Filters: Tags: deep learning (X) > Types: OGC WMS Layer (X) > Types: Map Service (X) > partyWithName: Jacob A Zwart (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Shapefile (3) Types Downloadable (3) OGC WFS Layer (3) Shapefile (3) Contacts Samantha K Oliver U.S. Geological Survey U.S. Geological Survey - ScienceBase Integrated Information Dissemination Division Jordan S Read More... Categories Data (3) Tag Types Theme (3) Place (3) USGS Scientific Topic Keyword (2) Harvest Set (2) Tag Schemes none (3) U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST (3) Department of Commerce, 1995, Countries, Dependencies, Areas of Special Sovereignty, and Their Principal Administrative Divisions, Federal Information Processing Standard (FIPS) 10-4, Washington, D.C., National Institute of Standards and Technology (3) ISO 19115 Topic Category (3) USGS Thesaurus (3) View Results as: JSON ATOM CSV

Predicting water temperature in the Delaware River Basin: 1 Waterbody information for 456 river reaches and 2 reservoirs This dataset provides one shapefile of polylines for the 456 river segments in this study, and one shapefile of reservoir polygons for the Pepacton and Cannonsville reservoirs. Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: DE, Delaware, MD, Maryland, NJ, All tags... NY, New Jersey, New York, PA, Pennsylvania, US, United States, deep learning, environment, forecast, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, streams, temperature, water, water resources, Fewer tags Data to support near-term forecasts of stream temperature using process-guided deep learning and data assimilation This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that made real-time predictions in the Delaware River Basin during 2021. 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) at five sites. This data release captures the entire forecasting period that is reported in Zwart et al. 2022, and is an extension of a previous data release that contains all data needed to build these models but only extends to July 16, 2021 (Oliver et al. 2021). Additionally, this release contains a tidy version of the model predictions with paired... Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Hydrology, NY, New York, US, USGS Science Data Catalog (SDC), All tags... United States, Water Quality, Water Resources, data assimilation, deep learning, environment, forecasting, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, rivers, temperature, water, water resources, Fewer tags Model predictions for heterogeneous stream-reservoir graph networks with data assimilation This data release provides the predictions from stream temperature models described in Chen et al. 2021. Briefly, various deep learning and process-guided deep learning models were built to test improved performance of stream temperature predictions below reservoirs in the Delaware River Basin. The spatial extent of predictions was restricted to streams above the Delaware River at Lordville, NY, and includes the West Branch of the Delaware River below Cannonsville Reservoir and the East Branch of the Delaware River below Pepacton Reservoir. Various model architectures, training schemes, and data assimilation methods were used to generate the table and figures in Chen et a.l (2021) and predictions of each model are... Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Hydrology, NY, New York, PA, Pennsylvania, All tags... US, USGS Science Data Catalog (SDC), United States, Water Quality, Water Resources, climate change, deep learning, environment, hybrid modeling, inlandWaters, machine learning, modeling, reservoirs, temperature, water, water resources, Fewer tags