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USGS1992

Toward digital geologic map standards: a progress report

Establishing modern scientific and technical standards for geologic maps and their derivative map products is vital to both producers and users of such maps as we move into an age of digital cartography. Application of earth-science data in complex geographic information systems, acceleration of geologic map production, and reduction of population costs require that national standards be developed for digital geologic cartography and computer analysis. Since December 1988, under commission of the Chief Geologic of the U.S. Geological Survey and the mandate of the National Geologic Mapping Program (with added representation from the Association of American State Geologists), a committee has been designing a comprehensive set of scientific map standards. Three primary issues were: (1) selecting scientific symbology and its digital representation; (2) creating an appropriate digital coding system that characterizes geologic features with respect to their physical properties, stratigraphic and structural relations, spatial orientation, and interpreted mode of origin; and (3) developing mechanisms for reporting levels of certainty for descriptive as well as measured properties. Approximately 650 symbols for geoscience maps, including present usage of the U.S Geological Survey, state geological surveys, industry, and academia have been identified and tentatively adopted. A proposed coding system comprises four-character groupings of major and minor codes that can identify all attributes of a geologic feature. Such a coding system allows unique identification of as many as 105 geologic names and values on a given map. The new standard will track closely the latest developments of the Proposed Standard for Digital Cartographic Data soon to be submitted to the National Institute of Standards and Technology by the Federal Interagency Coordinating Committee on Digital Cartography. This standard will adhere generally to the accepted definitions and specifications for spatial data transfer. It will require separate specifications of digital cartographic quality relating to positional accuracy and ranges of measured and interpreted values such as geologic age and rock composition. Provisional digital geologic map standards will be published for trial implementation. After approximately two years, when comments on the proposed standards have been solicited and modifications made, formal adoption of the standards will be recommended. Widespread acceptance of the new standards will depend on their applicability to the broadest range of earth-science map products and their adaptability to changing cartographic technology.

Conference Paper↗

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↗

USGS2021

Identifying mismatches between conservation area networks and vulnerable populations using spatial randomization

Grassland birds are among the most globally threatened bird groups due to substantial degradation of native grassland habitats. However, the current network of grassland conservation areas may not be adequate for halting population declines and biodiversity loss. Here, we evaluate a network of grassland conservation areas within Wisconsin, U.S.A., that includes both large Focal Landscapes and smaller targeted conservation areas (e.g., Grassland Bird Conservation Areas, GBCAs) established within them. To date, this conservation network has lacked baseline information to assess whether the current placement of these conservation areas aligns with population hot spots of grassland-dependent taxa. To do so, we fitted data from thousands of avian point-count surveys collected by citizen scientists as part of Wisconsin's Breeding Bird Atlas II with multinomial N -mixture models to estimate habitat–abundance relationships, develop spatially explicit predictions of abundance, and establish ecological baselines within priority conservation areas for a suite of obligate grassland songbirds. Next, we developed spatial randomization tests to evaluate the placement of this conservation network relative to randomly placed conservation networks. Overall, less than 20% of species statewide populations were found within the current grassland conservation network. Spatial tests demonstrated a high representation of this bird assemblage within the entire conservation network, but with a bias toward birds associated with moderately tallgrasses relative to those associated with shortgrasses or tallgrasses. We also found that GBCAs had higher representation at Focal Landscape rather than statewide scales. Here, we demonstrated how combining citizen science data with hierarchical modeling is a powerful tool for estimating ecological baselines and conducting large-scale evaluations of an existing conservation network for multiple grassland birds. Our flexible spatial randomization approach offers the potential to be applied to other protected area networks and serves as a complementary tool for conservation planning efforts globally.

