This year Dunedin was said to have experienced a ‘one in one hundred year’ flood. NIWA’s flow prediction model uses a unique method that feeds real-time measured river flow observations back into the model. A quick version is a snapshot of the.

“There’s clearly a difference in costs when you have to replace a floor rather than clean it, but the judgement on when to replace is variable. To understand the magnitude of current and future floods, accurate data are essential. NIWA’s Andrew Tait says local government and other owners/operators of buildings, infrastructure and services must use the information to take a ‘risk-based approach’ to managing their systems. running the code. By the end of the weekend, all roads in and out of Whanganui were closed. It’s too simple to think of floods as simply heavy rain running into rivers, which then overrun their banks. In the exhausted and frustrated aftermath, one question arose: why? “We don’t have a long record to assess: just over 100 years of data on river flow, and nearly 150 years of rainfall data. In the context of flooding, susceptible is a road that can be flooded because it is in a flood plain; exposed is a road that has flooding due to rainwater or overflow from a nearby channel; infected is a road that is flooded and cannot be used; and recovered is a road where the floodwater has receded. Armed with river flows forecast from 1 to 36 hours ahead of the rain actually making it into the rivers, the council will be able to judge the likelihood of floods and make plans. The difficulty is knowing how much more.”. Floods are among the most destructive natural disasters, which are highly complex to model. Copy and Edit 3. Although the data we collected are useful for estimating direct costs for buildings and contents damage immediately following the flood, economic losses associated with clean-up, temporary accommodation and business disruption will accrue for many months to come. Data will be used to set up the tailored West Coast model from various sources, such as rain gauges, soil conditions from Landcare Research, land cover, geology and river network data, and river flow data. In addition to an upgraded weather model resolution representing New Zealand in 1.5 square kilometre blocks, TopNet is also being fine-tuned to specific catchments.

Conditions can vary greatly across any catchment – the area where water is draining into common end points. Also, the existing flood monitoring systems provide limited information about the propagation of flooding in road networks and the impacts on urban mobility. Roddy Henderson of NIWA’s Natural Hazards Centre says it is essential to update the estimates because New Zealand only has relatively short periods of data on record. These have only been validated so far at a global scale. “We model those flow data across all non-monitored streams, using factors such as rain intensity across the catchment in which the stream lies, differences in land use, and soil make-up.

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