Preprints
https://doi.org/10.5194/egusphere-2026-1199
https://doi.org/10.5194/egusphere-2026-1199
23 Mar 2026
 | 23 Mar 2026
Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Global vegetation responses to wet and dry soil moisture extremes

Xueyan Cheng, Chunhui Zhan, Martin G. De Kauwe, Anke Hildebrandt, and Rene Orth

Abstract. Hydrological extremes are continuing to intensify under climate change. However, the responses of vegetation to dry and wet soil moisture extremes, and the dominant drivers of these responses, have not yet been analyzed consistently. In this study, we utilize long-term observations of Normalized Difference Vegetation Index (NDVI) as a proxy of vegetation responses to soil moisture extremes. We then analyze related drivers with a machine-learning attribution approach to assess the role of pre-extreme vegetation conditions, characteristics of extremes, and of the environmental background. Vegetation generally loses greenness during dry extremes, indicated by widespread and consistent negative NDVI anomalies. This is mainly modulated by pre-extreme vegetation conditions and the characteristics of the extreme (especially seasonal timing) which reflect varying vegetation vulnerability. In contrast, wet extremes lead to more heterogeneous responses, including both positive and negative NDVI anomalies. This is modulated by multiple aspects including pre-extreme vegetation conditions, the characteristics of the extreme (especially seasonal timing) as well as environmental background variables such as climate (e.g., long-term mean air temperature, aridity) and topographic variability. This illustrates that vegetation response to wet extremes is complex and potentially influenced by different processes. Further, regions with negative NDVI anomalies during extremes that are strongly modulated by environmental background indicate localized vulnerability arising from adverse climatic, soil or topographic conditions, such that vegetation stress can occur even under extremes with less severity. These results highlight the roles of seasonal timing and of environmental background conditions for impacts of soil moisture extremes on vegetation. This clarifies the predictability of ecosystem responses to hydrological extremes, and serves as a basis for related management planning.

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Xueyan Cheng, Chunhui Zhan, Martin G. De Kauwe, Anke Hildebrandt, and Rene Orth

Status: open (until 04 May 2026)

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Xueyan Cheng, Chunhui Zhan, Martin G. De Kauwe, Anke Hildebrandt, and Rene Orth

Data sets

Data associated with Global vegetation responses to wet and dry soil moisture extremes Xueyan Cheng et al. https://zenodo.org/records/18234862

Xueyan Cheng, Chunhui Zhan, Martin G. De Kauwe, Anke Hildebrandt, and Rene Orth
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Latest update: 23 Mar 2026
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Short summary
Using long-term satellite greenness data and a machine-learning attribution approach, we assessed vegetation responses to wet and dry soil moisture extremes and identified their dominant drivers. Dry extremes caused widespread negative greenness anomalies mainly controlled by pre-extreme conditions and seasonal timing, while wet extremes showed more heterogeneous responses additionally shaped by climate and topography, highlighting contrasting ecosystem sensitivity to hydrological extremes.
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