A system dynamics mode-based exploratory analysis of salt water intrusion in coastal aquifers

Coastal communities dependent upon groundwater resources for drinking water and irrigation are vulnerable to salinization of the groundwater reserve. The increasing uncertainty associated with changing climatic conditions, population and economic development, and technological advances poses significant challenges for freshwater management. The research reported in this paper offers an approach for investigating and addressing the challenges to freshwater management using innovative exploratory modeling techniques. We present a generic system dynamics model of a low lying coastal region that depends on its groundwater resources. This systems model covers population, agriculture, industry, and the groundwater reserve. The system model in turn is coupled to a powerful scenario generator, which is capable of producing a comprehensive range of plausible future scenarios. Each scenario describes a unique future pathway of the evolution of population, the economy, agricultural and water purification technologies. We explore the behavior of the systems model across a wide range of scenarios and analyze the implications of these scenarios for freshwater management in the coastal region. In particular, the results are summarized in a decision tree that provides insights into the expected outcomes given the various uncertainties, thus supporting the development of effective policies for managing the coastal aquifer.Multi Actor SystemsTechnology, Policy and Managemen

Strategies to combat salt water intrusion in coastal aquifers: A model-based exploratory analysis

Coastal communities dependent upon groundwater resources for drinking water and irrigation are vulnerable to salinization of the groundwater reserve. The increasing uncertainty associated with changing climatic conditions, population and economic development, and technological advances in agriculture, water treatment, and water purification, poses significant challenges for freshwater management. The research reported in this paper offers an approach for investigating and addressing the challenges to freshwater management using innovative exploratory modeling techniques. We present a generic systems model of a low lying coastal region that depends on its groundwater resources. This systems model covers population, agriculture, industry, and the groundwater reserve. The model captures the key dynamics of these subsystems and their interactions (adapted from Hoekstra, 1998). The systems model in turn is coupled to a powerful scenario generator, which is capable of producing a comprehensive range of plausible future scenarios (Lempert et al., 2003). Each scenario describes a unique future pathway of the evolution of population, the economy, agricultural and water purification technologies. We explore the behavior of the systems model across the wide range of scenarios and analyze the implications of these scenarios for freshwater management in the coastal region. In particular, the results are summarized in a decision tree that provides insights into the expected outcomes given the various uncertainties, thus supporting the development of effective policies for managing the coastal aquifer.Multi Actor SystemsTechnology, Policy and Managemen

Is real options analysis fit for purpose in supporting climate adaptation planning and decision-making?

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, flexible strategies which can be adapted in response to how the uncertainty is resolving are attractive. Traditional cost-benefit analysis cannot account for the value created through optionality. ROA sets out to amend this. There are however several profound problems with how ROA tries to do this. It is typically not clear what is the baseline plan, without options, against which value is to be estimated. Different baselines significantly change option value. Even if option value can unequivocally be established for a given scenario, ROA relies on expected values over a set of scenarios. First, this requires assigning weights, or probabilities, to scenarios. Given the long-time horizon involved in climate adaptation, these probabilities are meaningless. Second, the expected value over a set of scenarios need not obtain in any single scenario and is thus not a meaningful summary of option value. This article is categorized under:. Climate Economics > Iterative Risk-Management Policy Portfolios.Policy Analysi

The treatment of uncertainty in airport strategic planning

The treatment of uncertainty in the long-term planning of infrastructures in general and of mainports such as airports and seaports is a key challenge for decisionmakers. Moreover, these uncertainties have increased over the last decades due to changes in owner structure, changes in rules and regulations, and the ever increasing connectedness of the world. This dissertation explores how the treatment of uncertainties in airport planning can be improved. Currently, the treatment is limited to one or a few forecasts for the future. Such an approach limits the exploration of the multiplicity of futures to those that are judged to be most likely. However, if the last decade has taught is anything, then it is that the future will be substantially different from the one we are anticipating now. The implication of this for decisionmaking is that any plan or policy optimized for one or a few forecasts is likely to perform poorly. An alternative approach that is capable of handling the multiplicity of futures and accepts the limits on predictability is needed. Such an approach should result in a plans consist of time-urgent low regret options that can be taken immediately, while establishing a framework for guiding future actions. Thus the decisionmaker is able to adapt the plan to the way in which the future unfolds. This dissertation presents such a dynamic adaptive planning approach, tailors this approach to the specifics of airport planning, and provides computational evidence for the efficacy of plans that are designed utilizing this approach.Policy AnalysisTechnology, Policy and Managemen

The Exploratory Modeling Workbench: An open source toolkit for exploratory modeling, scenario discovery, and (multi-objective) robust decision making

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 presently irresolvable uncertainties. This is achieved by conducting series of computational experiments that cover how the various uncertainties might resolve. This paper presents an open source library supporting this. The Exploratory Modeling Workbench is implemented in Python. It is designed to (i) support the generation and execution of series of computational experiments; and (ii) support the visualization and analysis of the results from the computational experiments. The Exploratory Modeling Workbench enables users to easily perform exploratory modeling with existing models, identify the policy-relevant uncertainties, assess the efficacy of policy options, and iteratively improve candidate strategies.Policy Analysi

