What Could Delay the Activation of an Early Warning System?
By Saqar ' M Al Zaabi, on 15 June 2020
This blog has been jointly written by Saqar Alzaabi and Salma Alzadjali, PhD students at the IRDR, UCL.
The recipe for effectively responding to extreme weather emergencies is based on the triangle of forecasting, warning and evacuation. Kelman and Ahmed, in their recent article in the Conversation, have illustrated how these three were utilized to save millions of lives in Bangladesh’s response to cyclone Amphan. Despite the apparent rationality of such a thoughtful process, making decisions on reality does not necessarily follow along as activating emergency plans and warning the public of a possible threat might be constrained by a number of factors. While it is difficult to pinpoint a specific cause behind a delayed warning, this blog argues the implication of relying on the intensity of the hazard when establishing situational awareness of a possible emergency, and the embedded problem of excluding the vulnerability of the place in the warning system.
While being busy responding to the COVID-19 pandemic, Oman had also been affected by a tropical depression between May 29 and June 1, 2020, that formed over its southern coast. According to the Indian Met Department (IMD), the sustained surface wind speed did not exceed 25knots. Similar to many countries, Oman relies on the Saffir-Simpson hurricane classification scale that is purely based on wind intensity. The higher the wind speed, the higher the tropical system is classified. And, the higher the classification, the higher degree of response is triggered.
Despite the fact that it was forecasted in advance, the first bulletin was issued on May 27 by the national early warning centre, when, in fact, heavy rainfall had already taken place. The delay in initiating the warning process, i.e., communicating the risk to the public, had not only led to the underestimation of its impacts but also delayed the activation of the response and mobilization of resources. The depression was not forecasted to intensify, based on its wind of course, into a tropical storm or a cyclone. Therefore, it was not anticipated to cause significant impacts, again based on the intensity of the wind, neither the strength of the rainfall nor the vulnerability of the place as these are not integrated into the warning system.
However, the stationary movement of the depression caused hefty downpours in different areas of the southern region. The highest accumulated rainfall according to the Ministry of Regional Municipalities and Water Resources was 1055 mm between May 27 and June 1, and the maximum daily rainfall was 552 mm on May 30, according to government sources. Recent cyclones that struck the same region such as Mekunu and Luban in 2018 brought a maximum daily rainfall of about 492 mm and 176.6 mm, respectively. Despite that, they triggered a national early warning response that was widely broadcasted in advance through several multimedia channels and in eight different languages.
The depression had caused wide-scale flooding. Four people died due to flash flooding and a building collapse. Several others were injured. Many houses and businesses were flooded. Main roads became inaccessible. Disruption of power and water lasted for several hours to a couple of days in some areas. Despite being a depression, significant damages as a consequence had occurred. The place, due to its physical built environment conditions, is already vulnerable to heavy rainfall. Poorly-constructed infrastructure and inefficient drainage systems are already existing and providing the right conditions for an emergency to take place. Classifying the emergency based on the intensity of the hazard instead of the vulnerability of the area did not only delay warnings but also result in a large demand for urgent emergency services.
While it remains essential to understand the intensities of weather phenomena, the vulnerability of the place is the crucial element in understanding the possibility of an emergency taking place. Therefore, an early warning system should integrate the vulnerability of the place rather than solely relying on the hazard’s intensity, especially if it is only based on one element. The intensity of the wind is one piece of information, and it could, in many cases, provides a less accurate and partial projection of a possible scenario. A GIS-based decision support system that integrates the vulnerability of the place, the possible hazards and exposure is one practical solution that could assist in establishing a better awareness and more accurate assessment of possible emergencies.