Kadam et al. (2025) Geospatial Analysis of Glacial Lake Area and Volume Changes in the Indian Himalayas

Identification

• Journal: ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
• Year: 2025
• Date: 2025-12-19
• Authors: Sonali Kadam, Ravindra Kale, Sanket Patil, Jagruti Kumbhar, Gayatri Khedkar, Shravani Jagtap, Jotiram Gujar
• DOI: 10.5194/isprs-annals-x-5-w2-2025-287-2025

Research Groups

• Bharati Vidyapeeth College of Engineering for Women Pune, Maharashtra, India
• National Institute of Hydrology, Roorkee, Uttarakhand, India
• Bharati Vidyapeeth's College of Engineering Lavale Pune, Maharashtra, India
• Chemical Engineering Department, Sinhgad College of Engineering Pune, Maharashtra

Short Summary

This study developed a scalable geospatial framework using Google Earth Engine and remote sensing to analyze the area and volume changes of glacial lakes across the Indian Himalayas from 2008 to 2017, revealing a significant and consistent increase in both, particularly in the eastern Himalayan region. The findings highlight the accelerating impact of climate change on the cryosphere and the increasing risk of Glacial Lake Outburst Floods (GLOFs).

Objective

• To quantify how much the Indian Himalayan glacial lakes' area and volume changed between 2008 and 2017 using a scalable, cloud-based geospatial workflow.
• To examine the output and performance of various empirical volume models within the same spatial context.

Study Configuration

• Spatial Scale: Indian Himalayan Region (IHR), encompassing northern Indian states and union territories (Jammu & Kashmir, Ladakh, Himachal Pradesh, Uttarakhand, Sikkim, and Arunachal Pradesh), located between approximately 26°N and 36°N latitude and 74°E and 92°E longitude.
• Temporal Scale: Annual changes from 2008 to 2017.

Methodology and Data

• Models used:
  • Empirical volume-area relationship: V = c * A^d (Cook and Quincey, 2015: c=0.104, d=1.42).
  • Other models (Evans, 1986; Huggel, 2002; Qi et al., 2022) were also tested for comparison in Python.
• Data sources:
  • Multi-temporal satellite imagery (implied Landsat from "remote sensing archives").
  • Digital Elevation Models (DEMs).
  • Open-access High Mountain Asia (HMA) inventories for annual vector shapefiles of glacial lakes.
  • Google Earth Engine (GEE) as the main processing platform.
  • Python scripts (Shapely, Pandas, GeoPandas, geemap, matplotlib, ipywidgets libraries) for data preparation, processing, analysis, and visualization.

Main Results

• The total surface area and estimated volume of glacial lakes in the Indian Himalayas significantly and consistently increased between 2008 and 2017.
• Volume growth consistently outpaced surface area growth, indicating that lakes are expanding horizontally and becoming deeper.
• The highest growth rates for both area and volume were observed in the eastern Himalayan region, particularly in Uttarakhand and Arunachal Pradesh.
• Lakes with the largest volumetric increases were predominantly found at elevations between 4500 meters and 5200 meters, corresponding to active glacier retreat zones.
• Lakes above 5500 meters remained mostly stable due to less meltwater availability and colder climates.
• Interactive visualization allowed tracking of individual lakes (e.g., GL078957E30911N showed significant area and volume increase, with centroid shifts indicating shape changes).

Contributions

• Developed a scalable, cloud-based geospatial framework for consistent, long-term monitoring of glacial lake area and volume changes in remote, data-poor mountainous regions.
• Provided updated decadal (2008-2017) insights into glacial lake dynamics across the Indian Himalayas, highlighting regional disparities and elevation-dependent growth patterns.
• Demonstrated the efficiency and repeatability of integrating remote sensing, empirical modeling, Python-based processing, and cloud GIS tools (Google Earth Engine) for high-altitude hydrological monitoring.
• Offered a reliable framework for tracking glacial lake dynamics, crucial for understanding climate change impacts, GLOF hazard mitigation, and informing early warning systems and climate adaptation plans.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Kadam2025Geospatial,
  author = {Kadam, Sonali and Kale, Ravindra and Patil, Sanket and Kumbhar, Jagruti and Khedkar, Gayatri and Jagtap, Shravani and Gujar, Jotiram},
  title = {Geospatial Analysis of Glacial Lake Area and Volume Changes in the Indian Himalayas},
  journal = {ISPRS annals of the photogrammetry, remote sensing and spatial information sciences},
  year = {2025},
  doi = {10.5194/isprs-annals-x-5-w2-2025-287-2025},
  url = {https://doi.org/10.5194/isprs-annals-x-5-w2-2025-287-2025}
}