Wisconsin↗

USGS2002

Geologic and aeromagnetic maps of the Fossil Ridge area and vicinity, Gunnison County, Colorado

This data set includes a GIS geologic map database of an Early Proterozoic metavolcanic and metasedimentary terrane extensively intruded by Early and Middle Proterozoic granitic plutons. Laramide to Tertiary deformation and intrusion of felsic plutons have created numerous small mineral deposits that are described in the tables and are shown on the figures in the accompanying text pamphlet. Also included in the pamphlet are numerous chemical analyses of igneous and meta-igneous bodies of all ages in tables and in summary geochemical diagrams. The text pamphlet also contains a detailed description of map units and discussions of the aeromagnetic survey, igneous and metmorphic rocks, and mineral deposits. The printed map sheet and browse graphic pdf file include the aeromagnetic map of the study area, as well as figures and photographs. Purpose: This GIS geologic map database is provided to facilitate the presentation and analysis of earth-science data for this region of Colorado. This digital map database may be displayed at any scale or projection. However, the geologic data in this coverage are not intended for use at a scale other than 1:30,000. Supplemental useful data accompanying the database are extensive geochemical and mineral deposits data, as well as an aeromagnetic map.

IMAP↗

USGS2025

Quantifying the substantive influence of public comment on United States federal environmental decisions under NEPA

A citizen’s right to comment on, and criticize, government decisions makes a difference. The U.S. National Environmental Policy Act of 1969 (NEPA) institutionalized public engagement in environmental review in the belief it would lead to better decisions and more sustainable outcomes. But, 50 years later, NEPA’s public comment process has been criticized as costly and slow, while doing little to change outcomes. Data science now makes it possible to track progress and evaluate the influence of public participation. We examined 108 environmental impact statement (EIS) processes spanning 22 years. Our analysis revealed that public comments resulted in substantive decision alterations in 62% of cases, with 64% showing modifications to alternatives, 42% showing modifications to mitigation plans and 11% leading to the selection of an entirely new preferred alternative. When federal agencies changed project alternatives (78 EISs), 88% of the time (69 of the 78 EISs) they credited public comments as the reason. In 45 of the 108 EISs, agencies modified mitigation plans and credited public comments as the reason 100% of the time. Agencies only occasionally selected a new preferred alternative (21 out of 104 EISs), but when they did, they credited public comments as the reason 100% of the time. As the United States and the 190+ states and countries that have adopted NEPA’s example consider how to address environmental change, it is important to assess the role of public participation in environmental decision making. Our data say public comments matter.

Environmental Research Letters↗

USGS2025

Potential interactions between birds and floating photovoltaic solar energy: Spatially informed species vulnerabilities, techno-ecological risks, and sustainability trade-offs

Floating photovoltaics (floating solar panels; FPV) can reduce the negative impacts of solar energy development in terrestrial environments, but their effects on freshwater ecosystems remain poorly understood. We examined potential FPV interactions with avian biodiversity, using previously modeled technical potential of FPV in the northeastern United States. We developed a vulnerability index based on avian species’: (i) morphological traits, (ii) level of conservation concern, and (iii) habitat requirements. Using eBird participatory science data, we assessed the risk of FPV to 291 species of birds occurring at FPV-suitable waterbodies based on their vulnerability index and estimated relative abundance at each location. The greatest risk of FPVs to birds was associated with waterbodies near the Atlantic coast and Great Lakes, and most (80%) of these high-risk waterbodies were smaller waterbodies. Because the avian risk at FPV-suitable waterbodies was not correlated with estimated energy generation, reducing risk to birds might not require energy trade-offs. Moreover, avoiding FPV installations at waterbodies predicted to pose high risk to birds is likely to return social and recreational benefits while minimizing risk of biofouling. Our analysis provides a framework for proactively evaluating risk, reducing potential adverse impacts of FPV to birds, and identifying cobenefits of sustainable FPV siting across waterscapes.

