Jan Kwakkel

• Dr.ir.
• Professor (Associate) at Delft University of Technology

Sustainable water management in a changing environment full of uncertainty is profoundly challenging. To deal with these uncertainties, dynamic adaptive policies that can be changed over time are suggested. This paper presents a model-driven approach supporting the development of promising adaptation pathways, and illustrates the approach using a h...

There is increasing interest in long-term plans that can adapt to changing situations under conditions of deep uncertainty. We argue that a sustainable plan should not only achieve economic, environmental, and social objectives, but should be robust and able to be adapted over time to (unforeseen) future conditions. Large numbers of papers dealing...

A new paradigm for planning under conditions of deep uncertainty has emerged in the literature. According to this paradigm, a planner should create a strategic vision of the future, commit to short-term actions, and establish a framework to guide future actions. A plan that embodies these ideas allows for its dynamic adaptation over time to meet ch...

The police control room determines where to send available police units to intercept a fleeing fugitive. Models can support the police with decision-making for fugitive interception. The police have, at most, a few minutes to determine an interception strategy. Therefore, a timely calculation of the interception positions is essential to support po...

This paper explores the spatial evolution of a flood-prone, suburban coastal area, Municipio X of Rome. The study investigates land use change through a diachronic analysis, providing empirical data to retrace the implication of the factors that shaped the study area and highlighting the connection between environmental vulnerabilities and planning...

Tin is an important metal for society with a high risk of supply disruptions. It is, therefore, classified as a critical material in many parts of the world. An exception is the European Union, for which tin was classified as a non‐critical material in 2023. However, there are many discrepancies in the literature regarding the definitions and value...

Cities play a critical role in developing adaptable strategies to address the challenges posed by climate change. However, the inherent complexity of urban environments and their uncertain future conditions necessitate exploring innovative approaches and tools to assist the current planning practices. This paper presents a workflow rooted in model-...

Introduction In early stages, the consequences of innovations are often unknown or deeply uncertain. This complicates health economic modelling. The field of decision-making under deep uncertainty (DMDU) uses exploratory modelling (EM) to help decision-makers make sound decisions under conditions of deep uncertainty (i.e., when stakeholders do not...

Decision-making under uncertainty is important for managing human-natural systems in a changing world. A major source of uncertainty that challenges decisions is rooted in their multi-actor settings, i.e., the poorly understood societal actors with diverse values, complex relationships, and conflicting management approaches. Despite general agreeme...

Objectives: In early stages, the consequences of innovations are often unknown or deeply uncertain, which complicates early health economic modeling (EHEM). The field of decision making under deep uncertainty uses exploratory modeling (EM) in situations when the system model, input probabilities/distributions, and consequences are unknown or debat...

To adapt to a changing climate, decision-makers design, evaluate, and implement measures that have an implication of justice on citizens in the present and well into the future. Decision-makers are often required to make decisions without certainty of the consequences and understanding their effects on intergenerational justice. Thus, managing the...

Robust Decision Making (RDM) is an established framework for decision making under deep uncertainty. RDM relies on the idea of scenario neutrality, namely that decision robustness is not affected by how scenarios are generated if these are uniformly distributed and span a sufficiently large range of future states of the world. Several authors have...

To support equitable adaptation planning, quantitative assessments should consider the fairness of the distribution of outcomes to different people. What constitutes a fair distribution, however, is a normative question. In this study, we explore the use of different moral principles drawn from theories of distributive justice to evaluate fairness....

Global mean sea-level rise (SLR) has accelerated since 1900 from less than 2 mm/year during most of the century to more than 3 mm/year since 1993. Decision-makers in coastal countries, however, require information on SLR at the regional scale, where detection of an acceleration in SLR is difficult, because the long-term sea-level signal is obscured...

To support equitable planning, model-based analyses can be used to explore inequality patterns arising from different scenarios. Scenario discovery is increasingly used to extract insights from ensembles of simulation. Here, we apply two scenario discovery approaches for unraveling inequality patterns and their drivers, with an application to spati...

This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results obtain...

The need for explicitly considering equity in climate change adaptation planning is increasingly being recognized. However, evaluations of adaptation often adopt an aggregated perspective, while disaggregation of results is important to learn about who benefits when and where. A typical example is adaptation of rice agriculture in the Vietnam Mekon...

Models for supporting climate adaptation and mitigation planning, mostly in the form of Integrated Assessment Models, are poorly equipped for aiding questions related to fairness of adaptation and mitigation strategies, because they often disregard distributional outcomes. When evaluating policies using such models, the costs and benefits are typic...

