Filters: Date Range: {"choice":"week"} (X) > Tags: {"scheme":"none"} (X) > partyWithName: U.S. Geological Survey (X) > Categories: Data (X)
Folders: ROOT > ScienceBase Catalog ( Show direct descendants )
3 results (31ms)
LocationFilters
Date Types (for Date Range)
Tag Types Tags (with Scheme=none) |
Continuous water-temperature data were collected at multiple sites along the Middle Fork and mainstem Willamette Rivers between Jasper and Newberg, Oregon, to support effectiveness monitoring for a large-scale channel and floodplain restoration program (Willamette Focused Investment Partnership, WFIP). Continuous water temperature loggers were deployed at a subset of WFIP restoration sites where river restoration activities were implemented to improve habitat conditions for native fish species. Data from water-temperature monitoring will be used to evaluate the effectiveness of restoration activities at improving habitat conditions for ESA-listed salmonids and other native fish in the Willamette River. Additionally,...
Continuous water-temperature data were collected at multiple sites along the Middle Fork and mainstem Willamette Rivers between Jasper and Newberg, Oregon, to support effectiveness monitoring for a large-scale channel and floodplain restoration program (Willamette Focused Investment Partnership, WFIP). Continuous water temperature loggers were deployed at a subset of WFIP restoration sites where river restoration activities were implemented to improve habitat conditions for native fish species. Data from water-temperature monitoring will be used to evaluate the effectiveness of restoration activities at improving habitat conditions for ESA-listed salmonids and other native fish in the Willamette River. Additionally,...
Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state-of-the-art modeling approaches use hydrodynamic models, which can produce accurate results but are limited by significant computational costs. We developed a machine learning (ML) model to predict the 250 mg/L Cl- isochlor, also known as the salt front, using daily river discharge, meteorological drivers, and tidal water level data. We use the ML model to predict the location of the salt front, measured in river miles (RM) along the Delaware River, during the period 2001-2020, and we compare the ML model results to results from the hydrodynamic...
|
|