Climate change, uncertainty and investment in flood risk reduction

Economic analysis of flood risk management strategies has become more complex due to climate change. This thesis investigates the impact of climate change on investment in flood risk reduction, and applies optimisation methods to support identification of optimal flood risk management strategies. Chapter 2 provides an overview of cost-benefit analysis (CBA) of flood risk management strategies under climate change uncertainty and new information. CBA is applied to determine optimal dike heights under climate change uncertainty and new information in Chapter 3. Chapter 4 studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a flood protection standard. Chapter 5 departs from expected cost minimisation, and applies the minimax regret decision criterion to identify maximum regret minimising flood risk management strategies under the arrival of new climate impact information. The thesis concludes that the modelling of new climate-related information may improve an economic analysis of flood risk management strategies</p

Can altruism stabilise international climate agreements?

We study the impact of altruism on the stability of international climate agreements. We consider the standard two-stage game for the analysis of international environmental agreements where countries announce their participation at the first stage and abatement levels are chosen at the second stage. We modify the game to consider altruism in the participation decision, i.e. countries consider, to a certain extent, the net benefits for other countries in their decisions. We study two types of altruism: impartial altruism, where countries show a concern for all other countries, and community altruism, where the concern extends only to coalition partners. We use the stability of coalitions model (STACO) to illustrate the impacts of both types of altruism on the stability of a climate agreement. We find that a limited degree of altruism is sufficient to stabilise the Grand Coalition such that a globally efficient climate policy can emerge while in the absence of altruism only a fraction of countries would join a climate agreement and the benefits of cooperation would largely remain unexploited. Our results indicate how moving beyond national interests can support the success of international climate agreement

Economic analysis of adaptive strategies for flood risk management under climate change

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management

Can altruism stabilise international climate agreements?

We study the impact of altruism on the stability of international climate agreements. We consider the standard two-stage game for the analysis of international environmental agreements where countries announce their participation at the first stage and abatement levels are chosen at the second stage. We modify the game to consider altruism in the participation decision, i.e. countries consider, to a certain extent, the net benefits for other countries in their decisions. We study two types of altruism: impartial altruism, where countries show a concern for all other countries, and community altruism, where the concern extends only to coalition partners. We use the stability of coalitions model (STACO) to illustrate the impacts of both types of altruism on the stability of a climate agreement. We find that a limited degree of altruism is sufficient to stabilise the Grand Coalition such that a globally efficient climate policy can emerge while in the absence of altruism only a fraction of countries would join a climate agreement and the benefits of cooperation would largely remain unexploited. Our results indicate how moving beyond national interests can support the success of international climate agreement

Economic analysis of adaptive strategies for flood risk management under climate change

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management

A Minimax Regret Analysis of Flood Risk Management Strategies Under Climate Change Uncertainty and Emerging Information

This paper studies the dynamic application of the minimax regret (MR) decision criterion to identify robust flood risk management strategies under climate change uncertainty and emerging information. An MR method is developed that uses multiple learning scenarios, for example about sea level rise or river peak flow development, to analyse effects of changes in information on optimal investment in flood protection. To illustrate the method, optimal dike height and floodplain development are studied in a conceptual model, and conventional and adaptive MR solutions are compared. A dynamic application of the MR decision criterion allows investments to be changed after new information on climate change impacts, which has an effect on today’s optimal investments. The results suggest that adaptive MR solutions are more robust than the solutions obtained from a conventional MR analysis of investments in flood protection. Moreover, adaptive MR analysis with multiple learning scenarios is more general and contains conventional MR analysis as a special case.</p

Impacts of Rainfall Variability and Expected Rainfall Changes on Cost-Effective Adaptation of Water Systems to Climate Change

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable

Impacts of Rainfall Variability and Expected Rainfall Changes on Cost-Effective Adaptation of Water Systems to Climate Change

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable

Bulbar muscle MRI changes in patients with SMA with reduced mouth opening and dysphagia.

Item does not contain fulltextOBJECTIVE: We performed a study in patients with proximal spinal muscular atrophy (SMA) to determine the prevalence of reduced maximal mouth opening (MMO) and its association with dysphagia as a reflection of bulbar dysfunction and visualized the underlying mechanisms using MRI. METHODS: We performed a cross-sectional study of MMO in 145 patients with SMA types 1-4 and 119 healthy controls and used MRI in 12 patients to visualize mandibular condylar shape and sliding and the anatomy of muscle groups relevant for mouth opening and closing. We analyzed associations of reduced MMO with SMA severity and complaints of dysphagia. RESULTS: Reduced MMO was defined as an interincisal distance </= 35 mm and was found in none of the healthy controls and in 100%, 79%, 50%, and 7% of patients with SMA types 1, 2, 3a, and 3b/4, respectively. MRI showed severe fatty degeneration of the lateral pterygoid muscles that mediate mouth opening by allowing mandibular condylar sliding but relatively mild involvement of the mouth closing muscles in patients with reduced MMO. Reduced MMO was associated with SMA type, age, muscle weakness, and dysphagia (p < 0.05). CONCLUSIONS: Reduced MMO is common in SMA types 1-3a and is mainly caused by fatty degeneration of specific mouth opening muscles. Reduced MMO is a sign of bulbar dysfunction in SMA