The College of Agriculture and Natural Resources at Michigan State University is excited and honored to host the International Congress on Environmental Modelling & Software in 2024. Every day, Spartans work to solve the most pressing global challenges, while providing life-changing opportunities to a diverse and inclusive academic community. Michigan State University is beautiful during the summer and offers special access to cutting edge labs, affordable housing for student attendees and real-life examples of environments being modelled by researchers attending the 12th International Congress on Environmental Modelling & Software.
Stream A. Decision making and public participation in environmental modelling
Nagesh Kolagani, Alexey Voinov & Steven Gray
This stream through its various sessions seeks to bring together academic experts, action researchers and practitioners to explore recent developments in participatory decision making, modelling, design and research to solve complex problems of today. We will focus on questions related to the latest trends in participatory research, what role AI and Machine Learning can play in advancing participatory methods, how to organise, support and promote stakeholder participation, as well as how diversity among stakeholder groups can help and related areas.
Stream B. Modeling environmental fate of contaminants, human well-being and ecological public health
Chris Knightes & Junzhi Liu
Environmental modelling of the environmental fate of a variety of contaminants in and across all environmental media is a powerful tool for regulatory and management strategies. Topics in this stream may cover aspects of modelling the chemical and physical transformation of pollutants in air, water and soil, the impact of pollution on human and ecosystem health, biodiversity and the integrated assessment of potential synergies and unintended consequences of technical, behavioural and nature-based solutions.
Stream C. Computational methods, workflows, informatics and integrated systems in environmental modelling
Min Chen, Cheng-Zhi Qin & Vidya Samadi
This stream will cover a range of approaches including open integrated system, and computational intelligence methods in environmental modeling, e.g., computational workflow development, data analytics, and hybrid models of AI and environmental informatics.
Stream D. System design, identification and uncertainty in modelling complex environmental & agricultural systems
Georgii Alexandrov, Val Snow and Saman Razavi
Modelling complex environmental and agricultural systems inevitably leads to a problem of the design or structure of the system and the identification of the “true values” of numerous parameters that affect model predictions. This stream will include topics related to the methods, tools, and applications in systems design, parameter identification, and evaluation of uncertainty of model predictions. We particularly welcome sessions and submissions that address the impact of a lack of knowledge about the systems design or parameters on likely outcomes in agricultural or environmental problems.
This is a companion discussion topic for the original entry at https://www.comses.net/events/732