Articles | Volume 9, issue 1
Earth Surf. Dynam., 9, 105–121, 2021
Earth Surf. Dynam., 9, 105–121, 2021

Research article 02 Mar 2021

Research article | 02 Mar 2021

Computing water flow through complex landscapes – Part 3: Fill–Spill–Merge: flow routing in depression hierarchies

Richard Barnes et al.

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Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations
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Cross-cutting themes: Quantitative and statistical methods in Earth surface dynamics
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Cited articles

Agenis-Nevers, M., Bokde, N. D., Yaseen, Z. M., and Shende, M.: GuessCompx: An empirical complexity estimation in R, arXiv [preprint], arXiv:1911.01420v1, 2019. a
Arnold, N.: A new approach for dealing with depressions in digital elevation models when calculating flow accumulation values, Prog. Phys. Geogr., 34, 781–809,, 2010. a
Barnes, R.: Parallel non-divergent flow accumulation for trillion cell digital elevation models on desktops or clusters, Environ. Modell. Softw., 92, 202–212,, 2017. a, b
Barnes, R.: r-barnes/richdem: Zenodo DOI Release, Software, Zenodo,, 2018. a
Barnes, R.: Accelerating a fluvial incision and landscape evolution model with parallelism, Geomorphology, 330, 28–39,, 2019. a, b
Short summary
Existing ways of modeling the flow of water amongst landscape depressions such as swamps and lakes take a long time to run. However, as our previous work explains, depressions can be quickly organized into a data structure – the depression hierarchy. This paper explains how the depression hierarchy can be used to quickly simulate the realistic filling of depressions including how they spill over into each other and, if they become full enough, how they merge into one another.