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Field Observations During the Ninth Microwave Water and Energy Balance Experiment (MicroWEX-9): from March 24, 2010 through January 6, 2011

Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Robert Terwilleger, Alejandro Monsivais-Huertero, Jasmeet Judge, Juan Fernandez-Diaz, Daniel Preston, Tyler Cheney, and Jason Motsinger

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For accurate prediction of weather and near-term climate, root-zone soil moisture is one of the most crucial components driving surface hydrological processes. Soil moisture in the top meter governs moisture and energy fluxes at the land-atmosphere interface, and it plays a significant role in the partitioning of precipitation into runoff and infiltration.

Energy and moisture fluxes at the land surface can be estimated by Soil-Vegetation-Atmosphere-Transfer (SVAT) models. These models are typically used in conjunction with numerical weather and near-term climate prediction models and surface-subsurface hydrological models. Even though the biophysics of moisture and energy transport is well-captured in most current SVAT models, the errors in initialization, forcings, and computation accumulate over time, and the model estimates of soil moisture in the root zone diverge from reality. Remotely sensed microwave observations can be assimilated in these models to improve root-zone soil moisture estimates.

The microwave signatures at low frequencies, particularly at 1.4 GHz (L-band), are very sensitive to soil moisture in the top few centimeters in most vegetated surfaces. Many studies have been conducted in agricultural areas, such as bare soil, grass, soybean, wheat, pasture, and corn, to understand the relationship between soil moisture and microwave remote sensing. It is important to know how microwave signatures vary with soil moisture, evapotranspiration (ET), and biomass during the growing season for a dynamic agricultural canopy with a significant wet biomass of 10–12 kg/m2.


The goal of MicroWEX-9 was to conduct a season-long experiment that incorporated passive microwave observations as well as Light Detection and Ranging (LiDAR) observations for a growing season of elephant grass. The variety of sensors would allow for further understanding of the land-atmosphere interactions during the growing season, and their effect on observed passive microwave signatures at 6.7 GHz and 1.4 GHz, as well as LiDAR scans. These observations match that of the satellite-based passive microwave radiometers, Advanced Microwave Scanning Radiometer (AMSR), and the Soil Moisture and Ocean Salinity (SMOS) mission, respectively, and the upcoming NASA Soil Moisture Active Passive (SMAP) mission. Specific objectives of MicroWEX-9 included the following:

  1. To understand the growth and development of elephant grass and establish vegetation sampling methodologies accepted by agronomists that can be used in calibrating crop-growth models and are relevant to microwave remote sensing observations.
  2. To re-design the installation structures to meet the demands of a dense, high elephant grass canopy.
  3. To collect passive microwave, LiDAR, and other ancillary data to develop preliminary algorithms to estimate microwave signatures for elephant grass.
  4. To evaluate feasibility of soil moisture retrievals using passive microwave data at 6.7 GHz and 1.4 GHz for the growing elephant grass canopy.

Related publications can be found on the Microwave Water and Energy Balance Experiments topic page:

Publication #AE494

Release Date:May 14, 2019

Reviewed At:June 16, 2022

Fact Sheet

About this Publication

This document is AE494, one of a series of the Department of Agricultural and Biological Engineering, UF/IFAS Extension. Original publication date November 2013. Visit the EDIS website at for the currently supported version of this publication.

About the Authors

Tara Bongiovanni and Pang-Wei Liu are graduate research assistants of the Center for Remote Sensing (CRS); Karthik Nagarajan is a post-doctoral researcher of CRS; Robert Terwilleger is an undergraduate research assistant of the CRS; Alejandro Monsivais-Huertero is an assistant professor at ESIME Unidad Ticomán, Instituto Politécnico Nacional, Mexico, Jasmeet Judge is an assistant professor and director of CRS; Juan Fernandez-Diaz is a graduate research assistants of the National Center for Airborne Laser Mapping (NCALM) at the University of Houston (UH); Daniel Preston is an engineering technician of CRS; Tyler Cheney and Jason Motsinger are affiliated with UF's Research Experience for Undergraduates; Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Robert Terwilleger, Alejandro Monsivais-Huertero, Jasmeet Judge, and Daniel Preston are affiliated with the Department of Agricultural and Biological Engineering; UF/IFAS Extension, Gainesville, FL 32611. Juan Fernandez-Diaz is affiliated with the Civil Engineering Department, University of Houston.


  • Jasmeet Judge