Within-field soil moisture variability and time-invariant spatial structures of agricultural fields in the US Midwest

Yi Yang, Bin Peng, Kaiyu Guan, Ming Pan, Trenton E. Franz, Michael H. Cosh, Carl J. Bernacchi

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding soil moisture variability and estimating high-resolution soil moisture at subfield to field scales is critical for agricultural research and applications. However, systematic investigation of subfield scale soil moisture variability over cropland is still lacking from both measurement and satellite remote sensing. In this study, we aim to investigate (1) the characteristics of within-field soil moisture distribution over typical cropland in the US Midwest and (2) the capabilities of satellite remote sensing in capturing the spatiotemporal variabilities of soil moisture at subfield scale. Specifically, we conducted soil moisture field experiments in three typical commercial agricultural fields (∼85 acres per field) in central Illinois, representing typical commercial farmlands in the US Midwest, and compared the soil moisture measurements with satellite remote sensing data from optical and active microwave sensors. In each field, dense soil moisture samples (spaced at 50–60 m) were obtained for two dry down events in May and July 2021, and multiple long-term soil moisture stations were installed. We found prominent time-invariant spatial structures of soil moisture at within-field scales both during the dry down period and over longer time scales, and the stability is minimally affected by plant water use during the growing season. Comparing the field campaign measurements with satellite remote sensing data, we found that surface reflectance of shortwave infrared bands, such as SWIR1 (1610 nm) from Sentinel-2, can capture relative surface soil moisture patterns at within-field scales, but their relationships with soil moisture are field specific. These findings and the improved understanding of within-field soil moisture dynamics could potentially help future research on high-resolution soil moisture estimation with multi-source remote sensing data.

Original languageEnglish (US)
JournalVadose Zone Journal
DOIs
StateAccepted/In press - 2024

ASJC Scopus subject areas

  • Soil Science

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