Snowpack measurements in Ca
Monitoring of the Sierra Nevada snowpack began in 1910. Today, snow is measured monthly at 278 snow courses, and daily at 125 snow pillows. However, the operating courses and pillows do not cover the highest elevations well, and they are not physiographically representative measurements of snow at any elevation. The measurement network also lacks data on soil moisture, solar radiation, wind speed, and relative humidity that have immediate application to estimating snowmelt runoff. Satellite observations are able to show the distribution of snow over topography, which surface measurements do not, and in the Sierra Nevada they show considerable snow at the higher elevations after all snow has disappeared from the snow courses and pillows. The connection between the snowpack and operational, seasonal forecasts of snowmelt-generated streamflow is at present largely through empirical relations based on past snowmelt events. These historical data document that climate change is occurring. However, climate change means that the empirical relations are becoming less reliable. Better accuracy and coverage are needed for optimal water resources management.
Issue and proposed solution
With better management, California’s existing water supply could go further to meeting the needs of the state’s urban and agricultural uses. Currently, California’s water reservoirs are controlled and regulated using forecasts based upon more than 75 years of historical data. In the face of global climate change, these forecasts are becoming increasingly inadequate to precisely manage water resources. We propose implementing an intelligent water infrastructure system that leverages the newest frontiers of information technology. The immediate need is for further development of currently operating basin-scale prototype information systems. As the next step toward broader implementation a partnership involving the Department of Water Resources, the University of California and key stakeholders is required to evaluate, refine and implement this technology.
American River Hydrological observatory
American River Hydrological Observatory spans the upper reaches of the 4500 km2 American River basin. With $3M of National Science Foundation funding, we are installing 18 Wireless Sensor Networks each of which covers 1 km2 of physiographically representative forest. Each network consists of 35 stations measuring snow depth, solar radiation temp/rH, and soil moisture. At present there are 10 networks operating with close to 100 sensors. The network sends back data over cell or satellite modem links. Relatively small investments in satellite remote sensing data, ground-based measurements and cyber-infrastructure have the potential to dramatically improve hydrologic information, reduce uncertainty in water availability, and improve water-supply reliability. One challenge associated with wind and solar is intermittency and our inability to predict and control the energy sources. In California, hydropower can fill gaps left by renewable power generation sources. To provide the most electricity when it is most needed, improved planning and operation of hydropower systems will require more real-time informed decision support than in the past. We are working with major hydroelectric operators to optimize usage of dams for generation, flood control and water distribution.