Hydropower has been around for a long time. Over its long history, it has become a steady (if not sometimes forgotten) backdrop to the complicated balancing act of providing reliable national energy grids. Dependable, relatively predictable and dispatchable, hydropower now is stepping into a much more dynamic role in energy markets. 

U.S. power markets, in particular, are evolving rapidly. The increased penetration of wind and solar power means energy grids have to balance volatility, price cannibalization and variable resources that may cause imbalance in grid frequencies. And while this has driven battery storage in markets with high levels of wind and solar, such as ERCOT and CAISO, there still is a need for long-duration storage and dispatchable power. 

Increased weather volatility isn’t just grabbing headlines; it’s reshaping how we generate and trade electricity. To meet market needs and new policies like the extended day-ahead market (EDAM) in California, hydropower is taking center stage. Its reliable supply is crucial for dynamic, inter-market energy trading. 

Why Hydro, Why Now?

With the intermittency of wind and solar now a fundamental part of energy markets, and daily (even hourly — nay, even minute-by-minute) fluctuations common, energy traders need precise generation forecasts for dispatchable resources more than ever. Hydropower, with its storage and ability to quickly adjust output, is uniquely suited for this.  

The overlooked challenge in deploying hydropower, as modern energy grids now demand, is that traditional water forecasting methods haven’t kept pace with emerging climatic trends and variability. 

Conventional forecasts often miss short-term variability for a variety of reasons, including sudden snowmelt, basin-specific behaviors, or unexpected storm impacts. This leaves energy traders with uncertainty, putting resource allocation at risk, and driving (sometimes extreme) fluctuations in price as resources either fall short or overload the market. More precise inflow forecasting doesn’t just improve resource adequacy — it enables energy traders to capture value across volatile markets.  

Accurate short- and medium-term projections empower traders to position hydro assets strategically across day-ahead, real-time and ancillary service markets, so they can make timing decisions with higher confidence. Enhanced lead-time visibility enables bidding strategies that respond dynamically to shifting local marginal prices (LMPs), grid congestion and imbalance settlement penalties.    

By reducing forecast error, traders can better anticipate when to hold back water for peak pricing events or dispatch preemptively during surplus periods, improving P&L performance. Forecast granularity also supports more effective hedging, as predictable inflow reduces exposure to weather-driven volume risk. In intertie-heavy markets like CAISO, EDAM or SPP, forecasting upstream hydrology allows traders to arbitrage regional differences in supply-demand balance, particularly during snowmelt or storm-driven volatility. 

AI Forecasting: More Than Just Hype

While the challenge of adapting to a new model of energy trading won’t be solved overnight, the step change in artificial intelligence and machine learning, and their respective deployment into streamlining the energy transition for legacy energy grids, bring significant advantages in lessening the impact of intermittent energy resource and climatic volatility. 

The soon-to-launch Western EDAM will integrate Pacific Northwest hydropower more closely with California’s demanding markets. Accurate, real-time inflow forecasting is quickly shifting from being advantageous to becoming essential. 

Uncertainty at NOAA

NOAA’s public weather data is invaluable. Unfortunately, recent budget cuts introduce uncertainty about its long-term reliability and resilience, in spite of the heroic efforts by those who remain at the agency.  

Crucially, over the longer term, the private sector has the ability to consistently invest in research and development that will further enhance the latest AI forecasting technologies. While we believe a partnership between national forecasting and private solutions is most desirable, reduced funding for public forecasting may see the gap in accuracy between public and private forecasting increase. 

Hydro Steps up

Realizing hydropower’s full potential starts with accurately forecasting water, an essential first step for navigating the intricate constraints and optimization challenges it faces. Traders who embrace advanced forecasting tools will transform water into a strategic asset while generating enhanced returns. 

We’re moving beyond an era of simply spinning turbines. Hydropower is now positioned at the forefront of strategic energy trading, proactive market engagement and informed risk management in an increasingly volatile landscape. With enhanced forecasting capabilities, hydropower is confidently embracing this expanded role. 

Marshall Moutenot is CEO of Upstream Tech, a software company that provides services in the land and water management industries.