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USGS2008

Multiyear riparian evapotranspiration and groundwater use for a semiarid watershed

Riparian evapotranspiration (ET) is a major component of the surface and subsurface water balance for many semiarid watersheds. Measurement or model-based estimates of ET are often made on a local scale, but spatially distributed estimates are needed to determine ET over catchments. In this paper, we document the ET that was quantified over 3 years using eddy covariance for three riparian ecosystems along the Upper San Pedro River of southeastern Arizona, USA, and we use a water balance equation to determine annual groundwater use. Riparian evapotranspiration and groundwater use for the watershed were then determined by using a calibrated, empirical model that uses 16-day, 250-1000 m remote-sensing products for the years of 2001-2005. The inputs for the model were derived entirely from the NASA MODIS sensor and consisted of the Enhanced Vegetation Index and land surface temperature. The scaling model was validated using subsets of the entire dataset (omitting different sites or years) and its capable performance for well-watered sites (MAD=0.32 mm day-1, R2=0.93) gave us confidence in using it to determine ET over the watershed. Three years of eddy covariance data for the riparian sites reveal that ET and groundwater use increased as woody plant density increased. Groundwater use was less variable at the woodland site, which had the greatest density of phreatophytes. Annual riparian groundwater use within the watershed was nearly constant over the study period despite an on-going drought. For the San Pedro alone, the amounts determined in this paper are within the range of most recently reported values that were derived using an entirely different approach. However, because of our larger estimates for groundwater use for the main tributary of the San Pedro, the watershed totals were higher. The approach presented here can provide riparian ET and groundwater use amounts that reflect real natural variability in phreatophyte withdrawals and improve the accuracy of a watershed's water budget. ?? 2008 Elsevier Ltd. All rights reserved.

Journal of Arid Environments↗

USGS2021

Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data

Widespread occurrence of cyanobacterial harmful algal blooms (CyanoHABs) and the associated health effects from potential cyanotoxin exposure has led to a need for systematic and frequent screening and monitoring of lakes that are used as recreational and drinking water sources. Remote sensing-based methods are often used for synoptic and frequent monitoring of CyanoHABs. In this study, one such algorithm – a sub-component of the Cyanobacteria Index called the CI cyano , was validated for effectiveness in identifying lakes with toxin-producing blooms in 11 states across the contiguous United States over 11 bloom seasons (2005–2011, 2016–2019). A matchup data set was created using satellite data from MEdium Resolution Imaging Spectrometer (MERIS) and Ocean Land Colour Imager (OLCI), and nearshore, field-measured Microcystins (MCs) data as a proxy of CyanoHAB presence. While the satellite sensors cannot detect toxins, MCs are used as the indicator of health risk, and as a confirmation of cyanoHAB presence. MCs are also the most common laboratory measurement made by managers during CyanoHABs. Algorithm performance was evaluated by its ability to detect CyanoHAB ‘Presence’ or ‘Absence’, where the bloom is confirmed by the presence of the MCs. With same-day matchups, the overall accuracy of CyanoHAB detection was found to be 84% with precision and recall of 87 and 90% for bloom detection. Overall accuracy was expected to be between 77% and 87% (95% confidence) based on a bootstrapping simulation. These findings demonstrate that CI cyano has utility for synoptic and routine monitoring of potentially toxic cyanoHABs in lakes across the United States.

