hydromt_wflow.WflowModel.setup_laimaps#

WflowModel.setup_laimaps(lai_fn: str | DataArray, lulc_fn: str | DataArray | None = None, lulc_sampling_method: str = 'any', lulc_zero_classes: List[int] = [], buffer: int = 2)[source]#

Set leaf area index (LAI) climatology maps per month [1,2,3,…,12].

The values are resampled to the model resolution using the average value. Currently only directly cyclic LAI data is supported.

If lulc_fn is provided, mapping tables from landuse classes to LAI values will be derived from the LULC data. These tables can then be re-used later if you would like to add new LAI maps derived from this mapping table and new landuse scenarios. We advise to use a larger buffer to ensure that LAI values can be assigned for all landuse classes and based on a lage enough sample of the LULC data.

Adds model layers:

  • LAI 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:

  • lai_fn (str, xarray.DataArray) –

    Name of RasterDataset source for LAI parameters, see data/data_sources.yml.

    • Required variables: ‘LAI’ [-]

    • Required dimensions: ‘time’ = [1,2,3,…,12] (months)

  • lulc_fn (str, xarray.DataArray, optional) – Name of RasterDataset source for landuse-landcover data. If provided, the LAI values are mapped to landuse classes and will be saved to a csv file.

  • lulc_sampling_method (str, optional) –

    Resampling method for the LULC data to the LAI resolution. Two methods are supported:

    • ’any’ (default): if any cell of the desired landuse class is present in the resampling window (even just one), it will be used to derive LAI values. This method is less exact but will provide LAI values for all landuse classes for the high resolution landuse map.

    • ’mode’: the most frequent value in the resampling window is used. This method is less precise as for cells with a lot of different landuse classes, the most frequent value might still be only a small fraction of the cell. More landuse classes should however be covered and it can always be used with the landuse map of the wflow model instead of the original high resolution one.

    • ’q3’: only cells with the most frequent value (mode) and that cover 75% (q3) of the resampling window will be used. This method is more exact but for small basins, you may have less or no samples to derive LAI values for some classes.

  • lulc_zero_classes (list, optional) – List of landuse classes that should have zero for leaf area index values for example waterbodies, open ocean etc. For very high resolution landuse maps, urban surfaces and bare areas can be included here as well. By default empty.

  • buffer (int, optional) – Buffer around the region to read the data, by default 2.