SAGA-GIS Tool Library Documentation (v7.2.0)

Tool Fill Sinks (Wang & Liu)

This tool uses an algorithm proposed by Wang & Liu to identify and fill surface depressions in digital elevation models.
The method was enhanced to allow the creation of hydrologic sound elevation models, i.e. not only to fill the depression(s) but also to preserve a downward slope along the flow path. If desired, this is accomplished by preserving a minimum slope gradient (and thus elevation difference) between cells.
This is the fully featured version of the tool creating a depression less DEM, a flow path grid and a grid with watershed basins. If you encounter problems processing large data sets (e.g. LIDAR data) with this tool try the basic version (Fill Sinks XXL).


References:
Wang, L. & H. Liu (2006): An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling. International Journal of Geographical Information Science, Vol. 20, No. 2: 193-213.

Parameters

 NameTypeIdentifierDescriptionConstraints
InputDEMGrid (input)ELEVDigital elevation model-
OutputFilled DEMGrid (output)FILLEDDepression-free digital elevation model-
Flow DirectionsGrid (output)FDIRComputed flow directions, 0=N, 1=NE, 2=E, ... 7=NW-
Watershed BasinsGrid (output)WSHEDDelineated watershed basins-
OptionsGrid systemGrid systemPARAMETERS_GRID_SYSTEM--
Minimum Slope [Degree]Floating pointMINSLOPEMinimum slope gradient to preserve from cell to cell; with a value of zero sinks are filled up to the spill elevation (which results in flat areas). Unit [Degree]Minimum: 0.000000
Default: 0.100000

Command-line

Usage: saga_cmd ta_preprocessor 4 [-ELEV <str>] [-FILLED <str>] [-FDIR <str>] [-WSHED <str>] [-MINSLOPE <double>]
  -ELEV:<str>       	DEM
	Grid (input)
  -FILLED:<str>     	Filled DEM
	Grid (output)
  -FDIR:<str>       	Flow Directions
	Grid (output)
  -WSHED:<str>      	Watershed Basins
	Grid (output)
  -MINSLOPE:<double>	Minimum Slope [Degree]
	Floating point
	Minimum: 0.000000
	Default: 0.100000