The intensifying effects of climate change highlight the significance of understanding water–carbon fluxes in agroecosystems. Water use efficiency (WUE) is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET), and it is a critical metric that reflects the balance between carbon sequestration and water loss. However, the responses of water–carbon fluxes to varying hydrological conditions and extreme environmental factors remain inadequately understood and warrant further investigation. We examined the responses of water–carbon fluxes to hydrological conditions over six wheat growing seasons in the Guanzhong Plain using continuous eddy covariance observations and structural equation modeling. Strong correlations were found among water–carbon fluxes and WUE under mild drought, whereas extremely wet and drought conditions reduced the contribution of increased GPP to WUE. Color mapping of flux data and environmental indicators revealed ET–GPP and GPP–WUE coupling is optimal for intermediate environmental indicator values (approximately 25–75% of their ranges). Structural equation modeling analysis indicated photosynthetically active radiation (PAR) and leaf area index (LAI) were the key factors controlling water–carbon fluxes, while LAI and vapor pressure deficit (VPD) were the major WUE drivers. Atmospheric and soil drought significantly weakened the direct effects of VPD and soil water content on water–carbon fluxes, respectively. Furthermore, extreme drought and wet conditions reduced PAR and WUE responses to LAI. Thus, extreme environmental conditions significantly reduced the effects of key drivers of water–carbon fluxes. This study provides new insights into the use of ecological and biological indicators for the precise monitoring and interpretation of water–carbon fluxes. These findings may provide a theoretical basis for optimizing water–carbon management and monitoring in agroecosystems under climate variability and extreme environmental events.
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Xuanang Liu
Yao Li
Xiaoyan Xu
Ecological Indicators
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Liu et al. (Sat,) studied this question.
www.synapsesocial.com/papers/69fd7d4abfa21ec5bbf05e2d — DOI: https://doi.org/10.1016/j.ecolind.2026.114918
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