hydromt_wflow.workflows.soilgrids.soilgrids

hydromt_wflow.workflows.soilgrids.soilgrids(ds, ds_like, ptfKsatVer, logger=<Logger hydromt_wflow.workflows.soilgrids (WARNING)>)

Returns soil parameter maps at model resolution based on soil properties from SoilGrids dataset. Ref: Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M., Kilibarda, M., Blagotic, A., et al.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS ONE, 12, https://doi.org/10.1371/journal.pone.0169748, 2017.

The following soil parameter maps are calculated: - thetaSaverage saturated soil water content [m3/m3] - thetaRaverage residual water content [m3/m3] - KsatVervertical saturated hydraulic conductivity at soil surface [mm/day] - SoilThicknesssoil thickness [mm] - SoilMinThicknessminimum soil thickness [mm] (equal to SoilThickness) - Mmodel parameter [mm] that controls exponential decline of KsatVer with soil depth

(fitted with curve_fit (scipy.optimize)), bounds of M are checked - M_ : model parameter [mm] that controls exponential decline of KsatVer with soil depth (fitted with numpy linalg regression), bounds of M_ are checked - M_original : M without checking bounds - M_original_ : M_ without checking bounds - c_0 : Brooks Corey coefficient [-] based on pore size distribution index at depth

1st soil layer (100 mm) wflow_sbm - c_1 : idem c_0 at depth 2nd soil layer (400 mm) wflow_sbm - c_2 : idem c_0 at depth 3rd soil layer (1200 mm) wflow_sbm - c_3 : idem c_0 at depth 4th soil layer (> 1200 mm) wflow_sbm - KsatVer_[z]cm : KsatVer [mm/day] at soil depths [z] of SoilGrids data [0.0, 5.0, 15.0, 30.0, 60.0, 100.0, 200.0]

Parameters

• ds (xarray.Dataset) – Dataset containing soil properties.

• ds_like (xarray.DataArray) – Dataset at model resolution.

• ptfKsatVer (str) – PTF to use for calculcation KsatVer.

Returns

ds_out – Dataset containing gridded soil parameters.

Return type

xarray.Dataset