scholarly journals Hyperspectral imaging for high-resolution mapping of soil profile organic carbon distribution in an Austrian Alpine landscape

2020 ◽  
Author(s):  
Yaser Ostovari ◽  
Baptist Köppendörfer ◽  
Julien Guigue ◽  
Jan Willem Van Groenigen ◽  
Rachel Creamer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Organic Carbon ◽  
Hyperspectral Imaging ◽  
Soil Profile ◽  
Partial Least Square ◽  
Learning Approaches ◽  
Soil Cores ◽  
Undisturbed Soil ◽  
Undisturbed Soil Cores ◽  
Soc Stocks

<p>Studies on soil organic carbon (SOC) stocks mostly focus on topsoils (< 30 cm). However, 30 to 63% of the SOC are stored in the subsoils (30 to 100 cm), and the factors controlling SOC storage in subsoils may be substantially different than in topsoils. The low mean SOC content in subsoils makes its quantification and characterization challenging. Thus, new approaches are required to depict the SOC stocks distribution in full soil profile. Hyperspectral imaging of soil core samples can provide high spatial resolution of the vertical distribution of SOC in a soil profile. The main objective of the ongoing study, within the Horizon 2020 European Project Circular Agronomics, is to apply laboratory hyperspectral imaging with a variety of machine learning approaches for the mapping of OC distribution in undisturbed soil cores. Soil cores were collected down to a depth of one meter in grasslands of 15 organic farms located in the Lungau Valley, in Austria. Some samples were divided into five depths in the field for classical bulk soil measurements (total carbon and nitrogen, texture, pH, EC and bulk density) on disturbed samples. Undisturbed soil cores were sliced vertically for laboratory hyperspectral imaging in the range of Vis-NIR (400-1000 nm). We were able to reveal the hotspots of OC and map the OC distribution in soil profile by applying a variety of machine learning approaches (i.e. partial least square and random forest regression) as a function of spectral responses. A digital elevation model was further exploited to investigate the effects of topographical factors such as elevation, aspect and slope on SOC profile distribution. Landsat 8 data were also used to depict the spatial variability of land insensitive cover/vegetation in study area.</p>

Isoproturon movement and dissipation in undisturbed soil cores from a grassed buffer strip

Agronomie ◽  
2000 ◽  
Vol 20 (3) ◽  
pp. 297-307 ◽  
Author(s):  
Pierre Benoit ◽  
Enrique Barriuso ◽  
Philippe Vidon ◽  
Benoit Réal
Keyword(s):  
Soil Cores ◽  
Undisturbed Soil ◽  
Buffer Strip ◽  
Undisturbed Soil Cores

Relationship Between Soil Properties and Nitrogen Mineralization in Undisturbed Soil Cores from California Agroecosystems

2018 ◽  
Vol 50 (1) ◽  
pp. 77-92 ◽  
Author(s):  
Kenneth Miller ◽  
Brenna J. Aegerter ◽  
Nicholas E. Clark ◽  
Michelle Leinfelder-Miles ◽  
Eugene M. Miyao ◽  
...  
Keyword(s):  
Soil Properties ◽  
Nitrogen Mineralization ◽  
Soil Cores ◽  
Undisturbed Soil ◽  
Undisturbed Soil Cores

A comparison of soil organic carbon concentration maps of Great Britain

2021 ◽  
Author(s):  
Christopher Feeney ◽  
Jack Cosby ◽  
David Robinson ◽  
Amy Thomas ◽  
Bridget Emmett
Keyword(s):  
Machine Learning ◽  
Great Britain ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Patterns ◽  
Learning Approaches ◽  
Human Disturbances ◽  
Organic Carbon Concentration ◽  
Scale Properties ◽  
Meta Analyses

