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Extraction of cross sections from digital elevation model for one‐dimensional dam‐break wave propagation in mountain valleys
Author(s) -
Pilotti Marco
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr017017
Subject(s) - thalweg , digital elevation model , geology , sinuosity , cross section (physics) , elevation (ballistics) , process (computing) , channel (broadcasting) , bathymetry , computer science , geometry , algorithm , geomorphology , remote sensing , mathematics , oceanography , physics , quantum mechanics , sediment , operating system , computer network
Shallow Water Equations (SWE) provide a fundamental component for the quantification and mapping of hydraulic hazard. In steep mountain valleys, the use of one‐dimensional SWE (also known as St. Venant Equations, SVE) is often legitimate and computationally competitive against two‐dimensional solvers. However, in the same environment, the solution of SVE is hindered by the need of an accurate bathymetric reconstruction, which implies a number of cross sections which cannot be readily acquired by conventional field surveys. On the other hand, Digital Elevation Models ( DEM ) with resolution adequate for studies of flood propagation are available in many areas of the world. In this paper, I propose to compute cross sections automatically by operating along the channel network derived from a valley's raster DEM , on the basis of algorithms that hitherto have been used for geomorphological and hydrological purposes. The extraction process can be refined by varying cross section inter‐distance and width, in order to prevent superimpositions that might occur due to the sinuosity of the thalweg and to better capture the valley's local topography. At the end of this process, the geometric functions needed by SVE solvers can be computed for each cross section. A software tool that implements the described algorithm is provided to the scientific community.

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