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Updated: Sep 17, 2025
12:44
Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
8.1K
Snow drought to hydrologic drought progression using machine learning and probabilistic analysis.
Pouya Moghaddasi1, Keyhan Gavahi2, Hamid Moradkhani3
1Department of Civil, Construction and Environmental Engineering, Center for Complex Hydrosystems Research, The University of Alabama, Tuscaloosa, USA. pmoghaddasi@crimson.ua.edu.
Scientific Reports
|July 2, 2025
Summary
Declining snowpack impacts water resources. This study shows Snow Water Equivalent (SWE) strongly influences streamflow, with a 60-90 day lag, and predicts hydrologic drought progression.
Area of Science:
- Hydrology
- Water Resource Management
- Climate Science
Background:
- Snowpack is a vital natural reservoir for water resources, crucial for agriculture, domestic use, and ecosystems.
- Declining snowpack presents significant challenges to water availability, especially in regions reliant on snowmelt.
- Understanding the relationship between snowpack and streamflow is critical for effective water resource management.
Purpose of the Study:
- To investigate the relationship between Snow Water Equivalent (SWE) and streamflow in snow-dominated watersheds.
- To utilize the Long Short-Term Memory (LSTM) model and probabilistic analysis to understand snow's influence on streamflow.
- To identify reliable SWE datasets and assess spatial variations in the SWE-streamflow relationship.
Main Methods:
- Employed the Long Short-Term Memory (LSTM) model, typically used for prediction, to analyze the influence of SWE on streamflow.
- Conducted a comparative analysis of multiple SWE products, with a focus on the University of Arizona (UAZ) dataset.
- Performed spatial analysis across western US basins and probabilistic analysis to track drought progression.
Main Results:
- A strong correlation was found between SWE and streamflow, with a significant influence observed at a 60-90 day lookback period.
- The UAZ SWE dataset demonstrated consistent reliability, highlighting the impact of winter SWE on spring and summer streamflow.
- Basins in the western United States showed robust model performance, confirming a strong SWE-streamflow link in these regions.
- Probabilistic analysis revealed a clear progression from snow drought to hydrologic drought, with increasing likelihood over time.
Conclusions:
- The study confirms a significant relationship between SWE and streamflow, crucial for water resource management in snow-dominated areas.
- The UAZ dataset and western US basins provide reliable insights into snowmelt-runoff processes.
- The identified progression from snow drought to hydrologic drought serves as an effective early warning system for drought conditions.
Keywords:
Drought progressionHydrologic droughtLong short-term memory (LSTM)Probabilistic analysisSnow droughtUnited StatesMore Related Videos
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