MODIS satellite image of Sierra Nevada snowcover Big data and mountain water supplies Roger Bales...
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Transcript of MODIS satellite image of Sierra Nevada snowcover Big data and mountain water supplies Roger Bales...
MODIS satellite image of Sierra Nevada snowcover
Big data and mountain water
supplies
Roger BalesSNRI, UC Merced
& CITRIS
Example: forecasting the amount & timing of spring/summer snowmelt runoff in mountain rivers
Uses of data: hydropower scheduling, water allocations for agriculture & cities, dam operations, forest management, drought & flood planning
Past : reliance on historical runoff data, measurements at a few index sites, statistical correlations
Future: blending data from satellites, wireless sensor networks, advanced modeling tools
Available now: technology, satellite data, prototype ground data, strong community interest
Missing pieces: operational-quality wireless sensor networks, cyberinfrastructure to clean/integrate data & deliver custom information for decision support
R. Bales
infiltration
evapotranspiration
snowmelt
streamflow
sublimation
ground & surface water exchange
precipitation
Water balance – fluxes Reservoirs: Snowpack storageSoil-water storage
Myths:
We can, with a high degree of skill, estimate or predict the magnitude of these fluxes & reservoirs
Better hydrologic modeling using existing data sources will yield significant improvement
R. Bales
Example: forecasting the amount & timing of spring/summer snowmelt runoff in mountain rivers
Uses of data: hydropower scheduling, water allocations for agriculture & cities, dam operations, forest management, drought & flood planning
Past : reliance on historical runoff data, measurements at a few index sites, statistical correlations
Future: blending data from satellites, wireless sensor networks, advanced modeling tools
Available now: technology, satellite data, prototype ground data, strong community interest
Missing pieces: operational-quality wireless sensor networks, cyberinfrastructure to clean/integrate data & deliver custom information for decision support
R. Bales
Observed changes in water cycle go beyond historical levels
Knowles et al.,2006
-2.2 std devsLESS as snowfall
+1 std devMORE as snowfall
less snow more rain
Mote, 2003
TRENDS (1950-97) in April 1 snow-water content at
western snow courses
less spring snowpack
earlier snowmelt
Stewart et al., 2005
Combined stresses:Climate warmingLandcover changePopulation pressures
R. Bales
Example: forecasting the amount & timing of spring/summer snowmelt runoff in mountain rivers
Uses of data: hydropower scheduling, water allocations for agriculture & cities, dam operations, forest management, drought & flood planning
Past : reliance on historical runoff data, measurements at a few index sites, statistical correlations
Future: blending data from satellites, wireless sensor networks, advanced modeling tools
Available now: technology, satellite data, prototype ground data, strong community interest
Missing pieces: operational-quality wireless sensor networks, cyberinfrastructure to clean/integrate data & deliver custom information for decision support
R. Bales
Empirical & regressionmethods
Volume forecasts
Precipitation forecast
Decision making
Ground data
Seasonal water-supply forecasting – current
R. Bales
Example: forecasting the amount & timing of spring/summer snowmelt runoff in mountain rivers
Uses of data: hydropower scheduling, water allocations for agriculture & cities, dam operations, forest management, drought & flood planning
Past : reliance on historical runoff data, measurements at a few index sites, statistical correlations
Future: blending data from satellites, wireless sensor networks, advanced modeling tools
Available now: technology, satellite data, prototype ground data, strong community interest
Missing pieces: operational-quality wireless sensor networks, cyberinfrastructure to clean/integrate data & deliver custom information for decision support
R. Bales
Energy balance modeling scheme
solar longwavemeteorological
data albedo vegetation
xy
t
snow
energybalancemodel
vegetation
topographysoils
data cube precipitation
Time
SWEpixel by
pixel SWE & SCA
pixel by pixel runoff potential
keep it simple – but not too simple!
here is where the big data & information processing comes in
R. Bales
Example: forecasting the amount & timing of spring/summer snowmelt runoff in mountain rivers
Uses of data: hydropower scheduling, water allocations for agriculture & cities, dam operations, forest management, drought & flood planning
Past : reliance on historical runoff data, measurements at a few index sites, statistical correlations
Future: blending data from satellites, wireless sensor networks, advanced modeling tools
Available now: technology, satellite data, prototype ground data, strong community interest
Missing pieces: operational-quality wireless sensor networks, cyberinfrastructure to clean/integrate data & deliver custom information for decision support
R. Bales
lidar
A new generation of integrated measurements
satellite snowcover
low-cost sensors
Process research & advanced modeling tools
wireless sensor
networks
R. Bales
Example: forecasting the amount & timing of spring/summer snowmelt runoff in mountain rivers
Uses of data: hydropower scheduling, water allocations for agriculture & cities, dam operations, forest management, drought & flood planning
Past : reliance on historical runoff data, measurements at a few index sites, statistical correlations
Future: blending data from satellites, wireless sensor networks, advanced modeling tools
Available now: technology, satellite data, prototype ground data, strong community interest
Missing pieces: operational-quality wireless sensor networks, cyberinfrastructure to clean/integrate data & deliver custom information for decision support
R. Bales
Basin-wide deployment of hydrologic instrument clusters – American R. basin
Strategically place low-cost sensors to get spatial estimates of snowcover, soil moisture & other water-balance components
Network & integrate these sensors into a single spatial instrument for water-balance measurements.
in progress
R. Bales