climate conditions might affect ungulate movements and range habitats. Does earlier spring green-up make ungulates leave their winter ranges sooner? Do persistent drought conditions reduce the carrying capacity of seasonal range habitats or lead to shifts in migration pathways? These and other questions remain largely unanswered but could have cascading effects on ungulate population dynamics and migratory behavior. In February 2018, the Secretary of the Interior signed Department of the Interior Secretarial Order 3362 (SO3362), “Improving Habitat Quality in Western Big-Game Winter Range and Migration Corridors.” The order, which focuses on elk, mule deer, and pronghorn in 11 Western States, directs the Bureau of Land Management (BLM), the U.S. Fish and Wildlife Service (FWS), the National Park Service (NPS), and the U.S. Geological Survey (USGS) to partner with State wildlife agencies on their priorities and objectives for identifying and conserving ungulate migration corridors and winter-range habitat. The USGS Climate Adaptation Science Centers (CASCs) were established to help managers of the Nation’s fish, wildlife, waters, and lands understand the effects of climate change and adapt to changing conditions. To support the recent Department of the Interior (DOI) emphasis on ungulate migration corridors and winter-range habitat, this report assesses current information on how climate change could affect elk, mule deer, and pronghorn migration. The report synthesizes the drivers of migration, outlines what is known about how climate change might affect these drivers, and summarizes management priorities and science needs related to ungulate migration corridors and range habitat. A review of the literature on ungulate migration shows that the core drivers of spring migration are the timing of spring green-up and snowmelt, and the core driver of fall migration is winter severity. After exploring what is known about how these drivers affect or could be affected by climate change, several pathways through which ungulate migration could be altered were identified: (1) ungulates alter migration timing to better track plant phenology or in response to changes in winter conditions; (2) ungulates change their migration route or distance traveled during migration to accommodate changes in environmental conditions; and (3) ungulate populations that are currently migratory may begin to demonstrate interannual variability in whether they migrate, depending on environmental conditions and density-dependence, and may remain resident for sets of consecutive years. Through discussions with managers, physical barriers to movement such as roads and fences were identified as a core concern. In addition, the primary research needs of States are the acquisition and analysis of data on ungulate movements, to refine delineation of winter range, summer range, and corridors, and to support a better understanding of how ungulates use these habitats. When it comes to understanding climate effects, managers were more concerned with understanding the vulnerability of winter- and summer-range habitats than the vulnerability of migration corridors because of the influence of summer and winter forage on ungulate condition and reproductive success. Managers were also concerned about how forage quality and quantity might change because of stressors such as drought, wildfire, and invasive species and how they might need to alter habitat-treatment strategies as a result. More baseline data are needed before effective projections of ungulate migration, at a West-wide scale under climate change, can be made. These data needs include (1) more clearly defined corridors and seasonal range habitats; (2) a comprehensive understanding of the ecological drivers of migration across ungulate species and populations; and (3) the identification of environmental thresholds for key variables that influence migration, above which ungulates alter migratory behavior. The CASCs have several opportunities to play a role in addressing these needs. The CASCs could initiate projects to identify past and potential future changes and trends in key variables known to affect ungulate migration, such as plant phenology, forage quality, or winter severity. However, it would be difficult to use this information to determine what those trends mean for ungulate migration due to the lack of knowledge about environmental thresholds for ungulates. Additional projects would be required to compare multiple years of movement data with key variables to define thresholds. Once available, information on environmental thresholds could be integrated with projections of key variables to forecast the likelihood that the migration routes or the distance traveled could change—another area in which the CASCs could contribute. A more immediate role for the CASCs would be to carry out synthesis projects. One such project could summarize the “state of the science” on the drivers of ungulate migration. Although there are dozens of population- and location-specific studies on this topic, collating this information could help highlight trends in migration drivers that span species and geographies: a necessary first step toward determining the extent to which migration drivers could be affected by climate change. A second project could focus on what is known about how climate variability and change affect ungulate life-histories, population dynamics, and migration in the Western United States. The goal of this effort could be to identify knowledge clusters and information gaps that require further investigation. Together, these synthesized products could focus future scientific activities on the most pressing issues of ungulate migration and climate change in the Western United States.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2021

Managing water resources on Long Island, New York, with integrated, multidisciplinary science

