EGU2020-6902, updated on 21 Jan 2021
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Soil Quality and Health – can it be quantified?

Kirsty Hassall1, Joanna Zawadzka2, Alice Milne1, Gordon Dailey1, Jim Harris2, Ron Corstanje2, and Andrew Whitmore1
Kirsty Hassall et al.
  • 1Rothamsted Research, Harpenden, United Kingdom
  • 2Cranfield University, Cranfield, United Kingdom

Soil quality and health (SQH) are terms used extensively to characterise soils. However, the exact definitions of quality and health are often qualitative with differing meanings to different stakeholders. Collecting and combining these differing viewpoints is a non-trivial task. In this work, we will discuss how we have used the Bayes Net framework to define a hierarchical structure that enables a subjective concept such as soil quality and health to be quantified from multiple sources of information including diverse sources of expert knowledge and linking this through to national databases.

Information within a Bayes Net is encapsulated through a set of conditional probability tables that describe the conditional dependencies of all variables of interest. It is well known that humans are particularly poor at estimating such probabilities which, when a Bayes Net relies upon experts from differing disciplines and stakeholders from disparate application areas to quantify their beliefs through these conditional probability tables, is often a major limitation to these techniques. Here, we demonstrate an elicitation web app that mitigates some of the difficulties associated with quantifying subjective opinion. Moreover, we show how an inference network of known associations aids in the extraction of information from increasingly subjective sources within the hierarchical framework.

How to cite: Hassall, K., Zawadzka, J., Milne, A., Dailey, G., Harris, J., Corstanje, R., and Whitmore, A.: Soil Quality and Health – can it be quantified?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6902,, 2020

Display materials

Display file