More data required to better predict increase in extreme rainfall

Until now, the process of trying to predict an increase in extreme rainfall has been made by using intensity-duration-frequency (IDF) curves – a decades-old system that uses long-term rainfall records collected by monitoring stations. For a more comprehensive picture of the possible extremes, more data should be taken into consideration.

Although the most discussed effect of global climate change may be rising temperatures, the prospect of frequent extreme rainfall is a more serious immediate concern.

Already some regions are dealing with increasing rainfall and serious storms. According to the Intergovernmental Panel on Climate Change, intense rain events have become more common over the past 50 years.

As these events become more common, our infrastructure must be able to handle them.

Drains need to be up to the job, or the roads will flood. Dams need to be able to protect communities from flash flooding, especially in dry riverbed areas.

Airport runways need to slope, so the rain runs off into the drains (which must work).

But how much rain will these drains, dams and runways have to cope with in the future?

Until now, that projection has been made by using intensity-duration-frequency (IDF) curves – a decades-old system that uses long-term rainfall records collected by monitoring stations.

For a more comprehensive picture of the possible extremes, more data should be taken into consideration.

Advances in climate research and hydrology recognise the existence of trends in rainfall records.

If we are trying to predict future rainfall, it is only right to include these trends.

We have tried to do exactly that by developing our own IDF curves that also take time and climate indices into account.

By factoring in these trends and oscillations in rainfall over time, we hope to develop a non-stationary IDF curve methodology that predicts extreme rain events in a given area with greater accuracy.

We tested our new methodology in various parts of the world – in Abu Dhabi, Quebec, Ontario, Arizona, California, Nevada and New Mexico.

Of the 31 monitoring stations that exhibited potential rain trends or cycles, 27 had rainfall intensity records that could be better modelled by accounting for time, climate indices or both.

Our IDF curves have the potential to give urban planners, architects and engineers a better picture of what their buildings will have to cope with.

We hope our research will be used to revise IDF relationships wherever trends and cycles are found in rainfall records.

Further advances in this area will help arid countries deal with increased rainfall.

In the case of the UAE, the country could better plan for extreme rainfall events.

Being able to accurately predict uncommonly heavy rainfall events is important in protecting people, property and investment from harm and losses.

Updated and enhanced IDF-curve methodologies can also help us make better use of rainwater, by designing drainage systems that capture and channel it instead of allowing it to escape.

With this project and others, we believe the UAE can better prepare for the impacts of climate change and even increase its recovery of rainwater.

Latifa Yousef is studying for a master’s in water and environmental engineering at the Masdar Institute of Science and Technology.

Published: May 17, 2014 04:00 AM

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