The Department of Budget and Management (DBM) has released ₱1 billion to the University of the Philippines to expand Project NOAH, the country's flagship hazard-forecasting program, with the money going to artificial intelligence (AI) flood modeling, LiDAR mapping, and real-time hazard assessment tools. GMA News reported the release on August 24, and the DBM framed it as a bet on prevention rather than disaster response.
"This ₱1-billion investment in Project NOAH is an investment in prevention," DBM Acting Secretary Kim Robert de Leon said. "We are putting science, AI, and real-time hazard information to work so government can act earlier, communities can prepare better, and more Filipino lives and livelihoods can be protected."
Where the ₱1 billion goes
The release is part of UP's 2026 appropriation and breaks down into two tranches, per Newsbytes.PH:
- ₱935 million for research services
- ₱65 million for general management and supervision
In practical terms, the budget pays for information and communications technology (ICT) and scientific equipment, LiDAR-generated mapping systems, highly specialized technical personnel, and the operational support systems that keep hazard monitoring running. LiDAR — light detection and ranging — uses laser scanning from aircraft to build detailed elevation maps, the raw material for street-level flood simulations.
What Project NOAH does
Project NOAH, short for Nationwide Operational Assessment of Hazards, is implemented by the UP Resilience Institute (UPRI), whose mandate covers research on disaster risk reduction, climate adaptation, and hazard assessment. Project NOAH is the institute's most visible public-facing program. The program combines AI-enhanced models, LiDAR mapping, and data analytics to produce real-time hazard assessments and predictive flood scenarios — in effect, maps that tell national agencies and local governments which communities are likely to flood, how deep, and how soon, before the water rises. Those outputs feed disaster planning, pre-emptive evacuations, and emergency response. The point is to shift government action earlier in the timeline: instead of mobilizing rescue teams after a flood, agencies get the information to warn, prepare, and move people while the skies are still gathering.
The funding buys more of that predictive capacity: more sensors and equipment gathering data, sharper elevation maps, and the specialists who turn both into usable warnings.
Prevention over reaction
De Leon was explicit about the philosophy behind the release. "Hindi natin kailangang hintayin na tumaas ang tubig bago tayo kumilos," he said in the government's announcement — we do not need to wait for the water to rise before we act. "The goal is to know where the danger is, who is at risk, and what needs to be done before disaster strikes."
He added a fiscal argument: "Every peso we invest in better forecasting and preparedness can help save lives, protect livelihoods, and avoid far greater losses later on."
For a country hit by around twenty tropical cyclones a year, the difference between a forecast that names a province and one that names a barangay is measured in lives and livelihoods. The test of this ₱1 billion will be visible in the next habagat season: whether local governments get flood scenarios early enough, and granular enough, to move people and assets before the water arrives — and whether the warnings actually reach the communities that need them. The money is now with UP; the monsoon will grade the results.
