Satellite-Derived Landscape Characteristics Distinguish Streamflow Drought Occurrence
The consequences of drought for rivers depend not only on the atmospheric water deficit but also on how catchments store and release water. It remains unclear how well catchment characteristics distinguish streamflow drought occurrence under similar meteorological conditions. We combined AlphaEarth satellite descriptors with principal component analysis to examine this question in 361 relatively undisturbed catchments across the conterminous United States. Using the three-month Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI), we linked meteorological droughts to subsequent streamflow droughts and assessed whether catchment landscapes helped explain differences in their occurrence, intensity and duration under comparable meteorological and initial streamflow conditions. Occurrence was most clearly associated with PC1, the dominant component of the AlphaEarth descriptors, whose landscape differences were partly reflected in drainage density and forest cover. At comparable meteorological drought durations and the same meteorological intensity and initial streamflow conditions, catchments in the upper PC1 quartile had estimated occurrence probabilities 8.1–20.9 percentage points below those in the lower quartile. The separation was greater for moderate-or-stronger drought, at 13.8–22.3 points. Higher PC1 also tended to accompany lower drought intensity, but the evidence for intensity and duration differences was less conclusive than for occurrence. These findings support the use of a common satellite-derived landscape description to identify catchments more susceptible to streamflow drought under comparable meteorological conditions, while showing that occurrence probability alone cannot indicate how severe or persistent the resulting drought will be.
Authors
- Dongdong Kong (ORCID: https://orcid.org/0000-0003-1836-8172)
- Mingzhong Xiao (ORCID: https://orcid.org/0000-0002-9462-2577)
Institutions
- Sun Yat-sen University (CN)
- China University of Geosciences (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-11-02
- DOI
- https://doi.org/10.3390/rs18213772
- Primary Topic
- Hydrology and Drought Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00