The observation record length necessary to generate robust soil moisture percentiles

Trent W. Ford, Qing Wang, Steven M. Quiring

Research output: Contribution to journalArticlepeer-review


The ability to use in situ soil moisture for large-scale soil moisture monitoring, model and satellite validation, and climate investigations is contingent on properly standardizing soil moisture observations. Percentiles are a useful method for homogenizing in situ soil moisture. However, very few stations have been continuously monitoring in situ soil moisture for 20 years or more. Therefore, one challenge in evaluating soil moisture is determining whether the period of record is sufficient to produce a stable distribution from which to generate percentiles. In this study daily in situ soil moisture observations, measured at three separate depths in the soil column at 15 stations in the United States and Canada, are used to determine the record length that is necessary to generate a stable soil moisture distribution. The Anderson-Darling test is implemented, both with and without a Bonferroni adjustment, to quantify the necessary record length. The authors evaluate how the necessary record length varies by location, measurement depth, and month. They find that between 3 and 15 years of data are required to produce stable distributions, with the majority of stations requiring only 3-6 years of data. Not surprisingly, more years of data are required to obtain stable estimates of the 5th and 95th percentiles than of the first, second, and third quartiles of the soil moisture distribution. Overall these results suggest that 6 years of continuous, daily in situ soil moisture data will be sufficient in most conditions to create stable and robust percentiles.

Original languageEnglish (US)
Pages (from-to)2131-2149
Number of pages19
JournalJournal of Applied Meteorology and Climatology
Issue number10
StatePublished - 2016
Externally publishedYes


  • Data processing
  • Data quality control
  • Soil moisture
  • Statistical techniques
  • Variational analysis

ASJC Scopus subject areas

  • Atmospheric Science


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