The devastating floods last December exposed serious deficiencies in Malaysia’s disaster response protocols.
Part of the problem was due to the outdated approach to flood management.
Last month, Association of Water and Energy Research Malaysia president S. Piarapakaran said the government needed to adopt a “more holistic approach” to tackle the issue.
Piarapakaran suggested that data be gathered and then funnelled into a central collection system where a computer simulation model could be created to better predict weather, inundation, and water flow patterns.
“Gather as much data as possible from various agencies, including the Department of Irrigation and Drainage, and put them into the simulation model.
“Based on the results, the authorities can then decide on suitable mitigation plans. Simulation models have to be based on concrete data, which will ensure higher accuracy,” he said.
In the aftermath of Hurricane Katrina in 2005, the United States’ Defence Advanced Research Projects Agency (DARPA) commissioned a programme to develop a system that detects and automatically alerts users to flooding.
DARPA is an agency under the Department of Defence responsible for the development of emerging technologies with military applications.
DARPA’s requirements were stringent – the system had to be simple, cost-effective, rugged, operate autonomously and with minimal maintenance, and had to have machine-learning (artificial intelligence) capability. It also had to have the ability to store data from previous floods and use that information to accurately predict future occurrences.
The system that was finally developed jointly by DARPA and Intellisense Systems Inc., was first deployed in 2018 in Mecklenburg County, Charlotte, North Carolina, after the region was hit by Hurricane Florence, in September that year.
The deployment of the Advance Warning Equipment (AWARE) Flood System was coordinated by the US Department of Homeland Security (DHS) Science and Technology Directorate.
It comprises a network of sensor nodes that independently monitor waterway, and other environmental conditions to help determine the risk of flooding. Warnings can be sent in near real time.
Following a two-year trial period, DHS concluded that the system had been effective in improving its flood risk analytics.
Critically, it gives the authorities the ability to predict future floods, by accurately modelling projected rainfall, water level elevation, flow patterns based on each area’s topography and factoring in local geographical features and man-made structures.
In the austere fiscal environment of the 21st century, the government needs to adopt smart solutions that act as a force multiplier to enhance their disaster relief management efforts.
Agencies can no longer function in isolation, and the flow of information cannot be dictated, or impeded by personalities, politics, or personal agenda.
While the construction of more SMART tunnels, and the purchase of boats, dinghies and RHIBs may alleviate the problem to a certain extent, a new approach – including a radical shift in thinking – clearly needs to be adopted. And quickly.
With the Northeast Monsoon threatening to stretch until March, another RM6.1 billion flood disaster is something we can ill afford.
