Story by Rhoda Avila, Humanitarian Advocacy Manager, Oxfam Philippines.
For many residents in the Philippine city of Cotabato, flooding is a recurring problem. The city is a virtual drain of the major river of its province, Maguindanao. The rainy season always brings with it floods, which displaces communities and further strains their already meagre resources.
Sahara Nongka, who lives in Tamontaka 4 village, says the flooding in 2020 was more severe compared to the previous year. Thanks to an innovative EU-supported project on disaster preparedness, Sahara was ready for the disaster.
She used the project’s cash assistance for transportation expenses so that her family could move to her in-laws, where it was safer. Unlike previous occasions when she felt that she was burdening her relatives, Sahara used the money to buy rice and food, and diapers for her infant.
The EU project, implemented by its humanitarian aid partner Oxfam, combines risk-forecasting models and financial technologies to save lives, increase preparedness, and mitigate disaster risks by facilitating cash transfers pre-disaster.
The support resulted even more critical in a year where the rains were unusually heavy due to the weather pattern La Niña, and, worse, came on top of the coronavirus pandemic. The compounded crises affected communities' health, mobility, and livelihoods.
Ready for the floods
In early October 2020, the Philippines' forecasting agency predicted heavy rains over the area of Maguindanao. Together with local authorities, the EU partners began closely monitoring the city's most flood-prone areas. Soon after, the pre-emptive cash payout to vulnerable households in the flood-prone areas was triggered.
By 20 October, the payouts were made. The floods, which were 6 feet high, came 4 days later. By then, the pre-emptive cash support had already been extended to 852 families in 5 flood-prone villages of Cotabato City.
Babo Kagi-Guiara Guilingan, another recipient of the cash support, prepared for the floods and the resulting constraints which would prevent her from going out to make a living. She bought rice for her family, which they could cook as porridge, to make sure they would not go hungry during the flooding.
This was very different from last year’s flood when Babo Kagui-Giuara had to borrow 3,000 pesos (some €50) at a high 15% interest rate, which took 8 months to repay. With the pre-disaster cash assistance, not only was Babo able to secure food for the family, but she also saved at least 300 pesos in interest if she had to take out a loan at high-interest rates.
Another villager, Samir Diocolano, received support and used the cash to buy food. It was not possible for him to fish, his main source of income, during the floods.
The cash support also ensured that his 2 elderly parents and 8 siblings had food during the floods. He also bought medication that his father needed. Equally important, having cash enabled him to secure his fishing boat and gear, which would have otherwise been damaged by the floods.
The decisions and actions taken by Sahara, Babo Kagi-Guiara, and Samir are examples of disaster preparedness measures that individuals can take if they are supported early on.
This is in essence the approach taken by the EU-supported project, which aims to:
- improve disaster preparedness,
- return the dignity of decision-making back to affected people,
- and reduce the vulnerability of highly at-risk communities.
Often, communities' lack of disaster preparedness stems from meagre financial resources and an inability to predict the onset of major disruptive events. This project aims to change that by using forecasting information and providing cash assistance to vulnerable households even before a disaster strikes, which increases community access to resources to better protect their lives and livelihoods.
“The forecast of the flooding in Cotabato City in October, and the pre-emptive pay-outs that were made, show the potentials of this model,” says Arlynn Aquino, who oversees EU humanitarian programmes in the Philippines. “It is the first payout done within this project and lessons from these experiences will be utilised to enhance the model, particularly the triggers and the timings.”