Characterizing hydrologic networks: Developing a tool to enable research of macroscale aquatic networks. (June 2018)

• Record Type: Journal Article
• Authors: Winslow, Luke A.; Hahn, Tobi H.; DeVaul Princiotta, Sarah; Leach, Taylor H.; Rose, Kevin C.
• Is Part Of: Environmental modelling & software. Volume 104(2018)
• Page Start: 94
• Page End: 101
• Publication Date: 2018-06
• Subjects: R package -- Lakes -- Streams -- Hydrologic network -- Limnology -- Data integration -- Macrosystem ecology; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.03.012
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Addressing continental scale challenges affecting inland aquatic systems requires data at comparable scales. Critically, local in-situ observations for both lotic and lentic ecosystems are frequently fragmented across federal, state and local agencies, and nonprofit or academic organizations and must be linked to other geospatial data to be useful. To advance macro-scale aquatic ecosystem science, better tools are needed to facilitate dataset integration. Key to integration of aquatic data is the linking of spatial data to the hydrologic network. This integration step is challenging as hydrologic network data are large and cumbersome to manage. Here we develop a new R package, hydrolinks, to ease linking aquatic data to the hydrologic network. We use hydrolinks to evaluate the spatial data quality for all lake and stream sites available through the U.S. Water Quality Portal. We find that 76.5% of lake sites and 13.9% of stream sites do not correspond with mapped waterbodies. Highlights: R package for linking macroscale data to the hydrologic network. Package automates difficult and time consuming processes. Open-source for reproducibility, openness, and future improvements. Federal database example highlights frequent occurrence of mis-labeled hydrologic data.