Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions

Research output: Chapter in Book/Report/Conference proceedingAbstract

Abstract

Many large soil profile databases are compilations of multiple surveys and include a variation in observation uncertainty. This uncertainty is often unknown and therefore ignored in studies. Question remains how the uncertainty can be derived and incorporated in the subsequent analysis? Over the past 15 years a database of over 1800 georeferenced soil profile observations has been compiled during the WU-SGL Field-training Geosciences course for a 340 km2 study area in Southern Spain. In this database of site and soil profile observations, effective soil depth was one of the quantitative variables observed by students. However, in what way can we actually assess best the uncertainty of these observations? Secondly, how can we produce the best prediction for soil depth in this study area, using the available explanatory variables and taking observation uncertainty into account? Soil depth in the study area depends a.o. on parent material, slope angle and landscape position. For both the aforementioned questions the knowledge on spatial heterogeneity of the explanatory variables between and within discrete mapping units is crucial. In this study we elaborated on observation uncertainty and recommend which digital soil mapping model yields the best prediction of soil depth in the study area, using the calibrating and validating potential of such a large database. Finally, the impact of soil depth uncertainty on the available water capacity is evaluated for different soil mapping units.
Original languageEnglish
Title of host publicationSoli Science in a Changing World: programme and abstract book
EditorsJakob Wallinga, Gerben Mol, Titia Mulder, Anne Zaal, Boris Jansen
Place of PublicationWageningen
PublisherWageningen University & Research
Pages197-197
ISBN (Print)9789463430616
Publication statusPublished - 2017
EventWageningen Soil Conference 2017: Soil Science in a changing world - Wageningen University, Wageningen
Duration: 27 Aug 201731 Aug 2017

Conference

ConferenceWageningen Soil Conference 2017
CityWageningen
Period27/08/1731/08/17

Fingerprint

soil depth
soil profile
soil
available water capacity
slope angle
parent material
prediction
student
soil function

Cite this

Schoorl, J. M., Stoorvogel, J. J., Claessens, L. F. G., & Heuvelink, G. B. M. (2017). Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions. In J. Wallinga, G. Mol, T. Mulder, A. Zaal, & B. Jansen (Eds.), Soli Science in a Changing World: programme and abstract book (pp. 197-197). Wageningen: Wageningen University & Research.
Schoorl, J.M. ; Stoorvogel, J.J. ; Claessens, L.F.G. ; Heuvelink, G.B.M. / Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions. Soli Science in a Changing World: programme and abstract book. editor / Jakob Wallinga ; Gerben Mol ; Titia Mulder ; Anne Zaal ; Boris Jansen. Wageningen : Wageningen University & Research, 2017. pp. 197-197
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abstract = "Many large soil profile databases are compilations of multiple surveys and include a variation in observation uncertainty. This uncertainty is often unknown and therefore ignored in studies. Question remains how the uncertainty can be derived and incorporated in the subsequent analysis? Over the past 15 years a database of over 1800 georeferenced soil profile observations has been compiled during the WU-SGL Field-training Geosciences course for a 340 km2 study area in Southern Spain. In this database of site and soil profile observations, effective soil depth was one of the quantitative variables observed by students. However, in what way can we actually assess best the uncertainty of these observations? Secondly, how can we produce the best prediction for soil depth in this study area, using the available explanatory variables and taking observation uncertainty into account? Soil depth in the study area depends a.o. on parent material, slope angle and landscape position. For both the aforementioned questions the knowledge on spatial heterogeneity of the explanatory variables between and within discrete mapping units is crucial. In this study we elaborated on observation uncertainty and recommend which digital soil mapping model yields the best prediction of soil depth in the study area, using the calibrating and validating potential of such a large database. Finally, the impact of soil depth uncertainty on the available water capacity is evaluated for different soil mapping units.",
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Schoorl, JM, Stoorvogel, JJ, Claessens, LFG & Heuvelink, GBM 2017, Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions. in J Wallinga, G Mol, T Mulder, A Zaal & B Jansen (eds), Soli Science in a Changing World: programme and abstract book. Wageningen University & Research, Wageningen, pp. 197-197, Wageningen Soil Conference 2017, Wageningen, 27/08/17.

Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions. / Schoorl, J.M.; Stoorvogel, J.J.; Claessens, L.F.G.; Heuvelink, G.B.M.

Soli Science in a Changing World: programme and abstract book. ed. / Jakob Wallinga; Gerben Mol; Titia Mulder; Anne Zaal; Boris Jansen. Wageningen : Wageningen University & Research, 2017. p. 197-197.

Research output: Chapter in Book/Report/Conference proceedingAbstract

TY - CHAP

T1 - Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions

AU - Schoorl, J.M.

AU - Stoorvogel, J.J.

AU - Claessens, L.F.G.

AU - Heuvelink, G.B.M.

PY - 2017

Y1 - 2017

N2 - Many large soil profile databases are compilations of multiple surveys and include a variation in observation uncertainty. This uncertainty is often unknown and therefore ignored in studies. Question remains how the uncertainty can be derived and incorporated in the subsequent analysis? Over the past 15 years a database of over 1800 georeferenced soil profile observations has been compiled during the WU-SGL Field-training Geosciences course for a 340 km2 study area in Southern Spain. In this database of site and soil profile observations, effective soil depth was one of the quantitative variables observed by students. However, in what way can we actually assess best the uncertainty of these observations? Secondly, how can we produce the best prediction for soil depth in this study area, using the available explanatory variables and taking observation uncertainty into account? Soil depth in the study area depends a.o. on parent material, slope angle and landscape position. For both the aforementioned questions the knowledge on spatial heterogeneity of the explanatory variables between and within discrete mapping units is crucial. In this study we elaborated on observation uncertainty and recommend which digital soil mapping model yields the best prediction of soil depth in the study area, using the calibrating and validating potential of such a large database. Finally, the impact of soil depth uncertainty on the available water capacity is evaluated for different soil mapping units.

AB - Many large soil profile databases are compilations of multiple surveys and include a variation in observation uncertainty. This uncertainty is often unknown and therefore ignored in studies. Question remains how the uncertainty can be derived and incorporated in the subsequent analysis? Over the past 15 years a database of over 1800 georeferenced soil profile observations has been compiled during the WU-SGL Field-training Geosciences course for a 340 km2 study area in Southern Spain. In this database of site and soil profile observations, effective soil depth was one of the quantitative variables observed by students. However, in what way can we actually assess best the uncertainty of these observations? Secondly, how can we produce the best prediction for soil depth in this study area, using the available explanatory variables and taking observation uncertainty into account? Soil depth in the study area depends a.o. on parent material, slope angle and landscape position. For both the aforementioned questions the knowledge on spatial heterogeneity of the explanatory variables between and within discrete mapping units is crucial. In this study we elaborated on observation uncertainty and recommend which digital soil mapping model yields the best prediction of soil depth in the study area, using the calibrating and validating potential of such a large database. Finally, the impact of soil depth uncertainty on the available water capacity is evaluated for different soil mapping units.

M3 - Abstract

SN - 9789463430616

SP - 197

EP - 197

BT - Soli Science in a Changing World: programme and abstract book

A2 - Wallinga, Jakob

A2 - Mol, Gerben

A2 - Mulder, Titia

A2 - Zaal, Anne

A2 - Jansen, Boris

PB - Wageningen University & Research

CY - Wageningen

ER -

Schoorl JM, Stoorvogel JJ, Claessens LFG, Heuvelink GBM. Consequences of uncertainty in field observations of soil depth for digital soil mapping of soil functions. In Wallinga J, Mol G, Mulder T, Zaal A, Jansen B, editors, Soli Science in a Changing World: programme and abstract book. Wageningen: Wageningen University & Research. 2017. p. 197-197