Science for the Total Environment↗

USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗

USGS2019

Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests

In order to produce useful hydrologic and aquatic habitat data from the Landsat system, the U.S. Geological Survey has developed the “Dynamic Surface Water Extent” (DSWE) Landsat Science Product. DSWE will provide long-term, high-temporal resolution data on variations in inundation extent. The model used to generate DSWE is composed of five decision-rule based tests that do not require scene-based training. To allow its general application, required inputs are limited to the Landsat at-surface reflectance product and a digital elevation model. Unlike other Landsat-based water products, DSWE includes pixels that are only partially covered by water to increase inundation dynamics information content. Previously published DSWE model development included one wetland-focused test developed through visual inspection of field-collected Everglades spectra. A comparison of that test’s output against Everglades Depth Estimation Network (EDEN) in situ data confirmed the expectation that omission errors were a prime source of inaccuracy in vegetated environments. Further evaluation exposed a tendency toward commission error in coniferous forests. Improvements to the subpixel level “partial surface water” (PSW) component of DSWE was the focus of this research. Spectral mixture models were created from a variety of laboratory and image-derived endmembers. Based on the mixture modeling, a more “aggressive” PSW rule improved accuracy in herbaceous wetlands and reduced errors of commission elsewhere, while a second “conservative” test provides an alternative when commission errors must be minimized. Replication of the EDEN-based experiments using the revised PSW tests yielded a statistically significant increase in mean overall agreement (4%, p = 0.01, n = 50) and a statistically significant decrease (11%, p = 0.009, n = 50) in mean errors of omission. Because the developed spectral mixture models included image-derived vegetation endmembers and laboratory spectra for soil groups found across the US, simulations suggest where the revised DSWE PSW tests perform as they do in the Everglades and where they may prove problematic. Visual comparison of DSWE outputs with an unusual variety of coincidently collected images for locations spread throughout the US support conclusions drawn from Everglades quantitative analyses and highlight DSWE PSW component strengths and weaknesses.

Remote Sensing↗

USGS2003

The National Map: from geography to mapping and back again

When the means of production for national base mapping were capital intensive, required large production facilities, and had ill-defined markets, Federal Government mapping agencies were the primary providers of the spatial data needed for economic development, environmental management, and national defense. With desktop geographic information systems now ubiquitous, source data available as a commodity from private industry, and the realization that many complex problems faced by society need far more and different kinds of spatial data for their solutions, national mapping organizations must realign their business strategies to meet growing demand and anticipate the needs of a rapidly changing geographic information environment. The National Map of the United States builds on a sound historic foundation of describing and monitoring the land surface and adds a focused effort to produce improved understanding, modeling, and prediction of land-surface change. These added dimensions bring to bear a broader spectrum of geographic science to address extant and emerging issues. Within the overarching construct of The National Map, the U.S. Geological Survey (USGS) is making a transition from data collector to guarantor of national data completeness; from producing paper maps to supporting an online, seamless, integrated database; and from simply describing the Nation’s landscape to linking these descriptions with increased scientific understanding. Implementing the full spectrum of geographic science addresses a myriad of public policy issues, including land and natural resource management, recreation, urban growth, human health, and emergency planning, response, and recovery. Neither these issues nor the science and technologies needed to deal with them are static. A robust research agenda is needed to understand these changes and realize The National Map vision. Initial successes have been achieved. These accomplishments demonstrate the utility of The National Map to the Nation and give confidence in evolving its future applications.

Photogrammetric Engineering and Remote Sensing↗

USGS1981

Assessment of impacts of proposed coal-resource and related economic development on water resources, Yampa River basin, Colorado and Wyoming: A summary

