National Stream Summarization: Standardizing Stream-Landscape Summaries
As research and management of natural resources shift from local to regional and national scales, the need for information about aquatic systems to be summarized to multiple scales is becoming more apparent. Recently, four federally funded national stream assessment efforts (USGS Aquatic GAP, USGS National Water-Quality Assessment Program, U.S. Environmental Protection Agency [EPA] StreamCat, and National Fish Habitat Partnership) identified and summarized landscape information into two hydrologically and ecologically significant scales of local and network catchments for the National Hydrography Dataset Plus (NHDPlus). These efforts have revealed a significant percentage of assessment funds being directed to the collection and processing of data instead of for the assessments themselves. Additionally, although similar data are being summarized across these efforts, each is creating its own implementation. This duplication of effort is inefficient and may be producing inconsistent results.
To address these issues, the USGS, EPA, and Michigan State University participants have used CDI funds to support progress towards collaborative efforts with the end goal of developing a common workflow (for example, code) to accurately and efficiently summarize landscape information into local and network catchments of the NHDPlus.
Principal Investigator : Daniel J Wieferich, Jeff T Falgout, Dana Infante, Scott Leibowitz, Marc Weber, Brad Williams
Cooperator/Partner : Jeff N Houser, Abigail J Lynch, Bradly Potter, Alan H Rea, Roland Viger, Michael E Wieczorek
Accomplishments
Current accomplishments and continued efforts are described below.
- The project team documented comparisons of existing workflows and resulting datasets to help identify commonalities and differences of current efforts that need to be addressed as a standardized workflow is developed.
- An interagency agreement was established to outline and facilitate a 1-year commitment between the EPA and USGS where EPA staff will assist in the implementation, development, and refinement of a standardized software to process stream summarization (FY 2017 Planned Accomplishment). The interagency agreement will also facilitate a proposal for a single, common dataset repository and metadata documentation of landscape information summarized to the NHDPlusV2 (FY 2017 Planned Accomplishment).
- A face-to-face meeting took place during August 3–5, 2016, to compare current stream summarization efforts, understand needs of potential user groups across the Federal government, and identify a path forward.
- A confluence page was developed to help build a community of practice and to help disseminate and coordinate current and future efforts related to the CDI project.
Note: This description is from the Community for Data Integration 2016 Annual Report.
- Source: USGS Sciencebase (id: 56d88158e4b015c306f6d001)
xstrm_local
xstrm
Daniel Wieferich
Roland J Viger
Chief, Geo-Intelligence Branch
Abigail J. Lynch, Ph.D.
Research Fish Biologist, National CASC
Jeff Houser, PhD
Research Ecologist
Michael E Wieczorek
Geographer/GIS Specialist
Brad Williams
Computer Scientist
Jeff Falgout
Computer Scientist
Alan H Rea, P.E. (Retired) (Former Employee)
Hydrologist and National Hydrography Co-Lead
As research and management of natural resources shift from local to regional and national scales, the need for information about aquatic systems to be summarized to multiple scales is becoming more apparent. Recently, four federally funded national stream assessment efforts (USGS Aquatic GAP, USGS National Water-Quality Assessment Program, U.S. Environmental Protection Agency [EPA] StreamCat, and National Fish Habitat Partnership) identified and summarized landscape information into two hydrologically and ecologically significant scales of local and network catchments for the National Hydrography Dataset Plus (NHDPlus). These efforts have revealed a significant percentage of assessment funds being directed to the collection and processing of data instead of for the assessments themselves. Additionally, although similar data are being summarized across these efforts, each is creating its own implementation. This duplication of effort is inefficient and may be producing inconsistent results.
To address these issues, the USGS, EPA, and Michigan State University participants have used CDI funds to support progress towards collaborative efforts with the end goal of developing a common workflow (for example, code) to accurately and efficiently summarize landscape information into local and network catchments of the NHDPlus.
Principal Investigator : Daniel J Wieferich, Jeff T Falgout, Dana Infante, Scott Leibowitz, Marc Weber, Brad Williams
Cooperator/Partner : Jeff N Houser, Abigail J Lynch, Bradly Potter, Alan H Rea, Roland Viger, Michael E Wieczorek
Accomplishments
Current accomplishments and continued efforts are described below.
- The project team documented comparisons of existing workflows and resulting datasets to help identify commonalities and differences of current efforts that need to be addressed as a standardized workflow is developed.
- An interagency agreement was established to outline and facilitate a 1-year commitment between the EPA and USGS where EPA staff will assist in the implementation, development, and refinement of a standardized software to process stream summarization (FY 2017 Planned Accomplishment). The interagency agreement will also facilitate a proposal for a single, common dataset repository and metadata documentation of landscape information summarized to the NHDPlusV2 (FY 2017 Planned Accomplishment).
- A face-to-face meeting took place during August 3–5, 2016, to compare current stream summarization efforts, understand needs of potential user groups across the Federal government, and identify a path forward.
- A confluence page was developed to help build a community of practice and to help disseminate and coordinate current and future efforts related to the CDI project.
Note: This description is from the Community for Data Integration 2016 Annual Report.
- Source: USGS Sciencebase (id: 56d88158e4b015c306f6d001)