A subaqueous soil‐landscape conceptual model to guide soil survey in Chesapeake Bay subestuaries

2021 ◽  
Author(s):  
Barret M. Wessel ◽  
Martin C. Rabenhorst ◽  
Brian A. Needelman
Keyword(s):  
Chesapeake Bay ◽  
Conceptual Model ◽  
Soil Survey ◽  
Soil Landscape ◽  
Subaqueous Soil

Distribution and causes of intricate saline - sodic soil patterns in an upland South Australian hillslope

Soil Research ◽  
2009 ◽  
Vol 47 (3) ◽  
pp. 328 ◽  
Author(s):  
M. Thomas ◽  
R. W. Fitzpatrick ◽  
G. S. Heinson
Keyword(s):  
Soil Survey ◽  
Terrain Analysis ◽  
Topographic Wetness Index ◽  
Sodic Soil ◽  
Near Surface ◽  
Landscape Processes ◽  
Surface Water Flow ◽  
Geophysical Surveys ◽  
Soil Landscape ◽  
D Loop

We describe a soil–landscape investigation conducted in a South Australian upland hillslope (128 ha) to understand the distribution and causes of saline–sodic soil patterns using convenient, ground-based geophysical surveys of the hillslope. These surveys included: (i) EM31 for deep (~6 m) apparent electrical conductivity (ECa) patterns, (ii) EM38 for shallow (>1.5 m) ECa patterns, and (iii) Bartington MS2-D loop sensor for surface volume magnetic susceptibility (κ) patterns. From these surveys we inferred hillslope distributions of: (i) deep (~6 m) concentrations of salinity associated with deep groundwater systems and deposits of magnetic gravels (dominated by maghemite and hematite) (EM31 sensor); (ii) shallow (<1.5 m) soil salinity (EM38 sensor); and (iii) preservation of pedogenic magnetic materials (e.g. maghemite and hematite) (MS2-D loop sensor). We also describe terrain analysis to locate near-surface hydropedological patterns using topographic wetness index. When combined in 3D geographic information system, strong visual matches were identified between patterns in: (i) geophysical surveys, (ii) terrain, and (iii) soil survey data, thus allowing integrated interpretations of soil–landscape pedogenic processes to be made on a whole-of-landscape basis. Such mechanistic interpretations of soil–landscape processes reveal and map intricate saline and sodic soil–regolith patterns and groundwater and fresh surface water flow paths that were not revealed during a previous traditional soil survey.

Development in Soil Survey; History of Geomorphology and Soil Landscape Projects

Soil Horizons ◽  
2008 ◽  
Vol 49 (4) ◽  
pp. 98
Author(s):  
W. D. Nettleton ◽  
W. C. Lynn
Keyword(s):  
Soil Survey ◽  
Soil Landscape ◽  
History Of

Quantitative soil - landscape models for the Haldon and Hurunui soil sets, New Zealand

Soil Research ◽  
2005 ◽  
Vol 43 (2) ◽  
pp. 127 ◽  
Author(s):  
Jochen Schmidt ◽  
Phil Tonkin ◽  
Allan Hewitt
Keyword(s):  
New Zealand ◽  
Soil Properties ◽  
Soil Survey ◽  
Fuzzy Classification ◽  
Aerial Photographs ◽  
Soil Profiles ◽  
Land Resource ◽  
Landscape Models ◽  
Soil Landscape ◽  
Landscape Units

Limited resources and large areas of steeplands with limited field access forced soil and land resource surveyors in New Zealand often to develop generalised models of soil–landscape relationships and to use these to produce soil maps by manual interpretation of aerial photographs and field survey. This method is subjective and non-reproducible. Recent studies showed the utility of digital information and analysis to complement manual soil survey. The study presents quantitative soil–landscape models for the Hurunui and Haldon soil sets (New Zealand), developed from conceptual soil–landscape models. Spatial modelling techniques, including terrain analysis and fuzzy classification, are applied to compute membership maps of landform components for the study areas. The membership maps can be used to derive a ‘hard’ classification of land components and uncertainty maps. A soil taxonomic model is developed based on field data (soil profiles), which attaches dominant soil profiles and soil properties, including their uncertainties, to the defined land components. The method presented in this study is proposed as a potential technique for modelling land components of steepland areas in New Zealand, in which the spatial soil variation is dominantly controlled by landform properties. A soil map was developed that includes the uncertainty in the fundamental definitions of landscape units and the variability of soil properties within landscape units.

