Modeling and indexing the drought severity by augmenting SPI metric system to incorporate multi-modal ground temperature data

TL;DR

This paper enhances drought assessment by augmenting the SPI metric with ground temperature data, providing a dual evaluation of drought severity that considers both intensity and duration, specifically applied to Sri Lanka's paddy regions.

Contribution

It introduces a novel drought severity metric combining precipitation and ground temperature data, improving the accuracy of drought assessment over traditional SPI.

Findings

Enhanced drought severity evaluation with dual assessment

Better alignment with historical drought records

Improved detection of drought conditions in paddy regions

Abstract

Drought is a global threat caused by the persistent challenges of climate change. It is important to identify drought conditions based on the 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. 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 the 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 index.