NIWA launches high resolution flood forecasting


There was a common factor in the floods that hit swathes of New Zealand midway through this year — they were all forecastable…providing you have a high resolution weather forecasting capability, a national catchment model, a water flow prediction model and an impact prediction and assessment model that all interact with each other in real time.

NIWA, and New Zealand, now have this capability.

It takes a lot more than a simple weather forecast, because factors other than rainfall influence floods. In a country that gets as much rain as we do, it was an obvious choice for NIWA to invest in developing and improving high resolution flood event and impact forecasting tailored to New Zealand’s climate and topography. The science is now at a stage where I believe we should be introducing a routine national flood forecasting and response service. The next step is to invest in tailoring NIWA’s flood forecasting models for each of the nation’s key at-risk catchment areas.

I argue that not to utilise the nation’s flood forecasting capability would be a travesty – especially when we can be sure there are more floods to come. Furthermore, we can be sure that, as a consequence of a changing climate, some of these floods may well be worse than we’ve yet experienced and more frequent – 1 in 100 year floods may occur every decade or so. We forecast that the changing climate will bring warmer and wetter weather to parts of New Zealand. The [email protected] project is examining the extent to which climate change is already increasing flood frequency and intensity.

Visit the [email protected] website

NIWA can now forecast and monitor rainfall across the country to a resolution of 1.5 square kilometres. Our TopNet flow prediction model accounts for every step the water takes in its journey from the moment it hits the tree canopy to when it runs into waterways. TopNet can forecast, hours ahead, how rainfall will change river heights and flow rates. Then, the RiskScape tool shows where the water will go if these waterways flood. It can also estimate the cost of the damage to our buildings and businesses.

We are on the cusp of joining these tools together to make forecasts for river heights that will give local authorities time to deploy protective measures and move people and assets. We already have the ability to model and cost flood damage to better inform decisions on curbing or designing development in flood-prone zones.

For example, we are designing a system to forecast what happens in the catchments feeding the Buller and Grey Rivers. Our river flow prediction model feeds real-time measured river flow observations back into the model. This corrects the model on-the-fly to improve future forecasts. It ensures that errors in rainfall forecasts, such as were experienced in the Whanganui floods, are minimised in flood forecasts.

To be clear, New Zealand has the capability to forecast, within a few hours, all the floods experienced this year.

Let’s also be clear that this is no mean feat. Floods aren’t as simple as heavy rain running into rivers. As I said before, rainfall is not the only predictor of floods. But if our model is tailored to each catchment, we can be very accurate.

We are currently planning a feasibility study to run a flood forecast model for the whole country. The model will use data on soils and vegetation mapped across the whole of New Zealand. We will then run the model on our supercomputer to generate river height information.

NIWA has just completed linking our higher resolution weather model – forecasting down to an area of only 1.5 square kilometres – with the TopNet flow prediction model. We aim to provide the most accurate and timely warning of heights and flows ever possible for most waterways.

It’s time to bring an end to surprise floods. It’s time to bring an end to floodwater damaging buildings and displacing people and businesses. Science has the ability to help us react quickly, and adapt to the coming changes over time.

New Zealand needs to resolve to apply the knowledge it already has.

Note: This feature originally appeared in Water & Atmosphere, September 2015