Statistical methods

Skill statistics

HydroMT provides different functions to apply model skill statistics to compare model results with observations. The following statistics are available:

• Absolute and percentual bias

• Nash-Sutcliffe model Efficiency (NSE) and log Nash-Sutcliffe model Efficiency (log-NSE)

• Various versions of the Kling-Gupta model Efficiency (KGE)

• Coefficient of determination (R-squared)

• Mean Squared Error (MSE) and Root Mean Squared Error (RMSE)

Example application

As HydroMT provides methods to easily read the model results, applying a skill statistic just takes a few lines of code and can be applied directly across all observation locations in your model.

from hydromt.stats import nashsutcliffe
from hydromt_wflow import WflowModel
import xarray as xr
# read model results
# NOTE: the name of the results depends on the wflow run configuration (toml file)
mod = WflowModel(root=r'/path/to/wflow_model/root', mode='r')
sim = mod.results['Q_gauges_grdc']
# read observations
obs = xr.open_dataset(r'/path/to/grdc_obs.nc')
# calculate skill statistic
nse = nashsutcliffe(sim, obs)