Improving scenario discovery by bagging random boxes

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 of model outcomes that are of interest. To identify these regions, PRIM uses a hill-climbing optimization procedure. This suggests that PRIM can suffer from the usual defects of hill climbing optimization algorithms, including local optima, plateaus, and ridges and valleys. In case of PRIM, these problems are even more pronounced when dealing with heterogeneously typed data. Drawing inspiration from machine learning research on random forests, we present an improved version of PRIM. This improved version is based on the idea of performing multiple PRIM analyses based on randomly selected features and combining these results using a bagging technique. The efficacy of the approach is demonstrated using three cases. Each of the cases has been published before and used PRIM. We compare the results found using PRIM with the results found using the improved version of PRIM. We find that the improved version is more robust to new data, can better cope with heterogeneously typed data, and is less prone to overfitting.Policy Analysi

Blue limits of the Blue Planet: An exploratory analysis of safe operating spaces for human water use under deep uncertainty

In the Nature article ‘A safe operating space for humanity’, Rockström 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’ that has seen human civilizations arise, develop, and thrive. Rockström et al. have identified nine earth-system processes and associated thresholds which, if crossed, are expected to generate unacceptable environmental change. These include among others climate change, rate of biodiversity loss, interference with the nitrogen and phosphorus cycles, and global freshwater use. Rockström et al. provide only a best guess for the limits to global freshwater use. Molden (2009) concurs with Rockström et al. that there are physical limits to human interventions in natural processes. However, these limits are critically depended on local conditions, the role of management, and financial and institutional capacity in magnifying or ameliorating problems, and estimates of these limits are plagued by uncertainty. In case of the limits to the world water system, these uncertainties arise out of conflicting models, regional variations, limitation of expansion of water use through financial and institutional capacity, and uncertainty about the realization and efficiency of trans-boundary water transfers. This paper aims at investigating more thoroughly the limits to global freshwater use. To this end, the behavior of a dynamic model of the world water balance is explored across a wide variety of uncertainties. We find that the dynamics at a global level are not substantially affected by this. This is explained in light of the order of magnitude difference between annual human water use and annual runoff.Multi Actor SystemsTechnology, Policy and Managemen

Limits to Planetary Fresh Water Use: A Multi-Model Investigation

There has been a renewed interest over the last few years in limits to various earth bound systems and processes. This has been instigated by the work of Rockström and colleagues on planetary limits. Essentially, the planetary limit concept can be understood as a modern update to the seminal system dynamics work on limits to growth. The central idea of planetary limits is to identify thresholds in various earth bound systems and processes that, if crossed, would push the earth system out of its Holocene state. This work has been criticized for overlooking key feedbacks between the various earth bound systems and the ignoring the uncertainty that is intrinsic to any assessment of these limits. In this paper, we address these issues by using integrated system dynamics models in an exploratory way. We demonstrate this approach by investigating limits to planetary fresh water use using two world water models, namely ANEMI and WorldWater. The initial results suggests that sever water shortage is driven by the need to dilute waste water, and food demand and production. We discuss directions for improving the overall methodology and the case specific application.Multi Actor SystemsTechnology, Policy and Managemen

Exploratory system dynamics: A directed search for limits to global water use

Rockström et al. (2009) introduced the concept of a safe operating space for humanity that will not push the planet out of the ‘Holocene state’. These limits are being investigated for various earth bound systems. Estimates of these limits are plagued by uncertainty. In case of the limits to the world water system, these uncertainties arise out of conflicting models, regional variations, limitation of expansion of water use through financial and institutional capacity, uncertainty about the realization and efficiency of trans-boundary water transfers, and interdependency between the water system and other earth systems. This paper aims at investigating the limits to global freshwater use. To this end, the behavior of a System Dynamic model of the world water balance is explored across a wide variety of uncertainties. Active non-linear testing is used to identify the best case and worst case for water stress and world population. We find counter intuitive results related to the occurrence of maximum water stress, conclude that global limits can be investigated with a spatially aggregated model and are strengthened in our hypotheses that exploratory modeling adds to the understanding of complex and uncertain issues in a way that predictive approaches cannotMulti Actor SystemsTechnology, Policy and Managemen

On considering robustness in the search phase of Robust Decision Making: A comparison of Many-Objective Robust Decision Making, multi-scenario Many-Objective Robust Decision Making, and Many Objective Robust Optimization

In recent years, a family of approaches has emerged for supporting decision-making on complex environmental problems characterized 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 considered during the search for promising candidate solutions. To assess the efficacy of these three methods, we compare them using three different policy formulations of the lake problem: inter-temporal, planned adaptive, and direct policy search. The more robustness is considered in the search phase, the more robust solutions are also after re-evaluation but also the lower the performance in individual reference scenarios. Adaptive policy formulations positively affect robustness, but do not reduce the price for robustness. Multi-scenario MORDM strikes a pragmatic balance between robustness considerations and optimality in individual scenarios, at reasonable computational costs.Policy Analysi