Connecticut, Delaware, Maine, Maryland, Massachuse↗

USGS2007

Advanced technologies demonstrated by the miniature integrated camera and spectrometer (MICAS) aboard deep space 1

MICAS is an integrated multi-channel instrument that includes an ultraviolet imaging spectrometer (80-185 nm), two high-resolution visible imagers (10-20 ??rad/pixel, 400-900 nm), and a short-wavelength infrared imaging spectrometer (1250-2600 nm). The wavelength ranges were chosen to maximize the science data that could be collected using existing semiconductor technologies and avoiding the need for multi-octave spectrometers. It was flown on DS1 to validate technologies derived from the development of PICS (Planetary Imaging Camera Spectrometer). These technologies provided a novel systems approach enabling the miniaturization and integration of four instruments into one entity, spanning a wavelength range from the UV to IR, and from ambient to cryogenic temperatures with optical performance at a fraction of a wavelength. The specific technologies incorporated were: a built-in fly-by sequence; lightweight and ultra-stable, monolithic silicon-carbide construction, which enabled room-temperature alignment for cryogenic (85-140 K) performance, and provided superb optical performance and immunity to thermal distortion; diffraction-limited, shared optics operating from 80 to 2600 nm; advanced detector technologies for the UV, visible and short-wavelength IR; high-performance thermal radiators coupled directly to the short-wave infrared (SWIR) detector optical bench, providing an instrument with a mass less than 10 kg, instrument power less than 10 W, and total instrument cost of less than ten million dollars. The design allows the wavelength range to be extended by at least an octave at the short wavelength end and to 50 microns at the long wavelength end. Testing of the completed instrument demonstrated excellent optical performance down to 77 K, which would enable a greatly reduced background for longer wavelength detectors. During the Deep Space 1 Mission, MICAS successfully collected images and spectra for asteroid 9969 Braille, Mars, and comet 19/P Borrelly. The Borrelly encounter was a scientific hallmark providing the first clear, high resolution images and excellent, short-wavelength infrared spectra of the surface of an active comet's nucleus. ?? 2007 Springer Science+Business Media, Inc.

Space Science Reviews↗

USGS2023

Intensified warming and aridity accelerate terminal lake desiccation in the Great Basin of the western United States

Terminal lakes in the Great Basin (GB) of the western US host critical wildlife habitat and food for migrating birds and can be associated with serious human health and economic consequences when they desiccate. Water levels have declined dramatically in the last 100+ years due to diversion of inflows, drought and climate change. Satellite-derived environmental science data records (ESDRs) from the MODerate-resolution Imaging Spectroradiometer (MODIS) (snow cover, evapotranspiration (ET) and land surface temperature (LST)), enable a unique approach to evaluate the effects of aridification on terminal lakes and to study their individual vulnerabilities. Surface and air temperatures in the GB are rising dramatically, with a sharp rise in the rate of increase observed beginning around 2011, while the number of days of snow cover is declining especially in the western mountainous part of the GB as exemplified in Mono Basin, California. Rising temperatures coincide with fewer days of snow cover, a decrease of inflow to the lakes and greater evaporation of water from the lakes. MODIS ESDRs show strong and statistically significant increasing surface temperature (LST) in the GB, a reduction in the number of days of snow cover, and mixed results in ET. ET declined slightly in the more arid parts of the GB due to greater moisture restrictions to evaporation from extended drought, while ET increased in the more-vegetated, wetter, mountainous northeastern parts as temperatures have risen. Severe and costly ecological, human health and economic consequences are expected if the lakes continue to decline as predicted.

