CSDMS 2021: Changing Landscapes and Seascapes: Modeling for Discovery, Decision Making, and Communication

Eight grand challenges in socio-environmental systems modelling

Sondoss El Sawah

Australian Defense Force Academy, Australia

Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. With the advent of new techniques, data sources, and computational power on the one hand, and the growing sustainability challenges on the other, the expectation is that SES modeling should be more widely used to inform decision-making at multiple scales. This presentation will highlight the grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. These challenges include: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. The presentation will outline the steps required to surmount the underpinning barriers and priority research areas in SES modelling and propose clear directions for future generations of models and modeling, to both their developers and users.

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Of interest for:
  • Terrestrial Working Group
  • Coastal Working Group
  • Marine Working Group
  • Education and Knowledge Transfer (EKT) Working Group
  • Cyberinformatics and Numerics Working Group
  • Hydrology Focus Research Group
  • Chesapeake Focus Research Group
  • Critical Zone Focus Research Group
  • Human Dimensions Focus Research Group
  • Geodynamics Focus Research Group
  • Ecosystem Dynamics Focus Research Group
  • Coastal Vulnerability Initiative
  • Continental Margin Initiative
  • Artificial Intelligence & Machine Learning Initiative
  • Modeling Platform Interoperability Initiative
  • River Network Modeling Initiative