MODIS satellite image of Sierra Nevada snowcover
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Transcript of MODIS satellite image of Sierra Nevada snowcover
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MODIS satellite image of Sierra Nevada snowcover
Big data and mountain water
supplies
Roger BalesSNRI, UC Merced
& CITRIS
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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
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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
![Page 4: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/4.jpg)
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
![Page 5: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/5.jpg)
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
![Page 6: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/6.jpg)
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
![Page 7: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/7.jpg)
Empirical & regressionmethods
Volume forecasts
Precipitation forecast
Decision making
Ground data
Seasonal water-supply forecasting – current
R. Bales
![Page 8: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/8.jpg)
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
![Page 9: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/9.jpg)
Energy balance modeling scheme
solar longwavemeteorological
data albedo vegetation
xy
t
snow
energybalancemodel
vegetationtopography
soils
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
![Page 10: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/10.jpg)
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
![Page 11: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/11.jpg)
lidar
A new generation of integrated measurements
satellite snowcover
low-cost sensors
Process research & advanced modeling tools
wireless sensor
networks
R. Bales
![Page 12: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/12.jpg)
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
![Page 13: MODIS satellite image of Sierra Nevada snowcover](https://reader035.fdocuments.in/reader035/viewer/2022062501/5681691a550346895de0398e/html5/thumbnails/13.jpg)
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
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Turning unknowns into knows through new water information systems
Research support: NSF, NASA, CA-DWR, SCE, CITRIS
R. Bales