As disclosed in this superb article from Water Deeply.
Most Americans may not realize it, but we really don’t know with a lot of accuracy how much snow there is sitting in the mountains during winter. We also don’t always have a precise picture of where the snow level is when a storm moves in, or how much will run off when the snow melts.
One reason for this is that, in most areas, the weather sensor network in the mountains simply isn’t very dense. Gauges that measure rain and snow are often placed for convenient access. The highest elevations and forested areas often have no sensors, leaving huge data gaps in many watersheds.
This creates a host of problems, from estimating flood risk accurately to figuring out how much water is available for summer farm irrigation.
A team from the University of California and the United States Department of Agriculture (USDA) recently completed a project to fill the data gaps. With funding from the National Science Foundation, they developed a new wireless network consisting of 140 sensor pods installed across 830 square miles of the American River Basin. Previously, the area had only 27 sensors.
This critical California watershed drains through Sacramento, one of the most flood-prone metropolitan areas in the nation. And it now has the most data-rich precipitation monitoring network anywhere. This could vastly improve forecasting, especially as climate change disrupts previous expectations about storm behavior.
To learn more about the project, Water Deeply talked to Roger Bales, a distinguished professor of engineering at the University of California, Merced, director of the Sierra Nevada Research Institute, and project leader of the new sensor network.
Water Deeply: Why did you undertake this project? What was the need that drove it?
Roger Bales: We don’t do that good of a job of measuring the basic water balance in the mountains. Think of the water balance as being like this formula: precipitation = evapotranspiration + runoff. Water is coming in as precipitation, and it’s leaving either because the vegetation is putting it back into the atmosphere, or because it’s draining away as runoff. Some of that’s subsurface, but some of it comes out in runoff.
In the mountains, we don’t really measure precipitation very well. On any given day, in any given storm, you actually only know how much rainfall is occurring. There may be only a few rain gauges, and they are not at the highest elevations. You have snow pillows at the higher elevations, which are telemetered, and they give you the amount of snow falling in a few generally flat, open areas (think of a meadow). But that’s not representative of the landscape. Rain gauges also tend to be put in convenient locations to get to.
There are a lot of decisions that depend on knowing how much precipitation is occurring, and how much water is in storage. The two main storage reservoirs in the mountains, besides the dams at the base of the mountains, are the snowpack and the soil water storage. The seasonal snowpack changes every time there’s a storm or every time there’s snowmelt. It changes daily.
So the amount of precipitation and snow that falls is statistically related to runoff, but not in a mass balance sense. That is, you can’t take the sum of all the rain gauges or snow pillow data and say that’s how much rain fell or how much snow fell, because the rain gauges are too sparse and not representative. The operational network tends to be located at mid- and low-elevation clearings, not so much at the high elevations and not so much in forests.
We designed a network that is more representative of the landscape and has a denser set of sensors. We scaled this up from a small headwater catchment that we did in the Kings River Basin, going from about 400 acres to the whole snow-covered part of the American River Basin. We basically replicated what we did in the southern Sierra 14 times, and in that way we’ve covered the whole basin – at least the topography and land cover of the whole basin.
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