hydromt_wflow.workflows.soilgrids#

hydromt_wflow.workflows.soilgrids(ds, ds_like, ptfKsatVer, soil_fn, logger=<Logger hydromt_wflow.workflows.soilgrids (WARNING)>)[source]#

Returns soil parameter maps at model resolution based on soil properties from SoilGrids datasets. Both soilgrids 2017 and 2020 are supported. Soilgrids 2017 provides soil properties at 7 specific depths, while soilgrids_2020 provides soil properties averaged over 6 depth intervals. 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. Ref: de Sousa, L.M., Poggio, L., Batjes, N.H., Heuvelink, G., Kempen, B., Riberio, E. and Rossiter, D., 2020. SoilGrids 2.0: producing quality-assessed soil information for the globe. SOIL Discussions, pp.1-37. https://doi.org/10.5194/soil-2020-65

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 - `f : scaling parameter controlling the decline of KsatVer [mm-1] (fitted with curve_fit (scipy.optimize)), bounds are checked - f_ : scaling parameter controlling the decline of KsatVer [mm-1] (fitted with numpy linalg regression), bounds are checked - 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] - wflow_soil : USDA Soil texture based on percentage clay, silt, sand mapping: [1:Clay, 2:Silty Clay, 3:Silty Clay-Loam, 4:Sandy Clay, 5:Sandy Clay-Loam, 6:Clay-Loam, 7:Silt, 8:Silt-Loam, 9:Loam, 10:Sand, 11: Loamy Sand, 12:Sandy Loam]

Parameters:

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

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

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

  • soil_fn (str) – soilgrids version {‘soilgrids’, ‘soilgrids_2020’}

Returns:

ds_out – Dataset containing gridded soil parameters.

Return type:

xarray.Dataset