scholarly journals Processing of conventional soil survey data using geostatistical methods

2011 ◽  
Vol 50 (No. 8) ◽  
pp. 352-357 ◽  
Author(s):  
V. Penížek ◽  
L. Borůvka
Keyword(s):  
Survey Data ◽  
Extreme Values ◽  
Clay Content ◽  
Original Data ◽  
Soil Survey ◽  
Geostatistical Methods ◽  
Suitable Treatment ◽  
Simple Exclusion ◽  
Soil Units ◽  
Zonal Soils

The aim of this study is to find a suitable treatment of conventional soil survey data for geostatistical exploitation. Different aims and methods of a conventional soil survey and the geostatistics can cause some problems. The spatial variability of clay content and pH for an area of 543 km<sup>2</sup> was described by variograms. First the original untreated data were used. Then the original data were treated to overcome the problems that arise from different aims of conventional soil survey and geostatistical approaches. Variograms calculated from the original data, both for clay content and pH, showed a big portion of nugget variability caused by a few extreme values. Simple exclusion of data representing some specific soil units (local extremes, non-zonal soils) did not bring almost any improvement. Exclusion of outlying values from the first three lag classes that were the most influenced due to a relatively big portion of these extreme values provided much better results. The nugget decreased from pure nugget to 50% of the sill variability for clay content and from 81 to 23% for pH.

scholarly journals Geostatistical prediction of clay percentage based on soil survey data

2002 ◽  
Vol 11 (4) ◽  
pp. 381-390
Author(s):  
A. TALKKARI ◽  
L. JAUHIAINEN ◽  
M. YLI-HALLA
Keyword(s):  
Soil Properties ◽  
Spatial Variation ◽  
Survey Data ◽  
Clay Content ◽  
Spherical Model ◽  
Simulation Method ◽  
Soil Survey ◽  
Management Zones ◽  
Additional Information ◽  
Clay Percentage

In precision farming fields may be divided into management zones according to the spatial variation in soil properties. Clay content is an important soil characteristic, because it is associated with other soil properties that are important in management. Soil survey data from 150 sampling sites taken from an area of 218 ha were used to predict the spatial variation of clay percentage geostatistically in an agricultural soil in Jokioinen, Finland. The exponential and spherical models with a nugget component were fitted to the experimental variogram. This indicated that the medium-range pattern could be modelled, but the short-range variation could not, due to sparsity of sample points at short distances. The effect of sampling density on the kriging error was evaluated using the random simulation method. Kriging with a spherical model produced a map with smooth variation in clay percentage. The standard error of kriging estimates decreased only slightly when the density of samples was increased. The predictions were divided into three classes based on the clay percentage. Areas with clay content below 30%, between 30% and 60% and over 60% belong to non-clay, clay and heavy clay zones, respectively. With additional information from the soil samples on the contents of nutrients and organic matter these areas can serve as agricultural management zones.;

Use of Soil Survey Data for Regional Soil Water Simulation Models

1985 ◽  
Vol 49 (5) ◽  
pp. 1238-1244 ◽  
Author(s):  
J. H. M. Wösten ◽  
J. Bouma ◽  
G. H. Stoffelsen
Keyword(s):  
Soil Water ◽  
Survey Data ◽  
Simulation Models ◽  
Soil Survey ◽  
Water Simulation

scholarly journals Local soil quality assessment of north-central Namibia: integrating farmers' and technical knowledge

SOIL ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 47-62 ◽  
Author(s):  
Brice Prudat ◽  
Lena Bloemertz ◽  
Nikolaus J. Kuhn
Keyword(s):  
Soil Quality ◽  
Soil Degradation ◽  
Clay Content ◽  
Small Scale ◽  
Technical Knowledge ◽  
Local Conditions ◽  
North Central ◽  
Local Soil ◽  
Soil Units

Abstract. Soil degradation is a major threat for farmers of semi-arid north-central Namibia. Soil conservation practices can be promoted by the development of soil quality (SQ) evaluation toolboxes that provide ways to evaluate soil degradation. However, such toolboxes must be adapted to local conditions to reach farmers. Based on qualitative (interviews and soil descriptions) and quantitative (laboratory analyses) data, we developed a set of SQ indicators relevant for our study area that integrates farmers' field experiences (FFEs) and technical knowledge. We suggest using participatory mapping to delineate soil units (Oshikwanyama soil units, KwSUs) based on FFEs, which highlight mostly soil properties that integrate long-term productivity and soil hydrological characteristics (i.e. internal SQ). The actual SQ evaluation of a location depends on the KwSU described and is thereafter assessed by field soil texture (i.e. chemical fertility potential) and by soil colour shade (i.e. SOC status). This three-level information aims to reveal SQ improvement potential by comparing, for any location, (a) estimated clay content against median clay content (specific to KwSU) and (b) soil organic status against calculated optimal values (depends on clay content). The combination of farmers' and technical assessment cumulates advantages of both systems of knowledge, namely the integrated long-term knowledge of the farmers and a short- and medium-term SQ status assessment. The toolbox is a suggestion for evaluating SQ and aims to help farmers, rural development planners and researchers from all fields of studies understanding SQ issues in north-central Namibia. This suggested SQ toolbox is adapted to a restricted area of north-central Namibia, but similar tools could be developed in most areas where small-scale agriculture prevails.