Subaqueous Soil-Landscape Relationships in a Rhode Island Estuary

2003 ◽  
Vol 67 (5) ◽  
pp. 1487-1495 ◽  
Author(s):  
Michael P. Bradley ◽  
Mark H. Stolt
Keyword(s):  
Rhode Island ◽  
Soil Landscape ◽  
Subaqueous Soil

scholarly journals An expert system for allocating soils to landforms through the application of soil survey tacit knowledge

2005 ◽  
Vol 85 (1) ◽  
pp. 103-112 ◽  
Author(s):  
R. A. MacMillan ◽  
W. W. Pettapiece ◽  
J. A. Brierley
Keyword(s):  
Tacit Knowledge ◽  
Original Data ◽  
Soil Survey ◽  
Process Models ◽  
Rule Base ◽  
Landscape Models ◽  
Soil Landscape ◽  
The Individual ◽  
Relationship Of ◽  
The Relationship

Soil survey is a paradigm-based science that relies heavily on the application of conceptual soil-landscape models, which in turn are based upon tacit pedological knowledge. This tacit knowledge is generally acquired by systematic field observation and recording the relationships between the occurrence of soils and associated landform positions. Soil survey databases identify the types of soils within a delineated area but they do not generally describe the relationship of specific soils with specific landscape positions. A case in point is the recently completed 1:100 000 scale soil landscape database prepared for the agricultural region of Alberta, Canada. In order to utilize this database with various interpretative algorithms a procedure for allocating soils to specific landform positions needed to be developed. The development of this procedure initially involved capturing the local tacit pedological knowledge in a series of tables and programs. The procedure was then applied to the Alberta soil survey database to automatically assign soils to landform positions and then to assign specific slope characteristics to the individual soils. The resulting soil-landform product was more useable than the original data for input to land based process models. Key words: Soil survey, tacit knowledge, soil-landscape modeling, heuristic rule base, predictive mapping

scholarly journals Digital soil mapping and its implications in the extrapolation of soil-landscape relationships in detailed scale

2017 ◽  
Vol 52 (8) ◽  
pp. 633-642
Author(s):  
Mario Sergio Wolski ◽  
Ricardo Simão Diniz Dalmolin ◽  
Carlos Alberto Flores ◽  
Jean Michel Moura-Bueno ◽  
Alexandre ten Caten ◽  
...  
Keyword(s):  
Soil Mapping ◽  
Soil Survey ◽  
Digital Soil Mapping ◽  
Limiting Factor ◽  
Topographic Map ◽  
Kappa Index ◽  
Terrain Attributes ◽  
Soil Landscape ◽  
Mapping Techniques ◽  
Map Scale

Abstract: The objective of this work was to test the extrapolation of soil-landscape relationships in a reference area (RA) to a topographic map (scale 1:50,000), using digital soil mapping (DSM), and to compare these results to those obtained in similar studies previously conducted in Brazil. A soil survey in a 10 km2 RA, using conventional mapping techniques (scale 1:10,000), was made in order to map a 678 km2 physiographically similar area (scale 1:50,000) using DSM. The decision tree technique was employed to build a predictive extrapolation model based on soil classes and eight terrain attributes in the RA. The validation of DSM by application of field observation points resulted in a 66.1% global accuracy and in 0.36 kappa index. The most representative soils in the area were correctly predicted, whereas the less representative and less frequent soils in the landscape (and consequently with reduced sampling) had their prediction compromised. The RA proportion, which equals 1.5% of the total area, is a limiting factor in the formulation of soil-landscape relationships to precisely represent the mapped area by DSM.

Indicator of risk of water contamination by P for Soil Landscape of Canada polygons

2000 ◽  
Vol 80 (1) ◽  
pp. 153-163 ◽  
Author(s):  
M. A. Bolinder ◽  
R. R. Simard ◽  
S. Beauchemin ◽  
K. B. MacDonald
Keyword(s):  
Water Contamination ◽  
Overland Flow ◽  
Crop Residues ◽  
Census Data ◽  
Soil Survey ◽  
Inorganic Fertilizer ◽  
Soil Test ◽  
Soil P ◽  
Soil Landscape ◽  
Soil Test P

The indicator of risk of water contamination (IROWC) is a component of the Agriculture and Agri-Food Canada Agri-Environmental Indicator project. The IROWC measures progress in reducing the risk of water contamination from agricultural activities, focusing on N and P. The objective of this study was to propose a methodology for an IROWC-P applicable at the Soil Landscape of Canada (SLC) polygon level (1:1 000 000 map scale) using an indexing approach. The sources of data included Census of Agriculture, SLC and soil survey databases and provincial soil test data. The IROWC-P considers the following site characteristics: soil erosion and potential for overland flow, annual P balance (crop residues, manure and inorganic fertilizer), soil test P (STP) and degree of soil P saturation (DSPS). IROWC-P classifies polygons for their potential risk of P transfer to surface waters according to five vulnerability classes (i.e., very low, low, medium, high and very high). The methodology was tested on a pilot basis for selected SLC polygons in the province of Quebec using 1981 and 1991 census data. Preliminary results indicated that the proposed methodology showed some sensitivity to changes in agricultural practices between 1981 and 1991 and reflected differences in risk of P contamination from areas of intensive compared to areas of extensive agriculture. The difference between the selected areas was mainly attributed to the STP, DSPS, manure and inorganic fertilizer P polygon characteristics. The temporal variations in the IROWC-P ratings were attributed mainly to the manure and inorganic fertilizer P polygon characteristics. Key words: Degree of soil P saturation, soil P index, environmental risk, soil test P

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