Traditionally, System Dynamics (SD) is used for modelling and simulating dynamically complex issues and analysing their resulting non-linear behaviours over time in order to develop and test the effectiveness (and robustness) of structural policies brief explanation of traditional SD and typical SD diagrammatic conventions). Mainstream System Dynamicists have assumed for decades that uncertainties are omnipresent, and hence, that trajectories generated with SD simulation models should not be interpreted quantitatively as point or trajectory predictions, but that they should be interpreted qualitatively as general ‘modes of behaviour’. And although univariate and multivariate sensitivity analyses are mostly performed, they are mainly aimed at validation – not exploration. It seems therefore that in traditional SD uncertainties are accepted but are not really explored or explicitly taken into account.
SD models may also be built specifically for the purpose of exploring the potential influence of uncertainties on dynamically complex issues. Such Exploratory System Dynamics (ESD) models are preferably fast-to-build (hours or days) and easily-manageable models, and consequently, rather simple and highly aggregated. ESD is an interesting approach for exploring different model formulations and a plethora of uncertainties, and testing the effectiveness of policies in the face of these parametric and structural uncertainties. However, ESD in isolation may be insufficiently broad and systematic to firmly base (detailed) policymaking under deep uncertainty on. ESDMA (see below) which builds on ESD may be an option for robust policymaking in case of dynamically complex issues under deep uncertainty.
Contact: E. Pruyt
EMA consists of using exploratory models for generating tens of thousands to millions of scenarios (called an ensemble of future worlds) in order to analyse and test the robustness of policy options across this ensemble of future worlds – in other words whether the outcomes are acceptable over the entire scenario space. As such, it can be used to generate insights and understanding about the functioning of systems and the robustness of policies, by taking deep uncertainty seriously into account. In EMA, the question is not ‘when to measure more’ nor ‘when to model better’, but ‘how to explore and analyse dynamically complex systems under deep uncertainty’, and ‘which policies do effectively and robustly improve system behaviour under deep uncertainty’.Contact: J.H. Kwakkel, C. Hamarat
Since EMA requires handy models for generating (thousands of) plausible scenarios, and ESD requires methods for exploring deep uncertainty, they are actually natural complementary allies, and can be combined as Exploratory System Dynamics Modelling and Analysis (ESDMA). This multi-method is very useful (and sufficiently broad and systematic) for exploring and analysing (all) plausible developments over time, and for testing the effectiveness and robustness of adaptive policies without neglecting deep uncertainty and dynamic complexity.Contact: E. Pruyt, J.H. Kwakkel, C. Hamarat
The main aim of this research is to contribute to the practice of model-based decision support for decision making for dynamically complex policy issues under deep uncertainty. Until now, several scientific outputs (conference papers, posters, etc.) has been produced. The project team is leaded by Prof. Wil Thissen and the team members are Caner Hamarat and Erik Pruyt. This project is supported by NGI.Contact: C. Hamarat, E. Pruyt
Within the Energy Delta Gas Research (EDGaR) program, “the Next 50 Years” project aims to develop long-term sustainable robust strategies for the Dutch gas sector. The role of uncertainties in the gas sector and in the selection of strategies is to be investigated in a sub-project called “Dealing with uncertainties in the next 50 years” by primarily using Exploratory Modeling and Analysis. The project is conducted by Sibel Eker under the supervision of Els van Daalen and Erik Pruyt, and promoted by Prof. Wil Thissen. In this project, Technology Dynamics & Sustainable Development section of TPM Faculty and the consultancy company KEMA is closely cooperated.Contact: E. Pruyt, S. Eker
In the Nature article ‘A safe operating space for humanity’, Rockstrom et al. (2009) introduce the concept of a safe operating space for humanity. A safe operating space is the space for human activities that will not push the planet out of the ‘Holocene state’. Rockstrom et al. have identified nine earth-system processes and associated thresholds which, if crossed, are expected to generate unacceptable environmental change. For climate change, rate of biodiversity loss, and the nitrogen cycle the safe global limits are substantiated theoretically and methodologically. The threshold for the global fresh water cycle is a tentative ‘best guess’ (Rockstrom et al. 2009). The article is, thus, an open invitation for further research to improve the framework of planetary boundaries. This research proposal accepts this invitation and sets outs to contribute to establishing the planetary boundaries to global fresh water use.
