Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: using soil compaction as an example

Mads Troldborg*, Inge Aalders, Willie Towers, Paul D. Hallett, Blair M. McKenzie, A. Glyn Bengough, Allan Lilly, Bruce C. Ball, Rupert L. Hough

*Corresponding author for this work

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

The assessment of areas at risk from various soil threats is a key task within the proposed EU Soil Framework Directive. Such assessment is, however, hampered by the complex nature of the soil threats, which result from the sometimes poorly understood interaction of various soil physical properties, climatic factors and land management practices. Methodologies for risk assessment of soil threats are needed to protect the soil quality for future generations and to target resources to the areas at greatest risk. We present here a generic risk framework for the development of Bayesian Belief Networks (BBNs) to estimate the risk from soil threats. The generic BBN structure follows a standard risk assessment approach, where the risk is quantified by combining assessments of vulnerability and exposure. The soil's vulnerability to a given threat is determined from inherent soil and site characteristics as well as from climatic factors influencing soil characteristics, while the exposure estimate is based on an evaluation of the stresses inflicted by land management and climate. The generic framework is demonstrated by taking soil compaction as an example. Soil compaction is a major threat to soil function particularly in highly managed agricultural systems and is known to have many adverse effects on farming systems including decreased crop yield and soil productivity, increased management costs, increased emissions of greenhouse gases, and decreased water infiltration into the soil leading to accelerated run-off and risk of soil erosion. Existing modelling approaches to predict soil compaction risk either require data on soil mechanical behaviour that are difficult and expensive to collect, or are expert-based systems that are highly subjective and sometimes cannot accommodate the myriad of processes underlying compaction risk. Using the generic framework, a detailed BBN for assessing the risk of soil compaction is developed. The BBN allows for combining available data from standard soil surveys and land use databases with qualitative expert knowledge and explicitly accounts for uncertainties in the assessment of the risk. The BBN is applied to identify the distribution of the compaction risk across Scotland using data from the National Soils Inventory of Scotland. (C) 2013 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)56-68
Number of pages13
JournalSoil & Tillage Research
Volume132
DOIs
Publication statusPublished - Aug 2013

Keywords

  • soil compaction
  • risk assessment
  • uncertainty
  • Bayesian Belief Network
  • expert knowledge
  • soil framework directive
  • high axle load
  • induced subsoil compaction
  • tyre inflation pressure
  • African forestry soils
  • dry bulk-density
  • precompression stress
  • physical-properties
  • agricultural soils
  • arable soils
  • organic-matter

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