Valeriya Rakhmatova, Temur Khujanazarov, Kenji Tanaka, Yoshiya Touge, Bakhriddin E. Nishonov, Dmitry Belikov
Received 8 May, 2025
Accepted 23 September, 2025
Published online 16 January, 2026

Valeriya Rakhmatova¹⁾, Temur Khujanazarov²⁾, Kenji Tanaka²⁾, Yoshiya Touge²⁾, Bakhriddin E. Nishonov³⁾, Dmitry Belikov⁴⁾

1) Graduate School of Engineering, Kyoto University, Japan
2) Disaster Prevention Research Institute, Kyoto University, Japan
3) Hydrometeorological Research Institute, Uzbekistan
4) Center for Environmental Remote Sensing, Chiba University, Japan

Drought events in arid regions can be categorized as traditional, characterized by slow development and long duration, and flash, marked by rapid intensification over short timescales. This study assesses the spatial and temporal characteristics of both drought types in Uzbekistan’s Kashkadarya region from 1990 to 2019 using root-zone soil moisture (SM) data from the SiBUC land surface model, compared to ERA5-Land and CCISM datasets. SM anomalies were identified using percentile thresholds, alongside temperature and precipitation anomalies. Flash droughts typically developed in spring under combined short-term precipitation deficits and elevated temperatures, rapidly depleting SM during critical vegetation growth. Traditional droughts evolve more gradually, due to sustained precipitation deficits, with longer duration and greater spatial extent. Traditional droughts showed more severe SM anomalies often below –0.6, while flash droughts were more localized, with anomalies between –0.5 and –0.1. Model comparisons against CCISM indicate that ERA5-Land strongly overestimates wet-season SM, whereas SiBUC shows a weaker positive bias. Nevertheless, all datasets confirm intensifying drought frequency and severity in recent decades, particularly in dryland and pasture zones. These findings support importance of high-resolution SM data for improving drought monitoring, early warning systems, and targeted adaptation strategies in complex land use and water-stressed arid agricultural regions.

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