Robust global sensitivity analysis under deep uncertainty via scenario analysis
Complex social-ecological systems models typically need to consider deeply uncertain long
run future conditions. The influence of this deep (ie incalculable, uncontrollable) uncertainty …
run future conditions. The influence of this deep (ie incalculable, uncontrollable) uncertainty …
Incorporating deep uncertainty into the elementary effects method for robust global sensitivity analysis
Internally-consistent scenarios are increasingly used in social–ecological systems modelling
to explore how a complex system might be influenced by deeply uncertain future conditions …
to explore how a complex system might be influenced by deeply uncertain future conditions …
Robust sensitivity analysis to uncertainties in environmental and socio-economic scenarios: A perspective from a global socio-ecological system model
Uncertainties exist in modelling and simulating complex socio-ecological systems due to
unknown, unmeasurable, and uncontrollable occurrence probabilities of future conditions …
unknown, unmeasurable, and uncontrollable occurrence probabilities of future conditions …
A global sensitivity analysis approach for identifying critical sources of uncertainty in non-identifiable, spatially distributed environmental models: A holistic analysis …
Abstracts Environmental models have a key role to play in understanding complex
environmental phenomena in space and time. Although their inherent uncertainty and non …
environmental phenomena in space and time. Although their inherent uncertainty and non …
Position paper: Sensitivity analysis of spatially distributed environmental models-a pragmatic framework for the exploration of uncertainty sources
Sensitivity analysis (SA) has been used to evaluate the behavior and quality of
environmental models by estimating the contributions of potential uncertainty sources to …
environmental models by estimating the contributions of potential uncertainty sources to …
Uncertainty analysis in multi‐sector systems: Considerations for risk analysis, projection, and planning for complex systems
Simulation models of multi‐sector systems are increasingly used to understand societal
resilience to climate and economic shocks and change. However, multi‐sector systems are …
resilience to climate and economic shocks and change. However, multi‐sector systems are …
An uncertain future, deep uncertainty, scenarios, robustness and adaptation: How do they fit together?
A highly uncertain future due to changes in climate, technology and socio-economics has
led to the realisation that identification of “best-guess” future conditions might no longer be …
led to the realisation that identification of “best-guess” future conditions might no longer be …
Variance-based global sensitivity analysis and beyond in life cycle assessment: an application to geothermal heating networks
M Jaxa-Rozen, AS Pratiwi, E Trutnevyte - The International Journal of Life …, 2021 - Springer
Purpose Global sensitivity analysis increasingly replaces manual sensitivity analysis in life
cycle assessment (LCA). Variance-based global sensitivity analysis identifies influential …
cycle assessment (LCA). Variance-based global sensitivity analysis identifies influential …
Development of a sensitivity analysis framework for aquatic biogeochemical models using machine learning
H Cai, Y Shimoda, J Mao, GB Arhonditsis - Ecological Informatics, 2023 - Elsevier
Our evolving understanding of ecosystem functioning along with the advent of computational
power have paved the way for the development of complex mathematical models that …
power have paved the way for the development of complex mathematical models that …
Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational …
Dynamical earth and environmental systems models are typically computationally intensive
and highly parameterized with many uncertain parameters. Together, these characteristics …
and highly parameterized with many uncertain parameters. Together, these characteristics …