Expanded mining and use of coal resources in the Rocky Mountain region of the western United States will have substantial impacts on water resources, environmental amenities, and social and economic conditions. The U.S. Geological Survey has completed a 3-year assessment of the Yampa River basin, Colorado and Wyoming, where increased coal-resource development has begun to affect the environment and quality of life. Economic projections of the overall effects of coal-resource development were used to estimate water use and the types and amounts of waste residuals that need to be assimilated into the environment. Based in part upon these projections, several physical-based models and other semiquantitative assessment methods were used to determine possible effects upon the basin's water resources. Depending on the magnitude of mining and use of coal resources in the basin, an estimated 0.7 to 2.7 million tons (0.6 to 2.4 million metric tons) of waste residuals may be discharged annually into the environment by coal-resource development and associated economic activities. If the assumed development of coal resources in the basin occurs, annual consumptive use of water, which was approximately 142,000 acre-feet (175 million cubic meters) during 1975, may almost double by 1990. In a related analysis of alternative cooling systems for coal-conversion facilities, four to five times as much water may be used consumptively in a wet-tower, cooling-pond recycling system as in once-through cooling. An equivalent amount of coal transported by slurry pipeline would require about one-third the water used consumptively by once-through cooling for in-basin conversion. Current conditions and a variety of possible changes in the water resources of the basin resulting from coal-resource development were assessed. Basin population may increase by as much as threefold between 1975 and 1990. Volumes of wastes requiring treatment will increase accordingly. Potential problems associated with ammonia-nitrogen concentrations in the Yampa River downstream from Steamboat Springs were evaluated using a waste-load assimilative-capacity model. Changes in sediment loads carried by streams due to increased coal mining and construction of roads and buildings may be apparent only locally; projected increases in sediment loads relative to historic loads from the basin are estimated to be 2 to 7 percent. Solid-waste residuals generated by coal-conversion processes and disposed of into old mine pits may cause widely dispersed ground-water contamination, based on simulation-modeling results. Projected increases in year-round water use will probably result in the construction of several proposed reservoirs. Current seasonal patterns of streamflow and of dissolvedsolids concentrations in streamflow will be altered appreciably by these reservoirs. Decreases in time-weighted mean-annual dissolved-solids concentrations of as much as 34 percent are anticipated, based upon model simulations of several configurations of proposed reservoirs. Detailed statistical analyses of water-quality conditions in the Yampa River basin were made. Regionalized maximum waterquality concentrations were estimated for possible comparison with future conditions. Using Landsat imagery and aerial photographs, potential remote-sensing applications were evaluated to monitor land-use changes and to assess both snow cover and turbidity levels in streams. The technical information provided by the several studies of the Yampa River basin assessment should be useful to regional planners and resource managers in evaluating the possible impacts of development on the basin's water resources.

Colorado, Wyoming↗

USGS2022

Post-fire temporal trends in soil-physical and -hydraulic properties and simulated runoff generation: Insights from different burn severities in the 2013 Black Forest Fire, CO, USA

Burn severity influences on post-fire recovery of soil-hydraulic properties controlling runoff generation are poorly understood despite the importance for parameterizing infiltration models. We measured soil-hydraulic properties of field-saturated hydraulic conductivity (Kfs), sorptivity (S), and wetting front potential (ψf) for four years after the 2013 Black Forest Fire, Colorado, USA at six sites across a gradient of initial remotely sensed burn severity using the change in the normalized burn ratio (dNBR). These measurements were correlated with soil-physical property measurements of bulk density (ρb), loss on ignition (LOI, a measure of soil organic matter), and ground cover composition to provide insight into causal factors for temporal changes in Kfs, S, and ψf . Modeled infiltration using the Smith-Parlange approach parameterized with measured Kfs, S, and ψf further discerned the role of precipitation intensity on runoff generation. Temporal trends of soil-physical properties and ground cover showed influences from initial burn severity. Trends in soil-hydraulic properties , surprisingly, were not strongly influenced by initial burn severity despite inferred effects of ρb, LOI, and ground cover on trends in Kfs and S. Calculations of dNBR at the time of sampling showed strong correlations with Kfs and S, demonstrating a new approach for estimating long-unburned Kfs and S values, infiltration model parameters after fire, and assessing the time of return to pre-fire values. Simulated infiltration-excess runoff, in contrast, did depend on initial burn severity. Time series of the ratio S2/Kfs ≈ ψf tended to converge between 1 to 10 mm four years after wildfire, potentially (i) defining a long-unburned forest domain of S2/Kfs and ψf from 1 to 10 mm with relatively high Kfs values, and (ii) providing a new post-fire soil-hydraulic property recovery metric (i.e. S2/Kfs ≈ ψf in the range of 1 to 10 mm) for sites in the Rocky Mountains of the USA.

