CSDMS 2021: Changing Landscapes and Seascapes: Modeling for Discovery, Decision Making, and Communication
Eight grand challenges in socio-environmental systems modelling
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.
Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.
Of interest for: Terrestrial Working GroupCoastal Working GroupMarine Working GroupEducation and Knowledge Transfer (EKT) Working GroupCyberinformatics and Numerics Working GroupHydrology Focus Research GroupCarbonates and Biogenics Focus Research GroupChesapeake Focus Research GroupCritical Zone Focus Research GroupHuman Dimensions Focus Research GroupGeodynamics Focus Research GroupEcosystem Dynamics Focus Research GroupCoastal Vulnerability InitiativeContinental Margin InitiativeArtificial Intelligence & Machine Learning InitiativeModeling Platform Interoperability InitiativeRiver Network Modeling Initiative