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William P Kustas (Bill)

Hydrologist
 /ARSUserFiles/3166/images/Kustas_web.jpg William P. Kustas, Ph.D.
Research Hydrologist
USDA-ARS Hydrology and Remote Sensing Laboratory
Bldg. 007, Rm. 104, BARC-West
Beltsville, MD 20705-2350 USA
Voice: (301) 504-8498
Fax: (301) 504-8931
Bill.Kustas@usda.gov

 

Research Interests: (click here to see a list of current research projects)


Education:


Professional Experience:


Honors and Awards:


Committee Memberships and Offices held in AMS and other Scientific Organizations:


Editorial Appointments:


Contributions, Impact and Stature:

Dr. Kustas has over 390 scientific publications of which 265 appear in peer reviewed journals and 21 are book chapters. He is recognized world-wide as the leading expert in remote sensing applications for modeling land surface fluxes and soil-vegetation-atmosphere interactions. His international standing and scientific stature in remote sensing research was cited in Scientometrics (96:203-209, 2013) where a bibliometric analysis ranked him 5th most productive out of the top 20 remote sensing authors world-wide and in the top 10 in research impacts using three different citation metrics. In addition, in 2020 he was included by Stanford University scientists in a publication of a comprehensive list that identified the top 2% of scientists worldwide. The ISI Web of Science citation report computes an h-index of 74, and Google scholar computes an h-index of 90 for Dr. Kustas, exceeding most of his peers in remote sensing and hydrology.  He has mentored 30 postdoctoral and visiting scientists (4 ARS-funded postdoctoral positions) and 10 M.S. and 14 PhD students. He currently serves on 3 PhD committees and supervises and mentors 2 postdocs.  He has been awarded research grants from NASA and USDA totaling nearly $5 million in support for his research, particularly leading large-scale multidisciplinary experiments selected through peer-review. A key component of these projects was the leadership of large multidisciplinary teams. As principal investigator (PI)/Co-PI, Dr. Kustas designed and coordinated large scale interdisciplinary remote sensing field experiments supported by NASA/USDA in Arizona (Monsoon 90), Oklahoma (Washita 92 Washita 94, SGP 97, SGP 99, CLASIC07), Iowa (SMACEX/SMEX02), Texas (BEAREX08), and California (GRAPEX). These have involved the coordination of field- and post-experiment research activities, including multiple aircraft, for dozens of scientists, postdocs and graduate students. The resulting research has made break-through contributions to basin and regional hydrologic and atmospheric modeling using remote sensing.


Publication Databases:


Selected Publications: (please contact the author to determine reprint availability)

(view author's publications/interpretive summaries/technical abstracts since 1999)

Brutsaert, W. and Kustas, W. P.  Surface water vapor and  momentum fluxes under unstable conditions from a rugged-complex area.  J. Atmos. Sci. 44:421-431.  1987.

Kustas, W. P. and Brutsaert, W.  Budgets of water vapor in the unstable boundary layer over rugged terrain.  J. Clim. Appl. Meteorol. 26:607-620. 1987.

Kustas, W. P. and Daughtry, C. S. T.  Estimation of the soil heat flux/net  radiation ratio from spectral data.  Agric. Forest  Meteorol. 49:205-223. 1990.

Kustas, W. P.  Estimates of evapotranspiration with a one- and two-layer model of heat transfer over partial canopy cover.  J. Appl. Meteorol.  29:704-715. 1990.

Kustas, W. P., Goodrich,  D. C. and  Moran M. S., et al.  An interdisciplinary field study of the energy and water fluxes in the atmosphere- biosphere system over semiarid rangelands: Description and some preliminary results, Bull. Amer. Meteorol. Soc. 72:1683-1705. 1991.

Kustas, W. P., Hipps, L. E. and Humes, K. S. Calculation of basin-scale surface  fluxes by combining remotely sensed data and atmospheric properties in a semiarid landscape.  Bound. -Layer Meteorol. 73:105-124. 1995.

Norman, J. M., Kustas, W. P., and Humes, K. S.  A two-source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperature. Agric. Forest Meteorol. 77:263-293. 1995.

Kustas, W. P. and  Norman, J. M. A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations. Water Resour. Res. 33:1495-1508.  1997.

Kustas, W. P., Zhan, X. and Schmugge, T. J.  Combining optical and microwave remote sensing for mapping energy fluxes in a semiarid watershed.  Remote Sens. Environ. 64:116-131.  1998.

Kustas, W. P. and Norman, J. M.  Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover.  Agric. Forest Meteorol. 94:13-29. 1999

Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R., Meyers, T. P., Prueger, J. H., Starks, P. J. and Wesely, M. L. Correcting eddy-covariance flux underestimates over a grassland.  Agric. For. Meteorol.  103: 279-300. 2000.

Norman, J.M., Kustas, W. P., Prueger,  J.H. and Diak, G.R. Surface flux estimation using radiometric temperature: a dual temperature difference method to minimize measurement error.  Water Resour. Res.  36:2263-2274. 2000.  

