The Observation Record Length Necessary to Generate Robust Soil Moisture Percentiles

Abstract

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.

Comparison of Contemporary In Situ, Model, and Satellite Remote Sensing Soil Moisture With a Focus on Drought Monitoring

“…Despite SMAP L3 having the best match with the daily variability of in situ θ a , the SMAP distribution of daily θ a values is considerably smaller than that of the NLDAS‐2 and CPC models. The data record length is imperative for the stability of soil moisture percentiles based on that record (i.e., Ford et al, ), and therefore, the shorter SMAP data record enhances daily percentile variability and reduces the effectiveness of the SMAP product for identifying drought severity based on soil moisture percentiles. Concurrently, the data record length of in situ observations impacts the stability of in situ soil moisture percentiles as well.…”

Development and Evaluation of Soil Moisture‐Based Indices for Agricultural Drought Monitoring

“…For each station, the daily ePDF was based on 21 soil moisture values in Oklahoma (one for each year from 1996–2016) and 15 values in the Texas Panhandle (2002–2016), sample sizes that we determined to be large enough to create a stable sample distribution. Ford et al (2016) previously reported 3 to 6 yr of soil moisture data were required to create stable sample distributions for daily soil moisture data aggregated to the monthly timescale. Because our data were at the daily timescale, we expected that a somewhat longer data record would be needed to create a stable sample distribution.…”

“…Because our data were at the daily timescale, we expected that a somewhat longer data record would be needed to create a stable sample distribution. We applied the method of Ford et al (2016) to our daily data and found that, averaged across each station and day of the year, approximately 11 yr of data were required. We therefore concluded that the data record lengths in our study were sufficient to produce reliable ePDFs.…”

Using ARM Observations to Evaluate Climate Model Simulations of Land‐Atmosphere Coupling on the U.S. Southern Great Plains

“…The available 2003–2011 record length of warm‐season observations was assumed sufficient for estimation of SM and LAC statistics of acceptable accuracy (Findell et al, ; Ford et al, ). Analysis of the variations in R and I values for SM‐EF coupling that occur with the progressive inclusion of each year's warm season (Table S1) raises some caveats, however.…”