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Field Observations During the Third Microwave Water and Energy Balance Experiment (MicroWEX-3): June 16–December 21, 2004

Tzu-yun Lin, Jasmeet Judge, Kai-Jen Calvin Tien, Joaquin Casanova, Mi-young Jang, Orlando Lanni, Larry Miller, and Fei Yan

Abstract—Circular 1481

For accurate prediction of weather and near-term climate, root-zone soil moisture is one of the most crucial components driving the surface hydrological processes. Soil moisture in the top meter is also very important because it governs moisture and energy fluxes at the land-atmosphere interface and it plays a significant role in partitioning of the 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 climate prediction models and hydrological models. Even though the biophysics of moisture and energy transport is well-captured in most current SVAT models, the computational errors accumulate over time and the model estimates of soil moisture diverge from reality. One promising way to improve significantly the model estimates of soil moisture is by assimilating remotely sensed data that is sensitive to soil moisture, for example microwave brightness temperatures, and updating the model state variables.

The microwave brightness at low frequencies (< 10 GHz) is 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. Most of these experiments conducted in agricultural regions have been short-term experiments that captured only a part of growing seasons. It is important to know how microwave brightness signature varies with soil moisture, evapotranspiration (ET), and biomass in a dynamic agricultural canopy with a significant biomass (4-6 kgm2) throughout the growing season.

The goal of MicroWEX-2 was to understand the land-atmosphere interactions during the growing season of corn, and their effect on observed microwave brightness signatures at 6.7 GHz, matching that of the satellite based microwave radiometer, AMSR. Specific objectives of MicroWEX-2 are:

  1. To collect passive microwave and other ancillary data to develop and calibrate a dynamic microwave brightness model for cotton.
  2. To collect energy and moisture flux data at land surface and in soil to develop and calibrate a dynamic SVAT model for cotton.
  3. To evaluate feasibility of soil moisture retrievals using passive microwave data at 6.7 GHz for the growing cotton canopy.
  4. To evaluate feasibility of using Mid Infrared Reflectance for estimating vegetation water content and biomass during the cotton growing season.

The publication contains the detailed information regarding the sensors deployed and data collected during the MicroWEX-2. To view the entire publication, see the accompanying PDF file on EDIS:

For related documents, please visit:

Field Data Report for the First Microwave Water and Energy Balance Experiment (MicroWEX-1), July 17–December 16, 2003, Citra, Florida

Field Observations During the Second Microwave Water and Energy Balance Experiment (MicroWEX-3): from March 17 through June 3, 2004

Field Observations During the Fourth MIcrowave Water and Energy Balance Experiment (MicroWEX-4): March 10–June 14, 2005

Measurement of Soil Surface Roughness During the Fourth Microwave Water and Energy Balance Experiment: April 18–June 13, 2005

Publication #CIR1481

Release Date:September 22, 2020

Reviewed At:April 22, 2024

Related Experts

Judge, Jasmeet


University of Florida

Fact Sheet

About this Publication

This document is CIR1481, one of a series of the Department of Agricultural and Biological Engineering, UF/IFAS Extension. Original publication date January 2006. Visit the EDIS website at for the currently supported version of this publication.

About the Authors

Tzu-yun Lin, graduate assistant; Jasmeet Judge, assistant professor and Director of the Center for Remote Sensing; Kai-Jen Calvin Tien, graduate research assistant; Joaquin Casanova, undergraduate research assistant; Mi-young Jang, graduate research assistant; Orlando Lanni, engineer; Larry Miller, engineer; and Fei Yan, graduate research assistant; Department of Agricultural and Biological Engineering, UF/IFAS Extension, Gainesivlle, FL 32611.


  • Jasmeet Judge