Finding leverage points for sustainability transformation of industrial and infrastructure systems is challenging, given that transformation is emergent from the complex interactions among socio-technical system elements over time within a specific social, technical and geographical context. Participatory multi-modelling, in which modellers and sta...

To aid decision making about environmental systems under deep uncertainty, robustness metrics are commonly used to represent system performance over a number of scenarios. However, there are many robustness metrics and many ways of generating scenarios, making it difficult to know which to choose in order to quantify system robustness and to make r...

The importance of cooperation on transboundary waters is stated as a target in the United Nations 2030 Agenda for Sustainable Development Goals (SDG6: water). Cooperation on transboundary water management is critical, particularly because it concerns issues across multiple states, SDGs and targets regarding agriculture, energy, ecosystems, climate...

Progress to-date towards the ambitious global 2030 agenda for sustainable development has been limited, and upheaval from the COVID-19 pandemic will further exacerbate the already significant challenges to Sustainable Development Goal (SDG) achievement. Here, we undertake a model-based global integrated assessment to characterise alternative pathwa...

Modeling is a crucial approach for understanding the past and exploring the future of coupled human-natural systems. However, uncertainty in various forms challenges inferences from modeling results. Model-based support for decision-making has increasingly adopted an emerging exploratory approach. This approach addresses uncertainty explicitly thro...

Coastal cities combine intensive socioeconomic activities and investments with high exposure to flood hazards. Developing effective strategies to manage flood risk in coastal cities is often a costly and complicated process. In designing strategies, engineers rely on computationally demanding flood simulation models, but they can only compare a lim...

Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long‐term planning of water resources systems. These scenarios enable the determination of the robustness of a system—the consideration of performance across a range of plausible futures—and allow...

Scenario Discovery is a widely used method in model-based decision support for identifying common input space properties across ensembles of exploratory model runs. For model runs with behavior over time, these properties are identified by reducing each run to a single value, which obscures potentially decision-relevant dynamics. We address the pro...

Governing risks is not only a technical matter, but also a matter of ethical and societal considerations. In this article, we argue that in addition to scientific and technical uncertainties, we need to also address normative uncertainties of risk decisions. We define normative uncertainties as situations where there are different partially morally...

In designing and retrofitting infrastructure systems, engineers are increasingly confronted by uncertainties about the future operating conditions of these systems, stemming from climate change or rapid socio-economic development. Particularly for long-lived capital-intensive infrastructure components like pumping stations, current engineering prac...

Flood risk management decisions in many countries are based on decision‐support frameworks which rely on cost‐benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the...

Abstract. Coastal cities combine intensive socio-economic activity and investments with high exposure to flood hazards. Developing effective strategies to manage flood risk in coastal cities is often a costly and complicated process. In the design of these strategies, engineers rely on computationally demanding flood simulation models and only comp...

Even though real options analysis (ROA) is often thought as the best tool available for evaluating flexible strategies, there are profound problems with the assumptions underpinning ROA rendering it unsuitable for use in supporting planning and decision‐making on climate adaptation. In the face of dynamic and deep uncertainty about the future, flex...

In recent years, a family of approaches has emerged for supporting decision-making on complex environmental problems characterised by deep uncertainties and competing priorities. Many-Objective Robust Decision Making (MORDM), Multi-scenario MORDM and. Many-Objective Robust Optimization (MORO) differ with respect to the degree to which robustness is...

Transport network criticality analysis aims at ranking transport infrastructure elements based on their contribution to the performance of the overall infrastructure network. Despite the wide variety of transport network criticality metrics, little guidance is available on selecting metrics that are fit for the specific purpose of a study. To addre...

Rivers typically flow through multiple flood-protected areas which are clearly interconnected, as risk reduction measures taken at one area, e.g., heightening dikes or building flood storage areas, affect risk elsewhere. We call these interconnections ‘hydraulic interactions’. The current approach to flood risk management, however, neglects hydraul...

Aquifer Thermal Energy Storage (ATES) is a building technology used to seasonally store thermal energy in the subsurface, which can reduce the energy use of larger buildings by more than half. The spatial layout of ATES systems is a key aspect for the technology, as thermal interactions between neighboring systems can degrade system performance. In...

Most alluvial plains in the world are protected by flood defences, for example, embankments, whose primary aim is to reduce the probability of flooding of the protected areas. At the same time, however, the presence of embankments at one area influences hydraulic conditions of downstream areas located on the same river. These hydraulic interactions...