Colorado↗

USGS2012

Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics

Row-crop and poultry production have been implicated as sources of water pollution along the Choptank River, an estuary and tributary of the Chesapeake Bay. This study examined the effects of land use, subwatershed characteristics, and climatic conditions on the water quality parameters of a subwatershed in the Choptank River watershed. The catchments within the subwatershed were defined using advanced remotely-sensed data and current geographic information system processing techniques. Water and sediment samples were collected in May–October 2009 and April–June 2010 under mostly baseflow conditions and analyzed for select bacteria, nitrate-N, ammonium-N, total arsenic, total phosphorus (TP), orthophosphate (ortho-P), and particle-phase phosphorus (PP); n = 96 for all analytes except for arsenic, n = 136, and for bacteria, n = 89 (aqueous) and 62 (sediment). Detections of Enterococci and Escherichia coli concentrations were ubiquitous in this subwatershed and showed no correlation to location or land use, however larger bacterial counts were observed shortly after precipitation. Nitrate-N concentrations were not correlated with agricultural lands, which may reflect the small change in percent agriculture and/or the similarity of agronomic practices and crops produced between catchments. Concentration data suggested that ammonia emission and possible deposition to surface waters occurred and that these processes may be influenced by local agronomic practices and climatic conditions. The negative correlation of PP and arsenic concentrations with percent forest was explained by the stronger signal of the head waters and overland flow of particulate phase analytes versus dissolved phase inputs from groundwater. Service roadways at some poultry production facilities were found to redirect runoff from the facilities to neighboring catchment areas, which affected water quality parameters. Results suggest that in this subwatershed, catchments with poultry production facilities are possible sources for arsenic and PP as compared to catchment areas where these facilities were not present.

Choptank River↗

USGS2024

Assessing the vertical accuracy of digital elevation models by quality level and land cover

The vertical accuracy of elevation data in coastal environments is critical because small variations in elevation can affect an area’s exposure to waves, tides, and storm-related flooding. Elevation data contractors typically quantify the vertical accuracy of lidar-derived digital elevation models (DEMs) on a per-project basis to gauge whether the datasets meet quality and accuracy standards. Here, we collated over 5200 contractor elevation checkpoints along the Atlantic and Gulf of Mexico coasts of the United States that were collected for project-level analyses produced for assessing DEMs acquired for the U.S. Geological Survey’s Three-Dimensional Elevation Program. We used land cover data to quantify non-vegetated vertical accuracy and vegetated vertical accuracy statistics (overall and by point spacing bins) and assessed elevation error by land cover class. We found the non-vegetated vertical accuracy had an overall root mean square error of 6.9 cm and vegetated areas had a 95th percentile vertical error of 22.3 cm. Point spacing was generally positively correlated to elevation accuracy, but sample size limited the ability to interpret results from accuracy by land cover, particularly in wetlands. Based on the specific questions a researcher may be asking, use of literature or fieldwork could assist with enhancing error statistics in underrepresented classes.

Remote Sensing Letters↗

USGS2015

Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network

The U.S. Geological Survey is developing new Landsat science products. One, named Dynamic Surface Water Extent (DSWE), is focused on the representation of ground surface inundation as detected in cloud-/shadow-/snow-free pixels for scenes collected over the U.S. and its territories. Characterization of DSWE uncertainty to facilitate its appropriate use in science and resource management is a primary objective. A unique evaluation dataset developed from data made publicly available through the Everglades Depth Estimation Network (EDEN) was used to evaluate one candidate DSWE algorithm that is relatively simple, requires no scene-based calibration data, and is intended to detect inundation in the presence of marshland vegetation. A conceptual model of expected algorithm performance in vegetated wetland environments was postulated, tested and revised. Agreement scores were calculated at the level of scenes and vegetation communities, vegetation index classes, water depths, and individual EDEN gage sites for a variety of temporal aggregations. Landsat Archive cloud cover attribution errors were documented. Cloud cover had some effect on model performance. Error rates increased with vegetation cover. Relatively low error rates for locations of little/no vegetation were unexpectedly dominated by omission errors due to variable substrates and mixed pixel effects. Examined discrepancies between satellite and in situ modeled inundation demonstrated the utility of such comparisons for EDEN database improvement. Importantly, there seems no trend or bias in candidate algorithm performance as a function of time or general hydrologic conditions, an important finding for long-term monitoring. The developed database and knowledge gained from this analysis will be used for improved evaluation of candidate DSWE algorithms as well as other measurements made on Everglades surface inundation, surface water heights and vegetation using radar, lidar and hyperspectral instruments. Although no other sites have such an extensive in situ network or long-term records, the broader applicability of this and other candidate DSWE algorithms is being evaluated in other wetlands using this work as a guide. Continued interaction among DSWE producers and potential users will help determine whether the measured accuracies are adequate for practical utility in resource management.

