Socio-Environmental Systems Modelling

Current Issue

Vol. 5
Published January 20, 2023
Fifth Issue (in preparation)

Earlier Issues: Issue 1 (2019), Issue 2 (2020), Issue 3 (2021) and Issue 4 (2022).

Research Papers

Nicolas Salliou, Tony Arborino, Joan Iverson Nassauer, Diego Salmeron, Philipp Urech, Derek Vollmer, Adrienne Grêt-Regamey
Science-design loop for the design of resilient urban landscapes
Article Full Text (PDF)
Udita Sanga, Jineth Berrío-Martínez, Maja Schlüter‬
Modelling agricultural innovations as a social-ecological phenomenon
Article Full Text (PDF)

Special Issue: Large-scale behavioural models of land use change

Calum Brown, James Millington, Mark Rounsevell
Assessing the quality of land system models: moving from valibration to evaludation
Article Full Text (PDF)

Special Issue: Participatory & cross-scale modelling of SESs in the Anthropocene

Theodore C. Lim, Pierre D. Glynn, Gary W. Shenk, Patrick Bitterman, Joseph H. A. Guillaume, John C. Little, D. G. Webster
Recognizing political influences in participatory social-ecological systems modeling
Article Full Text (PDF) Model
Hsiao-Hsuan Wang, George van Voorn, William E. Grant, Fateme Zare, Carlo Giupponi, Patrick Steinmann, Birgit Müller, Sondoss Elsawah, Hedwig van Delden, Ioannis N. Athanasiadis, Zhanli Sun, Wander Jager, John C. Little, Anthony J. Jakeman
Scale decisions and good practices in socio-environmental systems modelling: guidance and documentation during problem scoping and model formulation
Article Full Text (PDF)

Special Issue: Sensitivity Analysis of Model Output

Hui Duan, Giray Okten
Control variate Monte Carlo estimators based on sparse polynomial chaos expansions
Article Full Text (PDF)
Nabir Mamnun, Christoph Völker, Sebastian Krumscheid, Mihalis Vrekoussis, Lars Nerger
Global sensitivity analysis of a one-dimensional ocean biogeochemical model
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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.