Authors: Jeffery S. Horsburgh, Daniel Slaugh, Kenneth Lippold, Maurier Ramirez – Utah State University
Title: Advancing HydroServer for Collecting, Managing, and Sharing Operational Hydrologic Monitoring Data
Abstract: Future iterations of the National Water Model will need to assimilate local-scale monitoring data to improve forecasts. A cooperative network of streamflow gages operated by a variety of organizations throughout the U.S. could enhance USGS’ existing gage network to make more data available to national-scale modeling, but no cyberinfrastructure currently exists to support such a network. This project seeks to improve operational data availability to support modeling and prediction by advancing tools available for managing and sharing hydrologic time series observations. Operational and scientific use of environmental sensor data requires effective software tools that enable data collection, management, and sharing. In many cases, hardware and software are needed that support the day-to-day data management needs of scientists and practitioners who operate networks of environmental monitoring sites to measure hydrologic systems and manage water resources. Given the volume of data collected, these groups struggle to perform the required data management needed to consistently produce data products of sufficient quality that they can be used in operational or scientific contexts. Furthermore, aggregating data across many sources is difficult given the variety in data management methods used. New standards for sharing sensor data have emerged recently, including the Open Geospatial Consortium’s (OGC) SensorThings standard, but without sufficient software implementation for adoption by researchers and practitioners who collect time series of hydrologic observations at operational streamflow gages. In this presentation, we will describe modernization of the open source HydroServer software stack for collecting, storing, managing, and sharing observations collected or derived from environmental sensors deployed at in situ monitoring sites using OGC’s SensorThings standard.