Articles | Volume 8, issue 2
Earth Surf. Dynam., 8, 431–445, 2020
https://doi.org/10.5194/esurf-8-431-2020
Earth Surf. Dynam., 8, 431–445, 2020
https://doi.org/10.5194/esurf-8-431-2020

Research article 02 Jun 2020

Research article | 02 Jun 2020

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

Richard Barnes et al.

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Cited articles

Akiba, T.: Software: Radix-Heap, Commit f54eba0a19782c67a9779c28263a7ce680995eda, available at: https://github.com/iwiwi/radix-heap (last access: 20 May 2020), 2015. a, b
Arnold, N.: A new approach for dealing with depressions in digital elevation models when calculating flow accumulation values, Prog. Phys. Geog., 34, 781–809, https://doi.org/10.1177/0309133310384542, 2010. a, b
Barnes, R.: Parallel Priority-Flood Depression Filling For Trillion Cell Digital Elevation Models On Desktops Or Clusters, Comput. Geosci., 96, 56–68, https://doi.org/10.1016/j.cageo.2016.07.001, 2016a. a
Barnes, R.: RichDEM: Terrain Analysis Software, Zenodo, https://doi.org/10.5281/zenodo.1295618, 2016b. a
Barnes, R. and Callaghan, K.: Depression Hierarchy Source Code, Zenodo, https://doi.org/10.5281/zenodo.3238558, 2019. a, b, c
Short summary
Maps of elevation are used to help predict the flow of water so we can better understand landslides, floods, and global climate change. However, modeling the flow of water is difficult when elevation maps include swamps, lakes, and other depressions. This paper explains a new method that overcomes these difficulties, allowing models to run faster and more accurately.