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USGS Mendenhall Postdoctoral  Research Fellowship Program

14-5. Application of Remotely Sensed Data for Improved Simulation of Hydrologic Processes

The intent of this postdoctoral position is to integrate hydrologic modeling with remote sensing research being conducted within and outside of USGS.  This project presents the opportunity for a strong scientist with a background in hydrology and remote sensing to explore the archive of remotely sensed products from the Earth Resources Observation Systems (EROS) Data Center ( to understand better the uncertainty in remote sensing products and to apply their use to hydrological simulation via the Precipitation Runoff Modeling System (PRMS).  PRMS is currently being implemented within a National Hydrologic Model (NHM) structure based on aggregated NHDPlus ( catchments for the contiguous United States (CONUS).  Many hydrological state variables and fluxes can be estimated and evaluated through satellite remote sensing. PRMS integrated with remotely sensed products can provide information for spatial and temporal domains which are crucial for research, development, and application at the national scale.

Integration of remotely sensed products with simulation models, aided by the data retrieval and processing capabilities now accessible through the Geo Data Portal (GDP;, will greatly enhance the NHM to support coordinated, comprehensive, and consistent hydrologic model development for numerous programs within each of the USGS mission areas ( ). Making remotely-sensed products easily accessible to a larger number of scientists through the GDP is an important component of this research. Use of the GDP will enhance efforts of the postdoctoral fellow as well as provide a lasting legacy by making data resources that are otherwise difficult to access and manipulate available to scientists and environmental resource managers.  The ultimate goal of this integration is to use the best available data sets and information to improve physically-based hydrologic modeling.

We invite applicants to submit innovative research proposals addressing the needs described in this Research Opportunity.  Although the proposed topics span a wide range of scientific issues, the common factor is the use of remotely sensed products to improve hydrologic simulation. As such, the project will involve the analysis of remotely sensed data products, hydrologic model development, and data integration and model analysis. The postdoctoral fellow is invited to examine data integration and model analysis in terms of:  estimating best-fit parameters, identifying data importance in relation to model performance, quantifying parameter and prediction uncertainty, and exploring model structural adequacy.

Issues that may be addressed within the course of the project to improve hydrologic modeling applications across the CONUS may include (but are not limited to) the integration of these data products:

  1. Growing Season -- output from the Remote Sensing Phenology program ( that describes temporal and spatial aspects of the annual growing season over the CONUS.
  2. Actual Evapotranspiration (AET) – output from two independent AET models at EROS based on the Normalized Difference Vegetation Index dynamics (VegET) and satellite Land Surface Temperature (SSEBop).
  3. Historic Land Cover -- a database of historic land cover at EROS dating back to 1939 on an annual time step and a 250m grid resolution.
  4. Fire-Scarred Landscape -- the Monitoring Trends in Burn Severity (MTBS; fire scars data set that contains information on the burn severity and perimeters of fires across the CONUS for 1984 through 2010.
  5. Vegetation Disturbances -- annual ecosystem performance and anomaly measures on a 250m grid from 2001-2010 in the Greater Platte and Upper Colorado basins.
  6. Data Integration and Model Analysis – use models to evaluate model adequacy and identify data importance to model parameters and predictions of interest, including issues of uncertainty.


Blodgett, D., Booth, N., Kunicki, T., Walker, J., Lucido, J., 2012. Description of the U.S. Geological Survey Geo Data Portal Data Integration Framework. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal, v.5, no.6, 1687-1691.

Foglia L., Hill, M.C.,  Mehl, S.W.,  Burlando, P., 2009. Sensitivity analysis, calibration, and testing of a distributed hydrological model using error-based weighting and one objective function. Water Resour. Res., v. 45.

Gupta H.V., Clark, M.P., Vrugt, J.A., Abramowitz, G., Ye, M., 2012. Towards a comprehensive assessment of model structural adequacy: Water Resour. Res., v. 48.

Hay, L.E., Leavesley, G.H., and Clark, M.P., 2006. Use of remotely-sensed snow covered area in watershed model calibration for the Sprague River, Oregon. Joint 8th Federal Interagency Sedimentation Conference and 3rd Federal Interagency Hydrologic Modeling Conference, April 2-6, 2006, Reno, Nevada.

Hill M.C., Tiedeman C.R., 2007. Effective groundwater model calibrations, with analysis of data, sensitivities, predictions, and uncertainty: Wiley, New York,  396-398.

Markstrom, S.L., Niswonger, R.G., Regan, R.S., Prudic, D.E., and Barlow, P.M., 2008. GSFLOW-Coupled Ground-water and Surface-water FLOW model based on the integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005). U.S. Geological Survey Techniques and Methods 6-D1, 240 p.

Rigge, M., Wylie, B., Gu, Y., Belnap, J., Phuyal, K., Tieszen, L., 2013, Monitoring the status of forests and rangelands in the Western United States using ecosystem performance anomalies, International Journal of Remote Sensing, 34:11, 4049-4068.

Senay, G.B., S. Bohms, R. Singh, P. Gowda, N. M.Velpuri, H. Alemu and J. Verdin, 2012. 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. Hydrol. Process., v. 25, 4037–4049.

Velpuri, N.M., and Senay, G.B., 2012. Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data. Hydrology and Earth System Sciences, v. 16, no. 10, 3561-3578.

Viger, R. J., Hay, L. E.; Jones, J. W.; Buell, G. R., 2010. Effects of including surface depressions in the application of the Precipitation-Runoff Modeling System in the Upper Flint River Basin, Georgia. U.S. Geological Survey Scientific Investigations Report 2010-5062, viii, 37 p.

Viger, R. J., Leavesley, G. H., 2007. Section 4. The GIS Weasel User's Manual. Geological Survey (U.S.) Techniques and Methods 6-B4, viii, 201 p.

Wagner, W. Verhoest, N. E. C., Ludwig, R., and Tedesco, M., 2009.  Remote sensing in hydrological sciences. Hydrol. Earth Syst. Sci., v. 13, 813–817.

Proposed Duty Station: Lakewood, CO; Boulder, CO

Areas of Ph.D.: Hydrology, geography, remote sensing, or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).

Qualifications: Applicants must meet one of the following qualifications - Research Civil Engineer, Computer Scientist, Environmental Engineer, Research Geographer, Research Hydrologist, Research Mathematician or Research Physical Scientist.

(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 Advisor(s): Lauren Hay, (303) 236-7279,;  Steven Markstrom, (303) 236-3330,;  Steven Regan, (303) 236-5008,;  Roland Viger (303) 541-3075,;   Jesslyn Brown, (605) 594-6003,;  Gabriel Senay, (605) 594-2758,; Terry Sohl, (605) 594-6537,; Bruce Wylie, (605) 594-6078,; Todd Hawbaker, (303) 236-1371,;  Nate Booth, (608) 821-3822,;  David Blodgett, (608) 821-3899,;  Mary C. Hill, (303) 541-3014,

Human Resources Office Contact: Jennifer Daberkow, (303) 236-9566,

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