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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...
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This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and 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).
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The Sea Surface Temperature (SST) data of the nearshore region of the North Pacific show temperature ranges in degrees C using points whose locations correspond to the centroids of AVHRR Pathfinder version 5 monthly, global, 4 km data set (PFSST V50). The pathfinder rasters are available from the Physical Oceanography Distributed Active Archive Center (PO.DAAC), hosted by NASA JPL. The data points in this dataset lie within a 20 km buffer from the GSHHS (Global Self-consistent, Hierarchical, High-resolution Shoreline) coastline. The GSHHS vector data are available from the National Geophysical Data Center (NGDC). Furthermore, each point in the SST dataset is categorized by the ecoregion in which it is located. This...
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This dataset contains inputs for a numerical groundwater-flow model of the Upper San Pedro Basin in southeastern Arizona and Northern Sonora, Mexico.
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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...
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Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 68 lakes in Minnesota and Wisconsin during 1980-2018. The data are organized into these items: Spatial data - One shapefile of polygons for all 68 lakes in this study (.shp, .shx, .dbf, and .prj files) Model configurations - Model parameters and metadata used to configure models (1 JSON file, with metadata for each of 68 lakes, indexed by "site_id") Model inputs - Data formatted as model inputs for predicting temperature a. Lake...
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This dataset includes compiled water temperature data from an instrumented buoy on Lake Mendota, 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).
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This dataset includes spatial location information from 167 temperature data loggers that were installed throughout the Willow/Rock/Frazer watersheds of northern Nevada between July 30 and August 14, 2015. One hundred twelve data loggers were installed in stream channels (some of which were dry), 50 data loggers were installed outside the stream channel to measure air temperature, and 5 data loggers were installed on ridgetops to measure air temperature across the watershed.
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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...
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These data can be used to replicate the application of MWBMglacier as described in two journal articles: 1) Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed (in review), and 2) Hydrologic regime changes in a high-latitude glacierized watershed under future climate conditions (doi:10.3390/w10020128). These simulations provide results from historical and 12 future general circulation model scenarios for the period 1949-2099 to determine the potential effects of climate change on the hydrology and water quality of a snow-dominated mountainous environment. In addition to the inputs and outputs, this Data Release includes summaries of the input and output data...
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This dataset provides bi-monthly data on seed biomass collected in shallow water habitats across the fresh to saline gradient at coastal sites in Barataria Bay, Louisiana. This project was co-funded by the South Central Climate Adaptation Science Center and the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperatives. An alternate reference to this product can be found here.
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This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). 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).
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This dataset includes compiled water temperature data from a variety of sources, including the Water Quality Portal (Read et al. 2017), the North Temperate Lakes Long-TERM Ecological Research Program (https://lter.limnology.wisc.edu/), the Minnesota department of Natural Resources, and the Global Lake Ecological Observatory Network (gleon.org). 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).
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This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, 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 Lake Mendota 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).
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This point shapefile approximates locations within 20 km of the North Pacific Coastline, as defined by the "World Country Boundaries (Generalized)" shapefile distributed by ESRI as part of their Data & Maps data series. They are based on raster data at 4 km resolution. Therefore there are between 3-5 points extending out from each location along the shoreline (at 4 km intervals).
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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...
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We used WARMER, a 1-D cohort model of wetland accretion (Swanson et al. 2014), which is based on Callaway et al. (1996), to examine SLR projections across each study site. Each cohort in the model represents the total organic and inorganic matter added to the soil column each year. WARMER calculates elevation changes relative to MSL based on projected changes in relative sea level, subsidence, inorganic sediment accumulation, aboveground and belowground organic matter productivity, compaction, and decay for a representative marsh area. Each cohort provides the mass of inorganic and organic matter accumulated at the surface in a single year as well as any subsequent belowground organic matter productivity (root growth)...
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These datasets include stream temperatures, air temperatures, and spatial location information from 167 temperature data loggers that were installed throughout the Willow/Rock/Frazer watersheds of northern Nevada between July 30 and August 14, 2015. One hundred twelve data loggers were installed in stream channels (some of which were dry), 50 data loggers were installed outside the stream channel to measure air temperature, and 5 data loggers were installed on ridgetops to measure air temperature across the watershed. Fifty-one air temperature data loggers and 97 stream temperature data loggers were recovered and downloaded in late July 2016.
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The Sea Surface Temperature (SST) data of the nearshore region of the North Pacific show temperature ranges in degrees C using points whose locations correspond to the centroids of AVHRR Pathfinder version 5 monthly, global, 4 km data set (PFSST V50). The pathfinder rasters are available from the Physical Oceanography Distributed Active Archive Center (PO.DAAC), hosted by NASA JPL. The grid cells in this dataset lie within a 20 km buffer from the GSHHS (Global Self-consistent, Hierarchical, High-resolution Shoreline) coastline. The GSHHS vector data are available from the National Geophysical Data Center (NGDC). These data have been QA'd in that we have selected only data values with associated quality flags of...


map background search result map search result map Probability of 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) Groundwater flow model of Northern Arizona by Pool and others, 2011 Temperate Northern Pacific Nearshore Points shapefile North Pacific Nearshore Sea Surface Temperature (SST) ESRI GRID format (1981-2009) Seed biomass from shallow coastal water areas along a salinity gradient in Barataria Bay, Louisiana (2015) Stream and air temperature data from the Willow, Rock, and Frazer watersheds of northern Nevada, USA, 2015-2016 Temperature data loggers in Willow/Rock/Frazer watersheds of northern Nevada, 2015 Climate Change Scenario Inundation Metrics along the Upper and Middle Mississippi and Lower Missouri Rivers Quantify Depth of Inundation for Floodplains on the Missouri River for a Calculated Return Interval of 5 Years Supporting data for two MWBMglacier applications to the Copper River basin in Alaska Sea Level Rise Systematic Mapping Literature Review WARMER model projections of sea-level rise for eight tidal marsh study areas on coastal Oregon and Washington, 2010-2110 Process-guided deep learning predictions of lake water temperature Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes) Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags) Process-guided deep learning water temperature predictions: 4 Training data Process-guided deep learning water temperature predictions: 4a Lake Mendota detailed training data Process-guided deep learning water temperature predictions: 5a Lake Mendota detailed prediction data Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data Process-guided deep learning water temperature predictions: 4a Lake Mendota detailed training data Process-guided deep learning water temperature predictions: 5a Lake Mendota detailed prediction data Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data Temperature data loggers in Willow/Rock/Frazer watersheds of northern Nevada, 2015 Stream and air temperature data from the Willow, Rock, and Frazer watersheds of northern Nevada, USA, 2015-2016 Quantify Depth of Inundation for Floodplains on the Missouri River for a Calculated Return Interval of 5 Years Climate Change Scenario Inundation Metrics along the Upper and Middle Mississippi and Lower Missouri Rivers WARMER model projections of sea-level rise for eight tidal marsh study areas on coastal Oregon and Washington, 2010-2110 Groundwater flow model of Northern Arizona by Pool and others, 2011 Supporting data for two MWBMglacier applications to the Copper River basin in Alaska Seed biomass from shallow coastal water areas along a salinity gradient in Barataria Bay, Louisiana (2015) Sea Level Rise Systematic Mapping Literature Review Process-guided deep learning predictions of lake water temperature Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags) Process-guided deep learning water temperature predictions: 4 Training data Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes) Probability of 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) Temperate Northern Pacific Nearshore Points shapefile North Pacific Nearshore Sea Surface Temperature (SST) ESRI GRID format (1981-2009)