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Estimating Snow-Related Daily Change Events in the Canadian Winter Season: A Deep Learning-Based Approach.

Karim Malik1, Isteyak Isteyak1, Colin Robertson2

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|July 25, 2025
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Summary
This summary is machine-generated.

This study introduces a novel AI model to track daily snow water equivalent (SWE) changes. Findings reveal increasing SWE change events, influenced by climate anomalies, particularly in spring.

Keywords:
Siamese Attention Networkclimate changedaily snow variabilitysnow water equivalentsnow-related change eventsstructural similarity

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Area of Science:

  • Hydrology
  • Climate Science
  • Artificial Intelligence

Background:

  • Snow water equivalent (SWE) is crucial for understanding snowmelt patterns and climate impacts.
  • Previous studies focused on broader snowmelt trends, necessitating finer temporal resolution for change detection.

Purpose of the Study:

  • To develop and validate a Siamese Attention U-Net (Si-Att-UNet) model for detecting daily SWE change events.
  • To analyze trends in daily SWE change events and their relationship with climate anomalies from 1979 to 2018.

Main Methods:

  • Utilized a Siamese Attention U-Net (Si-Att-UNet) model to compare pairs of SWE maps for change detection.
  • Treated daily SWE change detection as an image content comparison problem.
  • Applied the Mann-Kendall test to assess the significance of SWE change event trends.

Main Results:

  • The Si-Att-UNet model achieved high accuracy (99.3% F1 score) in detecting SWE similarity and dissimilarity.
  • A significant increase in daily SWE change events was observed between 1979 and 2018.
  • Low temperature and precipitation anomalies were found to reduce the frequency of SWE change events, especially in March and April.

Conclusions:

  • Daily SWE change events are increasing, with notable significance in spring months (March and April).
  • Climate variables, specifically temperature and precipitation anomalies, significantly influence daily snow water storage dynamics.
  • The study highlights the impact of climate change on snow hydrology and water resources.