ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0)

Glacier thickness plays a fundamental role in understanding ice dynamics, hydrological resources, and glacial hazards. Currently, ice thickness inversion models based on shallow ice approximation (SIA) have achieved significant progress in regional and global studies of glacier thickness and volume. However, these methods simplify the parameterization of basal sliding, introducing uncertainties and significant biases in thickness estimates. Here, we present an improved ice thickness estimation approach through the integration of basal sliding law into laminar flow equation, termed the Ice Thickness Model considering Sliding Law (ITMSL). We apply and evaluate the model's performance and limitations across High Mountain Asia (HMA), a region characterized by complex topography and data scarcity. The model enables automated large-scale ice thickness reconstruction while simultaneously determining basal sliding velocities and subglacial topography. Validation against ground-penetrating radar (GPR) measurements on 16 glaciers shows that, compared to existing laminar flow equation-based models Gantayat (Gantayat et al., 2014) and Millan (Millan et al., 2022), ITMSL achieves better performance, with accuracy improved by 20.62 % and 32.65 %, respectively. This study has demonstrated that ITMSL provides an improvement over previous methods, offering new insights for ice thickness modeling and its application in data-sparse high mountain regions.

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Publication Details

Journal
Geoscientific model development
Published
2026-09-22
DOI
https://doi.org/10.5194/gmd-19-8939-2026
Primary Topic
Cryospheric studies and observations
Type
article
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article

ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0)

Liming Jiang, Yuxuan Wu, Xiaoguang Pang, Yi Liu et al.
Geoscientific model development
Cryospheric studies and observations
article

ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0)

Liming Jiang, Yuxuan Wu, Xiaoguang Pang, Yi Liu, Xiaoen Li, Xi Lu, Tingting Yao
article en

Abstract

Glacier thickness plays a fundamental role in understanding ice dynamics, hydrological resources, and glacial hazards. Currently, ice thickness inversion models based on shallow ice approximation (SIA) have achieved significant progress in regional and global studies of glacier thickness and volume. However, these methods simplify the parameterization of basal sliding, introducing uncertainties and significant biases in thickness estimates. Here, we present an improved ice thickness estimation approach through the integration of basal sliding law into laminar flow equation, termed the Ice Thickness Model considering Sliding Law (ITMSL). We apply and evaluate the model's performance and limitations across High Mountain Asia (HMA), a region characterized by complex topography and data scarcity. The model enables automated large-scale ice thickness reconstruction while simultaneously determining basal sliding velocities and subglacial topography. Validation against ground-penetrating radar (GPR) measurements on 16 glaciers shows that, compared to existing laminar flow equation-based models Gantayat (Gantayat et al., 2014) and Millan (Millan et al., 2022), ITMSL achieves better performance, with accuracy improved by 20.62 % and 32.65 %, respectively. This study has demonstrated that ITMSL provides an improvement over previous methods, offering new insights for ice thickness modeling and its application in data-sparse high mountain regions.

Geoscientific model developmentVol. 19(18)
Wuhan Institute of Physics and Mathematics (CN), University of Chinese Academy of Sciences (CN), Innovation Academy for Precision Measurement Science and Technology, CAS (CN)
Openalex Percentile: Top 15%
Cryospheric studies and observations
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ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0) — Liming Jiang, Yuxuan Wu, et al. · Geoscientific model development (2026) | TGRS Research Map | TGRS