Collecting, Organizing, Managing, and Standards-Based Sharing of Hydrologic Observations Using HydroServer
Day 2 Session 1 (10:45AM)
Presenters:
Jeff Horsburgh (Utah State University)
Ken Lippold (Utah State University)
Daniel Slaugh (Utah State University)
Maurier Ramirez (Utah State University)
Many CIROH projects use time series of observational data beyond those provided by the USGS for modeling and other applications. HydroServer provides a hydrologic information system that supports storing and organizing observational data from environmental sensors, along with web service APIs and Python client tools that enable easy data retrieval for modeling and data analysis workflows.
This hands-on workshop introduces participants to HydroServer’s functionality through guided exercises. Participants will learn how to load data, organize time series of hydrologic observations within a workspace, share data using Open Geospatial Consortium (OGC)–compliant web services, and access data programmatically using HydroServer’s Python client package, hydroserverpy.
Learning Outcomes:
- Identify HydroServer’s functionality and its utility for managing sensor data in modeling workflows
- Navigate HydroServer’s Data Management App to create workspaces, monitoring sites, and datastream metadata
- Load observational data into HydroServer using simple software tools
- Use the hydroserverpy Python client package to interact with and retrieve data
Prerequisites:
- Hardware:
- Laptop computer with a web browser and internet access
- Programming:
- Basic Python familiarity is helpful for interacting with example code in shared Jupyter notebooks
- Software & Data:
- All example data and code will be accessed via a shared HydroShare resource
- Accounts:
- Participants who wish to follow along will need:
- HydroShare account
- CIROH 2i2c JupyterHub account
- User account on the HydroServer playground instance (provided for training)
Additional Notes
This workshop focuses on tools that support the collection, organization, storage, management, and sharing of hydrologic time series observations, such as data from streamflow gages, water quality monitoring stations, and weather stations. It fits within the Hydroinformatics category and includes web applications, data management, Python coding, OGC standards, and web-based APIs.