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NAME

r.hazard.flood - Fast procedure to detect flood prone areas.

KEYWORDS

raster, hydrology

SYNOPSIS

r.hazard.flood
r.hazard.flood --help
r.hazard.flood map=elevation flood=flood mti=MTI [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

--overwrite
Allow output files to overwrite existing files
--help
Print usage summary
--verbose
Verbose module output
--quiet
Quiet module output
--ui
Force launching GUI dialog

Parameters:

map=elevation [required]
Name of elevation raster map
flood=flood [required]
Name of output flood raster map
mti=MTI [required]
Name of output MTI raster map
Name of the output Modified Topographic Index (MTI) raster map

Table of contents

DESCRIPTION

r.hazard.flood is an implementation of a fast procedure to detect flood prone areas. It is based on a simple procedure that exploits the correlation between flood exposure and a Modified Topographic Index (MTI), calculated on the basis of the DTM and strongly influenced by the resolution of this latter.

Important:

Before running the program, the region should be aligned perfectly with the input map. The cell size taken in consideration is the one specified in the region settings. If it doesn't match with the elevation map, the result is nonsense. Note that this program only supports projected coordinate systems, LatLong is not supported.

NOTES

The availability of new technologies for the measurement of surface elevation has addressed the lack of high resolution elevation data, and this has led to an increase in the attraction of DEM-based automated procedures for hydrological applications including the delineation of floodplains. In particular, the exposure to flooding may be delineated quite well by adopting a modified topographic index (TIm) computed from a DEM. The comparison between TIm and flood inundation maps (obtained from hydraulic simulations) shows that the portion of a basin exposed to flood inundation is generally characterized by a TIm higher than a given threshold, tau. This allows the development of a simple procedure for the identification of flood prone areas that requires only two parameters for the calibration: the threshold tau and the exponent of TIm. Because the topographic index is sensitive to the spatial resolution of the digital elevation model, the threshold is automatically determinated from the cellsize.

The proposed procedure may help in the delineation of flood prone areas especially in basins with marked topography. The method is sensitive to the DEM resolution, but a cell size of ~100m is sufficient to reach good performances for the catchments investigated here. The procedure is also tested adopting DEMs from different sources, such as the shuttle radar topography mission (SRTM) DEM, ASTER GDEM, and national elevation data. This experiment highlights the reliability with the SRTM DEM for the delineation of flood prone areas. A useful relationship between model parameters and the reference scale of the DEM was also obtained providing a strategy for the application of this method in different contexts.

The use of the modified topographic index should not be considered as an alternative to standard hydrological-hydraulic simulations for flood mapping, but it may represent a useful and rapid tool for a preliminary delineation of flooding areas in ungauged basins and in areas where expensive and time consuming hydrological-hydraulic simulations are not affordable or economically convenient.

EXAMPLE

g.region raster=elevation -ap
r.hazard.flood map=elevation flood=flood mti=mti

Dependencies

r.area

CITE AS

Di Leo M., Manfreda S., Fiorentino M., An automated procedure for the detection of flood prone areas: r.hazard.flood, Geomatics Workbooks n.10, 2011. (PDF)

REFERENCES

Manfreda S., Di Leo M., Sole A., Detection of Flood Prone Areas using Digital Elevation Models, Journal of Hydrologic Engineering, (10.1061/(ASCE)HE.1943-5584.0000367), 2011.

AUTHOR

Margherita Di Leo (dileomargherita AT gmail DOT com)

SOURCE CODE

Available at: r.hazard.flood source code (history)

Latest change: Monday Jan 30 19:52:26 2023 in commit: cac8d9d848299297977d1315b7e90cc3f7698730


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