Developing HEPS for humanitarian action

Contributed by Liz Stephens

Evacuated villagers
Villagers evacuated before Typhoon Phailin, India

Within the HEPEX community I’m sure we would all like to see our research and forecasting efforts contributing to better preparedness before disasters; hopefully saving lives and livelihoods. We also know that in many situations our forecast models have seen a flood coming well in advance.

But for many disasters, a good forecast has not led to anything more than humanitarian organisations spreading the word that something is imminent, whereas many might hope that aid could be prepositioned or evacuations could be carried out – something that the Indian government  managed so effectively prior to Typhoon Phailin (though post-disaster recovery was arguably less successful). Moving supplies or evacuating people by road prior to a flood is much cheaper than using a helicopter during the disaster.

Ultimately, funding is required to evacuate or preposition supplies, but despite the known benefits of acting before a disaster strikes, donors are reluctant to release money when there is no certainty that the disaster will occur, and so a paradigm shift is needed to convince donors of the benefit of acting early even when the event will not happen on every occasion they do so. Coughlan de Perez et al. have an excellent paper, currently in NHESS discussions, on how the Red Cross are carrying out pilot schemes to effect this shift, but little work has been undertaken elsewhere to look at how forecasts could be used.

This is perhaps because another issue surrounding the use of forecasts is that humanitarian action usually falls within two categories, either response to a disaster that has already happened, or long-term disaster risk reduction. With funding channelled through these functions, who takes the responsibility for forecast-based action?

These are perhaps problems that do not fall within the typical HEPS-scientist skillset, but solving them is vital if we want to see our models used. I believe that we need to do our best from the modelling side to ensure that pilot schemes are successful, but we also need to appreciate that the successful use of forecasts is not solely a scientific problem related to model skill. How would you feel if your charity donation went towards preparing for a disaster that never happened?



  1. Liz, perhaps with an accumulation of numerous examples of (good) forecasts, where decision makers took the needed action (and the cases where they did not act) with the beneficial (bad) outcomes, a strong case can be made for taking the needed preemptive measures. I confess, I have not yet read the Coughlan de Perez et al paper. In any case, it’s unfortunate that most politicians, at least in the U.S. (but maybe this is just human nature), are reactive rather than proactive…

  2. Nice post — the examples remind us that the value of the forecast derives from its influence on decisions.

  3. Thomas – That would be lovely, though it’s a little bit of a chicken-egg situation; without examples decision-makers wouldn’t act, without acting it’s difficult to have examples. The pilot projects are designed to overcome this, hopefully they are successful but even then I wonder how easy it will be to scale it up.

    Fakhruddin – That looks like an interesting project, perhaps you might like to write a HEPEX blog about it at some point? The Red Cross have said that perhaps the only forecasts they do use are those for hurricanes in the Caribbean – largely because they have good skill some way in advance. You should make sure that they are aware of your project if they are not already.

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