Computing water flow through complex landscapes – Part&nbsp;2: Finding hierarchies in depressions and morphological segmentations

Barnes, Richard; Callaghan, Kerry L.; Wickert, Andrew D.

doi:10.5194/esurf-8-431-2020

Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations

Journal Article · Tue Jun 02 00:00:00 EDT 2020 · Earth Surface Dynamics (Online)

DOI:https://doi.org/10.5194/esurf-8-431-2020· OSTI ID:1631479

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Depressions – inwardly draining regions of digital elevation models – present difficulties for terrain analysis and hydrological modeling. Analogous “depressions” also arise in image processing and morphological segmentation, where they may represent noise, features of interest, or both. Here we provide a new data structure – the depression hierarchy – that captures the full topologic and topographic complexity of depressions in a region. We treat depressions as networks in a way that is analogous to surface-water flow paths, in which individual sub-depressions merge together to form meta-depressions in a process that continues until they begin to drain externally. This hierarchy can be used to selectively fill or breach depressions or to accelerate dynamic models of hydrological flow. Complete, well-commented, open-source code and correctness tests are available on GitHub and Zenodo.

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Research Organization:: Krell Institute, Ames, IA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: FG02-97ER25308

OSTI ID:: 1631479

Alternate ID(s):: OSTI ID: 1800917

Journal Information:: Earth Surface Dynamics (Online), Journal Name: Earth Surface Dynamics (Online) Journal Issue: 2 Vol. 8; ISSN 2196-632X

Publisher:: Copernicus Publicatons, EGUCopyright Statement

Country of Publication:: Germany

Language:: English

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