Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Publisher: Copernicus Publications
Journal: Earth Surface Dynamics
Languages: English
Types: Article
Subjects: QE, QE500-639.5, QA76, GB, GE, Dynamic and structural geology
The ability to model surface processes and to couple them to both subsurface and atmospheric regimes has proven invaluable to research in the Earth and planetary sciences. However, creating a new model typically demands a very large investment of time, and modifying an existing model to address a new problem typically means the new work is constrained to its detriment by model adaptations for a different problem. Landlab is an open-source software framework explicitly designed to accelerate the development of new process models by providing: (1) a set of tools and existing grid structures – including both regular and irregular grids – to make it faster and easier to develop new process components, or numerical implementations of physical processes; (2) a suite of stable, modular, and interoperable process components that can be combined to create an integrated model; and (3) a set of tools for data input, output, manipulation, and visualization. A set of example models built with these components is also provided. Landlab's structure makes it ideal not only for fully developed modelling applications, but also for model prototyping and classroom use. Because of its modular nature, it can also act as a platform for model intercomparison and epistemic uncertainty and sensitivity analyses. Landlab exposes a standardized model interoperability interface, and is able to couple to third party models and software. Landlab also offers tools to allow the creation of cellular automata, and allows native coupling of such models to more traditional continuous differential equation-based modules. We illustrate the principles of component coupling in Landlab using a model of landform evolution, a cellular ecohydrologic model, and a flood-wave routing model.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Adams, J. M.: landlab/pub_adams_etal_gmd v0.2 (Data set), Zenodo, doi:10.5281/zenodo.162058, 2016.
    • Adams, J. M., Nudurupati, S. S., Gasparini, N. M., Hobley, D. E. J., Hutton, E., Tucker, G. E., and Istanbulluoglu, E.: Landlab: Sustainable Software Development in Practice, The Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2), New Orleans, LA, USA, 16 November 2014, doi:10.6084/m9.figshare.1097629.v6, 2014.
    • 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 OverlandFlow component: a Python library for computing shallow-water flow across watersheds, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-277, in review, 2016.
    • ASCE-EWRI: The ASCE standardized reference evapotranspiration equation, in: Standardization of Reference Evapotranspiration Task Committee Final Report, edited by: Allen, R. G., Walter, I. A., Elliot, R. L., Howell, T. A., Itenfisu, D., Jensen, M. E., and Snyder, R. L., Technical Committee report to the Environmental and Water Resources Institute of the American Society of Civil Engineers from the Task Committee on Standardization of Reference Evapotranspiration, Reston, VA, USA, 2005.
    • Becker, C., Chitchyan, R., Duboc, L., Easterbrook, S., Penzenstadler, B., Seyff, N., and Venters, C. C.: Sustainability design and software: the karlskrona manifesto, in: IEEE/ACM 37th IEEE International Conference on Software Engineering, Florence, Italy, 16-24 May 2015, 467-476, doi:10.1109/ICSE.2015.179, 2015.
    • Berger, K. P.: Surface water-groundwater interaction: the spatial organization of hydrologic processes over complex terrain, PhD thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 242 pp., 2000.
    • Bras, R. L.: Hydrology: an introduction to hydrologic science, Addison Wesley Publishing Company, Boston, Mass., USA, 643 pp., 1990.
    • Braun, J. and Sambridge, M.: Modelling landscape evolution on geological time scales: a new method based on irregular spatial discretization, Basin Res., 9, 27-52, 1997.
    • Braun, J. and Willett, S. D.: A very efficient O(n), implicit and parallel method to solve the stream power equation governing fluvial incision and landscape evolution, Geomorphology, 180-181, 170-179, doi:10.1016/j.geomorph.2012.10.008, 2013.
    • Caracciolo, D., Noto, L. V., Istanbulluoglu, E., Fatichi, S., and Zhou, X.: Climate change and Ecotone boundaries: Insights from a cellular automata ecohydrology model in a Mediterranean catchment with topography controlled vegetation patterns, Adv. Water Resour., 73, 159-175, doi:10.1016/j.advwatres.2014.08.001, 2014.
