|Kustas, William - Bill|
|Rango, Albert - Al|
Submitted to: Photogrammetric Engineering and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2002
Publication Date: 6/5/2003
Citation: Kustas, W.P., French, A.N., Hatfield, J.L., Jackson, T.J., Moran, M.S., Rango, A., Ritchie, J.C., Schmugge, T.J. Remote sensing research in hydrometeorology. Photogrammetric Engineering and Remote Sensing. 2003. v. 69. p. 631-646. Interpretive Summary: A major focus of remote sensing research in hydrometeorology by Agricultural Research Service (ARS) scientists has been to develop instrumentation, algorithms and models for estimating hydrometeorological states and fluxes, including plant stress/condition. The primary set of state variables include land surface temperature, near-surface soil moisture, snow cover/water equivalent and landscape roughness and vegetation cover. The hydrometeorological fluxes are primarily soil evaporation and plant transpiration or evapotranspiration, which is also related to plant stress or condition and snowmelt runoff. ARS researchers have attempted to quantify the components of the water and energy balance equation using remote sensing methods with the main purpose of estimating crop water use. This is because water availability is probably the most common limiting factor to crop growth and yield. . Particularly noteworthy are the methods using remote sensing pioneered by ARS scientists for assessing crop water stress. In addition, ARS scientists are making important contributions in new research directions that are emerging to address difficult problems in hydrometeorological research.
Technical Abstract: This paper provides an overview of remote sensing research in hydrometeorology with an emphasis on the major contributions that have been made by United States Department of Agriculture-Agricultural Research Service (USDA-ARS) scientists. The major contributions are separated into deriving from remote sensing 1) hydrometeorological state variables and 2) energy fluxes, particularly evapotranspiration which includes plant water stress. For the state variables, remote sensing algorithms have been developed for estimating land surface temperatures, estimating near-surface soil moisture, determining snow cover and snow water equivalent from, and estimating landscape roughness, topography, vegetation height and fractional cover. For the hydrometeorological fluxes, including plant water stress, models estimating evapotranspiration have been developed using land surface temperature as a key boundary condition with recent schemes designed to more reliably handle partial vegetation cover conditions. Thes research efforts in estimating evapotranspiration have been utilized by ARS researchers in the development of the Crop Water Stress Index and Water Deficit Index for assessing plant water stress. In addition, the development of the Thermal Kinetic Window and Crop Specific Temperatures have revealed the dynamic interactions among foliage temperature, plant species, and the physical environment. ARS researchers continue to develop new and improved remote sensing algorithms for evaluating state variables and fluxes. Moreover they are involved in new research directions to address science questions impeding hydrometeorological research.