Monitoring the Evolution of Drought Severity in the Philippines during the 2019 El Niño

Drought events in the Philippines have resulted to significant loss in crop production, water shortages and adverse human health impacts. The anomalously high surface temperature and scarcity of rainfall associated with El Niño, are cited as the primary drivers of drought in the country. This study investigates the performance of different drought indices in characterizing the evolution of drought severity during the 2019 weak El Niño. Satellite data from MODIS, Landsat, TRMM, and GPM were used to derive Vegetation Health Index (VHI), Standardized Precipitation Index (SPI), Temperature Vegetation Dryness Index (TVDI), and Standardized Vegetation and Temperature Ratio (SVTR). The drought indices were evaluated and compared with drought indicators – Normalized Difference Vegetation Index (NDVI), soil moisture, and crop production and damage reports. The results showed consistency in spatiotemporal variation of drought events across different indices. Most of the stress started in the western part of the country, then became widespread in the northern and central regions. The affected land area increased from January to April (25% to 99%), due to lack of precipitation, decrease in soil moisture and increase in temperature within the period. The drought peak was identified during April for SVTR, VHI, and SPI-3 and during February for SPI-1, highlighting the difference between meteorological and agricultural drought processes. However, poor correlation was observed when the drought indices were compared against satellite soil moisture, which may be due to the low number of reliable pixels of the soil moisture product. Validation of drought indices against crop production and damage reports permits further investigation on the reliability of satellite-based indices for drought monitoring. Overall findings demonstrate the relevance of combining the strengths of drought indices and indicators in providing a robust drought metric that incorporates the soil-plant-water cycle relationship in characterizing drought events.