    • Caracciolo, D., Istanbulluoglu, E., and Noto, L. V.: An Ecohydrological Cellular Automata Model Investigation of Juniper Tree Encroachment in a Western North American Landscape, Ecosystems, doi:10.1007/s10021-016-0096-6, in press, 2016a.
    • Caracciolo, D., Istanbulluoglu, E., Noto, L. V., and Collins, S. L.: Mechanisms of shrub encroachment into Northern Chihuahuan Desert grasslands and impacts of climate change investigated using a cellular automata model, Adv. Water Resour., 91, 46-62, doi:10.1016/j.advwatres.2016.03.002, 2016b.
    • Chue Hong, N.: We are the 92 %, The Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2), New Orleans, LA, USA, 16 November 2014, doi:10.6084/m9.figshare.1243288.v1, 2014.
    • Crick, T., Hall, B. A., and Ishtiaq, S.: “Can I Implement Your Algorithm?”: A Model for Reproducible Research Software, The Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2), New Orleans, LA, USA, 16 November 2014, arXiv:1407.5981v2 [cs.SE], 2014.
    • Culling, W.: Soil creep and the development of hillside slopes, J. Geol., 71, 127-161, 1963.
    • de Almeida, G. A. M., Bates, P., Freer, J. E., and Souvignet, M.: Improving the stability of a simple formulation of the shallow water equations for 2-D flood modeling, Water Resour. Res., 48, W05528, doi:10.1029/2011WR011570, 2012.
    • Dietrich, W. E., Bellugi, D. G., Sklar, L. S., Stock, J. D., Heimsath, A. M., and Roering, J. J.: Geomorphic Transport Laws for Predicting Landscape Form and Dynamics, in: Prediction in Geomorphology, Geophysical Monograph-American Geophysical Union, Washington, DC, USA, 135, 1-30, 2003.
    • Eagleson, P. S.: Climate, soil, and vegetation: 2. The distribution of annual precipitation derived from observed storm sequences, Water Resour. Res., 14, 713-721, doi:10.1029/WR014i005p00713, 1978.
    • Easterbrook, S. M.: Open code for open science?, Nat. Geosci., 7, 779-781, doi:10.1038/ngeo2283, 2014.
    • Fernandes, N. F. and Dietrich, W. E.: Hillslope evolution by diffusive processes: The timescale for equilibrium adjustments, Water Resour. Res., 33, 1307-1318, doi:10.1029/97WR00534, 1997.
    • Goren, L., Willett, S. D., Herman, F., and Braun, J.: Coupled numerical-analytical approach to landscape evolution modeling, Earth Surf. Proc. Land., 39, 522-545, doi:10.1002/esp.3514, 2014.
    • Granjeon, D. and Joseph, P.: Concepts and Applications of a 3-D Multiple Lithology, Diffusive Model in Stratigraphic Modeling, in: Numerical Experiments in Stratigraphy Recent Advances in Stratigraphic and Sedimentologic Computer Simulations, SEPM Special Publications No. 62, SEPM, Tulsa, OK, USA, 197-210, 1999.
    • Harel, M. A., Mudd, S. M., and Attal, M.: Global analysis of the stream power law parameters based on worldwide 10Be denudation rates, Geomorphology, 268, 184-196, doi:10.1016/j.geomorph.2016.05.035, 2016.
    • Harlow, F. H. and Welch, J. E.: Numerical Calculation of TimeDependent Viscous Incompressible Flow of Fluid with Free Surface, Phys. Fluids, 8, 2182-2189, 1965.
    • Hobley, D. E. J., Sinclair, H. D., Mudd, S. M., and Cowie, P. A.: Field calibration of sediment flux dependent river incision, J. Geophys. Res., 116, F04017, doi:10.1029/2010JF001935, 2011.
