2012 AGU Chapman Conference on Remote Sensing of the ...

But this is not confirmed by remote sensing data, thoseresults seem to be out of phase with the change of shoreline,in the other word in a given year the time of peak andbottom of the water level and mass is not coinciding withprogression and regression of water into the land, whichseems to indicate that an increase in water extent of CaspianSea is not directly linked to the water elevation and mass; themismatch might be caused by change in convexity of watersurface.Data Used ListMajor dataset, (GIS layers are not mentioned here)Moran, Thomas C.Comparing annual evapotranspiration estimatesderived from remote sensing and surfacemeasurement for water-limited catchments inCaliforniaMoran, Thomas C. 1 ; Hahn, Melanie 1 ; Agarwal, Deb 2 ; vanIngen, Catharine 3 ; Baldocchi, Dennis D. 1 ; Hunt, James R. 11. University of California, Berkeley, CA, USA2. Lawrence Berkeley National Laboratory, Berkeley, CA,USA3. Formerly of: Microsoft Bay Area Research Center,Microsoft Research, San Francisco, CA, USAQuantifying the partitioning of precipitation intoevapotranspiration (ET), surface runoff, and othercomponents is a long-standing goal of the hydrologicsciences given its importance to ecosystems and watermanagement. In particular, the challenges of accurateestimation of ET include direct measurement of water vaporfluxes, spatial heterogeneity, and uncertainty in thecontrolling processes. As a consequence, this is an active areaof research with various approaches. An increasing numberof eddy covariance flux towers provide reliable pointmeasurements of ET that are used to validate or calibrateother methods. At the catchment scale, a water balance canbe applied to estimate net ET. When rainfall, surface runoff,and subsurface components are well-characterized, ET canbe estimated with quantifiable confidence. Satellite remotesensing offers the promise of near real-time global ETestimates with spatial resolution near 1 sq km. To fullyrealize the potential of this approach, we must describe itsaccuracy and applicability in addition to its many benefits.Our research group has processed water balance data formore than one thousand catchments in California usingprecipitation and streamflow records that span more than acentury. From this data set, a subset of over 100 catchmentsare sufficiently well-characterized so that estimation ofannual ET depth takes on the straightforward form ET = P -R, where P and R denote precipitation and runoff depth,respectively. This simplification is justified by the distinctwet and dry seasons of California’s Mediterranean climate,and it is supported by limited changes in groundwaterstorage from year to year. The study catchments cover thediversity of California climate zones and the data yearsinclude extreme variations in precipitation. These waterbalance estimates of annual ET are compared with fluxtower measurements to establish consistency between thetwo methods. We then examine remotely-sensed ET datafrom three independent research groups: the GlobalEvapotranspiration project at the University of Montana(Zhang, et al., 2009, WRR, doi:10.1029/2009WR008800); thenear-real-time global evapotranspiration data product fromthe University of Washington (Tang, et al., 2009, JGR,doi:10.1029/2008JD010854) and the Breathing Earth SystemSimulator model from UC Berkeley (Ryu, et al., GlobalBiogeochemical Cycles (in review)). In particular, we focus onthe performance of these remotely based estimates forconditions when annual ETxs is limited by water availability,106