Detecting drought-prone areas of rice agriculture using a MODIS-derived soil moisture index

This study examined the use of remote sensing in detecting and assessing drought in Iloilo Province, Philippines. A remote sensing-based soil moisture index (SMI), rainfall anomaly data from the Tropical Rainfall Measuring Mission (TRMM), and rice production departure (P-d) data were used for drought detection and validation. The study was conducted using two drought years (2001, 2005) and one non-drought year (2002). According to SMI data, the drought distribution was classified into four major groups. SMI values > 0.3 were considered not to be drought and SMI values <= 0.3 were classified as slight, moderate, and severe drought. Results based on SMI revealed that the study area experienced drought in 2001 and 2005, while 2002 exhibited no drought. On the other hand, TRMM-based rainfall anomaly data revealed negative values in 2001 and 2005 and positive values in 2002. Below-normal Pd values were observed in 2005 and above-normal values in 2002, whereas nearly normal values prevailed in 2001. Yield indicator data were crucial for the assessment of drought impacts on rice production. In most cases, the pattern of rice production and productivity revealed that the decline in the production or productivity of rice for a particular year coincided with lower SMI values and greater rainfall departure or negative anomaly.