    • Horritt, M. S. and Bates, P. D.: Evaluation of 1D and 2D numerical models for predicting river flood inundation, J. Hydrol., 268, 87- 99, doi:10.1016/S0022-1694(02)00121-X, 2002.
    • Howard, A. D.: A detachment-limited model of drainage basin evolution, Water Resour. Res., 30, 2261-2285, 1994.
    • Howard, A. D.: Simulating the development of Martian highland landscapes through the interaction of impact cratering, fluvial erosion, and variable hydrologic forcing, Geomorphology, 91, 332-363, doi:10.1016/j.geomorph.2007.04.017, 2007.
    • Hunter, N. M., Horritt, M. S., Bates, P. D., Wilson, M. D., and Werner, M. G. F.: An adaptive time step solution for raster-based storage cell modelling of floodplain inundation, Adv. Water Resour., 28, 975-991, 2005.
    • Hutton, E. W. H. and Syvitski, J. P. M.: Sedflux 2.0: An advanced process-response model that generates threedimensional stratigraphy, Comput. Geosci., 34, 1319-1337, doi:10.1016/j.cageo.2008.02.013, 2008.
    • Hutton, E. W. H., Piper, M. D., Peckham, S. D., Overeem, I., Kettner, A. J., and Syvitski, J. P. M.: Building Sustainable Software - The CSDMS Approach, The Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2), New Orleans, LA, USA, 16 November 2014, arxiv:1407.4106v2 [cs.SE], 2014.
    • Istanbulluoglu, E., Wang, T., and Wedin, D. A.: Evaluation of ecohydrologic model parsimony at local and regional scales in a semiarid grassland ecosystem, Ecohydrology, 5, 121-142, doi:10.1002/eco.211, 2012.
    • Itasca: FLAC: fast Lagrangian analysis of continua, Version 4, Itasca Consulting Group Inc., Minneapolis, USA, 2000.
    • Jenson, S. K. and Domingue, J. O.: Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis, Photogramm. Eng. Rem. S., 54, 1593-1600, 1988.
    • Julien, P. Y., Saghafian, B., and Ogden, F. L.: Raster-based hydrologic modeling of spatially-varied surface runoff, J. Am. Water Resour. As., 31, 523-536, doi:10.1111/j.1752- 1688.1995.tb04039.x, 1995.
    • Katz, D. S., Choi, S.-C. T., Wilkins-Diehr, N., Hong, N. C., Venters, C. C., Howison, J., Seinstra, F., Jones, M., Cranston, K. A., Clune, T. L., De Val-Borro, M., and Littauer, R.: Report on the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2), Journal of Open Research Software, 4, e7, doi:10.5334/jors.85, 2015.
    • Kelfoun, K., Samaniego, P., Palacios, P., and Barba, D.: Testing the suitability of frictional behaviour for pyroclastic flow simulation by comparison with a well-constrained eruption at Tungurahua volcano (Ecuador), B. Volcanol., 71, 1057-1075, doi:10.1007/s00445-009-0286-6, 2009.
    • Kessler, M. A., Anderson, R. S., and Stock, G. M.: Modeling topographic and climatic control of east-west asymmetry in Sierra Nevada glacier length during the Last Glacial Maximum, J. Geophys. Res, 111, F02002, doi:10.1029/2005JF000365, 2006.
    • Lague, D.: The stream power river incision model: evidence, theory and beyond, Earth Surf. Proc. Land., 39, 38-61, doi:10.1002/esp.3462, 2014.
    • Laio, F., Porporato, A., Ridolfi, L., and Rodriguez-Iturbe, I.: Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress II. Probabilistic soil moisture dynamics, Adv. Water Resour., 24, 707-723, doi:10.1016/S0309- 1708(01)00005-7, 2001.
    • Lambeck, K.: Geophysical Geodesy, The Slow Deformations of the Earth, Clarendon Press, Oxford, UK, 718 pp., 1988.
    • Mitas, L. and Mitasova, H.: Distributed soil erosion simulation for effective erosion prevention, Water Resour. Res., 34, 505-516, doi:10.1029/97WR03347, 1998.