Dynamic Adaptive Policy Pathways (DAPP) is a DMDU approach that explicitly includes decision making over time. The essence is proactive and dynamic planning in response to how the future actually unfolds. DAPP explores alternative sequences of decisions (adaptation pathways) for multiple futures and illuminates the path dependency of alternative st...

DAP is a DMDU approach for designing a plan that explicitly includes provisions for adaptation as conditions change and knowledge is gained.

A wide variety of tools and approaches for supporting the making of decisions under deep uncertainty have been put forward, but we lack a comparative overview.

Climate change raises serious concerns for policymakers that want to ensure the success of long-term policies. To guarantee satisfactory decisions in the face of deep uncertainties, adaptive policy pathways might be used. Adaptive policy pathways are designed to take actions according to how the future will actually unfold. In adaptive pathways, a...

Adaptive policies have emerged as a valuable strategy for dealing with uncertainties by recognising the capacity of systems to adapt over time to new circumstances and surprises. The efficacy of adaptive policies hinges on detecting on-going change and ensuring that actions are indeed taken if and when necessary. This is operationalised by includin...

Integrated assessment models often treat land-use change as an external driving force. In reality, land-use is influenced by environmental conditions. This paper explores the merits of endogenising land-use change, i.e. making the land-use change a dynamic internal process, in models used for supporting climate adaptation planning. For this purpose...

Coherent responses to important problems such as climate change require involving a multitude of stakeholders in a transformative process leading to development of policy pathways. The process of coming to an agreement on policy pathways requires critical reflection on underlying system conceptualizations and commitment to building capacity in all...

The modelling of social-ecological systems can provide useful insights into the interaction of social and environmental processes. However, quantitative social-ecological models should acknowledge the complexity and uncertainty of both underlying subsystems. For example, the agent-based models which are increasingly popular for groundwater studies...

Scenario discovery is a model‐based approach for scenario development, aimed at finding one or more subspaces within the uncertainty space associated with a model that is decision‐relevant. These identified subspaces can subsequently be translated into narratives or shared in other ways a broader participatory process. Finding such as subspace invo...

Large, complex coastal regions often require a combination of interventions to lower the risk of flooding to an acceptable level. In practice, a limited number of strategies are considered and interdependencies between interventions are often simplified. This paper presents the Multiple Lines of Defence Optimization System (MODOS)‐model. This quick...

Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery phase to i...

Complex environmental models typically require global sensitivity analysis (GSA) to account for non-linearities and parametric interactions. However, variance-based GSA is highly computationally expensive. While different screening methods can estimate GSA results, these techniques typically impose restrictions on sampling methods and input types....

Glynn et al. (2017) note the importance of engaging stakeholders in the process of public policymaking and analysis. In particular, they highlight the central role biases, beliefs, heuristics, and values (BBVH) play in such engagement. However, the framework they propose neglects uncertainty, which significantly restricts any ability to engage effe...

Methods for testing and analyzing agent-based models have drawn increasing attention in the literature, in the context of efforts to establish standard frameworks for the development and documentation of models. This process can benefit from the use of established software environments for data analysis and visualization. For instance, the popular...

The chapter concerns the measurement and forecasting of technological change, a topic relevant to many high-tech organizations and their customers. We revisit recent and classic data sets from technology forecasting data envelopment analysis (TFDEA) research and technometrics in light of a new visualization technique known as t-Distributed Stochast...

Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential cause...

Uncertainty assessment and management, as well as the associated decision making are increasingly important in a variety of scientific fields. While uncertainty analysis has a long tradition, meeting sustainable development goals through long-term Life Cycle Engineering (LCE) decision making demands addressing Deep Uncertainty (DU). DU characterize...

Aquifer Thermal Energy Storage (ATES) is an innovative building technology that can be used to store thermal energy in natural subsurface formations [1, 4, 10]. In combination with a heat pump, ATES can reduce the energy demand of larger buildings by more than half, which has made the technology increasingly popular in northern Europe (see Figure 1...

Energy transitions unfold under the influence of socio-technical, political and economic uncertainties. This paper introduces a narrative-informed exploratory approach for analysing future energy transition pathways under these uncertainty conditions. In this approach, exploratory modelling is used to explore the impact of various uncertainties, su...

There is a growing interest in model-based decision support under deep uncertainty, reflected in a variety of approaches being put forward in the literature. A key idea shared among these is the use of models for exploratory rather than predictive purposes. Exploratory modeling aims at exploring the implications for decision making of the various p...

Adaptation pathways approaches support long-term planning under uncertainty. The use of adaptation pathways implies a systematic monitoring effort to inform future adaptation decisions. Such monitoring should feed into a long-term collaborative learning process between multiple actors at various levels. This raises questions about who should monito...

