Journal Article

A Remote Sensing-Driven Dynamic Risk Assessment Model for Cyclical Glacial Lake Outbursts: A Case Study of Merzbacher Lake

Feng, Tianshi, Li, Xingdong, Xiang, Kaizheng, Lu, Yizhu, Liu, Hongjie, Song, Wenlong, Linghu, Shaobo, Chen, Long

2026

Overview

The increasing threat of Glacial Lake Outburst Floods (GLOFs), intensified by climate change, underscores the urgency for developing advanced early warning systems. The near-annual, cyclical outbursts of Lake Merzbacher in the Tien Shan mountains present a severe downstream threat, yet its remote location and lack of instrumentation pose a significant challenge to traditional monitoring. To bridge this gap, we develop and validate a dynamic risk assessment framework driven entirely by remote sensing data. Methodologically, the framework introduces an innovative Ice-Water Composite Index (IWCI) to resolve the challenge of lake area extraction under mixed ice-water conditions. This is coupled with a high-fidelity 5 m resolution Digital Elevation Model (DEM) of the lake basin, autonomously generated from GF-7 Dual-Line Camera (DLC) imagery, which enables accurate daily volume retrieval. Through systematic feature engineering, nine key hydro-thermal drivers are quantified from MODIS and other products to train a Random Forest (RF) machine learning model, establishing the non-linear relationship between catchment processes and lake volume. The model demonstrates robust predictive performance on an independent validation set (2023–2024) (R2 = 0.80, RMSE = 5.15 × 106 m3), accurately captures the complete lake-filling cycle from initiation to near-peak stage. Furthermore, feature importance analysis quantitatively confirms that Positive Accumulated Temperature (PAT) is the dominant physical mechanism governing the lake’s storage dynamics. This end-to-end framework offers a transferable paradigm for GLOF hazard management, enabling a critical shift from static, regional assessments to dynamic, site-specific early warning in data-scarce alpine regions.

• Publisher: MDPI AG
• Subject: Algorithms / Alpine regions / Bathymetry / Case studies / Climate change / Climatic changes / Dams / Data mining / data-scarce alpine region / Digital Elevation Models / dynamic risk assessment / Early warning systems / Emergency communications systems / Feasibility studies / Floods / Glacial lake outburst floods / Glacial lakes / GLOF / Instrumentation / Lake basins / Lakes / Learning algorithms / Machine learning / Meltwater / Monitoring systems / Mountains / Nonlinear phenomena / Nonlinear response / Outbursts / Physical factors / Regional analysis / Regions / Remote sensing / Retrieval / Risk assessment / Robustness / satellite photogrammetry / Satellites / Snow cover / Warning systems