Build reproducible watershed modeling pipelines in Python.

What you will find here

Watershed Modeling is a focused reference for automating hydrologic workflows in Python. Every page is built around concrete, reproducible patterns: which library to reach for, why a routing algorithm behaves the way it does on a given terrain, and how to wrap it in a defensible pipeline with logging, idempotency, and topology validation.

Whether you are moving from desktop GIS to a code-driven pipeline, integrating LiDAR into an operational workflow, or scaling watershed delineation across a continent of tiles, the content here favours the algorithmic depth and engineering rigour that production agency-grade work demands — not surface-level tutorials.

The collection now runs to 84 pages across four sections and 22 topic areas, every one of them carrying runnable Python, a validation protocol that can fail, and hand-authored diagrams of the mechanism being described. Recent additions cover hydro-conditioning through road embankments, stream-network vectorization and ordering, tiled processing for datasets larger than memory, design-storm construction, and flood-frequency and low-flow statistics from gauge records.

Browse the sections

Four sections cover the full hydrologic pipeline from raw elevation data through hydrologically sound catchments to simulated runoff hydrographs and the gauge statistics that check them. Each section drills into specific implementation guides with code, validation strategies, and the operational pitfalls that only surface in production.