Managing uncertainty in modelling of wicked problems: theory and application to Sustainable Aquifer Yield

This thesis presents two approaches to help manage uncertainty in modelling for the resolution of wicked problems , which have no clear problem definition, solution or measure of success. It focuses on Sustainable Aquifer Yield (SAY) as an example. SAY is defined as the pumping volume obtained by a management plan that is expected to satisfy objectives under future conditions within a groundwater system. Integrated modelling can help express, systematise and use knowledge of relevant behaviour of the system, while engaging diverse stakeholders and addressing their interests. Uncertainty is however a key and multifaceted issue when dealing with wicked problems. While many modelling methods exist to help address this uncertainty, there is a need for modellers to be able to integrate these methods purposefully for an applied problem. The research presented involved iteratively proposing two approaches to manage uncertainties in integrated modelling that supports decision making, and exploring the value of each approach by applying it to case studies. For each approach, the applications specifically a) address a technical problem, b) push boundaries on how the problem is viewed, specifically identifying hitherto neglected aspects, and c) address a context where accounting for contested views and surprise is imperative. This research process is described in terms of Critical Systems Practice and resulted in a compilation of linked publications. The first approach proposed is an Uncertainty Management Framework that can be used to help audit the treatment of uncertainty in a step-wise description of an analysis (e.g. evaluating a management plan). The framework provides a formal structure for managing uncertainty by incorporating an uncertainty typology and a set of fundamental uncertainty management actions, but may be too restrictive and demanding for some contexts. To address these limitations, a complementary second approach, designated Iterative Closed Question Modelling, addresses uncertainty by constructing models to test whether each possible answer to a closed question is plausible. The question, assumptions about plausibility and the process of constructing models are all considered uncertain and therefore themselves iteratively critiqued. This approach is formalised in terms of Boundary Critique such that it provides a philosophical foundation justifying the use of a broad range of methods to manage uncertainty in predictive modelling. The thesis concludes that uncertainty needs to be embraced as a natural part of researchers, policy makers and community coming to grips with an evolving situation, rather than being an obstacle to be eliminated. Training of modellers to manage uncertainty needs to specifically address: identification of model scenarios that contradict dominant conclusions; critique of model assumptions and questions from multiple stakeholders’ points of view; and negotiation of the modeller’s role in anticipating surprise (e.g. through understanding consequences of error, design of monitoring, contingency planning and adaptive management). The resulting emphasis on critical thinking about alternative models helps to remind the user that modelling is not a magic trick for seeing the future, but a structured way to reason about both what we do and do not know

A framework for characterising and evaluating the effectiveness of environmental modelling

Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures

Effective modeling for integrated water resource management: a guide to contextual practices by phases and steps and future opportunities

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management. © 2019 Elsevier Lt

Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015

An increasing amount of high-resolution global spatial data are available, and used for various assessments. However, key economic and human development indicators are still mainly provided only at national level, and downscaled by users for gridded spatial analyses. Instead, it would be beneficial to adopt data for sub-national administrative units where available, supplemented by national data where necessary. To this end, we present gap-filled multiannual datasets in gridded form for Gross Domestic Product (GDP) and Human Development Index (HDI). To provide a consistent product over time and space, the sub-national data were only used indirectly, scaling the reported national value and thus, remaining representative of the official statistics. This resulted in annual gridded datasets for GDP per capita (PPP), total GDP (PPP), and HDI, for the whole world at 5 arc-min resolution for the 25-year period of 1990-2015. Additionally, total GDP (PPP) is provided with 30 arc-sec resolution for three time steps (1990, 2000, 2015).The Author(s) 2018.Peer reviewe

Communicating uncertainty: design patterns for framing model results in scientific publications

Uncertainty is a prominent issue in modelling. We learn early in our studies that “all models are wrong, but some are useful.” We also learn accompanying techniques for quantifying performance, and methods for addressing uncertainty within our analyses. When it comes to publishing our results, communicating uncertainty appears to be part of the craft side of modelling, one that we learn best by experience. Sooner or later, we discover that reviewers (and the reader) are willing to accept limitations of our modelling if we use certain key phrases (e.g. “left to future work”) or subtly change our wording (e.g. “seems to indicate” vs. “proves”). Our writing effectively frames the model results, implicitly conveying the author’s judgement about model uncertainty, confidence about results and shaping the reader’s expectations of how the model may be wrong and how it is still useful. While it does not appear to have been broached in the literature on uncertainty in modelling, the framing of model results appears to be one of the primary means by which modellers have addressed uncertainty, and specifically communication of uncertainty, within scientific publications. It is one of the core practices that new modellers need to learn to ensure that their model-based analyses are considered to be credible and useful. Unfortunately, this practice cannot be easily distilled into an algorithm, method or recipe. As with other aspects of the ‘art’ of modelling, there does however appear to be some knowledge that should ideally be transferabl