Great Basin↗

USGS2022

Choosing an optimal duck season: Integrating hunter values and duck abundance

State wildlife agencies have long struggled to identify optimal hunting season dates for migratory game bird species that meet the diverse and often competing interests of stakeholders. Many approaches have been used to ensure the regulated community participates in the decision-making process, including public hearings, hunter season-date preference surveys, and hunter task forces or committees. Although hearings, surveys, and task force approaches include portions of the regulated community (typically the most avid) they may not necessarily reflect the opinions and values of all stakeholders. Additionally, these approaches rely heavily on limited anecdotal observations that may be unduly influenced by hunter avidity (e.g., days spent afield), hunter density, species preferences, and property access. To address the challenges caused by engaging only portions of the stakeholder community, we used a structured decision-making framework that included a 2017 duck hunter survey to elucidate values of a representative sample of the regulated community in each waterfowl hunting zone in the state of New York, USA. Rather than asking duck hunters about their specific duck hunting season date preferences, we asked them to rank 6 objectives describing what they value in their hunting experience (e.g., maximizing the opportunity to see mallards [ Anas platyrhynchos ] and black ducks [ Anas rubripes ], maximizing the number of weekend days). Four of the 6 objectives described duck species availability (i.e., abundance or immigration) and the remaining 2 described considerations that affect an individual hunter's opportunity or limitation to going duck hunting (i.e., holidays or conflicting hunting seasons). We used spatiotemporal abundance models derived from eBird citizen science data to estimate abundance and immigration rates of ducks in each waterfowl zone. We evaluated up to 9 unique season date alternatives developed by duck hunter task forces to determine which season date alternative best satisfied the competing objectives of duck hunters in each zone. The approach we developed allowed for selection of optimal duck hunting season dates and successfully involved avid duck hunters in the regulation development stages, while ensuring that the values of a representative sample of all stakeholders were directly considered through a clear and transparent decision-making process.

New York↗

USGS2024

Exploring and integrating differences in niche characteristics across regional and global scales to better understand plant invasions in Hawaiʻi

The spread of ecosystem modifying invasive plant (EMIP) species is one of the largest threats to native ecosystems in Hawaiʻi. However, differences in niche characteristics between Hawaiʻi’s isolated insular environment and the wider global distribution of these species have not been carefully examined. We used species distribution modeling (SDM) methods to assess similarities and differences in niche characteristics between global and regional scales for 17 EMIPs present in Hawaiʻi. With a clearer understanding of the global context of regional plant invasion, we combined two SDM methods to better understand the potential future regional spread: (1) a nested modeling approach to integrate global and regional invasive species distribution projections; and (2) integrating all available agency and citizen science data to minimize the effect of monitoring gaps and biases. Our results show there are multiple similarities in niche characteristics across regional and global scales for most species, such as similar sets of climatic determinants of distribution, similar responses along environmental gradients, and moderate to high niche overlap between global and regional models. However, some differences were apparent and likely due to several factors including incomplete regional spread, community assembly or diversity effects. Invaders that established earlier showed a higher degree of niche overlap and similar environmental gradient responses when comparing global and regional models. This pattern, coupled with the tendency for regionally-based projections to predict narrower distributions than global projections, indicates a potential for continued spread of several invasive species across the Hawaiian landscape. Our study has broader implications for understanding the distribution and spread of invasive species in other regions, as similar analyses and models, including a novel way to characterize environmental gradient response differences across regions or scales, can likely provide valuable information for conservation and management efforts.

Hawaii↗

USGS2011

Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.

Aquatic Botany↗

USGS2012

Landsat: building a strong future

Conceived in the 1960s, the Landsat program has experienced six successful missions that have contributed to an unprecedented 39-year record of Earth Observations that capture global land conditions and dynamics. Incremental improvements in imaging capabilities continue to improve the quality of Landsat science data, while ensuring continuity over the full instrument record. Landsats 5 and 7 are still collecting imagery. The planned launch of the Landsat Data Continuity Mission in December 2012 potentially extends the Landsat record to nearly 50 years. The U.S. Geological Survey (USGS) Landsat archive contains nearly three million Landsat images. All USGS Landsat data are available at no cost via the Internet. The USGS is committed to improving the content of the historical Landsat archive though the consolidation of Landsat data held in international archives. In addition, the USGS is working on a strategy to develop higher-level Landsat geo- and biophysical datasets. Finally, Federal efforts are underway to transition Landsat into a sustained operational program within the Department of the Interior and to authorize the development of the next two satellites — Landsats 9 and 10.

