Filters: Tags: Northeast CASC (X) > partyWithName: U.S. Geological Survey (X)

Filters Contacts (Less) U.S. Geological Survey Jordan S. Read Edward A Bulliner U.S. Geological Survey - ScienceBase Anuj Karpatne Gretchen J.A. Hansen Jared Willard Michael Steinbach Paul C. Hanson Vipin Kumar Xiaowei Jia Alison P. Appling Jacob A. Zwart Samantha K. Oliver William Watkins Garth Lindner Craig Paukert Kristina Stinson E. Robert Thieler Kristen Bouska Robert B Jacobson Sawyer Stippa Jordan S Read Luke Winslow Selena Ahmed University of Massachusetts Boris Dufour David Lutz GS ScienceBase Joshua Rapp Kyle Herreman Ryan Huish Toni Lyn Morelli Integrated Information Dissemination Division Climate Adaptation Science Centers Alison P Appling William D Watkins Samantha K Oliver Jacob A Zwart Dana Infante Gretchen Hansen Jana Stewart Joanna Whittier Jordan Read Kevin Rose Land Resources Montana State University Nick Sievert Northeast CSC U.S. Geological Survey - ScienceBase More... View Results as: JSON ATOM CSV

Wisconsin Lake Temperature Metrics Stable Clarity It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale. This data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July,... Categories: Data; Types: Citation; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, Wisconsin, climate change, environment, hydrodynamic model, inlandWaters, lakes, limnology, water clarity, water quality, water temperature, Fewer tags Process-guided deep learning water temperature predictions: 4c All lakes historical training data Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep learning models and deep learning models, and calibration data for process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological Research Project, and digitized temperature records from the MN Department of Natural Resources. Categories: Data; Tags: 007, 012, Fish, MN, Minnesota, All tags... Northeast CASC, Rivers, Streams and Lakes, US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Sap Quantity at Study Sites in the Northeast Maple syrup is produced from the sap of sugar maple collected in the late winter and early spring. Native American tribes have collected and boiled down sap for centuries, and the tapping of maple trees is a cultural touchstone for many people in the northeast and Midwest. Because the tapping season is dependent on weather conditions, there is concern about the sustainability of maple sugaring as climate changes throughout the region. Our research addresses the impact of climate on the quantity and quality of maple sap used to make maple syrup. Sap was sampled at 6 sites across the native range of sugar maple over 2 years as part of the ACERnet collaboration. At each site we sampled 15-25 mature sugar maple trees,... Categories: Data; Tags: Acer saccharum, Indigenous Peoples, Northeast CASC, Plants, Tribes and Tribal Organizations, All tags... Wildlife and Plants, biota, climate change, forest ecosystem service, maple syrup, predictive model, yield, Fewer tags Process-guided deep learning water temperature predictions: 6b Sparkling Lake detailed evaluation data This dataset includes "test data" compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. The dataset also includes Sparkling Lake model erformance as measured as root-mean squared errors relative to temperature observations during the test period. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Process-guided deep learning water temperature predictions: 4b Sparkling Lake detailed training data This dataset includes compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD). Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags Predicted Elevation predicted elevation with respect to projected sea levels for the Northeastern U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83) The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the... Categories: Data; Tags: Atlantic City, Atlantic Ocean, Bayesian network, Boston, CMGP, All tags... Chesapeake Bay, Coastal and Marine Geology Program, Connecticut, Delaware, Esri binary grid, Gridded Raster Dataset, Jersey Shore, Long Island, Maine, Maryland, Massachusetts, New England, New Hampshire, New Jersey, New York, Norfolk, North America, Northeast CASC, Ocean City, Sea-Level Rise and Coasts, U.S. Geological Survey, USGS, United States, Virginia, WHCMSC, Water, Coasts and Ice, Wetlands, Woods Hole Coastal and Marine Science Center, biota, elevation, environment, geoscientificInformation, imageryBaseMapsEarthCover, landscape change, oceans, probabilistic predictions, sea-level rise, Fewer tags Process-guided deep learning water temperature predictions: 5b Sparkling Lake detailed prediction data Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added... Categories: Data; Tags: 007, 012, Fish, Northeast CASC, Rivers, Streams and Lakes, All tags... US, United States, WI, Water, Coasts and Ice, Wildlife and Plants, Wisconsin, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperate lakes, temperature, thermal profiles, water, Fewer tags FishTail, Indices and Supporting Data Characterizing the Current and Future Risk to Fish Habitat Degradation in the Northeast Climate Science Center Region Human impacts occurring throughout the Northeast and Midwest United States, including urbanization, agriculture, and dams, have multiple effects on the region’s streams which support economically valuable stream fishes. Changes in climate are expected to lead to additional impacts in stream habitats and fish assemblages in multiple ways, including changing stream water temperatures. To manage streams for current impacts and future changes, managers need region-wide information for decision-making and developing proactive management strategies. Our project met that need by integrating results of a current condition assessment of stream habitats based on fish response to human land use, water quality impairment,... Categories: Data; Types: Citation; Tags: Aquatic Biology, Aquatic habitats, Connecticut, Data Visualization & Tools, Delaware, All tags... Fish, Illinois, Indiana, Iowa, Kentucky, Land Use Change, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Northeast CASC, Ohio, Pennsylvania, Rhode Island, Rivers, Streams and Lakes, Science Tools For Managers, USGS Science Data Catalog (SDC), Vermont, Virginia, Washington D.C., Water, Coasts and Ice, West Virginia, Wildlife and Plants, Wisconsin, climate change, climatologyMeteorologyAtmosphere, drainage basins, habitat fragmentation, inlandWaters, land use and land cover, rivers, streams, water quality, Fewer tags Science to Inform Management of Floodplain Conservation Lands under Non-Stationary Conditions Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Lower Missouri River, which simulated water surface elevations at cross sections spaced (<1... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Iowa, Kansas, Lower Missouri, Missouri, Nebraska, All tags... Northeast CASC, Other Water, Water, Coasts and Ice, environment, floodplains, floods, inlandWaters, river systems, streamflow AND mathematical modeling, wetland ecosystems, Fewer tags « 1 2