rwgen.WeatherGenerator.simulate
- WeatherGenerator.simulate(output_types='point', output_subfolders='default', output_format='txt', catchment_metadata=None, grid_metadata=None, epsg_code=None, cell_size=None, dem=None, simulation_length=30, n_realisations=1, timestep_length=1, start_year=2000, calendar='gregorian', random_seed=None, run_simulation=True, apply_shuffling=False)
Simulate rainfall and other weather (temperature, PET, …) variables.
- Parameters:
output_types (str or list of str) – Types of output (discretised) rainfall required. Options are
'point'
,'catchment'
and'grid'
.output_subfolders (str or dict) – Sub-folder in which to place each output type. If
'default'
thendict(point='point', catchment='catchment', grid='grid')
is used for a spatial model anddict(point='')
for a point model (i.e. output toself.output_folder
). If None then all output files are written toself.output_folder
.output_format (str) – Flag indicating output file format for point and catchment output. Current option is
txt
. Gridded output will be written in NetCDF format.catchment_metadata (geopandas.GeoDataFrame or str) – Geodataframe containing catchments for which output is required (or path to catchments shapefile). Optional.
grid_metadata (dict or str) – Specification of output grid to use for both gridded output (optional). This grid is also used to support catchment output. Dictionary keys use ascii raster header keywords, e.g.
dict(ncols=10, nrow=10, ...)
. Usexllcorner
andyllcorner
, as well as lowercase for each keyword. If None then a grid is defined to encompass catchment locations using thecell_size
argument. The path to an ascii raster file to use as a template for the grid can be given instead.epsg_code (int) – EPSG code for projected coordinate system used for domain (required if catchment or grid output is requested).
cell_size (float) – Cell size to use if grid is None but a grid is needed for gridded output and/or catchment output.
dem (xarray.DataArray or str) – Digital elevation model (DEM) [m] as data array or ascii raster file path. Optional but recommended.
simulation_length (int) – Number of years to simulate in one realisation (minimum of 1).
n_realisations (int) – Number of realisations to simulate.
timestep_length (int) – Timestep of output [hr]. Default is 1 (hour).
start_year (int) – Start year of simulation.
calendar (str) – Flag to indicate whether
gregorian
(default accounting for leap years) or365-day
calendar should be used.random_seed (int) – Seed to use in random number generation.
run_simulation (bool) – Flag for whether to run simulation. Setting to False may be used to update
self.simulation_args
to allowself.postprocess()
to be run withoutself.simulate()
having been run first (i.e. reading from existing simulation output files).apply_shuffling (bool) – Indicates whether to run model with or without shuffling following Kim and Onof (2020) method.