-
Predictive soil property map: Silt content
These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin... -
Prediction grids of pH for the Mississippi River Valley Alluvial and...
Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical... -
Data release: Process-guided deep learning predictions of lake water temperature
<p>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... -
Estimating environmental thresholds for three classes of sagebrush condition...
We employed decision-tree mapping models in two formats to establish a time series (2001 - 2015) of sagebrush condition class in the western United States. The formats were... -
Data used to model and map manganese in the Northern Atlantic Coastal Plain...
Data used to model and map manganese concentrations in groundwater in the Northern Atlantic Coastal Plain (NACP) aquifer system, eastern USA, are documented in this data... -
Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs
This dataset includes model inputs that describe local weather conditions for Lake Mendota, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded... -
Iron concentration rasters of groundwater in the Mississippi River Valley...
Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high... -
Process-guided deep learning water temperature predictions: 6c All lakes...
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were... -
Predictive soil property map: Sand content
These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin... -
Process-guided deep learning water temperature predictions: 5 Model 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-... -
Process-guided deep learning water temperature predictions: 4 Training data
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... -
Process-guided deep learning water temperature predictions: 5a Lake Mendota...
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-... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 3...
This dataset provides model parameters used to estimate water temperature from a process-based model (Hipsey et al. 2019) using uncalibrated model configurations (PB0) and the... -
1 Site Information: Deep learning approaches for improving prediction of...
<p>This data release component contains shapefiles of river basin polygons and monitoring site locations coincident with the outlets of those basins. A table of basin... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 6...
Water temperature estimates from multiple models were evaluated by comparing predictions to observed water temperatures. The performance metric of root-mean square error (in... -
Process-guided deep learning water temperature predictions: 4c All lakes...
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... -
Process-guided deep learning water temperature predictions: 4a Lake Mendota...
This dataset includes compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from North... -
Data release: Process-guided deep learning predictions of lake water temperature
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... -
Process-guided deep learning water temperature predictions: 5a Lake Mendota...
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-... -
Point data for four case studies related to testing of multi-order...
The location of a point (or pixel) within the conterminous U.S. can be assigned based on its position relative to the Nation’s stream network. Two metrics are recognized:...