Florida↗

USGS2019

Return flows from beaver ponds enhance floodplain-to-river metals exchange in alluvial mountain catchments

River to floodplain hydrologic connectivity is strongly enhanced by beaver- ( Castor canadensis ) engineered channel water diversions. The hydroecological impacts are wide ranging and generally positive, however, the hydrogeochemical characteristics of beaver-induced flowpaths have not been thoroughly examined. Using a suite of complementary ground- and drone-based heat tracing and remote sensing methodology we characterized the physical template of beaver-induced floodplain exchange for two alluvial mountain streams near Crested Butte, Colorado, USA. A flowpath-oriented perspective to water quality sampling allowed characterization of the chemical evolution of channel water diverted through floodplain beaver ponds and ultimately back to the channel in ‘beaver pond return flows’. Subsurface return flow seepages were universally suboxic, while ponds and surface return flows showed a range of oxygen concentration due to in-situ photosynthesis and atmospheric mixing. Median concentrations of reduced metals: manganese (Mn), iron (Fe), aluminum (Al), and arsenic (As) were substantially higher along beaver-induced flowpaths than in geologically controlled seepages and upstream main channel locations. The areal footprint of reduced return seepage flowpaths were imaged with surface electromagnetic methods, indicating extensive zones of high-conductivity shallow groundwater flowing back toward the main channels and emerging at relatively warm bank seepage zones observed with infrared. Multiple-depth redox dynamics within one focused seepage zone showed coupled variation over time, likely driven by observed changes in seepage rate that may be controlled by pond stage. High-resolution times series of dissolved Mn and Fe collected downstream of the beaver-impacted reaches demonstrated seasonal dynamics in mixed river metal concentrations. Al time series concentrations showed proportional change to Fe at the smaller stream location, indicating chemically reduced flowpaths were sourcing Al to the channel. Overall our results indicated beaver-induced floodplain exchanges create important, and perhaps dominant, transport pathways for floodplain metals by expanding chemically-reduced zones paired with strong advective exchange.

Colorado↗

USGS2026

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing↗

USGS2011

Relating nutrient and herbicide fate with landscape features and characteristics of 15 subwatersheds in the Choptank River watershed

Excess nutrients and agrochemicals from non-point sources contribute to water quality impairment in the Chesapeake Bay watershed and their loading rates are related to land use, agricultural practices, hydrology, and pollutant fate and transport processes. In this study, monthly baseflow stream samples from 15 agricultural subwatersheds of the Choptank River in Maryland USA (2005 to 2007) were characterized for nutrients, herbicides, and herbicide transformation products. High-resolution digital maps of land use and forested wetlands were derived from remote sensing imagery. Examination of landscape metrics and water quality data, partitioned according to hydrogeomorphic class, provided insight into the fate, delivery, and transport mechanisms associated with agricultural pollutants. Mean Nitrate-N concentrations (4.9 mg/L) were correlated positively with percent agriculture (R 2 = 0.56) and negatively with percent forest (R 2 = 0.60). Concentrations were greater ( p = 0.0001) in the well-drained upland (WDU) hydrogeomorphic region than in poorly drained upland (PDU), reflecting increased denitrification and reduced agricultural land use intensity in the PDU landscape due to the prevalence of hydric soils. Atrazine and metolachlor concentrations (mean 0.29 μg/L and 0.19 μg/L) were also greater ( p = 0.0001) in WDU subwatersheds than in PDU subwatersheds. Springtime herbicide concentrations exhibited a strong, positive correlation (R 2 = 0.90) with percent forest in the WDU subwatersheds but not in the PDU subwatersheds. In addition, forested riparian stream buffers in the WDU were more prevalent than in the PDU where forested patches are typically not located near streams, suggesting an alternative delivery mechanism whereby volatilized herbicides are captured by the riparian forest canopy and subsequently washed off during rainfall. Orthophosphate, CIAT (6-chloro- N -(1-methylethyl)-1,3,5-triazine-2,4-diamine), CEAT (6-chloro- N -ethyl-1,3,5-triazine-2,4-diamine), and MESA (2-[(2-ethyl-6-methylphenyl) (2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid) were also analyzed. These findings will assist efforts in targeting implementation of conservation practices to the most environmentally-critical areas within watersheds to achieve water quality improvements in a cost-effective manner.