Nutrients, harmful algal blooms, and synthetic chemicals like per- and polyfluoroalkyl substances (PFAS) and 1,4-dioxane threaten Long Island’s water resources by affecting the quality of drinking water and ecologically sensitive habitats that support the diverse wildlife throughout the island. Understanding the occurrence, fate, and transport of these potentially harmful chemicals is critical to protect these vital resources. The U.S. Geological Survey (USGS) is collecting and analyzing data to support informed water-resource management decisions. This fact sheet introduces ongoing efforts and future areas of study aimed to help water professionals develop a comprehensive science strategy to address contamination of the Long Island aquifer system, the sole source of drinking water for nearly 3 million people. These studies include surface and groundwater collection and groundwater flow modeling. Funding for the data collection has been provided by the USGS, New York State Department of Environmental Conservation, New York City Department of Environmental Protection, Suffolk County Water Authority, Nassau County Department of Public Works, State and local agencies, and Tribal and Federal partners. Without the foresight and long-term commitment of these funding partners, evaluating sustainability and planning for future water needs would not be possible.

New York↗
USGS2025

Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.

Understanding habitat connectivity is critical for managing nonindigenous aquatic species (NAS) spread. Dams and watershed boundaries can be impassable to NAS during typical conditions but may become temporarily passable during flooding. The goal of our project was to develop an approach for identifying locations of aquatic connectivity at a fine spatial scale along watershed boundaries using readily available data. To develop this approach, we focused on the potential for range expansion of invasive fish in the United States via possible cross-boundary habitat connections. First, we developed an index using metrics of elevation, watershed size, and geology at regular points along a watershed boundary to stratify points by likelihood of connectivity during high precipitation (>20 mm of precipitation in a 3-day period). We then used a subset of points across a gradient of connectivity likelihoods to gather Landsat-derived observed surface water data and developed a statistical model to predict surface water presence from landscape characteristics. We applied the model throughout the entire watershed boundary to identify locations of hydrologic connectivity during high-water events. The presence of surface water on watershed boundaries was predicted by the interactions between watershed boundary point elevation relative to the minimum adjacent HUC-12 elevations and watershed boundary point elevation relative to neighboring point elevations (marginal R 2 = 0.94). Our approach can be used to identify potential areas of surface water connectivity between watersheds quickly and easily at a fine spatial scale using readily available, remotely sensed data that can inform conservation and management actions across disciplines.

North Dakota, South Dakota↗
USGS2012

An economic value of remote-sensing information—Application to agricultural production and maintaining groundwater quality

Does remote-sensing information provide economic benefits to society, and can a value be assigned to those benefits? Can resource management and policy decisions be better informed by coupling past and present Earth observations with groundwater nitrate measurements? Using an integrated assessment approach, the U.S. Geological Survey (USGS) applied an established conceptual framework to answer these questions, as well as to estimate the value of information (VOI) for remote-sensing imagery. The approach uses moderate-resolution land-imagery (MRLI) data from the Landsat and Advanced Wide Field Sensor satellites that has been classified by the National Agricultural Statistics Service into the Cropland Data Layer (CDL). Within the constraint of the U.S. Environmental Protection Agency's public health threshold for potable groundwater resources, the USGS modeled the relation between a population of the CDL's land uses and dynamic nitrate (NO3-) contamination of aquifers in a case study region in northeastern Iowa. Employing various multiscaled, multitemporal geospatial datasets with MRLI to maximize the value of agricultural production, the approach develops and uses multiple environmental science models to address dynamic nitrogen loading and transport at specified distances from specific sites (wells) and at landscape scales (for example, across 35 counties and two aquifers). In addition to the ecosystem service of potable groundwater, this effort focuses on the use of MRLI for the management of the major land uses in the study region-the production of corn and soybeans, which can impact groundwater quality. Derived methods and results include (1) economic and dynamic nitrate-pollution models, (2) probabilities of the survival of groundwater, and (3) a VOI for remote sensing. For the northeastern Iowa study region, the marginal benefit of the MRLI VOI (in 2010 dollars) is $858 million ±$197 million annualized, which corresponds to a net present value of $38.1 billion ±$8.8 billion for that flow of benefits in perpetuity. Given that these economic estimates are derived from one case study in a part of only one State, the estimates provide a lower estimate related to the potential value of the Landsat Data Continuity Mission.

Professional Paper↗