The Effect of Soil Properties on Metal Bioavailability: Field Scale Validation to Support Regulatory Acceptance

2013 ◽  
Author(s):  
Amy Hawkins ◽  
Mark Barnett ◽  
Nick Basta ◽  
Elizabeth Dayton ◽  
Roman Lanno ◽  
...  
Keyword(s):  
Soil Properties ◽  
Scale Validation ◽  
Metal Bioavailability ◽  
Field Scale ◽  
Regulatory Acceptance

Sensitivity of selected water retention functions to compaction and inherent soil properties

Soil Research ◽  
1998 ◽  
Vol 36 (2) ◽  
pp. 317 ◽  
Author(s):  
V. Rasiah ◽  
L. A. G. Aylmore
Keyword(s):  
Soil Properties ◽  
Water Retention ◽  
Linear Regression Analysis ◽  
Coefficient Of Determination ◽  
Strongly Correlated ◽  
Limited Information ◽  
Field Scale ◽  
Soil Water Retention ◽  
Landscape Unit ◽  
Retention Characteristics

It is known that field-scale variations in subsurface hydraulic characteristics are influenced, to a large extent, by soil properties. Limited information, however, exists on the sensitivity of hydraulic functions to field-scale variations in soil properties. The sensitivity of 4 soil water retention functions, θ(h), to variations in soil properties and changes in bulk density (ρ) across and within soils along a 500-m transect has been assessed in this study. The θ(h) functions compared are those of van Genuchten, Brooks and Corey, Campbell, and Gardner. Water retention characteristics for 7 soils, each packed to 2 relative ρ, were established for each function. The coefficient of determination, R 2 , for the best fit of water retention ranged from 0·79 to 0· 98 for the Gardner and Campbell functions, from 0· 92 to 0·99 for the Brooks and Corey function, and from 0·83 to 0·99 for the van Genuchten function. Simple linear regression analysis indicated the nonlinear slope parameters of the 4 functions were more strongly correlated with soil properties. However, only the van Genuchten slope parameters were sensitive to changes in ρ. No consistency existed between the sensitivity of the linear parameters of the 4 functions and soil properties, and none were sensitive to changes in ρ. Except for the a parameter in the van Genuchten function, all the parameters in this function can be predicted with satisfactory confidence from soil properties and ρ. The results indicate that, of the 4 functions assessed, the van Genuchten θ(h) function is the most sensitive to field-scale variations in soil properties along a transect in a landscape unit and to changes in ρ.

Three-dimensional digital soil mapping of multiple soil properties at a field-scale using regression kriging

Geoderma ◽  
2020 ◽  
Vol 366 ◽  
pp. 114253 ◽  
Author(s):  
Yakun Zhang ◽  
Wenjun Ji ◽  
Daniel D. Saurette ◽  
Tahmid Huq Easher ◽  
Hongyi Li ◽  
...  
Keyword(s):  
Soil Properties ◽  
Three Dimensional ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Regression Kriging ◽  
Field Scale

Estimation of soil properties at the field scale from satellite data: a comparison between spatial and non-spatial techniques

2014 ◽  
Vol 65 (6) ◽  
pp. 842-851 ◽  
Author(s):  
F. Castaldi ◽  
R. Casa ◽  
A. Castrignanò ◽  
S. Pascucci ◽  
A. Palombo ◽  
...  
Keyword(s):  
Soil Properties ◽  
Satellite Data ◽  
Field Scale

Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties

2014 ◽  
Vol 94 (2) ◽  
pp. 189-208 ◽  
Author(s):  
Catherine A. Fox ◽  
Charles Tarnocai ◽  
Gabriele Broll ◽  
Monika Joschko ◽  
David Kroetsch ◽  
...  
Keyword(s):  
Soil Properties ◽  
Best Management Practices ◽  
Management Practices ◽  
Dynamic Properties ◽  
Experimental Studies ◽  
Density Level ◽  
Field Scale ◽  
Dynamic Soil Properties ◽  
Field Form ◽  
Fingerprint Code