Delaware, Maryland↗

USGS2017

Integrating Radarsat-2, Lidar, and Worldview-3 Imagery to maximize detection of forested inundation extent in the Delmarva Peninsula, USA

Natural variability in surface-water extent and associated characteristics presents a challenge to gathering timely, accurate information, particularly in environments that are dominated by small and/or forested wetlands. This study mapped inundation extent across the Upper Choptank River Watershed on the Delmarva Peninsula, occurring within both Maryland and Delaware. We integrated six quad-polarized Radarsat-2 images, Worldview-3 imagery, and an enhanced topographic wetness index in a random forest model. Output maps were filtered using light detection and ranging (lidar)-derived depressions to maximize the accuracy of forested inundation extent. Overall accuracy within the integrated and filtered model was 94.3%, with 5.5% and 6.0% errors of omission and commission for inundation, respectively. Accuracy of inundation maps obtained using Radarsat-2 alone were likely detrimentally affected by less than ideal angles of incidence and recent precipitation, but were likely improved by targeting the period between snowmelt and leaf-out for imagery collection. Across the six Radarsat-2 dates, filtering inundation outputs by lidar-derived depressions slightly elevated errors of omission for water (+1.0%), but decreased errors of commission (−7.8%), resulting in an average increase of 5.4% in overall accuracy. Depressions were derived from lidar datasets collected under both dry and average wetness conditions. Although antecedent wetness conditions influenced the abundance and total area mapped as depression, the two versions of the depression datasets showed a similar ability to reduce error in the inundation maps. Accurate mapping of surface water is critical to predicting and monitoring the effect of human-induced change and interannual variability on water quantity and quality.

Delaware, Maryland↗

USGS2019

Modeling barrier island habitats using landscape position information

Barrier islands are dynamic environments because of their position along the marine–estuarine interface. Geomorphology influences habitat distribution on barrier islands by regulating exposure to harsh abiotic conditions. Researchers have identified linkages between habitat and landscape position, such as elevation and distance from shore, yet these linkages have not been fully leveraged to develop predictive models. Our aim was to evaluate the performance of commonly used machine learning algorithms, including K-nearest neighbor, support vector machine, and random forest, for predicting barrier island habitats using landscape position for Dauphin Island, Alabama, USA. Landscape position predictors were extracted from topobathymetric data. Models were developed for three tidal zones: subtidal, intertidal, and supratidal/upland. We used a contemporary habitat map to identify landscape position linkages for habitats, such as beach, dune, woody vegetation, and marsh. Deterministic accuracy, fuzzy accuracy, and hindcasting were used for validation. The random forest algorithm performed best for intertidal and supratidal/upland habitats, while the K-nearest neighbor algorithm performed best for subtidal habitats. A posteriori application of expert rules based on theoretical understanding of barrier island habitats enhanced model results. For the contemporary model, deterministic overall accuracy was nearly 70%, and fuzzy overall accuracy was over 80%. For the hindcast model, deterministic overall accuracy was nearly 80%, and fuzzy overall accuracy was over 90%. We found machine learning algorithms were well-suited for predicting barrier island habitats using landscape position. Our model framework could be coupled with hydrodynamic geomorphologic models for forecasting habitats with accelerated sea-level rise, simulated storms, and restoration actions.

Remote Sensing↗

USGS2015

An automated approach for mapping persistent ice and snow cover over high latitude regions

We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly identify areas where substantial changes in glacier area have occurred since the most recent conventional glacier inventories, highlighting areas where updated inventories are most urgently needed. From a longer term perspective, the automated production of PISC maps represents an important step toward fully automated glacier extent monitoring using Landsat or similar sensors.

