Validating Soil Moisture with Farmers in Mind: A New Approach for Remote Sensing and Modeling in the US Corn Belt

Kyle DeLong; Brian Hornbuckle; Jun Wang; Michael Cosh; Daryl Herzmann

doi:10.1109/IGARSS52108.2023.10283201

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Conference proceeding

Validating Soil Moisture with Farmers in Mind: A New Approach for Remote Sensing and Modeling in the US Corn Belt

Kyle DeLong, Brian Hornbuckle, Jun Wang, Michael Cosh and Daryl Herzmann

IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, pp.2669-2672

07/16/2023

DOI: 10.1109/IGARSS52108.2023.10283201

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Abstract

Evaluation of soil moisture information should consider when key crop development stages occur and, ultimately, when farmers must make decisions based on soil moisture status. Therefore, we assessed the performance of three microwave satellites (SMAP, SMOS, and METOP/ASCAT) and three reanalysis models (MERRA-2, NARR, and WEPP) in the U.S. Corn Belt in the context of agricultural management. Thermal time and crop progress reports from the USDA-NASS defined critical transition periods of crop growth and management decisions for the validation process. Contrary to calendar timelines like annual segments, these key events separate the year into five irregular segments. Measurements at the South Fork Core Validation Site from 2016 to 2020 show that the two passive microwave satellites are dry compared to in-situ observations, but the active satellite and reanalysis model products were almost always wetter. Overall, most products perform the best during the pre-planting and post-harvest segments when no crops are present and worst during the active management phase when crops are starting to grow.

Corn Belt

Crops

Land surface

MERRA-2

METOP/ASCAT

Microwave measurement

NARR

Satellites

SMAP

SMOS

Soft sensors

Soil moisture

Validation

Vegetation mapping

WEPP

Details

Title: Subtitle: Validating Soil Moisture with Farmers in Mind: A New Approach for Remote Sensing and Modeling in the US Corn Belt
Creators: Kyle DeLong - Iowa State University
Brian Hornbuckle - Iowa State University
Jun Wang - University of Iowa
Michael Cosh - Iowa State University
Daryl Herzmann - Iowa State University
Resource Type: Conference proceeding
Publication Details: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, pp.2669-2672
Publisher: IEEE
DOI: 10.1109/IGARSS52108.2023.10283201
eISSN: 2153-7003
Grant note: Experiment (10.13039/100018206) National Science Foundation (10.13039/100000001)
Language: English
Date published: 07/16/2023
Academic Unit: Electrical and Computer Engineering; Chemical and Biochemical Engineering; Civil and Environmental Engineering; Physics and Astronomy
Record Identifier: 9984500084202771

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