Field Observations During the Eighth Microwave Water and Energy Balance Experiment (MicroWEX-8): from June 16 through August 24, 2009

Tara Bongiovanni, Heather Enos, Alejandro Monsivais-Huertero, Blaire Colvin, Karthik Nagarajan, Jasmeet Judge, Pang-Wei Liu, Juan Fernandez-Diaz, Roger De Roo, Yuriy Goykhman, Xueyang Duan, Daniel Preston, Ramesh Shrestha, Clint Slatton, Mahta Moghaddam, and Anthony England

Full text of this publication can be found at https://edis.ifas.ufl.edu/pdffiles/AE/AE47600.pdf.

Introduction

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 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 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 in a dynamic agricultural canopy with a significant biomass (4–6 kg/m2) throughout the growing season.

Objectives

The goal of MicroWEX-8 was to conduct a pilot study that incorporated active and passive microwave observations as well as Light Detection and Ranging (LiDAR) observations for a growing season of sweet corn. The variety of instruments 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, active microwave signatures at 1.14 GHz, and 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-8 included the following:

  1. To field-test the micrometeorological, microwave radiometer, radar, LiDAR, and other sensors to characterize errors.
  2. To collect passive and active microwave, LiDAR, and other ancillary data to develop preliminary algorithms to estimate microwave signatures for corn.
  3. To evaluate feasibilty of soil moisture retrievals using passive microwave data at 6.7 and 1.4 GHz and active microwave data at 1.14 GHz for the growing corn canopy.

Related publications can be found on the Microwave Water and Energy Balance Experiments topic page: https://edis.ifas.ufl.edu/TOPIC_Microwave_Water_and_Energy_Balance_Experiments

Publication #AE476

Date: 2021-09-27

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Fact Sheet

About this Publication

This document is AE476, one of a series of the Department of Agricultural and Biological Engineering, UF/IFAS Extension. Original publication date July 2011. Reviewed August 2017. Visit the EDIS website at https://edis.ifas.ufl.edu.

About the Authors

Tara Bongiovanni, research scientist, University of Texas-Austin; Heather Enos, Commercial Maintenance Solutions; Alejandro Monsivais-Huertero, professor, ESIME Unidad Ticomán, Instituto Politécnico Nacional, Mexico; Blaire Colvin, research assistant, Center for Remote Sensing (CRS); Karthik Nagarajan, researcher, Qualcomm; Jasmeet Judge, professor and director, CRS; Pang-Wei Liu, senior research scientist, NASA Goddard Space Flight Center; Juan Fernandez-Diaz, research assistant professor, National Center for Airborne Laser Mapping (NCALM), University of Houston (UH); Roger De Roo, senior research scientist University of Michigan; Yurity Goykhman, graduate research assistant, University of Michigan; Xueyang Duan, NASA Jet Propulsion Laboratory, CA; Daniel Preston, engineering technician, Mechanical and Aerospace Engineering; Ramesh Shrestha, professor director, NCALM at UH; Clint Slatton, associate professor, University of Florida; Mahta Moghaddam, professor, University of Southern California; and Anthony England, professor, University of Michigan; UF/IFAS Extension, Gainesville, FL 32611.

Contacts

  • Jasmeet Judge