Developing fresh water supply strategies for the long term needs to take into account the fact that the future is deeply uncertain. Not only the extent of climate change and the extent and nature of its impacts are unknown, also socio-economic conditions may change in unpredictable ways, as well as social preferences. Often, it is not possible to f...

A variety of model-based approaches for supporting decision-making under deep uncertainty have been suggested, but they are rarely compared and contrasted. In this paper, we compare Robust Decision-Making with Dynamic Adaptive Policy Pathways. We apply both to a hypothetical case inspired by a river reach in the Rhine Delta of the Netherlands, and...

The paper concerns the measurement and forecasting of technological change, a topic relevant to many high-tech organizations and their customers. We revisit recent and classic datasets from technology forecasting data envelopment analysis (TFDEA) research and technometrics in light of a new visualization technique known as t-distributed stochastic...

Aquifer Thermal Energy Storage (ATES) can yield significant reductions in the energy use and greenhouse gas (GHG) emissions of larger buildings, and the use of these systems has been rapidly growing in Europe – especially in the Netherlands, where over 3000 systems are currently active in urban areas. However, the successful management of this tech...

While the shale revolution was largely a US’ affair, it affects the global energy system. In this paper, we look at the effects of this spectacular increase in natural gas, and oil, extraction capacity can have on the mix of primary energy sources, on energy prices, and through that on internal political stability of rentier states. We use two expl...

Nowadays, decision-makers face deep uncertainties from a myriad of external factors such as climate change, population growth, new technologies, and economic developments. The challenge is to develop robust policies, which perform well across all possible resolutions of the uncertainties. One approach for achieving this is to design a policy to be...

This paper presents a strategic model for port-hinterland freight distribution networks. The approach utilizes a combination of a multi-objective optimization model to estimate locations and networks of distribution centers and an assignment model that recognizes distributed service level preferences. Our example application concerns the European c...

Developing model-based narratives of society’s response to climate change is challenged by two factors. First, society’s response to possible future climate change is subject to many uncertainties. Second, we argue that society’s mitigation action emerge out of the actions and interactions of the many actors in society. Together, these two factors...

Scenario discovery is a model-based approach to scenario development under deep uncertainty. Scenario discovery relies on the use of statistical machine learning algorithms. The most frequently used algorithm is the Patient Rule Induction Method (PRIM). This algorithm identifies regions in an uncertain model input space that are highly predictive o...

Deltas are generally recognized as vulnerable to climate change and therefore a salient topic in adaptation science. Deltas are also highly dynamic systems viewed from physical (erosion, sedimentation, subsidence), social (demographic), economic (trade), infrastructures (transport, energy, metropolization) and cultural (multi-ethnic) perspectives....

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 appropriate. Instead, multiple plausible futures need to be considered, which requires (i) uncertainties to be described with the aid of scenarios that represent cohe...

Big-data quality for policy Many people see big data as the solution to large societal challenges. But is this really the case? To what extend is the current interest in big data merely an example of the hype cycle, which is common to many technologies? Based on experiences in several big data projects, we explore what is truly novel about big data...

Scenario discovery is a novel model-based approach to scenario development in the presence of deep uncertainty. Scenario discovery frequently relies on the Patient Rule Induction Method (PRIM). PRIM identifies regions in the model input space that are highly predictive of producing model outcomes that are of interest. To identify these, PRIM uses a...

During the first months, the 2014 outbreak of the Ebola virus (EBOV) in West Africa was characterised by inadequate intervention capacities. In this paper, we investigate (1) the influence of limited but dynamic intervention capacities and their effect on the effective reproduction number, and (2) the effects of proactive versus reactive interventi...

Societal ageing is a messy problem with diverging stakeholder views regarding the desirability of policy measures. In this paper, we use a System Dynamics model representing the Dutch demographic and social security system to investigate if and when Dutch governmental retirement and healthcare contributions become unaffordable. Following the Robust...

Deltas are generally recognized as vulnerable to climate change and therefore a salient topic in adaptation science. Deltas are also highly dynamic systems viewed from physical (erosion, sedimentation, subsidence), social (demographic), economic (trade), infrastructures (transport, energy, metropolization) and cultural (multi-ethnic) perspectives....

Under the moniker of Adaptive Delta Management (ADM), adaptive policy making moved from science to practice within 10 years. This fast uptake of scientific work in policy analysis, was enabled by the development of the Dutch Delta Program that incorporated ADM as its main conceptual framework from its inception in 2010. The rapid absorption of ADM...