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How to account for particle size effects in a landscape evolution model when there is a wide range of particle sizes
Surface mining irreversibly disturbs the landscape. A first order priority is to establish an erosionally stable landscape. Soil and surface material particle size has a strong influence on soil erosion and a number of erosion models have been developed based on the relationship with particle size....
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Published in: | Environmental modelling & software : with environment data news 2020-02, Vol.124, p.104582, Article 104582 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Surface mining irreversibly disturbs the landscape. A first order priority is to establish an erosionally stable landscape. Soil and surface material particle size has a strong influence on soil erosion and a number of erosion models have been developed based on the relationship with particle size. Here we highlight the practicalities of assessing material particle size for a post-mining landscape. In particular, the CAESAR-Lisflood landscape evolution model (the focus here) requires a defined material particle size as input. A key feature which differentiates CAESAR-Lisflood is the ability to apply particle size data at the same resolution as the digital elevation model (DEM) representing the landform surface. Here we develop particle size distributions and demonstrate how they influence erosion for a potential post-mining landform. Field data from the site demonstrates that material particle size distribution changes little over a ten year period and yet a strong influence on erosion rates.
•Computer models can greatly improve mine site rehabilitation.•Surface material particle size has a strong influence on soil erosion.•We show that particle size a strong influence on erosion rates.•Particle size is an important factor for model input.•Model predictions compare well to other independent data. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2019.104582 |