New paper models wet chemistry soil data measurement error

16 Jun 2021


Photo by Kyle Spradley | © 2014 - Curators of the University of Missouri

High quality soil data are in demand, but eliminating sources of error in soil measurements is difficult. In a newly published European Journal of Soil Science paper, lead author and ISRIC PhD candidate Cynthia van Leeuwen analyzes the measurement error in wet chemistry soil data.

“Wet chemistry soil data are subject to many different error sources, such as the observer, the measurement instrument and lack of standardised methods. Identifying these error sources and quantifying their contribution to total measurement error gives insight to data quality,” van Leeuwen said. “We wanted to study this so that laboratories can have new information to improve their experimental measurement design.”

Van Leeuwen and her coauthors Wageningen University assistant professor Titia Mulder and ISRIC colleagues Niels Batjes and Gerard Heuvelink quantified uncertainties in synthetic and real-world wet chemistry soil data including batch and laboratory effects. Their findings demonstrate the importance of experimental measurement design and sufficient replicates.

“Uncertainty estimates are rarely specified for the wet chemistry soil data that underpin global data compilations such as WoSIS (World Soil Information Service). As a result, end-users have only limited insight concerning the quality, or uncertainty, of the compiled and standardised data,” ISRIC senior researcher Niels Batjes said. “Importantly, this research showed the need for an accurate experimental measurement design as well as having enough replicate measurements to be able to quantify the uncertainties.”

Using real world data from Wageningen Evaluating Programs for Analytical Laboratories (WEPAL), the study also indicated that the laboratory measurement error in soil data can be quite large. This study may help soil laboratories to refine their procedures and, ultimately, allow to improve the quantification of uncertainty in wet chemistry data, using probability distribution functions, in the World Soil Information Service (WoSIS).

The paper is available at: https://doi.org/10.1111/ejss.13137 If you are unable to access the full text, email Cynthia van Leeuwen at the email address below.

Citation: van Leeuwen CCE, Mulder VL, Batjes NH and Heuvelink GBM 2021. Statistical modelling of measurement error in wet chemistry soil data. European Journal of Soil Science , https://doi.org/10.1111/ejss.13137