In this article we look at the most important questions to ask about climate change, so we can make better decisions. Those questions are: Under what circumstances will a system fail? And can we extend a system’s breaking point?


Thinking forward prompts the question of when things will change, and by how much. Answering these questions often involves the use of climate projections. These often disagree and don’t provide much certainty on a timeline. This can be an issue when making decisions for systems that are vulnerable to climate change – like open water storages.

Climate change question 1: Under what circumstances will a system fail?

Climate change is gradually impacting our water resource systems. It is changing both demand and supply. Our systems are robust enough to resist some changes, including those seen in the last few decades. While the effects of climate change will continue to be gradual, uninterrupted change will cause our systems to fail, like the proverbial boiled frog.

This is why we need ‘tipping points’.

A ‘tipping point’ is the last point at which you would still consider performance satisfactory. This point has a corresponding climate described by measurements of variables like temperature, precipitation and evaporation. And, importantly, you can identify this climate without the use of climate change projections.

The previous blog post by Danlu Guo is a great example of how to do just that. Taking historical climate conditions – under which a system is performing well – and changing them can allow you to see the point in which the system breaks. Changes might include higher temperatures or different rainfall combinations.

To demonstrate this idea, we considered a simplified model of Lake Como, Italy. The lake regulator has to protect the city of Como from flooding, and ensure there is enough water for irrigating one of the largest agricultural regions in Europe. This creates challenging decisions: The two are competing interests.

After defining some ‘tipping points’ (for both the allowable flooded area and irrigation deficit) we varied annual temperatures and precipitation to see what would cause the system to fail.

Figure 1. Tipping points for Lake Como.

This figure shows changed rainfall by percentage, combined with a temperature change in degrees celsius. It shows that the system’s success limits are just under zero degrees change through to 15 degrees change, in an upward trend. Meaning that as temperature rises, the system is only successful in climate change scenarios if precipitation also increases, but then only within a small band of variation.


The figure shows that when the amount of rain increases the system floods, and when temperature increases, the system doesn’t have enough water for irrigation. But we also found some robustness when temperature and precipitation increase together. The system remains in a healthy balance as more rain occurs with more evaporation. Importantly, we can quantify the changes in climate that result in failure.

The next question to consider is: How far can this breaking point extend?

Climate change question 2: Can we extend the breaking point of the system?

The answer to this question depends on what a decision maker controls. Each of the climate scenarios in the above figure are fixed. The impact is a result of the physical system and its management.

For example, raising the reservoir walls would decrease the danger of flooding, and decrease the amount of failure scenarios in Figure 1. These large infrastructure actions are quite costly, and are not easily reversible. This could lead to regret if the climate were to change in a way that instead threatened irrigation.

Most water storage systems require a daily release decision. Changes to this operation are low cost, fast to implement and are quite flexible. The flexibility allows decision makers to tailor a response to a particular climate. This can be beneficial as the climate changes in unpredictable ways.

To illustrate, we took the same climate scenarios for Lake Como as above, and instead of using the current operation model, designed a new operation as a response to each individual climate. Figure 2 shows this. The green scenarios represent how far the failure boundary extended.

This ‘adaptive capacity’ approach helped Lake Como perform successfully in three times as many scenarios. Compared to Figure 1, it appears to be easier to adapt to irrigation deficit than to flooding.

Figure 2. Upper limit adaptive capacity.

Figure 2 has green (adaptation), blue (success) and red (failure) in a chart that shows change to rainfall by percent, and change to temperature by degrees celsius. It shows that the ‘adaptive capacity’ approach helped Lake Como perform successfully in three times as many climate change scenarios as those from the previous figure.


When will these tipping points occur?

Climate projection models are still the only way of answering this question.

Below are two projections for the The Lake Como scenario. They are in the same categories of the previous figures. For example, in 2025, 3/22 models predict failure, and 6/22 predict a climate that can be adapted to.

Looking at the projections alone doesn’t give you much information about the system. It is difficult to tell how close some of these projections are to failing. That information is important, given the errors they contain.

Figure 3. Climate projections for the Lake Como reservoir.

The figures show two separate climate change projections: One for 2025, one for 2050.


Identifying the above tipping points can be an important context for looking at projections.

Figure 4 (below) contains 22 climate model projections of the climate of Lake Como in 2025 and 2050. The figure shows that, while the projections change, how the system performs under specific climates does not.

This is where such an approach is useful. You can be more confident in the performance under some projections than others, based on how close they are to the tipping points.

Figure 4. Tipping point approach.

This figure shows the two climate change projections overlaid over one of the previous charts. It shows that while the climate may change, the system understanding does not – and how this might aid decision making.