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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),...
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...
Harmful algal blooms (HABs) have recently been observed in rivers, including the Illinois River in the Midwest United States. The Illinois River Basin has a history of eutrophication issues, primarily caused by the excessive loading of nitrogen and phosphorus from urban and agricultural sources. Recent events have seen the emergence of cyanobacterial harmful algal blooms in the area. This data release provides early warning indicator (EWI) metrics derived from a continuous chlorophyll concentration dataset obtained from seven water quality monitoring sites along the Illinois River. These metrics include the first-order autoregressive process (Ar1) and the standard deviation (SD) of chlorophyll, which serve as leading...
Daily 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 and mussel species. This data release supports a variety of flow and water temperature modeling efforts and provides the inputs and outputs of both machine learning and process-based modeling methods across 456 river reaches and 2 reservoirs in the DRB. The data are organized into these items: This research was funded by the USGS. Waterbody Information - One shapefile of polylines for the 456 river segments in this study, a reservoir polygon metadata file, and one shapefile of reservoir polygons for the Pepacton and Cannonsville reservoirs...
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