Central Mindanao University (CMU) is a premier university in Northern Mindanao with a mission to provide quality education. In response to Sustainable Development Goal #4 on Quality Education and the government's program on Geographically Isolated and Disadvantaged Areas (GIDAs), this… More

Central Mindanao University (CMU) is a premier university in Northern Mindanao with a mission to provide quality education. In response to Sustainable Development Goal #4 on Quality Education and the government's program on Geographically Isolated and Disadvantaged Areas (GIDAs), this study aims to assess the extent of CMU in providing academic services, particularly in GIDAs in Northern Mindanao, Philippines. This study employed an online survey among CMU students and alumni supplemented with secondary data. The study applied the Geographic Information System (GIS) to generate maps and spatially analyze the data. A total of 721 students and 641 alumni responded through the online survey, with 3,594 alumni sourced out from CMU graduation programs. The study's findings revealed that the distribution of students and alumni in CMU is mostly in Bukidnon, particularly in the central and southern parts. Most of the students and alumni in Northern Mindanao are spread in non-GIDAs, although a considerable percentage is in GIDAs. For CMU to respond to GIDAs and SDG Goal #4, the University should craft scholarship programs to attract students and extend its academic services in GIDAs to provide quality education in Northern Mindanao significantly. Less

Flooding is one of the most devastating natural disasters in the Philippines, especially in Mindanao. This study aimed to generate datasets of flooding along the Gingoog River based on Geographic Information System (GIS). The method employed simulation and mapping of… More

Flooding is one of the most devastating natural disasters in the Philippines, especially in Mindanao. This study aimed to generate datasets of flooding along the Gingoog River based on Geographic Information System (GIS). The method employed simulation and mapping of flood hazards using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) and the HEC-River Analysis System (HEC-RAS) within the GIS environment. Rainfall data on December 15, 2015, with a total amount of 20.8 mm and peak discharge of 43.49 m3s-1, were used to simulate flood hazards. The model was calibrated, and its accuracy was tested, and after which, its overall evaluation showed a satisfactory performance, implying applicability to simulate floods during extreme rainfall events. Using Light Detection and Ranging (LiDAR) data, flood maps of the three return periods were generated within HEC-RAS. Results showed that flooding extended up to 2.965 km2, 4.165 km2, and 5.040 km2 with maximum flood depths of 7.77 m, 8.12 m, and 8.49 m for 5-year, 25-year, and 100-year return periods, respectively. The model, together with the hydrologic behavior of the watershed such as the extent of flooding, is very helpful for the development and enhancement of early warning systems in the affected areas. Less