Articles | Volume 7, issue 3
Earth Surf. Dynam., 7, 737–753, 2019
Earth Surf. Dynam., 7, 737–753, 2019
Research article
22 Aug 2019
Research article | 22 Aug 2019

Computing water flow through complex landscapes – Part 1: Incorporating depressions in flow routing using FlowFill

Kerry L. Callaghan and Andrew D. Wickert

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Cited articles

Abdullah, A. F., Vojinovic, Z., Price, R. K., and Aziz, N. A. A.: Improved methodology for processing raw LiDAR data to support urban flood modelling – accounting for elevated roads and bridges, J. Hydroinform., 14, 253–269,, 2012. a
Abedini, M. J., Dickinson, W. T., and Rudra, R. P.: On depressional storages: The effect of DEM spatial resolution, J. Hydrol., 318, 138–150,, 2006. a, b
Adams, J. M., Gasparini, N. M., Hobley, D. E. J., Tucker, G. E., Hutton, E. W. H., Nudurupati, S. S., and Istanbulluoglu, E.: The Landlab v1.0 OverlandFlow component: a Python tool for computing shallow-water flow across watersheds, Geosci. Model Dev., 10, 1645–1663,, 2017. a
Appels, W. M., Bogaart, P. W., and van der Zee, S. E.: Influence of spatial variations of microtopography and infiltration on surface runoff and field scale hydrological connectivity, Adv. Water Resour., 34, 303–313,, 2011. a
Arnold, N.: A new approach for dealing with depressions in digital elevation models when calculating flow accumulation values, Prog. Phys. Geog., 34, 781–809,, 2010. a, b
Short summary
Lakes and swales are real landscape features but are generally treated as data errors when calculating water flow across a surface. This is a problem because depressions can store water and fragment drainage networks. Until now, there has been no good generalized approach to calculate which depressions fill and overflow and which do not. We addressed this problem by simulating runoff flow across a landscape, selectively flooding depressions and more realistically connecting lakes and rivers.