CUAHSI’s Data Down-low

Delaware River Watershed Initiative

Check out data from the Delaware River Watershed Initiative on HydroClient!

The Delaware River Watershed Initiative is an ambitious effort underway to protect and restore the Delaware River Basin’s water quality and overall ecological health. Kick-started by a $35 million commitment by the William Penn Foundation, the Delaware River Watershed Initiative (DRWI) is targeting eight “clusters” within the basin for conservation investment. More than 50 leading nonprofits have joined together, aligning priorities for land protection and restoration projects and assessing water quality impacts using standardized methods. Clusters were delineated using landscape variables including land use, conservation easements, and land trust areas in addition to input from local nonprofits. Monitoring sites in each cluster were chosen based on how representative of the cluster’s landscape they were. These sites represent the “typical” conditions of each cluster. The diversity of the landscape in each cluster influenced the number of sites, and they represent a range of watershed sizes (9-313 km2). Monitoring for the DRWI began in 2013 and will continue through at least 2020. Chemical, algae, fish, and macroinvertebrate data are collected at each of the sites. To learn more about the Delaware River Watershed.

Find this data on HydroClient by following these steps:

  1. Enter location: Delaware River, United States
  2. Narrow down Data Service: Delaware River Watershed Initiative (hint: click on the row to highlight it)

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Execute your HydroShare workflows using the CUAHSI-JupyterHub!

The CUAHSI-JupyterHub is a compute environment for working with HydroShare data, e.g. data analysis, executing model simulations, and building Jupyter workflows in Python or R. Navigate to your favorite HydroShare resource (or click the link below), select “Open With -> CUAHSI JupyterHub” and your data will be moved into an isolated compute environment specifically designed for you. This environment comes preconfigured with many scientific libraries and is ideal for sharing and research workflows and results, classroom exercises, and reproducing published results.

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