Modeling and indexing drought severity with multi-modal ground temperature data

Drought is a global threat caused by the persistent challenges of climate change. It is important to identify drought conditions based on weather variables and their patterns. In this study, we enhanced the Standardized Precipitation Index (SPI) by integrating ground temperature data to develop a more comprehensive metric for evaluating drought severity: the Multivariate Standardized Drought Index. Our metric offers a dual assessment of drought severity, taking into account both the intensity of the drought and its duration. We employ this evaluation in a primary paddy cultivation region of Sri Lanka, with the aim of shedding light on the prevailing drought conditions affecting paddy crops due to insufficient water supply and prolonged periods of elevated temperatures. Additionally, we calibrate our metric by aligning it with historical drought records and subsequently compare the outcomes with those derived from the conventional SPI.