Soil Sampling and Interpolation Techniques for Mapping Spatial Variability of Soil Properties

2015 ◽  
pp. 19-53 ◽  
Author(s):  
N.C. Wollenhaupt ◽  
D.J. Mulla ◽  
C.A. Gotway Crawford
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Sampling ◽  
Interpolation Techniques

Soil Spatial Variability in contaminated sites: field sampling procedure in Italy

2021 ◽  
Author(s):  
Piero Manna ◽  
Giuliano Langella ◽  
Simona Vingiani ◽  
Fabio Terribile
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Sampling ◽  
Sampling Scheme ◽  
Contaminated Sites ◽  
Contaminated Site ◽  
Field Sampling ◽  
Sampling Points ◽  
Location Type ◽  
Soil Spatial Variability

<p>Assessment of soil spatial variability is a debated crucial matter in the context of agriculture and environmental management, such as precision agriculture, land erosion and contaminated sites. In rural and industrial areas, the natural complex spatial variability of soil properties (mainly due to changing pedogenetic factors) is further complicated by anthropogenic activities related to soil management (such as deep plowing, sloping vineyards, etc.) or land contamination. Above all, natural and anthropogenic processes considerably overlap in industrial sites or areas affected by illegal waste dumping, where several times type/quantity and especially localization of contaminants are unknown. Proper investigation tools, as much as possible providing rapid, unexpensive and reliable data on soil properties and characteristics, are increasingly requested to scientific community for both the assessment of contamination geography and the soil sampling strategies. Then, focusing on soil sampling of contaminated sites in Europe, the procedure is currently performed according to national regulations, in terms of number, location, type and depth of sampling points.  The Italian regulation (Decree 471/99 - Annex 2) provides a sampling scheme in which the number of observations is commensurated to the geographical extent of the contaminated site. However, data obtained by some Italian surveyed sites, in which a denser sampling scheme was applied, evidenced that observations planned by the regulation were too low and unexpected “hot spots” were not adequately identified. For sure, contamination can frequently follow a very complex site-specific geospatial distribution. Hence, since number, location, type and depth of sampling points has very strong consequences in terms of public safety and costs of characterisation and remediation of contaminated sites, it is a key issue to set up the best strategies for ameliorating field sampling to achieve a proper understanding of the geospatial distribution of soil contamination.</p>

GENERAL AND SPATIAL VARIABILITY OF SOLONETZIC SOILS IN NORTH CENTRAL ALBERTA

1985 ◽  
Vol 65 (1) ◽  
pp. 157-167 ◽  
Author(s):  
M. R. CARTER ◽  
J. R. PEAREN
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Spatial Dependence ◽  
Periodic Variation ◽  
Local Area ◽  
Soil Sampling ◽  
North Central ◽  
Solonetzic Soil ◽  
Ap Horizon ◽  
Soil Variation

The general and spatial variation of several soil profile chracteristics, and properties of agronomic and ameliorative importance, were determined on a regional and local area of Solonetzic soil in north central Alberta. Differences in general variation as characterized by the mean, median, coefficient of variation (CV), and range allowed grouping of soil properties according to high (e.g. EC in the Ap horizon), medium and low (e.g. pH of the Ap horizon) variation. Such grouping, along with specific differences in soil variation between the regional and local area was associated with the saline-sodic characteristics of these Solonetzic soils. Spatial variability was studied using a geostatistical method (variograms) on soil samples obtained from a 5-m grid. The variograms for most of the various soil properties did not reveal strong spatial dependence. Large nugget variances accounted for 60–90% of the total variance. The semivariance approximated the overall variance usually within 10 m. Variograms suggested periodic variation for the pH and EC of the Ap horizon. Extractable Ca in the Bnt horizon and the depth of the Ap and Bnt horizons were anisotropic showing significant spatial dependence with direction of sampling. The implication of soil variability in regard to soil sampling is discussed. Key words: Spatial variability, Solonetzic soil, saline-sodic soil, soil sampling, variogram

Effect of Slope Mesorelief on the Spatial Variability of Soil Properties and Vegetation Index Based on Remote Sensing Data

2019 ◽  
Vol 55 (9) ◽  
pp. 1329-1337
Author(s):  
N. V. Gopp ◽  
T. V. Nechaeva ◽  
O. A. Savenkov ◽  
N. V. Smirnova ◽  
V. V. Smirnov
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Sensing Data

Spatial Variability of Rainfed Wheat Production Under the Influence of Topography and Soil Properties in Loess-Derived Soils, Northern Iran

2020 ◽  
Vol 14 (4) ◽  
pp. 597-608
Author(s):  
Mohammad Ajami ◽  
Ahmad Heidari ◽  
Farhad Khormali ◽  
Mojtaba Zeraatpisheh ◽  
Manouchehr Gorji ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Northern Iran ◽  
Wheat Production ◽  
Rainfed Wheat

scholarly journals Spatial variability in soil properties on slow-forming terraces in the Andes region of Ecuador

