Snowmelt season preparedness: leveraging AI to build resilience and mitigate risks

Photo by Ravi Pinisetti via Unsplash.
Jun 27, 2024
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Snowmelt season plays a crucial role in hydropower generation and ensuring supply for the health of river ecosystems, supporting aquatic life, and sustaining agriculture, industry, and human consumption downstream. Managing the patterns of snowmelt is crucial for ensuring adequate supply during the high-energy and irrigation demanding summer months across much of the Northern hemisphere.

Climate change has accelerated the melting of snowpacks across many regions, leading to earlier and more rapid snowmelt. Dwindling or unpredictable water reservoirs during the snowmelt season, also known as snow drought, impedes hydropower production, leading to disruptions in energy supply, increased reliance on fossil fuels, and heightened energy costs and regulatory risks. 

In the U.S., hydropower output decreased by 6% last year. This drop was primarily linked to elevated temperatures causing rapid snowmelt in the Northwest, resulting in significant water depletion and subsequently reducing energy generation in hydroelectric facilities and increasing reliance on fossil fuels. More recently, an ongoing statewide drought emergency in Washington state over 2023-2024 underscores the urgency of leveraging advanced forecasting technologies to navigate the complexities posed by climate change in day-to-day operations and long term planning. The state's reliance on snowpack as a primary water source underscores the vulnerability of its water supply to climatic fluctuations. With diminished snowpack levels threatening to exacerbate drought conditions, accurate and timely hydrological forecasts become paramount. 

One of the key advantages of HydroForecast over industry standard forecasts lies in its ability to anticipate the timing and magnitude of snowmelt runoff, especially in extreme years. The system employs a unique strategy: training a single model to comprehend hydrology across hundreds of diverse basins, which it then fine-tunes to predict local conditions. By integrating meteorological data, snowpack observations from remote sensing and gridded models, and in-situ data into a neural network, HydroForecast learns the nuances of snow processes and provide actionable insights into future water availability, helping utilities and hydropower operators anticipate and mitigate potential water deficits or surpluses. With rapid run times and streamlined experimentation, HydroForecast makes it easy to integrate and retrain with new data sources, promising agile and accurate forecasts. 

HydroForecast is a confluence of hydrology and machine learning

HydroForecast Seasonal predicts water volumes up to 1 year out 

HydroForecast Seasonal provides forecasts up to 1 year out, serving as a key input in assessing the impact of water availability scenarios and thereby allowing decision-makers to evaluate the efficacy of different management strategies in addressing drought conditions. Timely predictions empower stakeholders to adopt a proactive stance in mitigating the impacts of drought - from optimized scheduling of hydropower generation, balancing energy demand with water availability, to reducing reliance on costly backup sources.

Below is an example of HydroForecast’s Seasonal forecasts for a site in the Pacific Northwest, which has been experiencing below average flows. The black line tracks observations while  colored lines represent forecast traces from April through June. The model picked up early in the season on the lower flows and has continued to track the pattern. This information months ahead gives early warning of a drier season for planning purposes.

HydroForecast Short-term captures the precise timing of the peak of snowmelt 

By providing precise insights into when the snowpack will melt most rapidly anywhere from one to 10 days ahead, HydroForecast Short-term enables timely decisions for optimizing water storage, distribution, and flood prevention strategies. 

The Pacific Northwest suffered a strange season; while a wet spring brought much relief to drought conditions in certain snowy high elevation basins, significant rainfall during a period when reservoirs are filling from snowmelt can be a delicate situation to navigate. Thus managing the next week to 10 days ahead based on incoming weather was critical. 

Below is an example of a HydroForecast Short-term forecast for a site in the Pacific Northwest, where water flows have been below average. The black line shows the observed data, while the solid colored lines represent the short-term forecast projections, and the red dashed line represents an alternate forecast. HydroForecast successfully predicted a significant increase in snowmelt, a critical event overlooked by a leading industry forecast.

Watch this webinar recording or schedule a meeting to learn more about how HydroForecast can equip your organization with the tools you need to plan and operate in the midst of complex weather conditions and changing snow patterns.

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