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Lumped-parameter watershed hydrological model

Project description

DOI Documentation Status PyPI version Tests

MNiShed

Watershed hydrological model

MN = Minnesota · Mni = water (Dakota) · Mini = small (lumped) · Shed = watershed

MNiShed is a lumped, daily-timestep conceptual hydrological model. It routes precipitation through an optional snowpack stage and then through a cascade of one or more reservoirs (soil zone, groundwater, etc.), producing streamflow. A basin can be split into parallel sub-catchments — including open-water lakes — to represent contrasting hydrologic zones. Evapotranspiration is either read from a data file or computed with the Thornthwaite–Chang 2019 equation, optionally reshaped by a growing-degree-day vegetation-phenology coefficient, and scaled to close the long-run water balance. The model follows the CSDMS Basic Model Interface (BMI), and ships with a fast in-process calibration stack and post-fit diagnostics.


Read the full documentation on ReadTheDocs


Features

  • Process options — snowpack (degree-day melt, rain-on-snow), frozen ground, a configurable reservoir cascade (power-law or linear recession), tile drainage (two formulations), PDM saturation-excess, and direct runoff.
  • Parallel sub-catchments & lakes — split a basin into zones with independent physics; open-water lake elements with a threshold stage–discharge outlet, direct precipitation minus evaporation, and a bidirectional lake↔groundwater exchange.
  • Evapotranspiration — measured or Thornthwaite–Chang, with an optional growing-degree-day vegetation-phenology coefficient and water-balance closure.
  • Calibration — fast in-process calibration (build-once ScoringModel, config-driven Calibrator with declarative parameter targets), multi-window/decadal objectives, and SPOTPY (SCE-UA, DREAM) or Dakota drivers.
  • Analysis — post-fit parameter-identifiability diagnostics (likelihood profiles, a curvature eigenspectrum, ridges), a seasonal mass-balance diagnostic, Brutsaert–Nieber recession analysis, and data-driven priors.
  • Performance & interoperability — an optional Numba JIT time loop (verified identical to pure Python) and a CSDMS BMI wrapper.

Installation

pip install mnished

To install from source for development:

git clone https://github.com/MNiMORPH/MNiShed.git
cd MNiShed
pip install -e '.[bmi,jit]'   # optional extras: bmi, jit, docs, lint

The optional extras are bmi (CSDMS BMI wrapper), jit (Numba JIT acceleration), docs (build the documentation), and lint (Ruff).

Quick start

Python API

import mnished

b = mnished.Buckets()
b.initialize('config.yml')
b.run()
b.compute_NSE(verbose=True)
b.plot()

Command-line interface

mnished -y config.yml

See the Quick Start guide for the configuration file format and input data requirements.

Citation

If you use MNiShed, please cite it using the metadata in CITATION.cff or via the Zenodo record:

Wickert, A. D. (2026). MNiShed: Watershed hydrological model. https://doi.org/10.5281/zenodo.6787390

Contact

Please report bugs and request features via GitHub Issues.

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