HydroLite Studio

Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for HydroLite Studio

Inspiration

Hydrologic work often moves between isolated GIS, rainfall-runoff, drainage, and reporting tools. HydroLite Studio brings the common project workflow into one traceable workbench without pretending to replace every specialist model.

What it does

HydroLite Studio helps users validate watershed inputs, run SCS-CN runoff, simplified unit-hydrograph routing, and Muskingum channel routing, then compare scenarios, check water balance, and generate reports. It adds optional bridges for Google Earth Engine summaries, SWMM coupling and result extraction, QGIS/GeoJSON preparation, OpenHydroNet-ready input packages, and a small HEC-HMS completed-event comparison workflow.

How we built it

The project is a Python and Streamlit workbench with CSV/YAML project data, reproducible command-line workflows, regression tests, and optional external-model backends. It keeps original data immutable and treats conditional GIS, GEE, SWMM, and HEC-HMS components as graceful extensions.

How Codex and GPT-5.6 were used

HydroLite Studio was developed collaboratively with Codex during OpenAI Build Week. GPT-5.6 in Codex supported repository navigation, implementation planning, local backend diagnosis, regression testing, and user documentation. The hydrologic calculations and generated outputs remain explicitly checked through reproducible tests and commands.

Challenges

Optional Mac backends can be unavailable or binary-incompatible. We designed them to fail gracefully so the core HydroLite project workflow, validation, results, and reporting remain usable.

Accomplishments

We created a project-centered workflow that lets users move from templates and validation to scenarios, comparison, reports, and local/cloud demo paths. The guided Streamlit workbench makes the complete flow more approachable for new users.

What we learned

Integrated engineering software needs transparent boundaries: reproducible inputs, explicit validation, graceful optional tools, and clear statements about what is verified versus still partial.

What's next

The v0.7 roadmap covers QGIS bridge maturation, richer data import, lightweight calibration and sensitivity scans, report templates, and desktop-launcher exploration. Operational flood forecasting and full production calibration are not yet claims of this project.

Built With

• macos