<p>Soil organic carbon (SOC) is the largest reservoir of organic carbon in the terrestrial biosphere and is the main constituent of soil organic matter, which underpins key soil functions such as storage and filtration of water, and nutrient cycling. SOC concentrations are controlled by several dynamic variables, ranging from micro-scale properties like particle aggregation, to larger-scale drivers such as climate and land cover. Hence, soils are vulnerable to climate change and human disturbances, with implications for ecosystem services such as agriculture and global warming mitigation. Recent decades have seen greater efforts to monitor SOC dynamics, such as the UKCEH Countryside Survey, and to predict concentrations of SOC where we have no measurements, using geostatistics or machine learning approaches. Yet, there is still much to be understood about what controls spatial patterns of SOC, and how effectively different modelling approaches can capture this. Here, we compare predictions by nine maps of the spatial distribution of topsoil SOC in Great Britain. We found broad similarities in SOC concentrations predicted by all maps, which each showed right-skewed distributions with similar median values (43 to 97 g kg<sup>-1</sup>). The greatest differences between maps occur at higher latitudes and are reflected in the upper ends of the SOC distributions. While the maps generally exhibit a sharp rise in SOC concentrations with increasing latitude from ~54<sup>o</sup>N, values predicted by the ISRIC-2017 and FAO-GSOC maps show weaker increases with increasing latitude, and peak at lower values of 332 g kg<sup>-1</sup> and 354 g kg<sup>-1</sup>, respectively. We demonstrate that most of the maps, regardless of the modelling approach taken or the underlying data used, produced similar estimates of SOC concentration, including broad spatial patterns. This work will form the basis of more detailed future assessments of the sensitivity of SOC mapping to analytical methods versus the data used to drive these methods, and will be used to assess the importance of using stratified random field survey approaches for generating more accurate predictions of areas that cannot be sampled. Exploration of why and where different and coincident SOC predictions occur between maps should shed light on the utility of different modelling techniques and machine-learning meta-analyses of driving variables currently used to map SOC. Understanding how SOC predictions differ across all current national scale GB maps is a first step in improving modelling and assessment of SOC stock and change.</p>

Chromium(VI) leaching from large undisturbed soil lysimeters following application of a simulated copper-chromium-arsenic (CCA) timber preservative

Soil Research ◽  
2002 ◽  
Vol 40 (2) ◽  
pp. 351 ◽  
Author(s):  
P. L. Carey ◽  
V. J. Bidwell ◽  
R. G. McLaren
Keyword(s):  
Organic Matter ◽  
Soil Profile ◽  
Sandy Loam ◽  
Soil Analysis ◽  
Rainfall Simulation ◽  
Soil Cores ◽  
Undisturbed Soil ◽  
First Order ◽  
Copper Chromium ◽  
Soil Lysimeters

Copper, chromium, and arsenic (CCA) solutions are commonly used in New Zealand as a means of preserving softwood timbers such as Pinus radiata. With stock working solutions of CCA salts in timber treatment plants frequently 10% w/v or more, there exists a potential for spillage and leaching of these compounds to groundwater. High concentrations of Cr(VI) (up to 52 mg Cr/L) were found in the leachates of large undisturbed soil lysimeters where a Templeton sandy loam (Immature Pallic) had received surface applications of a simulated copper, chromium, and arsenic (CCA) timber preservative. Leaching was produced by using a combination of natural and imposed rainfall simulation over the lysimeters for a period of 102 days after CCA application. An average of 26% of the applied chromium was collected in the leachates after 102 days. Of the mean 74% of Cr(VI) still retained within the soil profile after leaching ended, almost half was located in the top 100 mm of the profile. No copper or arsenic was detected in any of the lysimeter leachates, with soil analysis indicating that these elements had been retained within the soil profile. In an incubation study, soil cores sampled from the same Templeton sandy loam and split into alternate 50-mm segments (to 450 mm) were stored at 10˚C for 102 days after addition of an identical CCA solution. These were periodically extracted for available chromium. Results showed that the reduction of dichromate/chromate anions (Cr2O72–/CrO42–) to the strongly sorbed chromic cation (Cr3+) was largely first-order and greatest in surface layers where soil organic matter contents were largest. After 102 days, <1% of the added Cr(VI) was still extractable in the 0–50 mm soil cores whilst ≈60% of Cr(VI) in the 400–450 mm cores (or deeper) was still extractable after the same period. A linear systems model comprising a series of conceptual mixing cells was used to describe the individual and mean Cr(VI) leaching breakthrough curves (BTCs). This State-Space Mixing Cell model proved effective in simulating the Cr(VI) leaching using first-order kinetics to quantify rate-limited local solute adsorption coupled to advective-dispersive transport. The solute mass involved in the model process was ≈30%. The bulk of the remaining 70% of applied dichromate was assumed to have undergone reduction to the non-mobile chromium cation. This study shows that there exists a significant potential for Cr(VI) to be a serious threat to groundwater in the event of a large uncontained spillage of a concentrated CCA solution. This potential can be significantly lessened if the Cr(VI) is reduced after retention in an organic matter rich layer.

