eSCAPE: Regional to Global Scale Landscape Evolution Model v2.0

Author:

Salles TristanORCID

Abstract

Abstract. The eSCAPE model is a Python-based landscape evolution model that simulates over geological time (1) the dynamics of the landscape, (2) the transport of sediment from source to sink, and (3) continental and marine sedimentary basin formation under different climatic and tectonic conditions. The eSCAPE model is open-source, cross-platform, distributed under the GPLv3 licence, and available on GitHub (http://escape.readthedocs.io, last access: 23 September 2019). Simulated processes rely on a simplified mathematical representation of landscape processes – the stream power and creep laws – to compute Earth's surface evolution by rivers and hillslope transport. The main difference with previous models is in the underlying numerical formulation of the mathematical equations. The approach is based on a series of implicit iterative algorithms defined in matrix form to calculate both drainage area from multiple flow directions and erosion–deposition processes. The eSCAPE model relies on the PETSc parallel library to solve these matrix systems. Along with the description of the algorithms, examples are provided to illustrate the model current capabilities and limitations. It is the first landscape evolution model able to simulate processes at the global scale and is primarily designed to address problems on large unstructured grids (several million nodes).

Publisher

Copernicus GmbH

Reference89 articles.

1. Ahrens, J., Jourdain, S., O'Leary, P., Patchett, J., Rogers, D. H., and Petersen, M.: An image-based approach to extreme scale in situ visualization and analysis, Proceedings of the International Conference for High Performance Computing, https://doi.org/10.1109/SC.2014.40, 2014. a

2. Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis., NOAA Technical Memorandum NESDIS NGDC-24, 19 pp., available at: http://www.ngdc.noaa.gov/mgg/global/global.html (last access: 23 September 2019), 2009. a

3. Armitage, J. J.: Short communication: flow as distributed lines within the landscape, Earth Surf. Dynam., 7, 67–75, https://doi.org/10.5194/esurf-7-67-2019, 2019. a, b, c, d

4. Balay, S., Brown, J., Buschelman, K., Gropp, W. D., Kaushik, D., Knepley, M. G., McInnes, L. C., Smith, B. F., and Zhang, H.: Argonne National Laboratory, PETSc, available at: http://www.mcs.anl.gov/petsc (last access: 23 September 2019), 2012. a, b, c

5. Barnes, R.: Parallel non-divergent flow accumulation for trillion cell digital elevation models on desktops or clusters, Environ. Model. Softw., 92, 202–212, https://doi.org/10.1016/j.envsoft.2017.02.022, 2017. a, b

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3