2003 ◽  
Vol 72 (1) ◽  
pp. 31-41 ◽  
Author(s):  
Gerd Dercon ◽  
Jozef Deckers ◽  
Gerard Govers ◽  
Jean Poesen ◽  
Henrry Sánchez ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
The Andes ◽  
Andes Region

scholarly journals Spatial variability and mapping of soil fertility status in a high-potential smallholder farming area under sub-humid conditions in Zimbabwe

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Gabriel Soropa ◽  
Olton M. Mbisva ◽  
Justice Nyamangara ◽  
Ermson Z. Nyakatawa ◽  
Newton Nyapwere ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Ph ◽  
Strong Evidence ◽  
Spatial Dependence ◽  
Random Component ◽  
Smallholder Farming ◽  
Mineral N ◽  
Spatial Trend ◽  
Spatial Trends

AbstractA study was conducted to examine spatial variability of soil properties related to fertility in maize fields across varying soil types in ward 10 of Hurungwe district, Zimbabwe; a smallholder farming area with sub-humid conditions and high yield potential. Purposively collected and geo-referenced soil samples were analyzed for texture, pH, soil organic carbon (OC), mineral N, bicarbonate P, and exchangeable K. Linear mixed model was used to analyze spatial variation of the data. The model allowed prediction of soil properties at unsampled sites by the empirical best linear unbiased predictor (EBLUP). Evidence for spatial dependence in the random component of the model was evaluated by calculating Akaike’s information criterion. Soil pH ranged from 4.0 to 6.9 and showed a strong spatial trend increasing from north to south, strong evidence for a difference between the home and outfields with homefields significantly higher and between soil textural classes with the sand clay loam fraction generally higher. Soil OC ranged from 0.2 to 2.02% and showed no spatial trend, but there was strong evidence for a difference between home and outfields, with mean soil OC in homefields significantly larger, and between soil textural classes, with soil OC largest in the sandy clay loams. Both soil pH and OC showed evidence for spatial dependence in the random effect, providing a basis for spatial prediction by the EBLUP, which was presented as a map. There were significant spatial trends in mineral N, available P and exchangeable K, all increasing from north to south; significant differences between homefields and outfields (larger concentrations in homefields), and differences between the soil textural classes with larger concentrations in the sandy clay loams. However, there was no evidence for spatial dependence in the random component, so no attempt was made to map these variables. These results show how management (home fields vs outfields), basic soil properties (texture) and other factors emerging as spatial trends influence key soil properties that determine soil fertility in these conditions. This implies that the best management practices may vary spatially, and that site-specific management is a desirable goal in conditions such as those which apply in Ward 10 of Hurungwe district in Zimbabwe.

Combining sub-field scale soil sampling and GIS interpolation techniques for mapping nutrient hotspots 

2021 ◽  
Author(s):  
Emma Hayes ◽  
Suzanne Higgins ◽  
Donal Mullan ◽  
Josie Geris
Keyword(s):  
Water Quality ◽  
Soil Nutrient ◽  
Nutrient Status ◽  
Soil Sampling ◽  
Nutrient Losses ◽  
Field Scale ◽  
Soil Nutrient Status ◽  
Interpolation Techniques ◽  
Nutrient Hotspots ◽  
Field Variability

<p>The EU Water Framework Directive (WFD) aims to target prevalent poor water quality status. Of the various contributing sources agriculture is particularly important due to the high loading rates of sediment and nutrient losses associated with fertilisation, sowing, and cropping regimes. Understanding soil nutrient status and the potential pathways for nutrient loss either through point or diffuse sources is an important step to improve water quality from an agricultural perspective. Research has demonstrated extensive in-field variability in soil nutrient status. A sampling regime that explores this variability at a sub-field scale is necessary. Traditional soil sampling consists of taking 20-30 cores per field in a W-shaped formation to produce a single bulked core, however, it generally fails to locate nutrient hotspots at finer resolutions. Inappropriate generalised fertilisation and management recommendations can be made in which nutrient hotspots or deficient zones are overlooked. Gridded soil sampling can reveal the full degree of in-field variability in nutrient status to inform more precise and site-specific nutrient applications. High soil phosphorus levels and the concept of legacy nutrient accumulation due to long-term over-application of phosphorus fertiliser in addition to animal slurry is a problem across the island of Ireland.</p><p>This research aims to locate and quantify the presence of soil nutrient hotspots at several field-scale locations in the cross-border Blackwater catchment in Northern Ireland / Republic of Ireland. Based on 35 m sampling grids, the nutrient content at unsampled locations in each field was determined using GIS interpolation techniques. Particular attention was paid to phosphorus, given its role in eutrophication. Gridded soil sampling enables the identification of nutrient hotspots within fields and when combined with an analysis of their location in relation to in-field landscape characteristics and knowledge of current management regimes, the risk of nutrient or sediment loss potential may be defined. This research concluded that traditional W soil sampling of producing one average value per field is not appropriate to uncover the degree of spatial variability in nutrient status and is inappropriate for catchment management of agricultural systems for controlling nutrient losses. Soil sampling at multiple locations per field is deemed to be cost-prohibitive for many farmers. However, sub-field scale soil sampling and appropriate geostatistical interpolation techniques can reveal the degree of variability and suggest an appropriate resolution for field-scale nutrient management that may be necessary to achieve measurable improvements in water quality.</p>

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