Assessment of the 2023-2024 El Nino-Driven Drought Impacts in the Philippines Using a Satellite-Based Combined Drought Index (CDI)
Michael Angelo Valete (a*), Christine Marie Oca (a), Dhann Collin Davies Vergara (a), James Cesar Refran (a), Gay Jane Perez (a,b)

a.) Philippine Space Agency, Quezon City, Philippines
b.) Institute of Environmental Science & Meteorology, University of the Philippines, Diliman, Quezon City, Philippines

michael.valete[at]philsa.gov.ph

Abstract

El Nino episodes in the Philippines trigger severe droughts, characterized by elevated land surface temperature, reduced water availability, and crop losses. This study evaluates the agricultural impacts of the 2023-2024 El Nino event using a satellite-derived Combined Drought Index (CDI). CDI integrates the following short-term meteorological and vegetation stress indicators: (1) Standardized Precipitation Index (SPI-3), (2) Temperature Condition Index (TCI), and (3) Vegetation Condition Index (VCI). CDI follows a rule-based progression framework, from no drought to full recovery, to characterize drought onset, persistence, temporary vegetation recovery, and return to normal conditions. The study validated the CDI against reported provincial crop production losses during the El Nino period and observed that provinces with higher CDI values generally correspond with drought-related production losses. The results show an overall accuracy of 63%, precision of 71%, hit rate of 70%, and an F-score of 70%. Even though the false alarm rate is at 53%, CDI effectively captured the broad timing and progression of drought conditions during the El Nino event. It reflected the steady increase of drought-affected areas, starting at 27% in January 2024 to 64% by May 2024, coinciding with rainfall deficits, heat stress, and vegetation decline. This study highlights the potential of a satellite-based CDI, grounded in drought evolution logic, as a practical tool for near-real-time monitoring, early warning, and agricultural drought preparedness in the Philippines.

Keywords: Agricultural Drought, Crop Production Loss, ENSO

Topic: Topic B: Applications of Remote Sensing