GRIT: Geospatial Rock-glacier Ice Thickness Model through Satellite-Derived Rheological Inversion

As climate change leads to the retreat of mountain glaciers worldwide, rock glaciers are increasingly recognised as important hydrological buffers in high-altitude catchments. Unlike clean-ice glaciers, these debris-covered formations are geophysically complex, making regional estimates of their water storage consistently challenging. Current assessments usually rely on simple area–volume scaling methods based on the surface slope, which overlook the flow behaviour of individual landforms.

In this contribution, we introduce GRIT (Geospatial Rock-glacier Ice Thickness Model), an open-source computational framework that infers ice thickness from satellite-derived surface kinematics, applying a Glen-type viscous flow law. It determines thickness by integrating local slope data from a high-resolution digital elevation model (DEM) with surface horizontal velocity measurements obtained through feature tracking in high-resolution optical satellite imagery.

To constrain the rheology, we calibrate the effective creep parameter (B) using 80 MHz ground-penetrating radar (GPR) profiles collected at the Vej del Buoc rock glacier in the Maritime Alps. Our results reveal a range of B values indicative of a significantly softer effective rheology than that of clean temperate ice, consistent with the presence of interstitial unfrozen water and debris inclusions that reduce the mixture's viscosity. GRIT is designed for scalability and can be applied to regional inventories to derive spatially explicit thickness and water-equivalent maps.

To our knowledge, this is the first satellite-based, geospatial rheological inversion toolbox specifically designed for determining rock-glacier ice thickness and water-equivalent storage. By combining satellite-observed movement with site-specific geophysical calibration, GRIT offers a scalable, physically grounded method for monitoring the debris-covered cryosphere in mountain basins with limited data and for incorporating rock-glacier ice storage into regional water resource evaluations.