Remote Sensing of Environment↗

USGS2017

Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States

Remote sensing-based field-scale evapotranspiration (ET) maps are useful for characterizing water use patterns and assessing crop performance. The relative impact of climate variability and water management decisions are better studied and quantified using historical data that are derived using a set of consistent datasets and methodology. Historical (1984–2014) Landsat-based ET maps were generated for major irrigation districts in California, i.e., Palo Verde and eight other sub-basins in parts of the middle and lower Central Valley. A total of 3396 Landsat images were processed using the Operational Simplified Surface Energy Balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study sites over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively good correspondence (R 2 up to 0.88, root mean square error as low as 14 mm/month) between SSEBop ET and validation datasets. In a pairwise comparison, annual variability of agro-hydrologic parameters of actual evapotranspiration ( ET a ), land surface temperature ( T s ), and runoff ( Q ) were found to be more variable than their corresponding climatic counterparts of atmospheric water demand ( ET o ), air temperature ( T a ), and precipitation ( P ), revealing process differences between regional climatic drivers and localized agro-hydrologic responses. However, only T a showed a consistent increase (up to 1.2 K) over study sites during the 31 years, whereas other climate variables such as ET o and P showed a generally neutral trend. This study demonstrates a useful application of “Big Data” science where large volumes of historical Landsat and weather datasets were used to quantify and understand the relative importance of water management and climate variability in crop water use dynamics in regards to the linkages among water management decisions, hydrologic processes and economic transactions. Irrigation district-wide ET a estimates were used to compute historical crop water use volumes and monetary equivalents of water savings for the Palo Verde Irrigation District (PVID). During the peak crop fallowing year in PVID, the water saved reached a maximum of ~ 107,200 acre-feet in 2011 with an estimated monetary payout value of $20.5 million. A significant decreasing trend in actual ET despite an increasing atmospheric demand in PVID highlights the role of management decisions in affecting local hydrologic processes. This study has importance for planning water resource allocation, managing water rights, sustaining agricultural production, and quantifying impacts of climate and land use/land cover changes on water resources. With increased computational efficiency, similar studies can be conducted in other parts of the world to help policy and decision makers understand and quantify various aspects of water resources management.

Arizona, California↗

USGS2018

A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data

This paper introduces our research in developing a probabilistic model to extract linear terrain features from high resolution DEM (Digital Elevation Model) data. The proposed model takes full advantage of spatio-contextual information to characterize terrain changes. It first derives a quantifiable measure of spatio-contextual patterns of linear terrain feature, such as ridgelines, valley lines and crater boundaries, and then adopts multiple neighborhood analysis and a probability model to address data uncertainty in terrain surface modeling. Different from traditional approaches, the proposed model has the ability to achieve near-automated processing, and to support effective extraction of terrain features in both smooth and rough surfaces. Through a series of experiments, we demonstrate that the proposed approach outperforms existing techniques, including: thresholding, stream/drainage network analysis, visual descriptor, object-based image analysis and edge detection. We hope this work contributes to both the geospatial data science and geomorphology communities with a new way of utilizing high-resolution imagery in terrain analysis.

International Journal of Geographical Information ↗

USGS2023

The future of ecosystem assessments is automation, collaboration, and artificial intelligence

Robust and routine ecosystem assessments will be fundamental to track progress towards achieving this decade’s global environmental and sustainability goals. Here we examine four needs that address common failure points of ecosystem assessments. These are (1) developing rapid, reproducible, and repeatable ecological data workflows, (2) harmonizing in situ and remotely sensed data, (3) integrating socioeconomic and biophysical data, and (4) increasing access to the digital resources and cyberinfrastructure needed to perform assessments. These four needs have profound potential to help us achieve our environmental objectives through cross-sector collaborations that leverage advancements in digital resources, remote data streams, and data science.

