Enhancing Soil Moisture–Based Drought Monitoring in Complex Mountainous Terrain

Assigned Session: Drought in mountain regions
Abstract ID: 3.167
| Accepted as Talk
| TBA
| TBA
Villegas-Lituma, C. (1)
Massart, S. (1); Schwaizer, G. (2); Juraj, P. (3); and Schramm, M. (1)
(1) Technische Universität Wien, Faculty of Mathematics and Geoinformation, Department of Geodesy and Geoinformation (GEO), Wiedner Hauptstraße 8-10, 1040 Wien, Wien, Austria
How to cite: Villegas-Lituma, C.; Massart, S.; Schwaizer, G.; Juraj, P.; and Schramm, M.: Enhancing Soil Moisture–Based Drought Monitoring in Complex Mountainous Terrain, #RMC26-3.167
Categories: No categories defined
Keywords: Soil moisture, drought monitoring, topography, snow masking
Categories: No categories defined
Keywords: Soil moisture, drought monitoring, topography, snow masking
Abstract
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The Austrian Alps supply about 60 % of the country’s electricity and represent a critical freshwater resource. As climate change increases the frequency and severity of droughts, reliable soil moisture observations are essential for drought early warning and effective water resource management. However, existing satellite-based surface soil moisture (SSM) products remain inadequate for mountainous regions. Scatterometer- and Synthetic Aperture Radar (SAR)-derived SSM datasets lack adequate snow cover masking, exclude steep slopes, and offer limited spatial resolution for capturing soil moisture variability across complex topography.

Within the Digital Twin for Austria – Alpine Hydrology and Future Hazards project, we address these limitations through two complementary strategies. First, we integrate daily satellite-derived snow cover from combined Sentinel-3 SLSTR and OLCI data (∼200 m) into HSAF ASCAT SSM (6.25 km) and HSAF DIREX SSM (500 m) to filter unreliable soil moisture observations and enable identification of true soil moisture anomalies. This daily satellite-based snow masking substantially improves retrieval accuracy. Both ASCAT and DIREX SSM show increased correlation with ERA5-Land, and in-situ validation for ASCAT SSM indicates a significant bias reduction, from 0.1–0.25 m³/m³ to 0.05–0.20 m³/m³, when snow-contaminated observations are properly filtered. Second, we introduce the AlpineSSM product, a novel Sentinel-1 retrieval that aggregates terrain-corrected backscatter into elevation bands stratified by sub-basin and binary north-south aspect, enabling soil moisture monitoring across over 80 % of the Austrian Alps, including slopes and high-altitude areas. Validation against ERA5-Land confirms robust performance at lower elevations (Pearson r > 0.46 below 400 m), while comparison with 264 Geosphere precipitation stations (2016–2024) demonstrates the product’s ability to track post-rainfall moisture anomalies, with strongest correlations for grasslands and south-facing slopes below 400 m (Spearman r > 0.47). Performance declines over dense vegetation and at higher elevations.

By enhancing operational products through satellite-based snow masking and introducing the AlpineSSM product, this work delivers more reliable and spatially comprehensive soil moisture retrieval across the Austrian Alps, addressing critical observational gaps that have historically limited drought detection in mountainous regions.

This work has been funded by Die Österreichische Forschungsförderungsgesellschaft for the project "Digital Twin for Austria - Alpine Hydrology and Future Hazards" [grant number: FO999918403]

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