Srivastava et al. (2025) Introducing Glaciohydrological Model Calibration Using Sentinel‐1 SAR Wet Snow Maps in the Himalaya‐Karakoram

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2025
• Date: 2025-11-25
• Authors: Smriti Srivastava, R. R. Forster, Summer Rupper, Mohd Farooq Azam, Umesh K. Haritashya
• DOI: 10.1029/2025wr040225

Research Groups

Not specified in the provided abstract.

Short Summary

This study introduces and validates a satellite-based calibration method for the SPHY glaciohydrological model using Sentinel-1 SAR wet snow maps and geodetic mass balance in the data-sparse Himalaya-Karakoram region, demonstrating its robustness for improving runoff estimates and understanding glaciohydrology.

Objective

• To introduce and validate a glaciohydrological model (SPHY) calibration method at glacier catchment-scale (2000–2023) using satellite-based Sentinel-1 Synthetic Aperture Radar (SAR) wet snow maps and geodetic mass balance estimates in the Himalaya-Karakoram (HK) region.
• To test the robustness of this satellite-based calibration against in situ runoff data for Chhota Shigri Glacier (CSG), Dokriani Bamak Glacier (DBG), and Gangotri Glacier System (GGS) catchments.

Study Configuration

• Spatial Scale: Glacier catchment-scale, specifically Chhota Shigri Glacier, Dokriani Bamak Glacier, and Gangotri Glacier System catchments within the Himalaya-Karakoram region.
• Temporal Scale: 2000–2023 for model calibration and mean annual runoff estimates; 2015–2023 for Sentinel-1 SAR-derived wet snow analysis.

Methodology and Data

• Models used: Spatial Processes in Hydrology (SPHY) glaciohydrological model.
• Data sources:
  • Satellite-based Sentinel-1 Synthetic Aperture Radar (SAR) wet snow maps.
  • Geodetic mass balance estimates.
  • In situ runoff data (used for validation).

Main Results

• The SPHY modeled runoff estimates show good agreement with in situ catchment-wide runoff data.
• Sentinel-1 SAR-derived wet snow percentage area exhibited strong spatial and temporal variability from 2015 to 2023.
• Mean annual runoff over 2000–2023 for the studied catchments:
  • Chhota Shigri Glacier (CSG): 1.79 ± 0.15 m³ s⁻¹
  • Dokriani Bamak Glacier (DBG): 1.63 ± 0.09 m³ s⁻¹
  • Gangotri Glacier System (GGS): 39.40 ± 3.15 m³ s⁻¹
• Maximum annual runoff occurred in 2021/2022, primarily attributed to heatwaves in early spring/summer 2022.
• Runoff composition varies by catchment:
  • Snowmelt runoff is highest in CSG (61%) and GGS (49%).
  • Rainfall-runoff dominates in DBG (42%).

Contributions

• Introduces a novel and robust satellite-based glaciohydrological model calibration approach using Sentinel-1 SAR wet snow maps and geodetic mass balance, particularly valuable for data-sparse glacierized catchments.
• Demonstrates the effectiveness of remote sensing data for improving runoff estimates and validating glaciohydrological models where in situ data is limited.
• Strengthens the understanding of past, present, and future glaciohydrological processes in regions like the Himalaya-Karakoram and Andes, which often lack comprehensive in situ runoff data.

Funding

Not specified in the provided abstract.

Citation

@article{Srivastava2025Introducing,
  author = {Srivastava, Smriti and Forster, R. R. and Rupper, Summer and Azam, Mohd Farooq and Haritashya, Umesh K.},
  title = {Introducing Glaciohydrological Model Calibration Using Sentinel‐1 SAR Wet Snow Maps in the Himalaya‐Karakoram},
  journal = {Water Resources Research},
  year = {2025},
  doi = {10.1029/2025wr040225},
  url = {https://doi.org/10.1029/2025wr040225}
}