Remote Sensing↗

USGS2017

Normalized difference vegetation index as an estimator for abundance and quality of avian herbivore forage in arctic Alaska

Tools that can monitor biomass and nutritional quality of forage plants are needed to understand how arctic herbivores may respond to the rapidly changing environment at high latitudes. The Normalized Difference Vegetation Index (NDVI) has been widely used to assess changes in abundance and distribution of terrestrial vegetative communities. However, the efficacy of NDVI to measure seasonal changes in biomass and nutritional quality of forage plants in the Arctic remains largely un-evaluated at landscape and fine-scale levels. We modeled the relationships between NDVI and seasonal changes in aboveground biomass and nitrogen concentration in halophytic graminoids, a key food source for arctic-nesting geese. The model was calibrated based on data collected at one site and validated using data from another site. Effects of spatial scale on model accuracy were determined by comparing model predictions between NDVI derived from moderate resolution (250 × 250 m pixels) satellite data and high resolution (20 cm diameter area) handheld spectrometer data. NDVI derived from the handheld spectrometer was a superior estimator ( R 2 ≥ 0.67) of seasonal changes in aboveground biomass compared to satellite-derived NDVI ( R 2 ≤ 0.40). The addition of temperature and precipitation variables to the model for biomass improved fit, but provided minor gains in predictive power beyond that of the NDVI-only model. This model, however, was only a moderately accurate estimator of biomass in an ecologically-similar halophytic graminoid wetland located 100 km away, indicating the necessity for site-specific validation. In contrast to assessments of biomass, satellite-derived NDVI was a better estimator for the timing of peak percent of nitrogen than NDVI derived from the handheld spectrometer. We confirmed that the date when NDVI reached 50% of its seasonal maximum was a reasonable approximation of the period of peak spring vegetative green-up and peak percent nitrogen. This study demonstrates the importance of matching the scale of NDVI measurements to the vegetation properties of biomass and nitrogen phenology.

