Triple collocation evaluation of in situ soil moisture observations from 1200+ stations as part of the U.S. national soil moisture network

Trent W. Ford, Steven M. Quiring, Chen Zhao, Zachary T. Leasor, Christian Landry

Research output: Contribution to journalArticlepeer-review

Abstract

Soil moisture is an important variable for numerous scientific disciplines, and therefore provision of accurate and timely soil moisture information is critical. Recent initiatives, such as the National Soil Moisture Network effort, have increased the spatial coverage and quality of soil moisture monitoring infrastructure across the contiguous United States. As a result, the foundation has been laid for a high-resolution, real-time gridded soil moisture product that leverages data from in situ networks, satellite platforms, and land surface models. An important precursor to this development is a comprehensive, national-scale assessment of in situ soil moisture data fidelity. Additionally, evaluation of the United States’s current in situ soil moisture monitoring infrastructure can provide a means toward more informed satellite and model calibration and validation. This study employs a triple collocation approach to evaluate the fidelity of in situ soil moisture observations from over 1200 stations across the contiguous United States. The primary goal of the study is to determine the monitoring stations that are best suited for 1) inclusion in national-scale soil moisture datasets, 2) deriving in situ–informed gridded soil moisture products, and 3) validating and benchmarking satellite and model soil moisture data. We find that 90% of the 1233 stations evaluated exhibit high spatial consistency with satellite remote sensing and land surface model soil moisture datasets. In situ error did not significantly vary by climate, soil type, or sensor technology, but instead was a function of station-specific properties such as land cover and station siting.

Original languageEnglish (US)
Pages (from-to)2537-2549
Number of pages13
JournalJournal of Hydrometeorology
Volume21
Issue number11
DOIs
StatePublished - Nov 2020

Keywords

  • Data quality control
  • Error analysis
  • Soil moisture

ASJC Scopus subject areas

  • Atmospheric Science

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