Soil water information is an essential input for environmental, hydrological or land surface models. There is a need for reliable soil water information with European coverage. In the last decades, research institutes, universities and other research facilities have developed local prediction methods. Maps with a European coverage were produced with the limited information available at the end of the 1990's. Their unknown reliability hinders the accuracy estimation of models relying on soil information. An up-to-date map of soil hydraulic properties could improve the predictions of such models.
A reliable soil water map can serve multiple purposes, including scientific research and application of models on different geographical scales. It is also essential for the development and spatial implementation of a comprehensive soil quality (SQ) indicator planned by the Joint Research Centre of the European Commission.
New soil hydraulic pedotransfer functions (PTFs) were recently developed (Toth et al., 2014) and could support the computational basis of the new series of maps of soil hydraulic properties.
The purpose of the study that JRC undertook is to assist with the implementation of the research programme on soil quality indicators, namely to facilitate the completion of a new soil quality indicator by supplying reliable spatial data on soil hydraulic properties.
For this, the following map layers were developed:
Water retention of topsoil
· saturated water content (cm3/cm3)
· water content at field capacity (cm3/cm3)
· water content at wilting point (cm3/cm3)
Hydraulic conductivity of topsoil
· saturated hydraulic conductivity (cm/day)
Besides the true values in the units mentioned above, values scaled between 1 and 10 without measurement units were also calculated. Although the concepts of field capacity and permanent wilting point have been widely criticised, their use in modelling remains common. They are oversimplifying concepts that should not be static and should vary not only with soil, but also with vegetation and climatic conditions. Still they provide an easy measure to approach water-holding capacity in soils.
The pan-European hydraulic PTFs recently published by Toth et al. (2014) are accessible in the R package euptf, distributed in ESDAC (http://esdac.jrc.ec.europa.eu/taxonomy/term/10), and documented in the R package vignette. The rules PTF01, PTF07, PTF10 and PTF13 were used to predict the water content at saturation (THS), field capacity (FC), wilting point (WP) and the saturated hydraulic conductivity (KS), respectively, based on the modified FAO texture class only.
Use was made of the European Soil Database that contains information based on expert knowledge at the Soil Typological Unit (STU) and the Soil Mapping Unit (SMU). Each SMU contains 1 to 10 STUs, for which the percentage of the SMU is known but not the position within the SMU. The soil properties are available at the STU level. The mapping of these properties require their aggregation at the SMU level. The soil hydraulic properties are largely non-linear and may not be simply averaged between STUs at the SMU level. An SMU's dominant STU is the STU covering the largest surface of that SMU. TXTSRFDOM is the dominant texture class of the topsoil. The value of the dominant STU were used to produce the map layers.
The variability of THS and KS calculated with PTF 01 and PTF13 is limited. They produce only few different values. The addition of information on the soil organic carbon content (PTF02 and PTF14) improves the accuracy of the predictions (see Toth et al., 2014). The OCTOP map of Jones et al. (2005) is based on the information contained in the ESDB (PTR21) improved by land cover and temperature. It is suitable to be used with other information from the ESDB.
The R package raster (Hijmans, 2015) was used to run the PTFs spatially and produce the raster layers.
The maps based on the ESDB lack accuracy, mostly due to the use of the dominant STU for a whole SMU. At the same resolution of 1 km, digital maps with particle size distribution rather than texture class could improve the accuracy.
For each variable, two raster layers were produced, one with the true value of the soil property and one with the values reclassified as equidistant classes ranging from 1 to 10. They were stored in GeoTif files with two bands each:
· ths_fao_octop.tif: saturated water content
· fc_fao.tif: water content at field capacity
· wp_fao.tif: water content at wilting point
· ks_fao_octop.tif. saturated hydraulic conductivity
- European soil database (distribution version v2.0). European Commission Joint Research Centre, Italy (available after registration from ESDAC).
- Hijmans, R. J., 2015. raster: Geographic data analysis and modeling. R package version 2.3-24. URL http://CRAN.R-project.org/package=raster
- Jones, R. J. A., Hiederer, R., Rusco, E., Montanarella, L., October 2005. Estimating organic carbon in the soils of Europe for policy support. European Journal of Soil Science 56, 655-671 (available after registration from ESDAC).
- Toth, B., Weynants, M., Nemes, A., Mako, A., Bilas, G., Toth, G., 2014. New generation of hydraulic pedotransfer functions for Europe. European Journal of Soil Science
More about the data:
The GeoTiff files are in the Coordinate System: ETRS_LAEA_10_52; pixels are aligned with other Rasters distributed in ESDAC.
Coverage: EU + Balkan + Norway
The first layer (Band 1) of each GeoTiff file gives the value of the property as given by the PTFs, using the topsoil FAO texture class from the ESDB as input. For the water contents (THS: saturation; FC: field capacity, -330 cm; WP: wilting point, -15848 cm), the units are cubic cm of water per cubic cm of soil, i.e. no units. For the saturated conductivity, the units are log10(cm/day), hence the negative values found in this layer.
The second layer of each GeoTiff (Band 2) is a classification of the values of the corresponding first layer into 10 equidistant classes.
These data/maps have been elaborated to the best of JRC’s knowledge. They are based on results published in peer-review articles and datasets available in ESDAC, but the data itself were not published for public or peer-reviewed scrutiny.
The persons that elaborated these maps are Gergely Toth and Melanie Weyants.