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USGS Mendenhall Postdoctoral  Research Fellowship Program

14-7. Combining Water-Balance and Remotely Sensed ET Estimation Methods

Evapotranspiration (ET) is a major component of the hydrologic cycle.  In most places in the United States more than half of precipitation is consumed by ET, and with increasing global temperatures that percentage is predicted to increase. Quantifying ET is therefore important if we are to predict available water and its potential future decline.   In spite of the important role of ET, it is not easy to measure at large spatial and temporal scales.  Water-balance and remotely sensed estimates of ET have received the most attention to date, but both methods have their advantages and disadvantages.  We seek a postdoctoral fellow to help develop ways of combining water-balance and remotely sensed ET measurements to produced improved estimates at monthly and annual time scales across large regions.

Water-balance methods are based on the assumption that the hydrologic budget of a watershed can be represented as the amount of precipitation minus ET minus outflow being equal to the change in storage.  For long (multi-year) time periods the change in storage can assumed to be negligible and ET can be calculated as the mean precipitation minus the mean streamflow out of the watershed (Sanford and Selnick, 2013).  Most remotely sensed methods are based on the assumption that the emitted signals being received at the satellites can be converted to quantities that represent the ET flux, often using surface energy-balance principles (Senay and others, 2013).   These signals have been measured as virtual snapshots in time intermittently at high spatial resolutions over continental scales for the past decade or so, and for the United States have been typically validated against eddy correlation ET estimates from the Ameriflux tower network:

The USGS seeks to develop accurate ET maps for the country at monthly and annual time scales. The challenge of using water-balance methods for this product is that these time scales have nontrivial changes in subsurface storage within basins that are difficult to quantify and lead to increased uncertainty in ET estimates.  The challenge of using remotely-sensed methods for this product is that these times scales require aggregation of several temporal “snapshots” and are limited by a small observation dataset for calibration/validation, leading to increased uncertainty in ET estimates.  A combination these two methods could help reduce uncertainty in the ET estimates for the desired monthly or annual time-averaged values (Senay and others, 2011).  The incorporation of robust climate data with broad coverage, such as the PRISM climate dataset (Daly and others, 2008), is certainly to be a necessary component of the improved calibration procedure.

The USGS also seeks to develop a method where hydrologic budget components (including ET) are quantified routinely and continually on a month-average basis and displayed on a county- or watershed-based map of a state or region.  The one-month time interval is convenient because mean precipitation data available at this temporal scale through the PRISM climate data center.  However, the challenge to the monthly time interval is that it requires the incorporation of seasonal change in subsurface storage.  To overcome this challenge it is proposed to use improved remotely sensed ET estimates.  The USGS Earth Resources Observation and Science Center (EROS) has been producing 1-km, monthly ET for the conterminous US since 2000.  These ET estimates could be improved by calibrating against watersheds with plentiful streamflow data over longer time periods where subsurface storage change is negligible.  Monthly budgets could be then be made on those same watersheds.  In addition, landscape parameters for runoff and recharge could be calibrated and used to help separate surface runoff from recharge.  The improved ET and recharge equations could then be used to extend the estimation of the monthly hydrologic components for all areas of interest.  The state of Virginia would be an ideal first site of this research, because of the long-term hydrologic budget components recently estimated for the state (Sanford and others, 2012).  Virginia also provides a wide variety of climates, terrains, and land covers (temperate coastal plain to continental mountains; forest, agriculture, and impervious surfaces) over which to test the ET calibration and estimation procedures.

The challenge of this aspect of the research is to find a compromise where rather simple transient budget calculations based on water balance can be coupled with high-resolution (monthly averaged PRISM) precipitation and remotely sensed ET data.  Monthly data sets would need to be able to be calculated on a routine basis as soon as the previous month’s precipitation and ET data become available.  Remotely sensed ET from Landsat and/or MODIS data will be a principal component of the method being developed, as well as PRISM climate data.  The timing for this research project is excellent because of the recent launch of Landsat 8, and because USGS EROS is about to release a monthly MODIS ET product online for access through the THREDDS server under the USGS Water SMART project.


Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J., and Pasteris, P. P., 2008, Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States> :   International Journal of Climatology, v. 28, no 15, p. 2031-2064.

Sanford, W. E., Nelms, D. L., Pope, J. P., and Selnick, D. L., 2102, Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis: U. S. Geological Survey Scientific Investigations Report 2011-5198, 152 p.

Sanford, W. E., and Selnick, D. L., 2013, Estimation of actual evapotranspiration across the conterminous United States using a regression based on climate and land-cover data:  Journal of the American Water Resources Association, v. 49, no. 1, p. 217-230.

Senay, G., Bohms, S., Singh, R., Gowda, P., Velpuri, N., Alema, H., and Verdin, J., 2013, Operational evapotranspiration modeling using remote sensing and weather datasets – a new parameterization for the SSEB ET approach:  Journal of the American Water Resources Association (in press).

Senay, G. B., Leake, S., Nagler, P. L., Artan, G., Dickinson, J., Cordova, J. T., and Glenn, E. P., 2011, Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods: Hydrological Processes, v. 25, p. 4037-4049.

Proposed Duty Station:  Reston, VA; Sioux Falls, SD

Areas of PhD:  Hydrology, Remote Sensing, Physical Geography, or related fields (candidates holding Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).

Qualifications:  Research Hydrologist, Research Physical Scientist, Research Geographer.

(This type of research is performed by those who have backgrounds for the occupations stated above.  However, other titles may be applicable depending on the applicant’s background, education, and research proposal.  The final classification of theposition will be made by the Human Resources specialist).

Research Advisors:  Ward Sanford, (703) 648-5882,; Gabriel Senay, (605) 594-2758,

Human Resources Office Contact: Junell Norris, (303) 236-9557,

Go back to Summary of Opportunities

U.S. Department of the Interior, U.S. Geological Survey
URL: Sanford.htm
Direct inquiries to Rama K. Kotra at
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Last modified: 17:58:10 Tue 23 Jul 2013
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