Unit 16 - Flooding simulation¶
Beside DEM (see Unit 15 - Data reprojection) also river streams are required. Such data can be downloaded from OSM database similarly as done in Unit 02 - First steps in the case of Jena city region.
Note
[bbox:50.85374080,11.50084754,50.98991003,11.67463202];
(
way
["waterway"="river"];
way
["waterway"="stream"]
);
/*added by auto repair*/
(._;>;);
/*end of auto repair*/
out;
ogr2ogr -f GPKG jena_rivers.gpkg -a_srs EPSG:4326 -t_srs EPSG:32632 /vsicurl_streaming/"\
http://overpass-api.de/api/interpreter?data=%5Bbbox%3A50%2E85374080%2C11%2E50084754%2C50%2\
E98991003%2C11%2E67463202%5D%3B%28way%5B%22waterway%22%3D%22river%22%5D%3Bway%5B%22waterway\
%22%3D%22stream%22%5D%3B%29%3B%28%2E%5F%3B%3E%3B%29%3Bout%3B%0A" lines
For simplification pre-processed river streams are included in sample
dataset as geodata/osm/jena-rivers.gpkg
file.
Flooding can be easily simulated by r.lake module which fills a lake to a target water level from a given start point or seed raster. The resulting raster map contains cells with values representing lake depth (NULL for all other cells beyond the lake).
The r.lake requires seeds coordinates and water level to be defined. The coordinates can be set also interactively as Fig. 95 shows.
Height of seed point can be determined by querying DEM map layer Query raster/vector map(s) from Map Display toolbar (see Fig. 96) or directly using r.what module:
r.what map=dem coordinates=681734,5644423
Note
Before running r.lake let’s start organizing our work. Till now we used PERMANENT mapsets only. There is input data like DEM, Jena city region, cloud mask vector map, Sentinel bands, results of NDVI computation and so on. Data organization can be improved by using multiple mapsets. Let’s create a new mapset flooding in the current location jena-region. New mapset from Data tab or by g.mapset module.
Before starting computation the computation region have to be set based on dem raster map.
g.region raster=dem
r.lake elevation=dem water_level=150 lake=lake coordinates=681734,5644423