The Hydroinformatics and Data Science track includes workshops focused on data science tools, computing technologies, and community datasets that support CIROH research-to-operations initiatives. Topics may include hydrologic data science, model and data fusion, collaboration via HydroShare, CIROH cloud and high-performance computing resources, GIS and remote sensing, National Water Model visualization tools such as the Tethys Platform, APIs and data access tools, real-time data collection, camera-based monitoring, computer vision applications, and related advancements.
Leads: Patrick Clemins (University of Vermont), Jeffery Horsburgh (Utah State University)
Workshop Listings
Essential Geospatial Data and Coding Skills for CIROH Researchers
Day 1 Session 1
Tony Castronova (CUAHSI)
Abner Bogan (CUAHSI)
Danielle Tijerina-Kreuzer (CUAHSI)
Irene Garousi-Nejad (CUAHSI)
This workshop equips participants with foundational geospatial data and coding skills essential for conducting research and contributing to CIROH science. Through hands-on, interactive coding exercises, participants will gain practical experience with tools and capabilities central to CIROH research while working through science use cases centered on CIROH high-value datasets.
Topics include accessing and using JupyterHub cloud computing resources, commonly used scientific Python libraries and analytical techniques, and creating scalable, shareable cloud-based analyses that leverage large datasets.
By the end of the workshop, participants will have a comprehensive understanding of available CIROH tools, techniques, and resources needed to effectively engage in CIROH research activities and maximize research productivity and impact.
Developing Interactive CIROH Research Applications with Python- only Tethys Component Apps
Day 1 Session 2
Shawn Crawley – Lynker
Nathan Swain – Aquaveo
Dan Ames – BYU
Tethys Component Apps represent a new approach to building web applications in the Tethys Platform. Through the integration of ReactPy, Tethys enables researchers to develop rich, responsive applications entirely in Python—without requiring JavaScript, HTML templating, or frontend frameworks.
This approach builds directly on the Python scripting workflows many CIROH researchers already use for data analysis, modeling, and visualization, making it possible to expose existing research code through interactive web interfaces.
In this hands-on workshop, participants will learn how to build a Tethys Component App using CIROH-relevant research and decision-support use cases. Attendees will create interactive pages composed of reusable components, manage application state, and respond to user-driven events—all in Python.
The workshop emphasizes practical patterns for adapting existing Python-based scientific workflows into maintainable, user-friendly web applications that support data exploration and decision-making for the CIROH community.
Day 2 Session 1
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.
Day 2 Session 2
Carlos Erazo (Tulane University)
Ibrahim Demir (Tulane University)
This workshop introduces students and researchers to HydroBlox, a web-based, no-code, plug-and-play hydrological research workflow platform. Participants will learn the complete lifecycle of a data project—from initial data acquisition and browser-based coding to advanced analysis and insight generation.The session culminates in the creation of a standalone, exportable application, providing attendees with a comprehensive toolkit for modern water data workflows and improved scientific reproducibility in hydrology.
Using TEEHR Dashboards to Explore Hydrologic Model Performance
Day 3 Session 1
Matt Denno (RTI)
Sam Lamont (RTI)
Katie van Werkhoven (RTI)
Sam Landsteiner (RTI)
This hands-on workshop introduces participants to TEEHR (Tools for Exploratory Evaluation in Hydrologic Research) as an evaluation framework aligned with the emerging Community Hydrologic Prediction Testbed (CHPT).
CHPT defines standardized experimental design and evaluation protocols for comparing hydrologic models and forecasts, while TEEHR provides the computational, visualization, and data management tools needed to implement these protocols at scale.
The workshop is organized into two complementary parts.
Part 1:
Participants are introduced to TEEHR-Cloud and a set of application-specific dashboards. Instructors will walk through dashboard structure and the types of analyses they support, demonstrating how users can explore model and forecast performance, compare results against benchmark or alternative models, and investigate evaluation outcomes.
Part 2:
Participants will work directly with TEEHR Python tools in a JupyterHub environment. Attendees will download data from the TEEHR data warehouse, load example (synthetic) model simulation data, and execute evaluation calculations and analyses in a Jupyter notebook. This portion illustrates an example evaluation protocol and shows how TEEHR supports transparent, reproducible workflows that connect computational analysis to dashboard-based interpretation.
The workshop leverages existing TEEHR Cloud infrastructure and emphasizes hands-on interaction with both dashboards and notebook-based workflows. It highlights how evaluation choices relate to different application goals, such as flood forecasting versus water supply forecasting.
Talk to NRDS: Building an LLM Chat for TethysDash to Explore the NextGen Research Data Stream
Day 3 Session 2
Giovanni Romero (Aquaveo)
Nathan Swain (Aquaveo)
Corey Krewson (Aquaveo)
Dan Ames (BYU)
Arpita Patel (AWI)
This workshop will immerse participants in using TethysDash to explore NextGen Research Data Stream (NRDS) forecasts through a local LLM chat experience. Instead of navigating complex folder structures and filenames, attendees will “talk to the data” using an Ollama-powered chatbox that converts prompts such as: “Show me streamflow for VPU_01 on the latest short-range run” into actionable dashboard updates.
A polished HydroFabric visualization panel (MapLibre + deck.gl) and the AI model chat UI (Ollama) will be prebuilt prior to the workshop. Participants will focus on building an AI-driven plugin for TethysDash with two core capabilities:
- Querying NetCDF time series for a user-selected stream or catchment and variable from NRDS outputs stored in the public S3 bucket
ciroh-community-ngen-datastream - Enabling hydrofabric switching directly from natural-language prompts (e.g., selecting hydrofabric version/VPU and corresponding run paths)
All components will run locally using Docker, Docker Compose, and Dev Containers. Participants will validate the full workflow from prompt → hydrofabric/run selection → click-to-timeseries visualization.
Workshop materials and code will be shared in advance via HydroShare.