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Lookup NU author(s): Dr David MilledgeORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright © 2026 the Author(s). The deep critical zone (CZ) has long been recognized for its importance in influencing shallow landslides but was not considered feasible to include in slope stability models at the watershed scale. Here, we demonstrate that simple approximations of the CZ in a fully coupled hydrologic and soil slope stability model can effectively capture the location, timing, and likely size of shallow landslides. To achieve this, we use coupled, process-based models that incorporate the effects of 1) deep CZ structures, 2) three-dimensional transient hydrology, and 3) multidimensional slope stability, calibrated with data from an intensively monitored field site. Our results show that the hydrologically active deep CZ guides groundwater flow, influencing where it drains from or exfiltrates to the soil mantle and producing distinct patterns of soil saturation and seepage forces at the soil–bedrock boundary. A deep conductive, weathered bedrock drains the soil mantle, reducing the likelihood of destabilizing pore pressures, while the downslope thinning of the CZ forces groundwater to the surface. This pattern creates localized instability and a tendency for similar-sized landslides across the landscape. In contrast, the absence of conductive weathered bedrock results in more widespread destabilizing pore pressures, leading to larger landslides and the likelihood of landslides earlier in a storm than in landscapes underlain by a deep CZ. Our findings suggest that first-order variations of deep CZs can provide physical explanations for variations observed in the susceptibility, magnitude, and timing of shallow landslides, and that CZ structure may be inferred from patterns and timing of landsliding.
Author(s): Moon S, Formetta G, Higa JT, Busti R, Bellugi DG, Milledge DG, Ebel BA, Dietrich WE
Publication type: Article
Publication status: Published
Journal: Proceedings of the National Academy of Sciences of the United States of America
Year: 2026
Volume: 123
Issue: 12
Print publication date: 24/03/2026
Online publication date: 18/03/2026
Acceptance date: 22/01/2026
Date deposited: 14/04/2026
ISSN (print): 0027-8424
ISSN (electronic): 1091-6490
Publisher: National Academy of Sciences
URL: https://doi.org/10.1073/pnas.2524542123
DOI: 10.1073/pnas.2524542123
Data Access Statement: Previously published data and models (see article for full references) were used for this work. All data and model information are included in the article and/or SI Appendix.
PubMed id: 41849384
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