CLOUD COMPUTING FOR DROUGHT MONITORING WITH GOOGLE EARTH ENGINE Landsat 8 John Abatzoglou Katherine Hegewisch Alex Peterson Donny VanSant Rick Allen Ayse Kilic Tyler Erikson David Thau Noel Gorelick Rebecca Moore Mike Hobbins Jim Verdin Justin Huntington Britta Daudert Charles Morton Dan McEvoy Andy Joros Landsat 8
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Cloud Computing for Drought Monitoring with Google Earth Engine
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CLOUD COMPUTING FOR DROUGHT
MONITORING WITH GOOGLE EARTH ENGINE
Landsat 8 John Abatzoglou
Katherine Hegewisch
Alex Peterson
Donny VanSant
Rick Allen
Ayse Kilic
Tyler Erikson
David Thau
Noel Gorelick
Rebecca Moore
Mike Hobbins
Jim Verdin
Justin Huntington
Britta Daudert
Charles Morton
Dan McEvoy
Andy Joros
Landsat 8
Introduction• Collaboration with Google Earth Engine Team
• DRI and U-Idaho received two Google Earth Engine Faculty Research grants in 2014 to develop
software and provide guidance for monitoring of drought and evapotranspiration (ET)
• One of many results – a web application so anyone can process and visualize map and time series
and users can download results
MODIS April – October 2014 Median NDVI made with Earth Engine in about 7 seconds
Landsat for Vegetation Water Use and
Drought Monitoring• Remote sensing using Landsat is arguably the only way to detect vegetation stress and
ET at field scales over large areas
• Landsat pixel size (30m x 30m) is optimal for evaluating individual fields, riparian zones, and meadows (1985-pres)
• MODIS pixel size (250m x 250m) is optimal for regional analysis (2000-pres)
• To better understand if vegetation changes are natural or anthropogenic we need ~30+ years of satellite data, and paired with climate archives
• Better understanding vegetation and ET varies with climate at field and regional scales will increase the effectiveness of biological and hydrological monitoring plans, and drought monitoring
Landsat MODIS
Cloud Computing with Climate and Remote Sensing Data
• Develop a tool to better understand the long term spatial and temporal variability of ET from irrigated agriculture and groundwater dependent ecosystems (riparian areas, wetlands, springs)
• Rely on Landsat satellite imagery (16 day return intervals) to compute vegetation indices and energy balanced based ET
• Rely on gridded weather data to estimate PPT and ETo
• Problem – lots and lots of data and processing..
• 21 scenes for NV
• 1000+ Landsat images per path/row since 1985
• Equates to >20,000 images to process..
Google Earth Engine Cloud Computing• Google has the entire archive of Landsat and MODIS imagery and CFSR, NLDAS, and downscaled NLDAS
gridded weather data available for massive parallel processing in the cloud
• This technology has changed the paradigm of how we process and analyze satellite imagery and gridded
• Arlemont Ranch well (117 S01 E35 35CC 1) measured by NDWR
• Digitized polygon around well, ~ 0.25 miles across; is largerly comprised of greasewood
• Evaluated spatial average Aug-Sept NDVI, PRISM PPT, and water levels
• NDVI declining; GW levels declining
Avg. PPT = 5in/yr
Pre
cip
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orm
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2013 July-Aug Max NDVI 2014 July-Aug Max NDVI
Indian Valley supports the largest
Sage-Grouse lek in NV (i.e. aggregation
of males dancing for females)
Indian Valley, NV
Remote Sensing for Sage-Grouse Sensitive Areas
Capture of Groundwater Discharge
• Appropriation of the full perennial yield assumes capture all the natural groundwater discharge
• By design, long-term groundwater pumping causes a lowering of the water table and reduces groundwater ET (ETg)• Capture of ETg is put to beneficial use (for humans)
• Capture of ETg reduces vegetation vigor and biological diversity
• In most cases, groundwater appropriation is based on the ETg from phreatophyte vegetation
Sources of Water to a Pumped Well
0.9
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0.00 10 20 30 40 50 60
TIME, IN YEARS
FR
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GW storage
“Capture”
- capture of SW and ETg
Theis (1940) “All water discharged by wells is balanced by a loss of
water somewhere else”
“the idea of safe yield…in which the size
of a development if it is less than or equal
to the recharge is considered to be ‘safe’
is fallacious”
“Often streams are depleted long before
the pumping reaches the magnitude of
recharge.”
“…if pumping equals recharge (or discharge),
eventually streams, marshes, and springs dry up”
“Despite being discredited repeatedly in the literature,
safe yield continues to be used as the basis of water-
management policies, leading to continued ground-
water depletion, stream dewatering, and loss of
wetland and riparian ecosystems.”
Monitoring, Management, Mitigation (3M) Plans
• Baseline and future hydrologic and biological monitoring (~7yrs)
• Establishment of groundwater management actions• Staged development
• Trigger levels
• Pumping schedules
• Assess response of ecosystems to withdraw
• Refinement of unreasonable adverse effects
• Mitigation measures• Operational adjustment
• Change in pumping location
• Reduction in pumping / curtailment
• Provide alternative water source
Shoshone Ponds
Stipulation Requirements for Hydrologic Monitoring