diff --git a/docs/changelog.rst b/docs/changelog.rst
index 7569adff..3c950911 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -21,6 +21,7 @@ New
 - `SfincsModel.setup_cn_infiltration_with_kr` to setup three layers related to the curve number (maximum and effective infiltration capacity; seff and smax) and recovery rate (kr). PR#87
 - `SfincsModelsetup_drainage_structures` to setup drainage structures (pumps,culverts) from a geodataframe. PR#90
 - Added `SfincsModel.setup_wind_forcing`, `SfincsModel.setup_wind_forcing_from_grid` and `SfincsModel.setup_pressure_forcing_from_grid` methods to easily add wind and pressure forcing.  PR #92
+- Added the option to use landuse/landcover data combined with a reclass table to `SfincsModel.setup_constant_infiltration`.  PR #103
 - Enabled to provide locations only (so no timeseries) for `SfincsModel.setup_waterlevel_forcing` and `SfincsModel.setup_discharge_forcing` PR #104
 - New optional buffer argument in  `SfincsModel.setup_discharge_forcing` to select gauges around boundary only. PR #104
 
diff --git a/hydromt_sfincs/sfincs.py b/hydromt_sfincs/sfincs.py
index 62a32fdc..8ce4312c 100644
--- a/hydromt_sfincs/sfincs.py
+++ b/hydromt_sfincs/sfincs.py
@@ -939,7 +939,13 @@ def setup_river_outflow(
             self.set_geoms(gdf_riv, name="rivers_outflow")
 
     # Function to create constant spatially varying infiltration
-    def setup_constant_infiltration(self, qinf, reproj_method="average"):
+    def setup_constant_infiltration(
+        self,
+        qinf=None,
+        lulc=None,
+        reclass_table=None,
+        reproj_method="average",
+    ):
         """Setup spatially varying constant infiltration rate (qinffile).
 
         Adds model layers:
@@ -950,16 +956,48 @@ def setup_constant_infiltration(self, qinf, reproj_method="average"):
         ----------
         qinf : str, Path, or RasterDataset
             Spatially varying infiltration rates [mm/hr]
+        lulc: str, Path, or RasterDataset
+            Landuse/landcover data set
+        reclass_table: str, Path, or pd.DataFrame
+            Reclassification table to convert landuse/landcover to infiltration rates [mm/hr]
         reproj_method : str, optional
             Resampling method for reprojecting the infiltration data to the model grid.
             By default 'average'. For more information see, :py:meth:`hydromt.raster.RasterDataArray.reproject_like`
         """
 
         # get infiltration data
-        da_inf = self.data_catalog.get_rasterdataset(qinf, geom=self.region, buffer=10)
-        da_inf = da_inf.raster.mask_nodata()  # set nodata to nan
+        if qinf is not None:
+            da_inf = self.data_catalog.get_rasterdataset(
+                qinf,
+                bbox=self.mask.raster.transform_bounds(4326),
+                buffer=10,
+            )
+        elif lulc is not None:
+            # landuse/landcover should always be combined with mapping
+            if reclass_table is None:
+                raise IOError(
+                    f"Infiltration mapping file should be provided for {lulc}"
+                )
+            da_lulc = self.data_catalog.get_rasterdataset(
+                lulc,
+                bbox=self.mask.raster.transform_bounds(4326),
+                buffer=10,
+                variables=["lulc"],
+            )
+            df_map = self.data_catalog.get_dataframe(
+                reclass_table,
+                variables=["qinf"],
+                index_col=0,  # driver kwargs
+            )
+            # reclassify
+            da_inf = da_lulc.raster.reclassify(df_map)["qinf"]
+        else:
+            raise ValueError(
+                "Either qinf or lulc must be provided when setting up constant infiltration."
+            )
 
         # reproject infiltration data to model grid
+        da_inf = da_inf.raster.mask_nodata()  # set nodata to nan
         da_inf = da_inf.raster.reproject_like(self.mask, method=reproj_method)
 
         # check on nan values