Browse the contents of 10th International Congress on Environmental Modelling and Software - Brussels, Belgium - June 2020:
- Stream F
F0. General presentations on environmental impact of climate change, environmental pollution and other anthropogenic effects
F1. Using Models to Simulate Impact of Nutrients, Acidification, Sediment transport and Toxicants in Coastal Environments
F2. Integrated methods and tools for coastal and fluvial flood risk management
F3. Large-scale impact modelling including the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)
F4. Modelling transport-related air pollution, from citizens science to dispersion models
- Stream E
E0. General presentations on modelling for the sustainable development goals under global change
E1. Holistic Water-Food-Energy-Environment Nexus for Guiding Resource Management
E2. Towards a new generation of spatio-temporal land-system models
E3. Integrated assessments of policy pathways towards achieving Sustainable Development Goals SDGs
E4. Modelling of Drinking Water Treatments to deal with global change
- Stream D
D0. General presentations on system identification and uncertainty in environmental computing
D1. Beyond Conventional Uncertainty Analysis: New Frameworks, Methods, and Tools for Uncertainty Assessment in Complex Socio-Environmental Models
D2. Best Practice in Agent-Based Model Parameterization and Validation
D3. Quantifying uncertainty in environmental systems: a Bayesian point of view
D4. Including uncertainty within optimisation solution methods used for optimal targeting of best management practices and environmental policy
D5. Advances in scenario discovery and robust decision-making frameworks for designing dynamically robust policy pathwaysD6. Sensitivity analysis for improved model diagnosis, parameter identification, and prediction
D7. Complexity, Sensitivity, and Uncertainty Issues in Integrated Environmental Models- Stream C
C0. General presentations on computational methods, workflows, and integrated systems in environmental modelling
C1. Methods for integrated modelling of spatial-environmental planning issues
C2. Integrated models for energy and climate policy
C3. Hybrid methods of process simulation and machine learning for advancing understanding
C4. Distributed computing in smart farming and agro-informatics
C5. Digital agriculture
C6. New and improved methods in agricultural systems modelling
C7. Large-scale behaviour modelling approaches
C8. Model-coupling frameworks-advances in design, application solutions
C9. Integrated systems for dynamic multi-scale environmental and earth system modeling
C10. Flexible and open modelling developments for hydro-social processes at catchment scale
C11. Toward rapid and real-time groundwater flow model assessments
C12. Environmental fluid mechanics - Theoretical, modeling and experimental approaches
- Stream B
B0. General presentations on processing and visualizing environmental information from big data, data mining, GIS, and remote sensing
B1. Integrating Big Data, Machine Learning and Computational Modeling: Smart Cyber-Physical Systems
B2. Hybrid approaches and predictive intelligence for sustainable environmental decision making
B3. Session on Data Mining as a Tool for Environmental Scientists: 7th edition (S-DMTES-2020)
B4. Modelling and Managing Urban Water and Energy Resources in the Era of Big Data
B5. Innovative IoT systems and IoT data processing techniques for Environmental monitoring
- Stream A
A0. General presentations on decision making & public participation in environmental modelling
A1. Towards Interdisciplinary and Transdisciplinary Collaboration in Environmental Modelling: Innovative Practices to Address Wicked Problems
A2. Participatory Modelling: How to overcome challenges in practice?
A3. Bringing local and expert knowledge together [] combining qualitative and quantitative tools to support participatory modelling
A4. Interactive tools and visualization to support environmental decision-making
A5. Modelling for Policy Support in the European Union
A6. Decision Making Under Uncertainty in Complex Human-Natural Systems in Policy and Practice
A7. Modelling data from Citizen Science based Environmental Campaigns