Engineers Model the California Reservoir Network

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Engineers Model the California Reservoir Network

Study offers reservoir managers insight on how to plan and respond to drought conditions

For the first time, engineers at Caltech have developed an empirical statewide model of the California reservoir network. The model was built from data gathered over a 13-year period that includes the latest drought, allowing researchers to make observations about how 55 of the state's major reservoirs respond to a variety of external conditions as a unified system.

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Satellite images show a 50 percent decrease in the water level of Shasta Lake
between September 2011 (top) and September 2014 (bottom). Shasta Lake was
among the 55 major California reservoirs included in this model
Credit: USGS/NASA, Landsat 5 (2011); Landsat 8 (2014)

Reservoirs act as the state's buffer against climate variability, stockpiling water during the rainy season for use during the dry. The water may be released to generate hydroelectric power, and can be diverted to agriculture and residential consumption. Meanwhile, a reservoir itself is often used for recreational purposes, such as swimming and boating.

The reservoirs are interconnected in that they are placed along major waterways, with some downstream of others, and also because they can receive similar amounts of water input and can be subject to similar management decisions.

The managers of these facilities must maintain a baseline amount of water in each reservoir. As the water level drops closer to that minimum mark, they dial back the amount of water released, which in turn affects all of the reservoirs downstream.

Reservoir managers try to avoid having to shut off the water release completely, since that can have catastrophic consequences for farms and communities that rely on the water. The behavior of a reservoir—the rising and falling of the water level—is determined in part by shifts in the climate and in part by the humans managing the outflow of the reservoir. These two components can make reservoir storage challenging to predict.

"The bread and butter of hydrology is using physical laws to describe water phenomena. But the behavior of these reservoirs is not solely determined by physical laws of the water cycle, but also by demands and what these reservoirs are being used for," says Caltech graduate student Armeen Taeb, lead author of a paper about the model that was published on November 22 by the journal Water Resources Research.

"The significant human component in the behavior of reservoirs means that physics-based modeling quickly becomes intractable in settings with large number of reservoirs."

To solve this issue, Taeb and his colleagues—Venkat Chandrasekaran, professor of computing and mathematical sciences and electrical engineering at Caltech, and John Reager and Michael Turmon of JPL—used statistical techniques to learn from the past to shed light on how reservoirs will respond to different climate patterns in the future.

They compared fluctuations in reservoir water levels between 2003 and 2016 to a variety of factors, such as precipitation, the severity of the drought, the snowpack levels in the Sierras, and levels of other California reservoirs. The researchers found that the biggest predictor of changes in the reservoir network was the Palmer Drought Severity Index, which was developed by the National Weather Service in 1965.

With this empirical model, Taeb says, managers can get a clearer picture of the demands that will be placed on their reservoirs, and can adjust their behavior earlier by curtailing water releases more gradually—reducing the possibility of having to cut off water releases altogether.

Read full article: Caltech

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