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

**Authors:** Sachini Karunarathne, Kushani De Silva, Sanjeewa Perera  
**arXiv:** [2309.11505](https://arxiv.org/abs/2309.11505)  
**Date:** 2023-09-07  
**Summary page:** https://www.summarizepaper.com/en/paper/2309.11505v1/

## Key points

- Drought is a global threat exacerbated by climate change
- Accurate identification and evaluation of drought conditions is crucial
- Researchers enhanced the Standardized Precipitation Index (SPI) by integrating ground temperature data
- The newly developed metric offers a dual assessment of drought severity, considering intensity and duration
- Ground temperature data improves accuracy in representing drought conditions, especially in regions with multiple weather seasons
- The metric was applied to assess drought severity in Sri Lanka's primary paddy cultivation region
- Insights from this study can inform agricultural planning and management in areas affected by drought
- The new metric was calibrated against historical records to assess its accuracy and reliability compared to the conventional SPI index
- A more appropriate probability distribution for rainfall data was used to obtain a precise representation of rainfall patterns
- Temperature data further enhanced the accuracy of the metric for measuring drought severity
- This study presents an innovative approach for modeling and indexing drought severity using ground temperature data
- Consideration of both precipitation and temperature variables is important when assessing drought conditions
- Valuable insights for effective water resource management and agricultural planning strategies are provided.

## Summary

Drought is a global threat that is exacerbated by the challenges of climate change. In order to effectively address this issue, it is crucial to accurately identify and evaluate drought conditions based on weather variables and their patterns. In this study, the researchers aimed to enhance the Standardized Precipitation Index (SPI) by integrating ground temperature data, in order to develop a more comprehensive metric for evaluating drought severity. The newly developed metric offers a dual assessment of drought severity, taking into account both the intensity of the drought and its duration. By incorporating ground temperature data, which is particularly relevant in regions characterized by multiple weather seasons, the researchers were able to construct a more accurate representation of drought conditions. To validate the effectiveness of their metric, the researchers applied it to assess drought severity in the primary paddy cultivation region of Sri Lanka. This region experiences insufficient water supply and prolonged periods of elevated temperatures, which significantly impact paddy crops. By shedding light on prevailing drought conditions affecting these crops, this study provides valuable insights for agricultural planning and management. In addition to evaluating current drought conditions, the researchers also calibrated their metric by aligning it with historical drought records. This comparison allowed them to assess the accuracy and reliability of their new metric when compared to outcomes derived from the conventional SPI index. The methodology employed in this study involved fitting a more appropriate probability distribution for rainfall data in order to obtain a more precise representation of rainfall patterns. The incorporation of temperature data further enhanced the accuracy of the metric for measuring drought severity. Overall, this study presents an innovative approach for modeling and indexing drought severity by augmenting existing metrics with ground temperature data. The findings highlight the importance of considering both precipitation and temperature variables when assessing drought conditions. By providing a more comprehensive understanding of drought severity in paddy cultivation regions like Sri Lanka, this research contributes valuable insights for effective water resource management and agricultural planning strategies.