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Pre-delineated MERIT-Hydro watershed boundaries for ~60,000 gauging stations across 16 countries

Project description

watershed-retrieve

PyPI version License: MIT Python 3.13+

Instant access to ~60,000 pre-delineated MERIT-Hydro watershed boundaries and river networks across 16 countries, served as GeoParquet. No data download required — basins are fetched on demand from a public CDN and cached locally.

Background

This library is a community contribution to the RivRetrieve ecosystem. Where RivRetrieve provides observed streamflow time series for gauging stations worldwide, watershed-retrieve adds the corresponding watershed boundaries and river networks, delineated on the MERIT-Hydro digital elevation model.

The watershed delineation was performed using a Rust reimplementation of the algorithm described in mheberger/delineator.

See the original proposal: kratzert/RivRetrieve-Python#87.

Installation

pip install watershed-retrieve

Quick Start

import watershed_retrieve as wr

# Zero-config — data is fetched from R2 CDN and cached locally
watershed = wr.get_watershed("portugal", "04K/04A")

# With river network
watershed, rivers = wr.get_watershed_with_rivers("portugal", "04K/04A")

# Bulk retrieval — all watersheds for a country
all_watersheds = wr.get_watersheds("portugal")

To use a local data directory instead of the CDN:

# Option 1: Environment variable
# export WATERSHED_RETRIEVE_DATA_DIR=/path/to/parquet/files

# Option 2: Programmatic
wr.configure("/path/to/parquet/files")

# Option 3: Explicit backend selection
from watershed_retrieve import Backend
wr.configure(backend=Backend.R2, cache_dir=Path("~/.my-cache"))

API Reference

Discovery

# List all supported countries
wr.available_countries()
# -> ['australia', 'brazil', 'canada', ..., 'usa']

# List gauge IDs for a country
wr.available_gauges("portugal")
# -> ['02G-02H', '02O-01H', ..., '16J-01H']  (73 gauges)

Single Watershed

# Watershed boundary (GeoDataFrame, 1 row)
gdf = wr.get_watershed("portugal", "04K/04A")

# Watershed + river network (WatershedResult — unpackable NamedTuple)
result = wr.get_watershed_with_rivers("portugal", "04K/04A")
watershed, rivers = result

Bulk Retrieval

# All watersheds for a country
gdf = wr.get_watersheds("portugal")  # -> GeoDataFrame (73 rows)

# Subset by gauge IDs
gdf = wr.get_watersheds("portugal", ["04K/04A", "05G/01A"])

# With rivers
result = wr.get_watersheds_with_rivers("portugal")
result.watershed  # GeoDataFrame
result.rivers     # GeoDataFrame

Gauge ID Normalization

Slashes are automatically normalized to dashes:

wr.get_watershed("portugal", "04K/04A")   # slash
wr.get_watershed("portugal", "04K-04A")   # dash — equivalent

Errors

from watershed_retrieve import (
    WatershedRetrieveError,     # base class
    CountryNotFoundError,       # invalid country name
    GaugeNotFoundError,         # gauge ID not in dataset
    DataNotFoundError,          # parquet file missing
    DataUnavailableError,       # region exists but data not yet extracted
    R2ConnectionError,          # CDN fetch failed
)

DataUnavailableError is raised for regions where gauging stations are registered in RivRetrieve but MERIT-Hydro basin delineation is pending (e.g., UK regions — the British Isles fall outside MERIT-Hydro coverage).

Supported Countries

Country Gauges Status
Australia ~5,200 Available
Brazil ~4,300 Available
Canada ~5,800 Available
Chile ~500 Available
Czech Republic ~400 Available
France ~5,400 Available
Germany ~500 Available
Japan ~1,200 Available
Lithuania ~70 Available
Norway ~600 Available
Poland ~600 Available
Portugal 73 Available
Slovenia ~200 Available
South Africa ~900 Available
Spain ~600 Available
UK (EA) ~1,500 Pending — MERIT-Hydro coverage gap
UK (NRFA) ~1,500 Pending — MERIT-Hydro coverage gap
USA ~32,000 Available

Development

# Install
git clone https://github.com/CooperBigFoot/watershed-retrieve.git
cd watershed-retrieve
uv sync

# Unit tests (no data or network needed)
uv run pytest tests/ -v -m "not integration and not network"

# Integration tests (requires local parquet data)
WATERSHED_RETRIEVE_DATA_DIR=/path/to/data uv run pytest tests/ -v -m integration

# Lint & format
uv run ruff check --fix src/ tests/
uv run ruff format src/ tests/

See CONTRIBUTING.md for full development guidelines.

License

MIT

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