Educational Game-based Applications

Design storms in a climate that won’t sit still

Students serve as County Engineer for Willow Creek for 20 years. They have a yearly budget, four aging road culverts, and a Public Trust meter that falls with every flood. Each year they decide which crossings to upgrade, then watch the storm season on an animated map and read the newspaper report. They also face trade-offs: buying a climate study, a developer who wants to pave the catchment, and debris warnings. At the end, the game reveals the hidden climate future and compares each pipe’s design level on paper with what it actually delivered.

Learning goal: a culvert designed for the historical “25-year storm” protects less every year as rainfall intensifies.
▶ Play in your browser · Classroom code lets a whole class face the same storms.

Bottom-up vulnerability analysis (decision scaling)

Mill Bend floods two ways: heavier storms push more water down the river, and a rising lake backs water up into town. Students choose a mix of defences (levee raises, an upstream reservoir, a wetland, floodproofing, a lake gate) and run a stress test across 240 possible futures. The response surface fills in square by square, a “breaking point” line appears, and then the climate-model projections drop onto the map. Over three missions, students design for a single best estimate, for an ensemble, and finally for deep uncertainty.

Learning goal: a design that passes the “most likely” future can still fail in a third of plausible ones, so it is better to find where the design breaks first.
▶ Play in your browser

Adaptive planning with signposts, tipping points and lead times

From 2025 to 2100, the lake rises along a hidden low, middle or high path, and students keep Harbourview’s Low District safe in real time. Every action has a cost and a lead time, from a 6-year dike raise to a 20-year storm-surge barrier. One option disappears in 2050. The game pauses at signposts and tipping points, and a metro-style pathways map draws each student’s route as it unfolds. At 2100, the student’s expected cost is compared with “build big now,” “wait and react,” and a planned adaptive pathway.

Learning goal: act one lead time before the tipping point, keep options open, and avoid locking in more than the future may need.
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Flood insurance, risk sharing and household behaviour

Students run Riverside’s flood insurance program for 25 years. Sixty-four households each decide every year whether to insure and whether to floodproof, based on cost, how risky flooding feels to them, and what their neighbours do. This builds on my research on evolutionary game theory and flood insurance. Students reform the program two policies at a time: pricing, subsidies, grants, mandatory cover, disaster aid and reinsurance. Then they watch premiums, claims and aid flow across the town.

Learning goal: see adverse selection, moral hazard and charity hazard happen, and balance coverage, risk reduction, affordability and public cost.
▶ Play in your browser