Dai (2026) Estimating snow water equivalent from satellite

Identification

• Journal: Elsevier eBooks
• Year: 2026
• Date: 2026-01-01
• Authors: Liyun Dai
• DOI: 10.1016/b978-0-323-85242-5.00081-6

Research Groups

• Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

Short Summary

This paper reviews the main satellite remote sensing techniques for estimating snow depth and snow water equivalent (SWE), describing their principles, advantages, and disadvantages. It highlights the significant challenge of snow depth retrieval in mountainous areas and suggests future research directions, including combining passive and active microwave remote sensing.

Objective

• To systematically review the progress of snow depth and SWE estimation methods using satellite remote sensing.
• To describe the principles, advantages, and disadvantages of various satellite remote sensing techniques (passive microwave, active microwave, altimetry).
• To discuss existing challenges, particularly in mountainous regions, and propose future research directions for improving retrieval accuracy.

Study Configuration

• Spatial Scale: Global to regional scales, covering various snowmelt-dominated regions and specific challenges in mountainous areas.
• Temporal Scale: Multi-decadal, reviewing techniques that provide long-term series data (e.g., passive microwave since 1978) and discussing progress over the last 40 years.

Methodology and Data

• Models used: Not applicable (review paper describing various algorithms and techniques).
• Data sources: Satellite remote sensing data, including:
  • Passive microwave (e.g., Nimbus-7 SMMR data)
  • Synthetic Aperture Radar (SAR)
  • Interferometric SAR (InSAR)
  • Lidar (satellite and airborne)
  • Specifically mentions Sentinel-1 SAR.

Main Results

• The paper systematically outlines the basic principles of snow depth estimation using passive microwave remote sensing, active microwave remote sensing (SAR/InSAR), and Lidar techniques.
• It details the advantages and disadvantages of each method, noting passive microwave's efficiency for large-scale monitoring due to long time series and high temporal frequency.
• A major challenge identified is the accurate retrieval of snow depth in mountainous areas due to complicated topography.
• Future research directions emphasize the need for new methods combining passive and active microwave remote sensing to improve retrieval accuracy, especially in complex terrain, leveraging the increasing availability of SAR data.

Contributions

• Provides a comprehensive and systematic review of the state-of-the-art satellite remote sensing techniques for snow depth and SWE estimation.
• Clearly articulates the principles, strengths, and limitations of passive microwave, active microwave, and altimetry methods.
• Identifies critical challenges in snow depth retrieval, particularly in mountainous regions, which is crucial for hydrological and climatic studies.
• Proposes concrete future research directions, advocating for integrated approaches (e.g., passive and active microwave combination) to advance the field.

Funding

• Not explicitly stated in the provided text.

Citation

@article{Dai2026Estimating,
  author = {Dai, Liyun},
  title = {Estimating snow water equivalent from satellite},
  journal = {Elsevier eBooks},
  year = {2026},
  doi = {10.1016/b978-0-323-85242-5.00081-6},
  url = {https://doi.org/10.1016/b978-0-323-85242-5.00081-6}
}