Physio-Chemical Parameters as Predictors to HABs Occurrence and Severity BORDIOS_5
Author(s):
Abstract
This study analyzed 108 months of hydro-climatic data from Irong-Irong Bay and Maqueda Bay (2016–2024) to determine key environmental predictors of harmful algal blooms (HABs). Using correlation analysis, SARIMAX modeling, and time-series forecasting, the research identified rainfall, humidity, temperature, and atmospheric pressure as significant drivers of bloom occurrence and severity. Results revealed a dominant 12-month seasonal cycle and projected increased HAB risks for 2025–2026. The study highlights the value of data-driven early warning systems and climate-informed coastal management. Findings support …
Register to Read Full Abstract
Create a free account to access the complete abstract and detailed research information.
Keywords
Unlock Full Research Details
Register for a free account to access:
- Complete abstract & research details
- AI-powered analysis & insights
- LGU implementation guides
- Policy recommendation tools
- Citation generator
Cite This Research
Bordios, Balindo (2025). Physio-Chemical Parameters as Predictors to HABs Occurrence and Severity BORDIOS_5. College of Education, Samar State University. Retrieved from https://gov-aideas.ssu.edu.ph/research/physio-chemical-parameters-as-predictors-to-habs-occurrence-and-severity-bordios_5
Quick Actions
Research Information
- Research Type
- Applied Research
- Sector
- Environment & Disaster Resilience
- College
- College of Education
- Published
- February 24, 2026
- Last Updated
- February 24, 2026
- Access Level
- Public
- File Size
- 24.6 MB