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This dataset consists of the current distribution (2000s) of mangrove forests in the southeastern U.S. This dataset was created from the current best available mangrove data on a state specific basis. Florida mangrove data was extracted from Florida Landuse Land Cover Classification System (FLUCCS). For Louisiana, we used observations of mangrove stands from aerial surveys by Michot et al. (2010). Mangrove presence in Texas came from maps produced by Sherrod & McMillan (1981) and the NOAA Benthic Habitat Atlas of Coastal Texas (Finkbeiner et al. 2009). Please note that this map depicts the distribution of mangrove forests and not mangrove individuals. More detailed information on this dataset is available in Osland...
Daily maximum water temperature predictions in the Delaware River Basin (DRB) can inform decision makers who can use cold-water reservoir releases to maintain thermal habitat for sensitive fish species. This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper DRB. The modeling approach includes process-guided deep learning and data assimilation (Zwart et al., 2023). The model is driven by weather forecasts and observed reservoir releases and produces maximum water temperature forecasts for the issue day (day 0) and 7 days into the future (days 1-7). In combination with data provided in Oliver et al. (2022),...
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This section contains forcing data for water temperature forecasting models reported in Zwart et al. (2023), including a process-based pre-trainer, gridded weather and forecasted weather data, and flow and temperature for reservoir inlets and outlets.
This section provides spatial data files that describe the river and reservoirs in the Delaware River Basin included in this release. One shapefile of polylines describes the 70 river reaches that define the modeling network, and another shapefile of polygons includes the two reservoirs (Pepacton, Cannonsville) for which data are included in this release.
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This section includes model parameters and metadata used to configure reservoir models.
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This section includes predictions from several models, including a model pre-trainer that is predictions from a distance-weighted-average lotic-lentic input network (DWALLIN) model, reservoir outlet temperature predictions from a process-based model, forecasts from a persistence stream water temperature model, and stream water temperature forecasts from two deep learning models, a long-short term memory network and recurrent convolutional graph network model.
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This section includes code that prepares data for model training and forecasts maximum stream temperature using neural network models. Finally, the code evaluates the models using various accuracy and uncertainty metrics.
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