Eight grand challenges in socio-environmental systems modeling

By Sondoss Elsawah and Anthony J. Jakeman

author-sondoss-elsawah
Sondoss Elsawah (biography)

As we enter a new decade with numerous looming social and environmental issues, what are the challenges and opportunities facing the scientific community to unlock the potential of socio-environmental systems modeling?

What is socio-environmental systems modelling?

Socio-environmental systems modelling:

  1. involves developing and/or applying models to investigate complex problems arising from interactions among human (ie. social, economic) and natural (ie. biophysical, ecological, environmental) systems.
  2. can be used to support multiple goals, such as informing decision making and actionable science, promoting learning, education and communication.
  3. is based on a diverse set of computational modeling approaches, including system dynamics, Bayesian networks, agent-based models, dynamic stochastic equilibrium models, statistical microsimulation models and hybrid approaches.

Read moreEight grand challenges in socio-environmental systems modeling

Good practices in system dynamics modelling

By Sondoss Elsawah and Serena Hamilton

sondoss-elsawah
Sondoss Elsawah (biography)

Too often, lessons about modelling practices are left out of papers, including the ad-hoc decisions, serendipities, and failures incurred through the modelling process. The lack of attention to these details can lead to misperceptions about how the modelling process unfolds.

serena-hamilton
Serena Hamilton (biography)

We are part of a small team that examined five case studies where system dynamics was used to model socio-ecological systems. We had direct and intimate knowledge of the modelling process and outcomes in each case. Based on the lessons from the case studies as well as the collective experience of the team, we compiled the following set of good practices for systems dynamics modelling of complex systems.

Read moreGood practices in system dynamics modelling

Sharing integrated modelling practices – Part 2: How to use “patterns”?

By Sondoss Elsawah and Joseph Guillaume

sondoss-elsawah
Sondoss Elsawah (biography)

In part 1 of our blog posts on why use patterns, we argued for making unstated, tacit knowledge about integrated modelling practices explicit by identifying patterns, which link solutions to specific problems and their context. We emphasised the importance of differentiating the underlying concept of a pattern and a pattern artefact – the specific form in which the pattern is explicitly described.

Read moreSharing integrated modelling practices – Part 2: How to use “patterns”?

Sharing integrated modelling practices – Part 1: Why use “patterns”?

By Sondoss Elsawah and Joseph Guillaume

sondoss-elsawah
Sondoss Elsawah (biography)

How can modellers share the tacit knowledge that accumulates over years of practice?

In this blog post we introduce the concept of patterns and make the case for why patterns are a good candidate for transmitting the ‘know-how’ knowledge about modelling practices. We address the question of how to use patterns in a second blog post.

Read moreSharing integrated modelling practices – Part 1: Why use “patterns”?

ICTAM: Bringing mental models to numerical models

By Sondoss Elsawah

sondoss-elsawah
Sondoss Elsawah (biography)

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey.

Read moreICTAM: Bringing mental models to numerical models