    • Narteau, C., Le Mouël, J. L., Poirier, J. P., Sepúlveda, E., and Shnirman, M.: On a small-scale roughness of the core-mantle boundary, Earth Planet. Sc. Lett., 191, 49-60, doi:10.1016/S0012- 821X(01)00401-0, 2001.
    • Narteau, C., Zhang, D., Rozier, O., and Claudin, P.: Setting the length and time scales of a cellular automaton dune model from the analysis of superimposed bed forms, J. Geophys. Res.-Earth, 114, F03006, doi:10.1029/2008JF001127, 2009.
    • NCALM: Raleigh Peak, Colorado: May 2010, CO10_Tucker (Data set), doi:10.5069/G9TM782F, 2010.
    • NSF: A vision and strategy for software for science engineering and education, available at: https://www.nsf.gov/pubs/2012/ nsf12113/nsf12113.pdf (last access: 24 November 2016), 2012.
    • Overeem, I., Berlin, M. M., and Syvitski, J. P. M.: Strategies for integrated modeling: The community surface dynamics modeling system example, Environ. Modell. Softw., 39, 314-321, doi:10.1016/j.envsoft.2012.01.012, 2013.
    • Peckham, S. D.: The CSDMS Standard Names: Cross-Domain Naming Conventions for Describing Process Models, Data Sets and Their Associated Variables, in: Proceedings of the 7th International Congress on Environmental Modelling and Software, 15-19 June 2014, San Diego, California, USA, edited by: Ames, D. P., Quinn, N. W. T., Rizzoli, A. E., ISBN: 978-88-9035-744-2, 2014.
    • Peckham, S. D., Hutton, E. W. H., and Norris, B.: A component-based approach to integrated modeling in the geosciences: The design of CSDMS, Comput. Geosci., 53, 3-12, doi:10.1016/j.cageo.2012.04.002, 2013.
    • Perron, J. T.: Numerical methods for nonlinear hillslope transport laws, J. Geophys. Res, 116, F02021, doi:10.1029/2010JF001801, 2011.
    • Perron, J. T. and Royden, L.: An integral approach to bedrock river profile analysis, Earth Surf. Proc. Land., 38, 570-576, doi:10.1002/esp.3302, 2012.
    • Piper, M., Hutton, E. W. H., Overeem, I., and Syvitski, J. P.: WMT: The CSDMS Web Modelling Tool, 2015 Fall Meeting, AGU, San Francisco, CA, USA, 14-18 December 2015, IN13B-1841, 2015.
    • Polakow, D. A. and Dunne, T. T.: Modelling fire-return interval T: stochasticity and censoring in the two-parameter Weibull model, Ecol. Model., 121, 79-102, 1999.
    • Prechelt, L.: An empirical comparison of C, CCC, Java, Perl, Python, Rexx and Tcl for a search/string-processing program, Technical Report 2000-5, University of Karlsruhe, Karlsruhe, Germany, 34 pp., 2000.
    • Rengers, F. K., McGuire, L. A., Kean, J. W., Staley, D. M., and Hobley, D.: Model simulations of flood and debris flow timing in steep catchments after wildfire, Water Resour. Res., 52, 6041- 6061, doi:10.1002/2015WR018176, 2016.
    • Slingerland, R. L. and Kump, L.: Mathematical Modeling of Earth's Dynamical Systems, Princeton University Press, Princeton, NJ, USA, 231 pp., 2011.
    • Slingerland, R. L., Harbaugh, J. W., and Furlong, K.: Simulating Clastic Sedimentary Basins: Physical Fundamentals and Computer Programs for Creating Dynamic Systems, Prentice-Hall, Englewood Cliffs, NJ, USA, 220 pp., 1994.
    • Stewart, C. A., Almes, G. T., and Wheeler, B. C. (Eds.): Cyberinfrastructure Software Sustainability and Reusability: Report from an NSF-funded workshop, Indiana University, Bloomington, IN, USA, available at: http://hdl.handle.net/2022/6701 (last access: 24 November 2016), 2010.