Fox, C. A., Tarnocai, C., Broll, G., Joschko, M., Kroetsch, D. and Kenney, E. 2014. Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties. Can. J. Soil Sci. 94: 189–208. Taxonomic protocols for A horizon description are limited when detailed monitoring of soil change in dynamic soil properties is required for determining the effectiveness of best management practices, remediation efforts, and assessing subtle impacts on soil properties from environmental and anthropogenic stressors. The A Horizon Framework was designed by consolidating protocols from national and international description systems and expert opinion to optimize descriptive capability through use of additional enhanced lowercase designators. The Framework defines new protocols and syntax resulting in a unique soil fingerprint code. Five levels of enhanced lowercase A horizon designators are defined: Level 1, Soil processes and environmental context; Level 2, Soil structure-bulk density; Level 3, Organic carbon; Level 4, pH and electrical conductivity; and, Level 5, Soil and landscape context (i.e., soil texture, surface conditions, current land use, slope character). An electronic Field Form based on the new Framework syntax automatically records the soil fingerprint code in an enhanced (all Levels included) and a minimum detail mode focused on the key dynamic properties. The soil fingerprint codes become a powerful tool by which to identify trends of soil change and small alterations in the dynamic soil properties. Examples of soil fingerprint codes from selected Canada and Germany long-term experimental studies are presented.

Covariates selection assessment for field scale digital soil mapping in the context of precision fertilization management

2020 ◽  
Author(s):  
Nada Mzid ◽  
Stefano Pignatti ◽  
Irina Veretelnikova ◽  
Raffaele Casa
Keyword(s):  
Soil Properties ◽  
Precision Agriculture ◽  
Prediction Models ◽  
Central Italy ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Soil Maps ◽  
Field Scale ◽  
Umbria Region ◽  
Digital Soil Maps

<p>The application of digital soil mapping in precision agriculture is extremely important, since an assessment of the spatial variability of soil properties within cultivated fields is essential in order to optimize agronomic practices such as fertilization, sowing, irrigation and tillage. In this context, it is necessary to develop methods which rely on information that can be obtained rapidly and at low cost. In the present work, an assessment is carried out of what are the most useful covariates to include in the digital soil mapping of field-scale properties of agronomic interest such as texture (clay, sand, silt), soil organic matter and pH in different farms of the Umbria Region in Central Italy. In each farm a proximal sensing-based mapping of the apparent soil electrical resistivity was carried out using the EMAS (Electro-Magnetic Agro Scanner) sensor. Soil sampling and subsequent analysis in the laboratory were carried out in each field. Different covariates were then used in the development of digital soil maps: apparent resistivity, high resolution Digital Elevation Model (DEM) from Lidar data, and bare soil and/or vegetation indices derived from Sentinel-2 images of the experimental fields. The approach followed two steps: (i) estimation of the variables using a Multiple Linear Regression (MLR) model, (ii) spatial interpolation via prediction models (including regression kriging and block kriging). The validity of the digital soil maps results was assessed both in terms of the accuracy in the estimation of soil properties and in terms of their impact on the fertilization prescription maps for nitrogen (N), phosphorus (P) and potassium (K).</p>

Field-Scale Variation in Microbial Activity and Soil Properties in Relation to Mineralization and Sorption of Pesticides in a Sandy Soil

2008 ◽  
Vol 37 (5) ◽  
pp. 1710-1718 ◽  
Author(s):  
F. P. Vinther ◽  
U. C. Brinch ◽  
L. Elsgaard ◽  
L. Fredslund ◽  
B.V. Iversen ◽  
...  
Keyword(s):  
Soil Properties ◽  
Microbial Activity ◽  
Sandy Soil ◽  
Field Scale ◽  
Scale Variation

Field scale temporal and spatial variability of δ13C, δ15N, TC and TN soil properties: Implications for sediment source tracing

Geoderma ◽  
2019 ◽  
Vol 333 ◽  
pp. 108-122 ◽  
Author(s):  
Adrian L. Collins ◽  
Emma Burak ◽  
Paul Harris ◽  
Simon Pulley ◽  
Laura Cardenas ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Sediment Source ◽  
Field Scale ◽  
Source Tracing ◽  
Temporal And Spatial Variability ◽  
Temporal And Spatial
Sign in / Sign up

Export Citation Format

Share Document