The effect of disaggregating soil data for estimating soil hydrological parameters at different scales

J.J. Stoorvogel*, V.L. Mulder, C.M.J. Hendriks

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

21 Downloads (Pure)


There is an increasing demand for soil data at different scales. Due to changing data requirements, environmental studies need to make key decisions in terms of i) which datasets to use, and ii) how to derive the necessary data from these datasets. This is particularly true for properties that are not included in standard soil profile descriptions like many soil hydrological properties. Often, data are disaggregated to account for spatial variability and processed using e.g., pedotransfer functions to derive the soil hydrological properties. However, the effect of disaggregation and the use of pedotransfer functions is often unclear. This paper aims to illustrate the potential effects by looking at three different case studies at the global, regional and local scale. The three cases clearly show that the disaggregation of data has considerable effect on the estimate of the water holding capacity and its spatial distribution. At the regional and local scale, actual measurements of the water holding capacity also differed considerably from the results of the pedotransfer functions. It is concluded that the choice of datasets and the procedures to derive the water holding capacity really matter. Too often, studies take a published dataset and a method without additional evaluation. It is recommended to pay more attention to these elements and carry out ensemble runs using different datasets and carry out comparative analysis using different methods to provide better insight in the accuracy of the final outcomes.
Original languageEnglish
Pages (from-to)185-193
Number of pages9
Publication statusPublished - Aug 2019
Externally publishedYes


Dive into the research topics of 'The effect of disaggregating soil data for estimating soil hydrological parameters at different scales'. Together they form a unique fingerprint.

Cite this