Journal cover Journal topic
SOIL An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/soil-2017-41
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Original research article
31 Jan 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal SOIL (SOIL).
Uncertainty indication in soil function maps – Transparent and easy-to-use information to support sustainable use of soil resources
Lucie Greiner1, Madlene Nussbaum2, Andreas Papritz3, Stephan Zimmermann4, Andreas Gubler1, Adrienne Grêt-Regamey5, and Armin Keller1 1Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zürich, Switzerland
2School of Agricultural, Forest and Food Science (HAFL), Bern University of Applied Sciences (BFH), 3052 Zollikofen, Switzerland
3Institute of Biogeochemistry and Pollutant Dynamics, Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland
4Forest Soils and Biogeochemistry, Soil Functions and Soil Protection, Swiss Federal Institute for Forest, Snow and Landscape Resea rch (WSL), 8903 Birmensdorf, Switzerland
5Planning of Landscape and Urban Systems, Swiss Federal Institute of Technology (ETH), 8093 Zürich, Switzerland
Abstract. The mapping of soil functions is increasingly being used to inform decision-making in spatial planning processes related to the capacity of soils to contribute to ecosystem services. In this study, we add to the transparency of soil function maps by indicating uncertainties arising from prediction uncertainties of soil properties as generated by digital soil mapping (DSM). For a study area in the Swiss Midlands, we map 10 static soil functions for agricultural soils together with their uncertainties, using soil property data generated by DSM. Mapping the ten soil functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of soil function fulfillment (SFF) across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that uncertainty indications in soil function maps are required to enable informed and transparent decisions on the sustainable use of soil resources.

Citation: Greiner, L., Nussbaum, M., Papritz, A., Zimmermann, S., Gubler, A., Grêt-Regamey, A., and Keller, A.: Uncertainty indication in soil function maps – Transparent and easy-to-use information to support sustainable use of soil resources, SOIL Discuss., https://doi.org/10.5194/soil-2017-41, in review, 2018.
Lucie Greiner et al.
Lucie Greiner et al.
Lucie Greiner et al.

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Short summary
To maintain the soil resource, spatial information on soil multi-functionality is key. Soil function (SF) maps rate soils potentials to fulfill a certain function, e.g. nutrient regulation. We show how uncertainties in predictions of soil properties generated by digital soil mapping propagate into soil function maps, present possibilities to display this uncertainty information and show that otherwise comparable SF assessment methods differ in their behaviour in view of uncertainty propagation.
To maintain the soil resource, spatial information on soil multi-functionality is key. Soil...
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