Kustas, W. P. and Norman, J. M. A two-source energy balance approach using directional radiometric temperature observations for sparse canopy covered surfaces. Agron. J. 92:847-854. 2000.

Kustas, W. P. and Norman.  J. M. Evaluating the effects of sub-pixel heterogeneity on pixel average fluxes.  Remote Sen. Environ. 74:327-342. 2000

Zhan, X. and Kustas, W.P. A coupled model of land surface CO2 and energy fluxes using remote sensing data. Agric. For. Meteorol. 107:131-152. 2001.

Albertson, J. D., Kustas, W.P. and  Scanlon, T. M.  Large eddy simulation over heterogeneous terrain with remotely sensed land surface conditions.  Water Resour. Res.  37(7):1939-1953. 2001.

Kustas, W.P., Prueger J. H. and Hipps, L.E.  Impact of using different time-averaged inputs for estimating sensible heat flux of riparian vegetation using radiometric surface temperature.  J. Appl. Meteorol. 41:319-332. 2002.

Kustas W.P., Bindlish, R., French, A. N., and Schmugge, T. J. Comparison of energy balance modeling schemes using microwave-derived soil moisture and radiometric surface temperature.  Water Resour. Res.  30:1039-1049. 2003.

Kustas, W.P. and Albertson, J.D. Effects of surface temperature contrast on land-atmosphere exchange: A case study from Monsoon 90. Water Resour. Res. 39(6), 1159. doi: 10.1029/2001WR001226. 2003.

Kustas, W.P., Anderson, M.C., Norman, J.N. and French, A.N.  Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship. Remote Sen. Environ. 85:429-440. 2003.

Kustas, W.P., Li, F., Jackson, T.J., Prueger, J.H., MacPherson, J.I., Wolden, M. Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa.  Remote Sens. Environ. 92:535-547. 2004.

Crow, W.T. and Kustas, W.P. Utility of assimilating surface radiometric temperature observations for evaporative fraction and heat transfer coefficient retrieval. Bound.-Layer Meteorol. 115:105-130.  2005

Li, F., Kustas, W.P., Prueger, J.H., Neale, C.M.U. and Jackson, T.J. Utility of remote sensing based two source energy balance model under low- and high- vegetation cover conditions. J. Hydromet. 6:878-891. 2005.

Kustas, W.P., Prueger, J.H., MacPherson, J.I., Wolde, M. and  Li F. Effects of land use and meteorological conditions on local and regional momentum transport and roughness for midwestern cropping systems. J. Hydromet. 6:825-839. 2005.

Kustas, W.P., Anderson, M.C., French, A.N., Vickers, D.  Using a remote sensing field experiment to investigate flux footprint relations and flux sampling distributions for tower and aircraft based observations. Adv. Water Resour. 29:355-368.2006.

Kustas, W.P., Anderson, M.C., Norman, J.M. and Li, F. Utility of radiometric aerodynamic temperature relations for heat flux estimation. Bound.- Layer Meteorol. 122:167-187. 2007.

Anderson, M.C., Kustas, W.P. and Norman, J.M.  Upscaling tower and aircraft fluxes from local to continental scales using thermal remote sensing. Agron. J. 99:240 254. 2007.

Li, F., Kustas, W.P., Anderson, M.C., Prueger, J.H. and Scott, R.L. Effect of remote sensing spatial resolution on interpreting tower based flux observations.  Remote Sens. Environ. 112: 337 349. 2008.

Agam, N., Kustas, W.P., Anderson, M.C., Li, F. and Colaizzi, P.D. Utility of thermal image sharpening for monitoring field scale evapotranspiration over rainfed and irrigated agricultural regions. Geophys. Res. Letters. 35, L02402, doi:10.1029/2007GL032195. 2008.

Crow, W.T., Kustas, W.P. and Prueger, J.H. Monitoring root zone soil moisture though the assimilation of a thermal remote sensing based soil moisture proxy into a water balance model. Remote Sens.Environ. 112(4):1268-1281. 2008.

Bertoldi, G., Kustas, W.P. and Albertson, J.D. Estimating spatial variability in atmospheric properties over remotely sensed land surface conditions. J. Appl. Meteorol. 47: 2147-2165. 2008.

Kustas, W.P., and Anderson, M.C. Advances in thermal infrared remote sensing for land surface modeling. Agric. Forest Meteorol. 149: 2071–2081. 2009.

Agam, N., Kustas, W.P., Anderson, M.C., Norman, J.M. et al. Application of the Priestly-Taylor approach in a two-source surface energy balance model.  J. Hydromet. 11 :185-198. 2010.

Scanlon, T.M., and Kustas, W.P., Partitioning carbon dioxide and water vapor fluxes using correlation analysis. Agric. Forest Meteorol. 150: 89–99. 2010.

Li, F., Crow, W.T., and Kustas, W.P., Towards the estimation of root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals, Adv. Water Resour., 33: 201-214. 2010.

