Articles | Volume 15, issue 4
Model description paper
 | Highlight paper
17 Feb 2022
Model description paper | Highlight paper |  | 17 Feb 2022

CSDMS: a community platform for numerical modeling of Earth surface processes

Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Benjamin Campforts, Tian Gan, Katherine R. Barnhart, Albert J. Kettner, Irina Overeem, Scott D. Peckham, Lynn McCready, and Jaia Syvitski

Related authors

Snow dune growth increases polar heat fluxes
Kelly Kochanski, Gregory Tucker, and Robert Anderson
The Cryosphere Discuss.,,, 2021
Manuscript not accepted for further review
Short summary
Short communication: Landlab v2.0: a software package for Earth surface dynamics
Katherine R. Barnhart, Eric W. H. Hutton, Gregory E. Tucker, Nicole M. Gasparini, Erkan Istanbulluoglu, Daniel E. J. Hobley, Nathan J. Lyons, Margaux Mouchene, Sai Siddhartha Nudurupati, Jordan M. Adams, and Christina Bandaragoda
Earth Surf. Dynam., 8, 379–397,,, 2020
Short summary
River patterns reveal two stages of landscape evolution at an oblique convergent margin, Marlborough Fault System, New Zealand
Alison R. Duvall, Sarah A. Harbert, Phaedra Upton, Gregory E. Tucker, Rebecca M. Flowers, and Camille Collett
Earth Surf. Dynam., 8, 177–194,,, 2020
Short summary
The evolution of snow bedforms in the Colorado Front Range and the processes that shape them
Kelly Kochanski, Robert S. Anderson, and Gregory E. Tucker
The Cryosphere, 13, 1267–1281,,, 2019
Short summary
Terrainbento 1.0: a Python package for multi-model analysis in long-term drainage basin evolution
Katherine R. Barnhart, Rachel C. Glade, Charles M. Shobe, and Gregory E. Tucker
Geosci. Model Dev., 12, 1267–1297,,, 2019
Short summary

Related subject area

Earth and space science informatics
SHAFTS (v2022.3): a deep-learning-based Python package for simultaneous extraction of building height and footprint from sentinel imagery
Ruidong Li, Ting Sun, Fuqiang Tian, and Guang-Heng Ni
Geosci. Model Dev., 16, 751–778,,, 2023
Short summary
Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI
Feng Yin, Philip E. Lewis, and Jose L. Gómez-Dans
Geosci. Model Dev., 15, 7933–7976,,, 2022
Short summary
A methodological framework for improving the performance of data-driven models, a case study for daily runoff prediction in the Maumee domain, U.S.
Yao Hu, Chirantan Ghosh, and Siamak Malakpour-Estalaki
EGUsphere,,, 2022
Short summary
Twenty-five years of the IPCC Data Distribution Centre at the DKRZ and the Reference Data Archive for CMIP data
Martina Stockhause and Michael Lautenschlager
Geosci. Model Dev., 15, 6047–6058,,, 2022
Short summary
Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion
Daiane Iglesia Dolci, Felipe A. G. Silva, Pedro S. Peixoto, and Ernani V. Volpe
Geosci. Model Dev., 15, 5857–5881,,, 2022
Short summary

Cited articles

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, b
Addor, N. and Melsen, L.: Legacy, rather than adequacy, drives the selection of hydrological models, Water Resour. Res., 55, 378–390,, 2019. a
Adorf, C. S., Ramasubramani, V., Anderson, J. A., and Glotzer, S. C.: How to professionally develop reusable scientific software – And when not to, Comput. Sci. Eng., 21, 66–79, 2018. a
Ahalt, S., Band, L., Christopherson, L., Idaszak, R., Lenhardt, C., Minsker, B., Palmer, M., Shelley, M., Tiemann, M., and Zimmerman, A.: Water Science Software Institute: Agile and open source scientific software development, Comput. Sci. Eng., 16, 18–26, 2014. a
AlNoamany, Y. and Borghi, J. A.: Towards computational reproducibility: researcher perspectives on the use and sharing of software, PeerJ Comput. Sci., 4, e163,, 2018. a, b
Short summary
Scientists use computer simulation models to understand how Earth surface processes work, including floods, landslides, soil erosion, river channel migration, ocean sedimentation, and coastal change. Research benefits when the software for simulation modeling is open, shared, and coordinated. The Community Surface Dynamics Modeling System (CSDMS) is a US-based facility that supports research by providing community support, computing tools and guidelines, and educational resources.