Alaska↗

USGS2015

Southern Salish Sea Habitat Map Series: Admiralty Inlet

In 2010 the Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, designed to support research in support of implementing the Puget Sound Action Agenda. The Action Agenda was created in response to Puget Sound having been designated as one of 28 estuaries of national significance under section 320 of the U.S. Clean Water Act, and its overall goal is to restore the Puget Sound Estuary's environment by 2020. The Southern Salish Sea Mapping Project was funded by the Assistance Program request for proposals process, which also supports a large number of coastal-zone- and ocean-management issues. The issues include the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature (Van Cleve and others, 2009), which endorses a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas (MPA) and recommendations for action. This publication is the first of four U.S. Geological Survey Scientific Investigation Maps that make up the Southern Salish Sea Mapping Project. The remaining three map blocks to be published in the future, located south of Admiralty Inlet, are shown in figure 1. Puget Sound is a deep, fjord-type estuary covering an area of 2,330 km 2 in the Pacific Northwest region of the United States (fig. 1). It is connected to the ocean by the Strait of Juan de Fuca, a turbulent passage approximately 160 km in length and 22 km wide at its west end, expanding to over 40 km wide at its east end (Thomson, 1994). During the Pleistocene, the area was occupied several times by lobes of continental ice, resulting in a complex basin-fill of glacial and interglacial deposits that are locally as thick as 1100 m (Johnson and others, 2001). The last glaciation, called the Fraser glaciation, began after 28,800±740 14 C yr B.P. when ice started a slow expansion (Clague, 1981). At peak advance the westward Juan de Fuca lobe reached the edge of the continental shelf through the Juan de Fuca Strait shortly before 14,460±200 14 C yr B.P. (Herzer and Bornhold, 1982). The southward Puget lobe advanced to its terminal position in Puget Sound by around 14,150 14 C yr B.P. (Porter and Swanson, 1998). Ice retreated from its maximum to northern Whidbey Island by 13,650±350 14 C yr B.P. (Dethier and others, 1995). Retreating glaciers resulted in a thick sequence of ice-contact, glacial-marine sediment, and early post-glacial sediments (Linden and Schurrer, 1988). These deposits have experienced the effects of a marine transgression followed by regression, resulting in a sea-level several tens of meters lower than the present day (Linden and Schurrer, 1988). A second transgression brought sea level to about the present level by around 5,470±120 14 C yr B.P. (Clague and others, 1982) establishing the present oceanographic and geologic environment Puget Sound is separated into four interconnected basins; Whidbey, Central (Main), Hood Canal, and South (Thomson, 1994). The Whidbey, Central, and Hood Canal basins are the three main branches of the Puget Sound estuary and are separated from the Strait of Juan de Fuca by a double sill at Admiralty Inlet. The Admiralty Inlet map area includes the Inlet and a portion of the Whidbey Basin (fig. 1). The shallower South Basin is separated by a sill at Tacoma Narrows and is highly branched with numerous finger inlets. Flow within Puget Sound is dominated by tidal currents of as much as 1 m/s at Admiralty Inlet, reducing to approximately 0.5 m/s in the Central Basin (Lavelle and others, 1988). The lack of silt and clay-sized sediments in the Admiralty Inlet map area is likely a result of the strong currents (see Ground-Truth Studies for the Admiralty Inlet Map Area, sheet 3). The subtidal component of flow reaches approximately 0.1 m/s and is driven by density gradients arising from the contrast in salty ocean water at the entrance and freshwater inputs from stream flow (Lavelle and others, 1988). The total freshwater input to Puget Sound is approximately 3.4 x 10 6 m 3 /day, primarily from the Skagit River (Cannon, 1983). The subtidal circulation mostly consists of a two-layered flow in the basins with fresher water exiting at the surface and saltier water entering at depth (Ebbesmeyer and Cannon, 2001). In general, surface waters flow north and deeper waters flow south; variations arise from wind effects that can drive a surface current in the same direction as the wind, and a baroclinic response in the lower layer to about 100-m depth (Matsuura and Cannon, 1997). Oceanographic properties are influenced by temporal forcing parameters such as reduced stream flow during the 2000-01 drought that increased surface salinity and decreased differences between surface and bottom waters (Newton and others, 2003). On offshore seismic-reflection profiles, Pleistocene strata (excluding latest Pleistocene glacial and post-glacial deposits) form a distinct seismic unit, bounded below by pre-Tertiary or Tertiary basement and above by typically flat-lying latest Pleistocene to Holocene deposits that fill in erosional or depositional relief (Johnson and others, 2001). Cores from central Puget Sound have accumulation rates that range from 85 to 1200 mg/cm 2 /yr, or 0.12 to 2.4 cm/yr; the highest accumulation rates are near the southern end of central Puget Sound (Carpenter and others, 1985). Carpenter and others (1985) un-weighted arithmetic mean of accumulation rates for central Puget Sound deeper stations is 480±340 (± one standard deviation) mg/cm 2 /yr. Lavelle and others (1985) also found rates as high as 1200 mg/cm 2 /yr over the past approximately 70 years in cores in the Central Basin off of and north and south of Elliott Bay. Puget Sound basin rates are comparable to rates in midshelf silt deposits on the Washington coast north of the Columbia River (Nittrouer and others, 1979). The deep subtidal (in other words, below SCUBA depths) habitats of Puget Sound are relatively poorly known. A few subtidal surveys exist for several habitat types from the 1960s and 1970s (reviewed in Dethier, 1990), using grab and box core data. The Dethier (1990) review divides habitat up into Coast and Marine Ecological Classification Standard (CMECS) substrate, water column energy, and depth zones but does not attempt to map these habitats, rather it is an inventory of habitats found in the area and the flora and fauna associated with each habitat. The approach of the Southern Salish Sea Mapping project is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, and bottom-sediment sampling data. This approach is based in part on methods presented and data collection and product needs identified at the Washington State Seafloor Mapping Workshop (Washington State Seafloor Mapping Workshop Steering Committee, 2008), attended by coastal and marine managers and scientists. The map products display seafloor geomorphology and substrate, and identify potential marine benthic habitats. It is emphasized that the more interpretive habitat and geology maps rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. Oceanographic current and wave data is not included in this analysis, however, the accompanying geographic information system (GIS) data set is designed and intended to be combined with oceanographic and biologic data sets assembled by others in the future and some of the GIS data has already been incorporated in the unpublished Nature Conservancy Benthic Habitats of Puget Sound database. This publication includes four map sheets, explanatory text, and a descriptive pamphlet. Each map sheet is published as a portable document format (PDF) file. ESRI ArcGIS compatible geotiffs (for example, bathymetry) and shapefiles (for example video observation points) will be available for download in the data catalog associated with this publication (Cochrane, 2015). An ArcGIS Project File with the symbology used to generate the map sheets is also provided. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html .

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