Socio-Environmental Systems Modelling

Current Issue

Vol 2 (2020)
Published September 26, 2019
Second Volume

This volume is in progress. Check the first volume here.

Peer-reviewed article

Sondoss Elsawah, Tatiana Filatova, Anthony J. Jakeman, Albert J. Kettner, Moira L. Zellner, Ioannis N. Athanasiadis, Serena H. Hamilton, Robert L. Axtell, Daniel G. Brown, Jonathan M. Gilligan, Marco A. Janssen, Derek T. Robinson, Julie Rozenberg, Isaac I. T. Ullah, Steve J. Lade
16226
Eight grand challenges in socio-environmental systems modeling
https://doi.org/10.18174/sesmo.2020a16226
Article Full Text (PDF)
Grace B. Villamor, David L. Griffith, Andrew Kliskey, Lilian Alessa
16312
Contrasting stakeholder and scientist conceptual models of food-energy-water systems: a case study in Magic Valley, Southern Idaho
https://doi.org/10.18174/sesmo.2020a16312
Article Full Text (PDF)
Meike Will, Jürgen Groeneveld, Karin Frank, Birgit Müller
16325
Combining social network analysis and agent-based modelling to explore dynamics of human interaction: A review
https://doi.org/10.18174/sesmo.2020a16325
Article Full Text (PDF)
Baihua Fu, Joseph H.A. Guillaume, Anthony J. Jakeman, Michael J. Asher
16227
A bricolage-style exploratory scenario analysis to manage uncertainty in socio-environmental systems modeling: investigating integrated water management options
https://doi.org/10.18174/sesmo.2020a16227
Article Full Text (PDF)
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About SESMO

SESMO is an Open Access, Community Driven, Scholarly Journal, that aims:

To progress our understanding, learning and decision making on major socio-environmental issues using advances in model-grounded processes that engage with institutional and governance contexts, cross-sectoral and scale challenges, and stakeholder perspectives.

Fit-for-purpose problem framing, model development and evaluation as well as eclectic uncertainty analysis are stressed so that the advantages and limitations of model-related assumptions are transparent. The aim is to advance model-grounded, learning and decision processes and their wider application to a new level that leads to innovations in thinking and practice to support resolution of grand challenge problems; including generating policy insights and evidence, and reducing and managing critical uncertainties (assumptions, model structure, parameterizations, inputs including future drivers, and boundary conditions). Papers may address how science can help identify and provide germane information and support required by managers, decision-makers and society at large.