hydromt_wflow.WflowModel.setup_laimaps_from_lulc_mapping#

WflowModel.setup_laimaps_from_lulc_mapping(lulc_fn: str | DataArray, lai_mapping_fn: str | DataFrame, output_name: str = 'vegetation_leaf_area_index')[source]#

Derive cyclic LAI maps from a LULC data source and a LULC-LAI mapping table.

Adds model layers:

  • vegetation_leaf_area_index map: Leaf Area Index climatology [-]

    Resampled from source data using average. Assuming that missing values correspond to bare soil, these are set to zero before resampling.

Parameters:

  • lulc_fn (str, xarray.DataArray) – Name of RasterDataset source for landuse-landcover data.

  • lai_mapping_fn (str, pd.DataFrame) – Path to a mapping csv file from landuse in source name to LAI values. The csv file should contain rows with landuse classes and LAI values for each month. The columns should be named as the months (1,2,3,…,12). This table can be created using the setup_laimaps() method.

  • output_name (str) – Name of the output vegetation__leaf-area_index map. By default “vegetation_leaf_area_index”.