Retaining Relative Height Information: An Enhanced Technique for Depression Treatment in Digital Elevation Models

This study presents an enhanced variant of the priority-flood based algorithm proposed by Wang and Liu for treating depressions in digital elevation models (DEMs). The enhanced variant redefines spill elevation, the key concept of the original algorithm, as the lowest elevation that a pixel needs to...

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Bibliographic Details
Main Authors: Bo Chen, Chunying Ma, Yao Xiao, Hanxin Gao, Peijun Shi, Jing Zheng
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/13/23/3347
Description
Summary:This study presents an enhanced variant of the priority-flood based algorithm proposed by Wang and Liu for treating depressions in digital elevation models (DEMs). The enhanced variant redefines spill elevation, the key concept of the original algorithm, as the lowest elevation that a pixel needs to have to ensure a non-ascending path toward the border of the DEM, plus the larger of a small number (~0.001) and the difference between the unaltered elevation values of the focal pixel and its immediate downhill neighbor. This redefinition is adopted to obtain an intermediate elevation surface to direct flow and ultimately to carve the original DEM. Each carving starts from a depression bottom and propagates downstream until a downhill cell is guaranteed in the original DEM. Tests of these algorithms on a complex terrain of the 260,000 km<sup>2</sup> Sichuan structural basin in China shows that the enhanced algorithm maximally preserves the original flow directions and extracts realistic drainage networks. Retaining the relative heights, and therefore flow directions, of cells within depressions allows the new algorithm to offer a depressionless DEM with small modification of its origin for further hydrologic applications. The enhanced depression treatment algorithm is provided as the freely available tool BNUSinkRemv.
ISSN:2073-4441