Peter Lehmann

ETH Zurich

Switzerland

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Articles (10)

Year:

2025

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2022

Year:

2022

Collaborators (5)

Christian Hauck

Professor

University of Fribourg

SWITZERLAND

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Jürg Schweizer

Head of institute

SWITZERLAND

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Dani Or

Professor of Soil and Environmental Physics

ETH-Bereich Hochschulen

SWITZERLAND

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Sara Bonetti

Assistant Professor

École Polytechnique Fédérale de Lausanne

SWITZERLAND

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Jordan Aaron

Prof. Dr. at ETH Zürich

ETH Zürich

SWITZERLAND

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Peter Lehmann

Research Interests

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Articles (10)

Optimising landslide initiation modelling with high-resolution saturation prediction based on soil moisture monitoring data

In situ soil moisture data improve precipitation-based shallow landslide early warning through innovative machine learning methods

The source, quantity, and spatial distribution of interfacial water during glide-snow avalanche release: experimental evidence from field monitoring

Analytical model for bare soil evaporation dynamics following wetting with concurrent internal drainage

Glide-snow avalanches: a mechanical, threshold-based release area model

Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks

Impact of topography on in situ soil wetness measurements for regional landslide early warning – a case study from the Swiss Alpine Foreland

Global Mapping of Potential and Climatic Plant‐Available Soil Water

Vegetation‐Promoted Soil Structure Inhibits Hydrologic Landslide Triggering and Alters Carbon Fluxes

Global Mapping of Soil Water Characteristics Parameters— Fusing Curated Data with Machine Learning and Environmental Covariates

Collaborators (5)

Christian Hauck

Jürg Schweizer

Dani Or

Sara Bonetti

Jordan Aaron

Make your next move.

Peter Lehmann

Research Interests

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Contact this professor

Articles (10)

Optimising landslide initiation modelling with high-resolution saturation prediction based on soil moisture monitoring data

In situ soil moisture data improve precipitation-based shallow landslide early warning through innovative machine learning methods

The source, quantity, and spatial distribution of interfacial water during glide-snow avalanche release: experimental evidence from field monitoring

Analytical model for bare soil evaporation dynamics following wetting with concurrent internal drainage

Glide-snow avalanches: a mechanical, threshold-based release area model

Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks

Impact of topography on in situ soil wetness measurements for regional landslide early warning – a case study from the Swiss Alpine Foreland

Global Mapping of Potential and Climatic Plant‐Available Soil Water

Vegetation‐Promoted Soil Structure Inhibits Hydrologic Landslide Triggering and Alters Carbon Fluxes

Global Mapping of Soil Water Characteristics Parameters&mdash; Fusing Curated Data with Machine Learning and Environmental Covariates

Collaborators (5)

Christian Hauck

Jürg Schweizer

Dani Or

Sara Bonetti

Jordan Aaron

Make your next move.

Global Mapping of Soil Water Characteristics Parameters— Fusing Curated Data with Machine Learning and Environmental Covariates