Our scientific approach is informed by four methodological points of critique on the method advanced by Rockström et al. notably, the ambiguous treatment of reductionism, the neglect of dynamic interactions between the subsystems, the importance of local conditions and scale and structural uncertainties in the relation between the sub-systems. There is uncertainty about the fundamental relations between subsystems, there is uncertainty about future developments external to the models, and there is uncertainty about the valuation of the model outcomes both now and in the future. These uncertainties are referred to as ‘deep’ uncertainty.
In this project, we propose an innovative, non-predictive re-use of the available predictive models, while focusing on the impacts of deep uncertainty and propose Exploratory Modelling and Analysis (EMA) as an appropriate methodology. EMA uses computational experiments to analyze complex and uncertain systems and assumes the existence of and uses multiple models that are consistent with the available information, data, and knowledge. EMA explores these models across the range of plausible parameter values and offers methodological support for drawing valid inferences. We apply the method to existing global and regional dynamic water cycle models and base our conclusions on the resulting safe operating spaces. For this interdisciplinary research we have arranged a team incorporating hydrologists and specialist in operations research, policy analysis and modelling and simulation. Furthermore this group is embedded in an international group of renowned specialist in similar fields.The Nature article ‘A safe operating space for humanity’ (Rockstrom et al. 2009), has received worldwide attention. The proposed research contributes directly to its practical implementation and develops a methodological approach based on integrated dynamic models combined with innovative methods to deal with deep uncertainty that allow for the direct demarcation of safe operating spaces. This method can be transferred to the other sub-systems and thus carries the potential to seriously influence the methodological merits of the safe operating space concept. Societal impact of this research can be expected in the field of long term policy development for which EMA was originally developed, especially through the design of adaptive policies.
Contact: J.H. Kwakkel
The programme is motivated by the observation that the adoption of innovative concepts and technologies in the Netherlands' energy system is much slower than required given the urgency of the foreseeable problems and the substantive system delays. The proposed research therefore aims at insights into, on the one hand, factors that contribute to inertia in Dutch energy transition and, on the other hand, innovative governance strategies for overcoming inertia and providing acceleration of the transition. To this end the programme will combine three complementary research approaches:
The programme will primarily focus on the built environment, and will consider variables at the macro, meso and micro-level, and their interactions. Project 1 will deliver interactive models for comparatively assessing the impact of governance strategies including policy instruments on choices and learning curves for specific technological applications in the Built Environment. Project 2 will deliver a procedure for informed decision-making and, as we expect, one or two specific pilots for the built environment. Project 3 will deliver specific insights into the impact of institutional constraints and dynamics for (multi-)actor decision-making. This project is funded by NWO. Project 1 and 3 are carried out at PA Simulation Lab. Project 2 is carried out at VU University Amsterdam under the supervision of Dr. M. Hisschemöller.
Contact: E. Pruyt
This project concentrates on robust decision making for fresh water supply for the Netherlands. Robust decision making is particularly suited for dealing with deep uncertainties: situations where possible developments can be imagined, but no reliable estimates can be given about their probabilities and outcomes. This includes the types of uncertainties that are often dealt with using scenario-approaches, but also wild-cards or surprise scenarios should be included, and situations in which there is no agreement about what models best represent system behavior.The approach - which is still under development - combines a broad analysis of uncertainties and their possible impacts with an assessment of the performance of selected policy alternatives under a wide range of possible assumptions about the future. The insights thus gained enable analysts and policy makers to identify the conditions under which policies will perform well, and conditions under which policies might fail. They may then select a base policy that will do well under most circumstances, identify future conditions under which policy adaptations are desired, as well as the type of adaptations. The insights gained may also help distinguish between more flexible policy options that allow for easy adaptation as circumstances change, and less flexible ones which may lead to lock-in situations.
Contact: J.H. Kwakkel