The use of food imports to overcome local limits to growth

There is a fundamental tension between population growth and carrying capacity, i.e., the population that could potentially be supported using the resources and technologies available at a given time. When population growth outpaces improvements in food production locally, food imports can avoid local limits and allow growth to continue. This import strategy is central to the debate on food security with continuing rapid growth of the world population. This highlights the importance of a quantitative global understanding of where the strategy is implemented, whether it has been successful, and what drivers are involved. We present an integrated quantitative analysis to answer these questions at sub-national and national scale for 1961–2009, focusing on water as the key limiting resource and accounting for resource and technology impacts on local carrying capacity. According to the sub-national estimates, food imports have nearly universally been used to overcome local limits to growth, affecting 3.0 billion people—81% of the population that is approaching or already exceeded local carrying capacity. This strategy is successful in 88% of the cases, being highly dependent on economic purchasing power. In the unsuccessful cases, increases in imports and local productivity have not kept pace with population growth, leaving 460 million people with insufficient food. Where the strategy has been successful, food security of 1.4 billion people has become dependent on imports. Whether or not this dependence on imports is considered desirable, it has policy implications that need to be taken into account.Peer reviewe

From ad-hoc modelling to strategic infrastructure : A manifesto for model management

Models are playing an increasingly prominent role in watershed management, and environmental management more generally. To successfully utilize model-based tools for governing water resources, modelling timelines must match decision making timelines, and modelling costs must fall within budget constraints. Clarity on management options for modelling processes, and effective strategies, are likey to improve outcomes. This paper provides a first conceptualisation of model management and lays out its scope. We define management of numerical models (MNM) as governance, operational support, and administration of modelling, and argue that it is a universal activity that is crucial but often overlooked in organizations that rely on modelling. The paper lays out the leverage points available to a model manager, based on a review of model management practices in several fields, highlights lessons learned, and opportunities for further improvement as model management becomes a mainstream concern in both research and practice.Peer reviewe

The use of food imports to overcome local limits to growth

There is a fundamental tension between population growth and carrying capacity, i.e., the population that could potentially be supported using the resources and technologies available at a given time. When population growth outpaces improvements in food production locally, food imports can avoid local limits and allow growth to continue. This import strategy is central to the debate on food security with continuing rapid growth of the world population. This highlights the importance of a quantitative global understanding of where the strategy is implemented, whether it has been successful, and what drivers are involved. We present an integrated quantitative analysis to answer these questions at sub‐national and national scale for 1961–2009, focusing on water as the key limiting resource and accounting for resource and technology impacts on local carrying capacity. According to the sub‐national estimates, food imports have nearly universally been used to overcome local limits to growth, affecting 3.0 billion people—81% of the population that is approaching or already exceeded local carrying capacity. This strategy is successful in 88% of the cases, being highly dependent on economic purchasing power. In the unsuccessful cases, increases in imports and local productivity have not kept pace with population growth, leaving 460 million people with insufficient food. Where the strategy has been successful, food security of 1.4 billion people has become dependent on imports. Whether or not this dependence on imports is considered desirable, it has policy implications that need to be taken into account

Sharing reasoning behind individual decisions to invest in joint infrastructure

Development of joint irrigation infrastructure increasingly depends on investment decisions made by individual farmers. Farmers base their decisions to invest on their current knowledge and understanding. As irrigation infrastructure development is ultimately a group decision, it is beneficial if individuals have a common understanding of the various values at stake. Sharing the personal reasoning behind individual decisions is a promising approach to build such common understanding. This study demonstrates application of participatory crossover analysis at a workshop in Tasmania, Australia. The workshop gave farmers the opportunity to discuss their broader considerations in investment decisions, beyond just financial or monetary factors. It centered on the question, "In what conditions would you-the individual farmer-invest?" The participants' willingness to pay, in the form of crossover points, was presented as a set of scenarios to start an explorative discussion between irrigators and non-irrigators. Evaluation feedback indicates that the workshop enabled participants to share new information, improved understanding of differences between neighbors, and generated more respect for others and their decisions. As expected, reasoning went beyond economic concerns, and changed over time. Lifestyle choices, long-term intergenerational planning, perceived risks, and intrinsic motivations emerged as factors influencing water valuation. Simply having a facilitated discussion about the reasons underlying individuals' willingness to pay seems to be a useful tool for better informed decision-making about joint irrigation infrastructure, and is worth testing in further case studies.Peer reviewe

A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

| openaire: EC/H2020/819202/EU//SOS.aquaterraClimate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño-Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations - the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) - have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks.Peer reviewe