Three-Dimensional Quantification of Macropore Networks in Undisturbed Soil Cores

1999 ◽  
Vol 63 (6) ◽  
pp. 1530-1543 ◽  
Author(s):  
Johan Perret ◽  
S. O. Prasher ◽  
A. Kantzas ◽  
C. Langford
Keyword(s):  
Three Dimensional ◽  
Soil Cores ◽  
Undisturbed Soil ◽  
Undisturbed Soil Cores

Effect of soil organic carbon loss on the stability and structure of microaggregates: First insights from an organic carbon depletion field trial in a loess soil

2020 ◽  
Author(s):  
Svenja Roosch ◽  
Vincent Felde ◽  
Daniel Uteau ◽  
Stephan Peth
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Aggregate Stability ◽  
Loess Soil ◽  
Conventional Tillage ◽  
High Resolution Computed Tomography ◽  
Undisturbed Soil ◽  
Physicochemical Stability ◽  
The Stability ◽  
Undisturbed Soil Cores

<p>Soil microaggregates are considered to play an important role in soil functioning and soil organic carbon (SOC) is of great importance for the formation and stabilization of these aggregates. The loss of SOC can occur, for example, after a change in land use and may lead to a decreased aggregate stability, which makes soils vulnerable to various threats, such as erosion or compaction. It is therefore important to understand the effect of SOC loss on aggregate stability in order to better understand and preserve the functioning of healthy soils.</p><p>We sampled two adjacent plots from a loess soil in Selhausen (North Rhine-Westphalia, Germany) in November of 2019 and measured aggregate stability and architecture of soil microaggregates. One plot was kept free from vegetation by the application of herbicides and by tillage (to a depth of 5 cm) from 2005 on, while the other plot was used for agriculture (conventional tillage). Over the course of 11 years, the SOC concentration in the bulk soil was reduced from 12.2 to 10.1 g SOC kg<sup>-1</sup> soil. We took 10 undisturbed soil cores from two depths of each plot (Ap and Bt horizons).</p><p>The stability of aggregates against hydraulic and mechanical stresses was tested using the widespread wet sieving approach and a newly developed dry crushing approach. Isolated microaggregates gained from the latter procedure were tested against tensile stress by adapting a crushing test in a load frame to the microaggregate scale. To shed light on the effect of a decreased SOC content on microaggregate structure, we scanned several microaggregates with a high-resolution computed tomography scanner (Zeiss Xradia 520 versa) at sub-micron resolutions and analyzed the features of their pore systems.</p><p>This will give us valuable insights into the interplay of mechanical and physicochemical stability, as well as the structural properties of microaggregates with regard to SOC depletion. The consequences for various soil functions provided by microaggregates, like the habitat function for microorganisms or their capacity to store and transport gas, water and nutrients, are discussed.</p>

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