
Drought in Jordan: Analysing Severity and Spatiotemporal Patterns

Abstract
This study utilizes 4°×4° high-resolution, satellite-based monthly precipitation estimates from PDIR-Now (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Near Real Time) for the period March 2000 to May 2023 to investigate drought severity and assess the spatial and temporal patterns of drought in Jordan. Monthly precipitation estimates were aggregated into rainy season (October to April) digital layers for the 2000/2001 to 2022/2023 seasons. To identify drought severity, the Modified Percent Departure from Normal (PDNm) was calculated and displayed spatially. The severity of the detected droughts was primarily in the mild to moderate range, accounting for 40% and 46% of cases, respectively. The Geometric distribution was employed to assess the temporal characteristics of drought as a function of space. The analysis shows that 1-year droughts are dominant in northern Jordan, with probabilities ranging from 0.6 to 0.75, while both 1-year and 2-year droughts are common in the south. In general, drought events lasting more than 2 years are rare. In terms of probability, the likelihood of a drought extending beyond 1 year was higher in the south (0.4 to 0.8). It is suggested that the short duration (1–2 years) of most droughts in Jordan prevents mild and moderate severity levels from escalating to extreme levels, as there is insufficient time for their intensity to increase. The findings of this study provide a scientific basis for updating reservoir design procedures to account for droughts of varying durations across different regions of Jordan, thereby enhancing water resources management and strengthening drought mitigation strategies. Moreover, the methodological framework proposed in this study is broadly applicable and can be used to detect and analyse spatial and temporal drought patterns in other regions.
© 2026 Zeyad S. Tarawneh, published by University of Žilina
This work is licensed under the Creative Commons Attribution 4.0 License.