Even at the best of times, the West's water supplies are fraught with political, economic and environmental wrangling. When devastating droughts occurred in the 1970s and the 2000s, farmers and fish alike suffered. Yet the ability to predict stream flows in the Western United States at seasonal lead times -- months or longer -- is scarcely better today than it was in the 1960s.
Forecasting models that incorporate high-powered computers and satellite data may soon modernize the way Western states manage freshwater supplies. Several such models are currently under development. Dennis Lettenmaier, professor of civil and environmental engineering at the UW, will describe the role of science in Western water management Friday in San Francisco at the American Association for the Advancement of Science annual meeting.
A half-century ago, resource managers would ski or hike to mountain stations and measure the amount of water stored in the snowpack. They took a metal tube and inserted it in the snow, then weighed the tube to calculate how much water it contained. Today's electronic systems automate this process, but use a similar principle, Lettenmaier said.
"If you know how much snow is on the ground in the spring, you have a pretty good idea of how much runoff will occur during the spring and summer," Lettenmaier said. "That's something that's been used for a long time. The question is: can we do better than that?"
A new generation of hydrologic forecasting models integrate not only scattered, ground-based measurements of snow depth, but also satellite measurements of snow extent. The University of Washington's West-Wide Seasonal Hydrologic Forecast System is an example of such a model. It recalculates conditions every day using weather data and satellite images. UW's model incorporates atmospheric climate forecasts and produces forecasts of stream flow for up to a year into the future.
The overall aim is to provide computerized water forecasts equivalent to modern weather-prediction models. The new forecast methods incorporate a wealth of other climate information to produce results earlier in the season, more accurately and for situations that are outside the norm. These methods recalculate conditions every day by incorporating satellite images of snowcover and computing the influence of that day's temperature and precipitation.
Forecasts based on physical processes avoid the problems inherent in statistical forecasting methods that rely on historical patterns. For example, after unusually heavy snowfall in the Southwest in 2003, traditional forecast models predicted that the spring and summer runoff in Utah's Virgin River would be as much as 10 times its normal rate, values that didn't seem believable. In the case of drought, snow levels in 1977 were so low that forecasted runoff for some California streams was negative.
"It's a classic problem of extrapolating a line out past the end of the observations," Lettenmaier said. When current conditions don't look like anything previously seen, methods that are too closely related to historic patterns can fail.
Water managers are beginning to feel a crunch related to climate change, Lettenmaier said. Springtime melt now starts some 20 days earlier than a half-century ago, which is "pretty unequivocally" seen as a signature of climate change, he said. The shift results in a bigger gap between when the fresh water flows down from the mountains and when it actually is most needed in the height of summer. Climate change constitutes an additional challenge, on top of factors such as population movement, agriculture changes and water use changes, that managers must contend with.
Knowing the amount of water ahead of time lets people prepare for droughts or flooding. Building more reservoirs would help, in particular to handle earlier runoff, but the West is unlikely to see any more dams built, Lettenmaier said. Instead, people can use forecasts to decide which crops to plant, whether to drain reservoirs to prepare for flooding and how to allocate water resources early in the season.
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