Environmental Research Letters↗

USGS2016

Flow management for hydropower extirpates aquatic insects, undermining river food webs

Dams impound the majority of rivers and provide important societal benefits, especially daily water releases that enable on-peak hydroelectricity generation. Such “hydropeaking” is common worldwide, but its downstream impacts remain unclear. We evaluated the response of aquatic insects, a cornerstone of river food webs, to hydropeaking using a life history–hydrodynamic model. Our model predicts that aquatic-insect abundance will depend on a basic life-history trait—adult egg-laying behavior—such that open-water layers will be unaffected by hydropeaking, whereas ecologically important and widespread river-edge layers, such as mayflies, will be extirpated. These predictions are supported by a more-than-2500-sample, citizen-science data set of aquatic insects from the Colorado River in the Grand Canyon and by a survey of insect diversity and hydropeaking intensity across dammed rivers of the Western United States. Our study reveals a hydropeaking-related life history bottleneck that precludes viable populations of many aquatic insects from inhabiting regulated rivers.

BioScience↗

USGS2025

Aggregating three sources of long-term trends of swallows and martins to identify priority conservation areas in the Great Lakes region

1. Long-term monitoring of bird populations across scales is important in evaluating conservation targets and creating effective conservation strategies. For nearly six decades, the Breeding Bird Survey (BBS) has served as the primary broad-scaled source of relative abundance trends of swallows and martins in North America. Recently, however, it has become possible to obtain breeding population trends using semi-structured eBird community science data. Moreover, weather surveil-lance radar data of swallow and martin roosting populations yield a third complementary source of trend information. 2. Using results from these three approaches, we propose a novel method of spatially combining estimates of percent change per year into a probability of directional agreement and/or disagreement that describes (1) the direction of the trend within a given region, (2) the amount of evidence associated with the estimate and (3) how much uncertainty surrounds it. We focus our efforts on an area of high Hirundinidae concentration in the North American Great Lakes region and predict trends from 2012 to 2022. 3. We found a high probability of agreement between all three sources about ob-served declines in swallow and martin trends in the region surrounding Lake Ontario and to the west of Lake Michigan. Focusing future research on these regions could improve our understanding of these declines and help build more targeted conservation initiatives. 4. Synthesis and applications. Our data integration methodology allows managers to identify regions that accumulate evidence of concerning trends across multiple wildlife monitoring schemes. These regions can thus be prioritized in conservation and management efforts. This approach can be generalized to other sources of long-term monitoring data of different species, at different stages of their annual cycle, in any geographic location.

Great Lakes region↗

USGS2023

Water quality impacts of climate change, land use, and population growth in the Chesapeake Bay watershed

The 2010 Chesapeake Bay Total Maximum Daily Load was established for the water quality and ecological restoration of the Chesapeake Bay. In 2017, the latest science, data, and modeling tools were used to develop revised Watershed Implementation Plans (WIPs). In this article, we examine the vulnerability of the Chesapeake Bay watershed to the combined pressures of climate change and growth in population, agricultural intensity, and economic activity for the 60-year period 1995–2055. The results will be used to revise WIPs, as needed, to account for expected increases in loads. Assessing changes relative to 1995 for the years 2025, 2035, 2045, and 2055, mean annual precipitation increases of 3.11%, 4.21%, 5.34%, and 6.91%, respectively, air temperature increases of 1.12, 1.45, 1.84, and 2.12°C, respectively, and potential evapotranspiration increases of 3.36%, 4.43%, 5.54%, and 6.35%, respectively, are projected. Population in the watershed is expected to grow by 3.5 million between 2025 and 2055. Watershed model results show incremental increases in streamflow (2.3%–6.2%), nitrogen (2.6%–10.8%), phosphorus (4.5%–26.7%), and sediment (3.8%–18.8%) loads to the tidal Bay due to climate change. Growth in population, agricultural intensity, development, and economic activity resulted in relatively smaller increases in loads compared to climate change.

Chesapeake Bay watershed↗