Disaster management: Early warning for swifter action

This article first appeared in Digital Edge, The Edge Malaysia Weekly, on January 23, 2023 - January 29, 2023.
Disaster management: Early warning for swifter action
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Early warning systems are a crucial adaptive measure to mitigate climate-related events. Affected communities require the alerts triggered by such systems for these may well save their properties, livelihoods and lives.

Take Hong Kong SAR, for example. The city pioneered a territorial landslide early warning system when faced with the threat of worsening landslides in the 1970s, the BBC reported. Deaths from landslides in Hong Kong dropped substantially after the system was introduced and other authorities around the world were inspired to implement landslide early warning systems. There has not been a single landslide fatality in Hong Kong since 2008.

In Malaysia, the importance of early warning systems cannot be overemphasised given the frequent heavy downpours the country has experienced, especially in the past two months. This year, the Department of Irrigation and Drainage (DID) will be rolling out a National Flood Forecasting and Warning System (NaFFWS) to prepare for gloomy days. The NaFFWS will be able to alert authorities 48 hours before a flood and can forecast flooding a week in advance.

HR Wallingford, the core developer of the system, has been involved in flood management schemes for over 70 years. It began its work with the DID in river modelling before naturally progressing into flood forecasting systems.

HR Wallingford uses a three-stage process to develop a flood forecasting system.

“First, you develop and calibrate your models and test them with historical rainfall data, then check your results against historical water data. We have all these measured data from the catchments,” says Emma Brown, project director of HR Wallingford.

“You’ve got a model now that can simulate what has happened in the past. HR Wallingford’s job, which is stage two, is to then turn that model into a live model, which can be fed with real gauge data that’s being recorded now and weather forecasts from the Malaysian Meteorological Department (MetMalaysia). We configure the model system so that it analyses the results and gives the operational forecaster at DID useful, clear and succinct information.

“Stage three is putting it into the server computer at the DID and getting it all running and operational.”

HR Wallingford’s work with the DID began with river modelling, which naturally progressed into flood forecasting systems. River modelling is when a model of a river is built using computer software. Rainfall can then be applied to the model, and water flowing through the river and across the flood plain can be simulated. With that, floods that occurred in the past can be reenacted.

The next step would be to take the model and link it to a rainfall forecast, which is the essence of a flood forecasting system.

“We survey and measure the heights of the land, and from that, you can build a model of the terrain. You can then apply rainfall to the model so that it stimulates the water flow in the river,” says Brown.

“The calibrated computer model simulates what happens if a certain amount of rain falls in a river basin or catchment area. How much of it is going to run off and how much will flow into the river? How quickly is that going to happen? That way, we can predict what will happen.”

With increased intensity of rainfall over shorter periods due to climate change, floods are here to stay. Authorities have no choice but to gather the resources needed to manage the natural disasters that are a consequence of extreme weather events.

To manage floods, the DID has embraced a merger of structural and non-structural methods. In short, structural methods are for building structures such as flood walls, dredging and barriers that prevent water from flowing out of rivers. Meanwhile, flood forecasting is a non-structural method that locates the area of flooding, thus allowing for flood mitigation efforts and for affected communities to be evacuated in time.

Time is of the essence in natural disasters.

“The first 48 hours are crucial as that’s when rainfall forecasts are most accurate. We can also anticipate what might happen a week ahead, although forecasts are less accurate during that period. It can be used to forecast floods, which are more accurate as it get closer,” says Brown.

In concrete jungles like Kuala Lumpur, rain runs off and reaches the river very quickly due to the lack of soil to absorb the moisture. As the water has nowhere else to go, flash floods occur.

KL has yet to be modelled as part of the NaFFWS. Brown says that urban areas, with their extensive drainage networks, require a lot of skill to model.

Flash floods are notoriously tough to predict due to their unpredictable nature.

“We are going to see more flash floods because there will be more rain of greater intensity. The skill is in developing an adaptable system. No catchment, river basin, river or city ever stays the same over time. It is constantly changing,” Brown points out.

“That means in a year or five years, whenever changes have occurred or the climate has changed, you can recalibrate the model to adjust the way it represents the rainfall-runoff process. We need to have that flexibility.”

The NaFFWS has been successfully trialled in three water catchments in Malaysia: Pahang, Terengganu and Kelantan. The second phase was to then broaden the system to 11 basins in the northwest of the country and 11 further catchments on the east coast.

Brown says the next step after implementing the system is to move into a maintenance phase, which involves monitoring how the models are working by tracking their performance. After assessing the performance of the two phases, the DID will decide whether further phases are needed to implement the system in other parts of Malaysia.