Woodruff et al. (2026) Assessment of Drought Impacts on Remotely Sensed Seasonal Snow Depletion Patterning: A Case Study Over the Boise River Basin, Idaho

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

Identification

• Journal: Hydrological Processes
• Year: 2026
• Date: 2026-01-01
• Authors: C. Woodruff, Russell J. Qualls, Patrick E. Clark
• DOI: 10.1002/hyp.70392

Research Groups

[Information not available in the provided abstract.]

Short Summary

This study developed a pattern-based cloud gap filling approach to provide reliable daily snow cover estimates and investigated whether moderate severe droughts alter snow depletion patterns or negatively impact cloud gap filling reliability. The research found that snow depletion patterns and the reliability of the cloud gap filling method remain robust even during moderate severe drought conditions.

Objective

• To provide a cloud-free, reliable, and dynamic estimate of daily snow cover using a pattern-based cloud gap filling approach.
• To determine if moderate severe droughts alter seasonal snow depletion patterns and negatively impact cloud gap filling reliability.

Study Configuration

• Spatial Scale: Boise River Basin, Idaho; watershed scale.
• Temporal Scale: Daily data over the period of 2000–2024, focusing on seasonal snow depletion patterns.

Methodology and Data

• Models used: Pattern-based cloud gap filling approach; statistical models (68 models) for snowline representation.
• Data sources: Daily optical remotely sensed snow cover data.

Main Results

• Moderate severe drought was uncorrelated with maximum snow extent, the onset of spring melt, and the rate of snow depletion.
• Snow depletion patterns at the watershed scale were similar and robust to moderate severe drought, showing an average correlation of 98.7%.
• Snowline representation was highly similar, with an average R² of 0.995 over 68 models.
• Average cloud gap filling estimated similarity was 96.73%, with only a slight reduction to 94.76% during severe drought.

Contributions

• Provides a novel pattern-based cloud gap filling approach for generating cloud-free, reliable, and dynamic daily snow cover estimates.
• Demonstrates that snow depletion patterns and the reliability of cloud gap filling are robust even under moderate severe drought conditions.
• Offers accurate snowline representation critical for real-time management of snowmelt runoff, addressing a key uncertainty in water resource management.

Funding

[Information not available in the provided abstract.]

Citation

@article{Woodruff2026Assessment,
  author = {Woodruff, C. and Qualls, Russell J. and Clark, Patrick E.},
  title = {Assessment of Drought Impacts on Remotely Sensed Seasonal Snow Depletion Patterning: A Case Study Over the Boise River Basin, Idaho},
  journal = {Hydrological Processes},
  year = {2026},
  doi = {10.1002/hyp.70392},
  url = {https://doi.org/10.1002/hyp.70392}
}