    • Tucker, G. E. and Bras, R. L.: A stochastic approach to modeling the role of rainfall variability in drainage basin evolution, Water Resour. Res., 36, 1953-1964, 2000.
    • Tucker, G. E. and Hancock, G. S.: Modelling landscape evolution, Earth Surf. Proc. Land., 35, 28-50, doi:10.1002/esp.1952, 2010.
    • Tucker, G. E. and Whipple, K. X.: Topographic outcomes predicted by stream erosion models: Sensitivity analysis and intermodel comparison, J. Geophys. Res, 107, 2179, doi:10.1029/2001JB000162, 2002.
    • Tucker, G. E., Lancaster, S. T., Gasparini, N. M., Bras, R. L., and Rybarczyk, S. M.: An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks, Comput. Geosci., 27, 959-973, 2001a.
    • Tucker, G. E., Lancaster, S. T., Gasparini, N. M., and Bras, R. L.: The Channel-Hillslope Integrated Landscape Development Model (CHILD), in: Landscape Erosion and Evolution Modeling, Springer US, Boston, MA, USA, 349-388, 2001b.
    • Tucker, G. E., Hobley, D. E. J., Hutton, E., Gasparini, N. M., Istanbulluoglu, E., Adams, J. M., and Nudurupati, S. S.: CellLab-CTS 2015: continuous-time stochastic cellular automaton modeling using Landlab, Geosci. Model Dev., 9, 823-839, doi:10.5194/gmd-9-823-2016, 2016.
    • van Rossum, G. and Drake, F. L.: Python reference manual, available at: http://www.python.org (last access: 24 November 2016), 2001.
    • Whipple, K. X. and Tucker, G. E.: Dynamics of the stream-power river incision model: Implications for height limits of mountain ranges, landscape response timescales and research needs, J. Geophys. Res, 104, 17661-17674, 1999.
    • Wickert, A. D.: Open-source modular solutions for flexural isostasy: gFlex v1.0, Geosci. Model Dev., 9, 997-1017, doi:10.5194/gmd9-997-2016, 2016.
    • Willgoose, G., Bras, R. L., and Rodriguez-Iturbe, I.: A coupled channel network growth and hillslope evolution model: 1. Theory, Water Resour. Res., 27, 1671-1684, doi:10.1029/91WR00935, 1991a.
    • Willgoose, G., Bras, R. L., and Rodriguez-Iturbe, I.: A coupled channel network growth and hillslope evolution model: 2. Nondimensionalization and applications, Water Resour. Res., 27, 1685-1696, doi:10.1029/91WR00936, 1991b.
    • Wobus, C. W., Whipple, K. X., Kirby, E., Snyder, N. P., Johnson, J., Spyropolou, K., Crosby, B. T., and Sheenan, D.: Tectonics from topography: Procedures, promise, and pitfalls, in: Tectonics, Climate, and Landscape Evolution, edited by: Willett, S. D., Hovius, N., Brandon, M. T., and Fisher, D., Geological Society of America Special Paper 398, Geological Society of America, Boulder, CO, USA, 55-74, 2006.
    • Zhou, X., Istanbulluoglu, E., and Vivoni, E. R.: Modeling the ecohydrological role of aspect-controlled radiation on tree-grass-shrub coexistence in a semiarid climate, Water Resour. Res., 49, 2872- 2895, doi:10.1002/wrcr.20259, 2013.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

    Title Trust
  • No similar publications.
  • BioEntity Site Name

Share - Bookmark

Funded by projects

  • NSF | Collaborative Research: SI2...
  • NSF | Collaborative Research: SI2...
  • NSF | Collaborative Research: SI2...
  • NSF | Collaborative Research: SI2...
  • NSF | Collaborative Research: SI2...
  • NSF | Collaborative Research: SI2...
  • NSF | National Center for Earth-s...

Cite this article