ASSESSING THE ROLE OF EARLY WARNING SYSTEMS IN ENHANCING FLOOD PREPAREDNESS AMONG STUDENTS OF A COMMUNITY COLLEGE

Aims: This study aims to assess the role of Early Warning Systems (EWS) in enhancing flood preparedness among students at Opol Community College in Misamis Oriental, Philippines. Study design: The study utilizes a quantitative research design, with a structured questionnaire administered to a random sample of students from various academic programs and year levels. Methodology: Data were collected using both online and in-person surveys, measuring students' perceptions of the accessibility, timeliness, and reliability of flood warnings, as well as their flood preparedness behaviors. The data were analyzed using descriptive statistics to summarize the responses and regression analysis to explore the relationships between EWS components and preparedness outcomes. Results: The study found that students generally agreed with the accessibility and effectiveness of early warning systems, particularly in terms of timeliness and community engagement. However, accessibility received a slightly lower rating, indicating barriers to full reach. Students showed strong knowledge of flood risks and preparedness, with notable participation in disaster preparedness activities. Regression analysis revealed that community engagement and awareness had the strongest positive impact on flood preparedness, with other factors like reliability of information and communication channels also influencing preparedness. Conclusion: The study concludes that while the EWS at Opol Community College are largely effective, improvements in accessibility, accuracy, and timeliness of flood warnings are necessary. The findings highlight the importance of enhancing community engagement, expanding educational programs, and ensuring that the information provided is reliable and timely. These improvements will help to further increase flood preparedness and foster a more resilient community. Regular monitoring and evaluations are essential for optimizing the effectiveness of early warning systems.