1. Real-time Sierra Nevada water monitoring system Context & need Importance. Climate change introduces uncertainty into water forecasts that are based on historical statistical relationships, with errors greatest for conditions further from the historical mean. Increasing pressures on mountain water supplies & flood control also make accurate forecasting more important to water decision makers than in the past. Accurate, real-time estimate of spatial snow amounts are critically needed & when available will provide an unprecedented, quantitative picture of snowcover across Sierra Nevada watersheds, which will inform water supply estimates, flood forecasts & resource management decisions. Soil moisture is emerging as a critical response variable, which exhibits basin-scale variability with snow Conceptual design. A ground-based basin-scale design will consist of instrument clusters located along transects. The clusters will sample the main variables controlling snow distribution & melt, i.e. elevation, aspect, vegetation & in some cases, distance to a major ridge (wind effects). Each cluster will extend over 1-2 km distance, & include 10-20 snow depth & soil moisture measurement nodes. On the order of 20 clusters will be deployed across a basin, taking advantage of existing snow & meteorological sites where possible. Missing elements & enabling technology. The current ground-based measurement system for snow, designed for statistical water-supply seasonal forecasts, does not provide representative measurements of snow depth or water equivalent. A system of continuous representative measurements using low-cost technology, when blended with accurate satellite snow-cover data, can provide an accurate, real-time estimate of spatial snow amounts. Three elements have recently come together that make deployment of a full-basin-scale measurement & information system feasible: i) accurate, sustained satellite estimates of snow covered area across mountain watersheds, ii) reliable, low-cost sensors & telemetry systems for snow and soil moisture, and iii) cyberinfrastructure advances to integrate data & deliver it in near real time. Daily snow water equivalent estimates by elevation band (cumulative amount melted) for Tuolumne R. basin, 2004. Melt is based on time series satellite snowcover & energy balance, estimated after snow has depleted. Accurate real-time forecast s require augmentation of existing, sparse snow telemetry data to estimate snow water equivalent across basin. UC contact: Roger Bales, Sierra Nevada Research Institute, UC Merced, rbales@ucmerced.edu Bias in April 1 forecasts (underforecast) for July-April unimpaired runoff for 15 Sierra Nevada basins. 2005 was about 150% of average accumulation, i.e. a wet year. Snow depth sensor with radio

2. Scenario for ground-based instrument deployment in American River basin, with existing instrumentation, land ownership & wilderness Real-time Sierra Nevada water monitoring system Meteorological station Snow pillow Snow course Wilderness boundary New instrument cluster Basin boundary Highway USFS land 1-25 26-50 51-75 76-100 % SCA Installing soil moisture probes Use of snow products in decision support Interpolated snow water equivalent from ground-based measurements, masked by satellite snow-covered area, gives much more accurate estimate of snowpack water volume across a basin than does use of point snow pillow data alone. Expected outcomes. Deployment of a full-scale basin system will inform water management in that basin, form the core of a new water information system for the Sierra Nevada, serve as a testbed for further deployment & provide data needed for research & development to modernize forecasting & decision-support systems. The resulting approach for estimating snowpack is robust relative to climate change, will improve forecast accuracy & will serve the state for decades to come.