Anderson, M. C., Kustas, W. P., Norman, J. M., Hain, C. et al.  Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery.  Hydrol. Earth Syst. Sci., 15, 223–239, 2011.

Anderson M.A., Kustas, W.P., Alfieri, J.G., Gao, F., Hain. C. et al. Mapping daily evapotranspiration at Landsat spatial scales during the BEAREX08 field campaign. Adv. Water Resour. 50:162–77. 2012.

Bertoldi, G., Kustas, W.P. and Albertson, J.D. Evaluating source area contributions from aircraft flux measurements over heterogeneous land cover by large eddy simulation. Bound-Layer Meteorol. 147:261-279. 2013.

Kongoli, C., Kustas, W.P., Anderson, M.C., Norman, J.M. et al.  Evaluation of a two-source snow-vegetation energy balance model for estimating surface energy fluxes in a rangeland ecosystem.  J. Hydromet. 15(1): 143-158. 2014.

Kustas, W.P., Alfieri, J.G., Agam, N. and Evett, S.R. Reliable estimation of water use at field scale in an irrigated agricultural region with strong advection. Irrig. Sci. DOI 10.1007/s00271-015-0469-1. 2015.

Ting, X., Kustas, W.P., Anderson, M.C., Alfieri, J.G. et al. Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes Hydrol. Earth Syst. Sci. 20:1523-1545. 2016.

Cristobal, J., Prakash, A., Anderson, M.C., Kustas, W.P. et al. Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model. Hydrol. Earth Syst. Sci. 21 (3):1339-1358. https://doi.org/10.5194/hess-21-1339-2017. 2017.

Andreu, A., Kustas, W.P., Polo, M.J., Carrara, A. and Gonzalez-Dugo, M.P. Modeling surface energy fluxes over a dehesa (oak savanna) ecosystem using a thermal based Two-Source Energy Balance Model ( TSEB) I. Remote Sen. 10 (567). https://doi.org/10.3390/rs10040567. 2018.

Kustas, W.P., Anderson, M.C., Alfieri, J.G., Knipper, K. et al. The grape remote sensing atmospheric profile and evapotranspiration eXperiment (GRAPEX). Bull. Am Meteorol Soc 9:1791–1812. https://journals.ametsoc.org/doi/10.1175/BAMS-D-16-0244.1. 2018.

Knipper, K.R., Kustas, W.P., Anderson, M.C. et.al. Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards. Irrig. Sci. https://doi.org/10.1007/s00271-018-0591-y. 2018.

Kustas, W.P., Alfieri, J.G., Nieto, H., Gao, F., et al. Utility of the two-source energy balance model TSEB in vine and inter-row flux partitioning over the growing season. Irrig. Sci. https://doi.org/10.1007/s0027 1-018-0586-8. 29018. 2018

Nieto, H., Kustas, W.P., Torres-Rúa, A., Alfieri, J.G. et al. Evaluation of TSEB turbulent fluxes using different methods for the retrieval of soil and canopy component temperatures from UAV thermal and  multispectral imagery. Irrig. Sci. https://doi.org/10.1007/s0027 1-018-0585-9. 2018.

Li, Y., Kustas, W. P., Huang, C., Nieto, H., Haghighi, E., Anderson, M. C. et al. Evaluating soil resistance formulations in thermal-based two-source energy balance (TSEB) model: Implications for heterogeneous semiarid and arid regions. Water Resour. Res. 55:1059–1078. https://doi.org/10.1029/2018WR022981. 2019.

Kool, D., Kustas, W.P., Ben-Gal,A., Agam, N. Energy partitioning between plant canopy and soil, performance of the two-source energy balance model in a vineyard Agric.  Forest Meteorol. https://doi.org/10.1016/j.agrformet.2021.108328. 2020.

Li, Y., Huang, Ch., Kustas, W.P., Nieto, H., Sun, L., Hou, J. Evapotranspiration partitioning at field scales using TSEB and multi-satellite data fusion in the middle reaches of Heihe river basin, northwest China. Remote Sens. https://doi.org/doi:10.3390/rs12193223. 2020.

Song, L., Ding, L., Kustas, W.P., Xu,Y., Liu, S. et al. Applications of a thermal-based two-source energy balance model coupled to surface soil moisture Remote Sens. Environ. https://doi.org/10.1016/j.rse.2022.112923. 2021.

Kustas, W.P., Nieto, H., Garcia-Tejera, O., Bambach, N. et  al.  Impact of advection on Two-Source Energy Balance (TSEB) canopy transpiration parameterization for vineyards in the California Central Valley.  Irrig. Sci. https://doi.org/10.1007/s00271-022-00778-y  2022.

Burchard-Levine, V., Nieto, H., Riaño, D., Kustas, W. P. et al. A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems. Global Change Bio. 28(4), 1493–1515. https://doi.org/10.1111/gcb.16002. 2022.



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