Short answer
A drought category table converts index values into drought classes. In SPI analysis, values between -1.0 and -1.49 are often called moderate drought, -1.5 to -1.99 severe drought, and -2.0 or lower extreme drought. These categories support communication, but they should not be treated as exact impact thresholds for every region or sector.
Purpose of drought category tables
Drought indices produce numbers, but most users need meaningful labels. Category tables help translate a numerical value into a drought condition that can be communicated in reports, maps, dashboards, and decision-support systems.
Categories also improve consistency. When all users apply the same threshold table, drought maps and event summaries become easier to compare across locations and time periods.
Common SPI category table
| SPI range | Common category | General interpretation |
|---|---|---|
| 2.00 or greater | Extremely wet | Very unusual wet conditions |
| 1.50 to 1.99 | Very wet | Strong positive precipitation anomaly |
| 1.00 to 1.49 | Moderately wet | Above-normal precipitation |
| -0.99 to 0.99 | Near normal | No strong standardized anomaly |
| -1.00 to -1.49 | Moderate drought | Noticeable dry anomaly |
| -1.50 to -1.99 | Severe drought | Strong dry anomaly |
| -2.00 or lower | Extreme drought | Very rare dry anomaly |
Limitations of category tables
Category tables simplify interpretation, but drought impacts do not always begin at the same index value. A moderate SPI value can be damaging during a sensitive crop stage, while a severe SPI value may have less impact if water storage is high or irrigation is available.
Categories also depend on time scale. SPI-1 moderate drought and SPI-12 moderate drought describe different processes. A category label without the time scale can be misleading.
Communication best practices
When using category tables, report the index, time scale, dataset, threshold, and period. Avoid using category names without context. Instead of saying “the region is in severe drought,” say “SPI-12 indicates severe precipitation drought for the selected dataset and baseline period.”
For public communication, category colors and labels should be consistent, but technical reports should include the underlying numerical values.
How DMAP-AI uses drought categories
DMAP-AI can classify index values into drought categories and summarize events by severity. This helps users quickly identify when dry periods reach moderate, severe, or extreme thresholds. The platform also preserves event statistics such as duration, minimum index value, and magnitude, which are more informative than the category label alone.
Frequently asked questions
Are drought categories universal?
They are standardized for many indices, but their impacts are not universal. Local vulnerability and sector-specific conditions matter.
Is SPI -1.49 very different from SPI -1.50?
Not physically. Category boundaries are useful communication tools, but the climate system does not change abruptly at the threshold.
Should wet categories also be reported?
Yes, when wet anomalies are relevant. Standardized indices describe both dry and wet departures from normal.
Selected references
- McKee, T. B., Doesken, N. J., and Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology.
- World Meteorological Organization. Standardized Precipitation Index User Guide. WMO-No. 1090.
- Mishra, A. K., and Singh, V. P. (2010). A review of drought concepts. Journal of Hydrology.
- Vicente-Serrano, S. M., Beguería, S., and López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate.
- Wilhite, D. A., and Glantz, M. H. (1985). Understanding the drought phenomenon: The role of definitions. Water International.