scholarly journals Characterization and Evaluation of Land Resources of Valia Block, Bharuch District, Gujarat

Agropedology ◽  
2019 ◽  
Vol 28 (2) ◽  
Author(s):  
G. Tiwari ◽  
◽  
A. Jangir ◽  
R. P. Sharma ◽  
B. Dash ◽  
...  
Keyword(s):  
Calcium Carbonate ◽  
Organic Carbon ◽  
Clay Content ◽  
Ground Truth ◽  
Alluvial Plain ◽  
Soil Survey ◽  
Alkaline Ph ◽  
Soil Series ◽  
Mapping Unit ◽  
High Calcium

Detailed soil survey (1:10000 scale) was carried out using base map prepared from satellite data (IRS-P6 LISS IV and Cartosat-1) and Digital Elevation Models (DEM) in conjunction with Survey of India (SOI) Toposheets of 1:50000 scale in Valia block, Bharuch district of Gujarat. On the basis of landform, slope, land use/land cover and ground truth, six landscape ecological Units (LEUs) were delineated and six soil series were identified in the block. Five soil series occur on alluvial plain (cover 66.16 %) and one soil series occupies pediplain 27.61 %. These series were mapped into ten soil mapping units as phases of soil series. The representative pedons of alluvial plain were moderately deep to very deep and their sand, silt and clay content ranged from 8.2 to 44.4, 9.8 to 40.2 and 43.8 to 55.6 per cent, respectively. These pedons were neutral to strongly alkaline (pH 6.8 - 9.7), non-saline with low to high organic carbon (0.18 – 1.2 %) content, low to high calcium carbonate (5.9 - 26.6 %) and high CEC [>35 cmol (p+) kg-1]. Exchangeable complex of these pedons were dominated by Ca2+ followed by Mg2+, Na+ and K+ cations with high base saturation (72.0 to 99. 4 %). Soils were classified as Vertic Haplustepts, Typic Haplusterts, Typic Calciustepts, Typic Haplustepts and Sodic Haplusterts. The representative pedon of pediplains was shallow, dark brown (7.5YR3/2), clayey, strongly alkaline (pH>8.5), non-saline (<2 dSm-1) and had moderate organic carbon (0.50-0.75 %) and calcium carbonate (5-15 %) with high CEC [>35 cmol (p+) kg-1] and classified as Lithic Haplustepts. The soils were evaluated for their suitability for commonly grown crops (cotton, pigeon pea, wheat and chick pea) and mapping unit 2 and 4 were highly suitable for cotton cultivation and other were moderately to marginal suitable for other crops.

Developing a reliable height function from the J-Leverett parameters to populate water saturation: a case study

2015 ◽  
Vol 55 (1) ◽  
pp. 291
Author(s):  
Bert Filippi ◽  
Bahman Joodi ◽  
Mohammad Sarmadivaleh
Keyword(s):  
Extreme Values ◽  
Water Saturation ◽  
Dynamic Modelling ◽  
Free Water ◽  
Height Function ◽  
Clay Content ◽  
The North ◽  
The North Sea ◽  
Capillary Pressures

Populating water saturation is a critical step in dynamic modelling. This work introduces a different height function that equates directly with the Leverett-J formula. In doing so, the model initialises under quiescent conditions without the need for end-point scaling. The resulting water saturation is a function of permeability, porosity, clay volume and height above the free water level. The Vcl—or clay content—is an important feature in this formulation because it compensates between extreme values of permeability and porosity. This peer-reviewed paper describes how a single height function was sufficient to match the log-derived water saturation for all wells in the Coracle sand of the Surprise Field in the North Sea. The process involved fitting a simple height formula, with the least possible parameters, to the J-function calculated from all the special core analysis (SCAL) data. These parameters were then tuned to match the log-derived water saturation. This technique was subsequently used in other fields where a single height function, which honoured the measured capillary pressures, accurately matched water saturation in all of the wells.

GROUPING OF LOWER FRASER VALLEY SOILS OF BRITISH COLUMBIA BY NUMERICAL METHODS

1973 ◽  
Vol 53 (4) ◽  
pp. 435-443
Author(s):  
B. KLOOSTERMAN ◽  
L. M. LAVKULICH
Keyword(s):  
British Columbia ◽  
Cluster Analysis ◽  
Survey Data ◽  
Soil Classification ◽  
Data File ◽  
Soil Survey ◽  
Data Sets ◽  
Lower Fraser Valley ◽  
Average Profile ◽  
Fraser Valley

The British Columbia Soil Survey Data File was used to numerically classify soils of the Lower Fraser Valley of British Columbia. The data employed in the numerical-classification procedure were routine soil survey data and this classification was compared with the Canadian Soil Classification System. Three types of soil-profile data sets were used: average surface slice, selected average profile, and average profile. Methods of statistical analysis were cluster analysis and hierarchial grouping analysis. No marked differences in grouping resulted by the two methods of analyses. The average profile method seemed to give better correspondence with the Canadian System of Soil Classification. Consideration of surface layers alone did not correspond with the Canadian Soil Classification. The hierarchical grouping scheme resulted in better defined groups than the cluster analysis approach.

A method of storage and rapid retrieval of soil survey data

1978 ◽  
Vol 14 (1) ◽  
pp. 41-43
Author(s):  
P. J. Cole ◽  
K. A. Watson
Keyword(s):  
Survey Data ◽  
Soil Survey
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