It appears increasingly likely that several climate targets set in international agreements will not be met. For the vast majority of the world’s population, which lives along coastlines, this poses a threat. The same goes for the population of the Netherlands, although…

For protection against flooding, the Netherlands has been using an advanced computational model for many years. This model weighs the costs of potential future dike elevations against the expected economic damage from flooding. The calculation is based on projected water levels in the North Sea and major rivers over the coming decades, as well as the economic value of the areas that must be protected against floods (including the monetary value of each resident, expressed as a standard amount).

The water-level calculations are carried out by Rijkswaterstaat (RWS), while the welfare-related calculations are produced by the Netherlands Bureau for Economic Policy Analysis (CPB). The outcome of such an RWS-CPB assessment may be that the costs of raising a dike exceed the expected costs of future flooding. The resulting government decision can then be to stop maintaining and elevating the dikes in a given area. One example concerns the South Holland island of Tiengemeten, which was largely evacuated after such a decision.

Changes in flora and fauna, and therefore in food supply, are another well-known consequence of global warming. There are more consequences still: some threatening, but others offering new opportunities.

The Netherlands can make an important contribution to managing—and, when necessary, anticipating—the many-headed monster that is global warming, but also to seizing any new opportunities it may create. The country is particularly well positioned to do so in areas such as water management and agriculture, two fields in which we are a global powerhouse.

Using computational models that integrate multiple disciplines, it is possible to provide timely and well-founded advice. Mathematics will play a key role in this work. Mathematicians can help develop and connect models originating from different fields. I expect computational models based on both fundamental laws (including the laws of nature) and data. These models will also include stochastic components to account for uncertainty. After all, it is crucial to understand how uncertainties in natural laws and data influence the outcomes of these calculations.

When a model predicts a potential disaster scenario, it may be possible to take effective measures in time, as was the case with Tiengemeten. One remaining challenge would be convincing policymakers and communities that these computational results represent expected facts rather than opinions. Scenarios that point to new opportunities—good news—may require less persuasion…

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This article was translated using AI-assisted tools and reviewed by an editor.