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Computational approaches for modelling soil water repellency: A comprehensive review

delete2026-08-10
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OA
AI
M
Muntasir Hasan Kanchan
D
David J. Henry
R
R.J. Harper
F
Ferdous Sohel *
DOI：10.1016/j.compag.2026.112283delete
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Abstract

Abstract

En 中文
• This paper reviews computational approaches for soil water repellency modelling. • It provides a taxonomy of such techniques for thorough analysis. • It synthesises statistical, machine/deep learning methods for SWR prediction. • It captures soil, climate, remote sensing, and management data for field-scale SWR assessment. • It analyses feature extraction, spatiotemporal modelling, and performance metrics.
Keywords:
Non-wetting soil
Artificial intelligence
Machine learning
Distribution
Deep learning
Statistical analysis

Journal

Computers and Electronics in Agriculture cover
Computers and Electronics in Agriculture
IF:
8.9
Papers:
9.9K
Citations:
4.8W

Organization

M
Murdoch University
Scholars:
5.2K
Papers: 5.3K
Citations: 8.4K
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