Confluence Retirement

Due to the feedback from stakeholders and our commitment to not adversely impact USGS science activities that Confluence supports, we are extending the migration deadline to January 2023.

In an effort to consolidate USGS hosted Wikis, myUSGS’ Confluence service is targeted for retirement. The official USGS Wiki and collaboration space is now SharePoint. Please migrate existing spaces and content to the SharePoint platform and remove it from Confluence at your earliest convenience. If you need any additional information or have any concerns about this change, please contact myusgs@usgs.gov. Thank you for your prompt attention to this matter.

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For more information, questions and answers from the presentation, and a recording of the meeting, please visit the CDI wiki. 

Collection of photos of people collaborating around climate scenarios and adaptation planning graphs.Image Removed

Open-source and open-workflow Climate Scenarios Toolbox for adaptation planning 


Collection of photos of people collaborating around climate scenarios and adaptation planning graphs.Image Added















Aparna Bamzai-Dodson, USGS, presented on the Climate Scenarios Toolbox (now renamed to the Climate Futures Toolbox!), an open-source tool that helps users formulate future climate scenarios for adaption planning. Scenario planning is a way to consider the range of possible outcomes by using projections based on climate data to develop usually 3-5 plausible divergent future scenarios (ex: hot and dry; moderately hot with no precipitation change; and warm and wet). Resource managers and scientists can use these scenarios to help predict the effects of climate change and attempt to select appropriate adaptation strategies. However, climate projection data can be difficult to work with in areas of discovery, access, and usage, involving multiple global climate model repositories, downscaling techniques, and file formats. The Climate Futures Toolbox aims to take the pain out of working with climate data. 

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CDI members are encourage to become engaged in the Toolbox by installing and using it, providing feedback on issues, and contributing code to the package. Since April's monthly meeting, the project has developed and undergone renaming, so this is a rapidly evolving endeavor. 

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Develop Cloud Computing Capability at Streamgages using Amazon Web Services GreenGrass IoT Framework for Camera Image Velocity Gaging 

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The first step required building a cloud infrastructure, with the help of Cloud Hosting Solutions (CHS). This involves connecting the edge computing (camera and raspberry PI footage of a stream) to an Amazon Web Services (AWS) IoT system and depositing camera footage and derivative products into a S3 bucket. The code for this portion of the product is in a preliminary GitLab repository that is projected to be published as a part of the long-term project. The team is also still working toward building the infrastructure through to data serving and dissemination. 

Workflow for getting streamflow data into a cloud computing system.Image Added

Other successes accomplished with this project so far include auto-provisioning (transmitting location and metadata) of edge computing systems to the cloud; establishing global actions (data is transmitted to the cloud framework and can roll into automated processing, like extracting video into frames); and building automated time-lapse computation. 

Engel and the project team have taken away a couple lessons from their experience with this project: first, cloud computing knowledge takes a lot of work and time to acquire, and second, in the short term, It can be difficult to establish a scope that encompasses the needs and wants of all stakeholders. 

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Establishing standards and integrating environmental DNA (eDNA) data into the USGS Nonindigenous Aquatic Species database 

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In order to successfully create a centralized AIS viewer, community standards need to be established so that data can be checked for quality and validity, especially within the FAIR data framework (Findable, Accessible, Interoperable, and Reusable). To establish community standards and successfully integrate eDNA into NAS, the project team accomplished several objectives: 

List of steps taken in integrating eDNA data into the Nonindigenous Aquatic Species DatabaseImage Added

1) Experimental Standards 

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