raven-symfluence 0.1.0

Raven hydrological modelling framework -- SYMFLUENCE plugin

raven-symfluence

A SYMFLUENCE plugin that runs the Raven hydrological modelling framework as a SYMFLUENCE model.

The plugin registers Raven via the symfluence.plugins entry point. It feeds Raven from SYMFLUENCE's model-ready datastore (canonical CFIF forcing + catchment attributes), drives it through RavenPy (which writes the .rvi/.rvp/.rvh/.rvt/.rvc files and runs the raven binary), and connects it to SYMFLUENCE's run + calibration pipeline.

Status: early / experimental. The pieces below run end-to-end and are covered by unit and integration tests, but they have only been exercised on synthetic fixtures and a small number of real basins with short calibration budgets. Treat results as preliminary and validate on your own domains. Issues and PRs welcome.

Install

pip install raven-symfluence            # plugin + SYMFLUENCE
pip install "raven-symfluence[raven]"   # also pulls RavenPy
symfluence binary install raven         # build the Raven engine from source

Use

Set HYDROLOGICAL_MODEL: RAVEN and pick a structure with RAVEN_MODEL_TEMPLATE. The eight RavenPy emulators are wired: GR4JCN, HBVEC, HMETS, MOHYSE, BLENDED, CANADIANSHIELD, HYPR, SACSMA. Then run the normal workflow:

symfluence list models            # RAVEN appears once installed
symfluence workflow run --config my_config.yaml

Lumped vs. distributed

RAVEN_SPATIAL_MODE: lumped (default) runs a single HRU/subbasin. RAVEN_SPATIAL_MODE: distributed reads the river-network topology (from the model-ready attributes store, or the TauDEM delineation shapefiles) and builds a routed multi-subbasin model — one land HRU per subbasin, in-channel routing via RAVEN_ROUTING_METHOD (default ROUTE_DIFFUSIVE_WAVE). Each subbasin is gauged, so a per-reach hydrograph is produced, which allows multi-gauge calibration:

HYDROLOGICAL_MODEL: RAVEN
RAVEN_MODEL_TEMPLATE: HMETS
RAVEN_SPATIAL_MODE: distributed
MULTI_GAUGE_CALIBRATION: true
GAUGE_SEGMENT_MAPPING: /path/to/gauge_segment_mapping.csv   # gauge id -> subbasin id
MULTI_GAUGE_OBS_DIR:   /path/to/obs                          # ID_<id>.csv per gauge

Distributed mode falls back to lumped for undelineated or single-subbasin domains. CanadianShield needs two HRUs per subbasin and currently runs lumped only.

Channel cross-sections for routing are estimated from drainage area via hydraulic-geometry relations (the attributes store carries no surveyed cross-sections), so routed timing is approximate.

Regionalization and multi-objective calibration

In distributed mode, PARAMETER_REGIONALIZATION: transfer_function lets selected parameters vary per subbasin as param_i = a + b·attr_norm_i; the optimizer calibrates the transfer-function coefficients rather than a value per subbasin, and values are applied via Raven's SBGroupPropertyMultiplier. The default GR4JCN mapping ties the production store to precipitation and the routing/snow stores to elevation; override with RAVEN_REGIONALIZATION_PARAM_CONFIG. Regionalization is a regularization aimed at ungauged/multi-gauge prediction — it will not always improve a single-outlet fit.

Calibration can also target SWE and ET alongside streamflow. Raven emits the matching :CustomOutput (SNOW for SWE, AET) when a SWE/ET objective is configured, and SYMFLUENCE's multi-objective framework combines them:

RAVEN_SPATIAL_MODE: distributed
PARAMETER_REGIONALIZATION: transfer_function
OBJECTIVE_WEIGHTS: {STREAMFLOW: 0.7, SWE: 0.2, ET: 0.1}

See the SYMFLUENCE docs for the full configuration reference.

Tests

pip install -e ".[raven]"
pytest                       # unit tests; integration tests need the raven binary

License

MIT (see LICENSE). Raven is developed at the University of Waterloo; RavenPy is developed by Ouranos; SYMFLUENCE is a separate project under its own license. This plugin is an independent integration and is not affiliated with or endorsed by any of them; install and use each under its own terms.

---

Repo and code assistance from Claude (Anthropic).