Three-dimensional mapping of soil organic matter content using soil type–specific depth functions

Kempen, B.; Brus, D.J.; Stoorvogel, J.J.

doi:10.1016/j.geoderma.2011.01.010

Cited by 127 publications

(78 citation statements)

References 21 publications

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“…Current pedometric approaches to mapping soil C acknowledge the importance of accounting for soil type when estimating the vertical distribution of SOC (Kempen et al 2011;Wiese et al 2016). Polyvalent cations can indeed cause departures from the generally assumed exponential decline of SOC concentration with depth (Hilinski 2001).…”

Section: Digressing From the Expected Profile-scale Depth Distributionsmentioning

confidence: 99%

Calcium-mediated stabilisation of soil organic carbon

2017

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Soils play an essential role in the global cycling of carbon and understanding the stabilisation mechanisms behind the preservation of soil organic carbon (SOC) pools is of globally recognised significance. Until recently, research into SOC stabilisation has predominantly focused on acidic soil environments and the interactions between SOC and aluminium (Al) or iron (Fe). The interactions between SOC and calcium (Ca) have typically received less attention, with fewer studies conducted in alkaline soils. Although it has widely been established that exchangeable Ca (Ca Exch ) positively correlates with SOC concentration and its resistance to oxidation, the exact mechanisms behind this relationship remain largely unidentified. This synthesis paper critically assesses available evidence on the potential role of Ca in the stabilisation of SOC and identifies research topics that warrant further investigation. Contrary to the common view of the chemistry of base cations in soils, chemical modelling indicates that Ca 2? can readily exchange its hydration shell and create inner sphere complexes with organic functional groups. This review therefore argues that both inner-and outer-sphere bridging by Ca 2? can play an active role in the stabilisation of SOC. Calcium carbonate (CaCO 3 ) can influence occluded SOC stability through its role in the stabilisation of aggregates; however, it could also play an unaccounted role in the direct sorption and inclusion of SOC. Finally, this review highlights the importance of pH as a potential predictor of SOC stabilisation mechanisms mediated by Al-or Fe-to Ca, and their respective effects on SOC dynamics.

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Section: Digressing From the Expected Profile-scale Depth Distributionsmentioning

confidence: 99%

Calcium-mediated stabilisation of soil organic carbon

2017

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“…As a result, there is a large discrepancy between continuous and high resolution mapping of the horizontal variability on the one hand, and the coarse and discontinuous mapping of the vertical component on the other. Recently, some authors have used continuous functions to estimate the SOC depth-profile using an exponential depth function (Kempen et al, 2011;Meersmans et al, 2009). However, this approach has a limited flexibility to describe complex SOC profiles as it only allows representing a continuous increase or decrease of the SOC content along the profile.…”

Section: Introductionmentioning

confidence: 99%

High resolution characterization of the soil organic carbon depth profile in a soil landscape affected by erosion

Aldana-Jague

Sommer

Saby

et al. 2016

Soil and Tillage Research

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A B S T R A C TThe identification of soil management strategies as well as the evaluation of their effectiveness requires detailed information on the spatial and temporal patterns of soil organic carbon storage. High-resolution SOC profile data are generally not available and traditional methods for collecting these are time consuming and costly. Recent studies use geo-statistical approaches to assess the three-dimensional patterns of SOC storage. However, there is still a large discrepancy between the continuous and high resolution mapping of the horizontal SOC variability on the one hand, and the coarse and discontinuous mapping of the vertical SOC profile on the other. In this study, we combine spectroscopic techniques with spatial modeling in a small, cultivated catchment in Germany and we evaluate the contribution of soil redistribution processes and topographical parameters to the observed spatial and vertical patterns. Using high-resolution data from soil cores, we evaluated the robustness of a third order polynomial function to model the vertical SOC profile. Using a crossvalidation, our results show that this approach results in a robust model (RSME = 0.24%) and performs better than the widely used exponential depth model (RMSE = 0.39%). In a next step, we evaluated the relationship between the parameters of the SOC depth model and co-variables including soil redistribution (inferred from 137 Cs data) and topographical indices using a multiple linear regression model. The performance was calculated by cross-validation and we found a low robustness of the models because of the low number of profiles (i.e. n = 19). A statistical evaluation of the co-variables highlighted two key factors influencing the SOC vertical distribution. Soil redistribution processes mainly influenced the surface SOC content (first centimeters) whereas the shape of the depth distribution was controlled by slope curvature alone. The mapping of polynomial parameters was validated using an external SOC profile dataset and showed a poor prediction of the surface content but a good prediction of the depth distribution once the surface SOC content is known (RMSE = 0.15-0.25%C). This suggests that estimating the vertical SOC profile from topsoil data by applying remote sensing data, in combination with our SOC profile model, is promising and can will result in an accurate mapping of 3D SOC patterns at a very high resolution.

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“…Therefore, terrain attributes (TA) derived from digital elevation models (DEM) are being increasingly used as auxiliary covariates in the spatial prediction of soil classes and properties (Kempen et al, 2011;ten Caten et al, 2013;Teske et al, 2014), due to the high ratio of TA with soil genesis and the wide availability of DEMs (McBratney et al, 2003;Behrens et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

Moura-Bueno

Dalmolin

Caten

et al. 2016

Rev. Bras. Ciênc. Solo

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ABSTRACT:Terrain attributes (TAs) derived from digital elevation models (DEMs) are frequently used in digital soil mapping (DSM) as auxiliary covariates in the construction of prediction models. The DEMs and information extracted from it may be limited with regard to the spatial resolution and error magnitude, and can differ in the behavior of terrain features. The objective of this study was to evaluate the quality and limitations of free DEM data and to evaluate a topographic survey (TS) underlying the choice of a more appropriate model, for use in DSMs at a scale of 1:10,000. The study was conducted in an area of 937 ha in the watershed of Lajeado Giruá, in southern Brazil. The DEMs: DEM-TS, DEM-Topographic Map (TM), DEM-ASTER, DEM-SRTM, and DEM-TOPODATA were evaluated with regard to the precision elevation by statistical tests based on field reference points, the root mean square error (RMSE), identification of the number and size of spurious depressions, and the application of the Brazilian Cartographic Accuracy Standards Law (BCASL) to define the scale of each DEM. In addition, the TA derived from each DEM was compared with the TA from DEM-TS, considered to be terrain reality. The results showed that the elevation data of DEM-TS had the best quality (RMSE = 1.93 m), followed by DEM-SRTM (RMSE = 5.95 m), DEM-Topographic Map (RMSE = 8.28 m), DEM-TOPODATA (RMSE = 9.78 m) and DEM-ASTER (RMSE = 15.57 m). The DEM-TS was well-represented at a 1:10,000 scale, while the DEM-Topographic Map and DEM-SRTM fitted 1:50,000, the DEM-TOPODATA 1:50,000 and the DEM-ASTER a 1:100,000 scale. The results of DEM-SRTM and DEM-TOPODATA were closest to terrain reality (DEM-TS) and had the lowest number of spurious depressions and RMSE values for each evaluated attribute, but were inadequate for not fitting detailed scales compatible with small areas. The techniques for the acquisition of elevation data of each DEM and mainly the flat to gently undulating topography were factors that influenced the results. For a DSM at a scale of 1:10,000 in similar areas, the most appropriate model is DEM-TS.

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Three-dimensional mapping of soil organic matter content using soil type–specific depth functions

Cited by 127 publications

References 21 publications

Calcium-mediated stabilisation of soil organic carbon

Calcium-mediated stabilisation of soil organic carbon

High resolution characterization of the soil organic carbon depth profile in a soil landscape affected by erosion

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

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