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• Soil moisture estimation is influenced by multi-factor uncertainties • Soil property has little effect on calculating θ sat , K sat , B , ψ sat • UWEnKF is an effective and practical technique for soil moisture assimilation • Model performance can be improved with a decreasing simulation time step • UWEnKF provides a better soil moisture estimation with higher assimilation frequency Accurate quantification of soil moisture contributes significantly to an understanding of land surface processes. In-situ observable soil moisture data are often sparsely distributed, and model performance is influenced by many factors. In this study, 14 numerical experimental schemes about the effects of uncertainties in multiple factors (soil property, time step, assimilation interval, precipitation, soil layer thickness and initial value) on soil moisture estimation were evaluated based on the unscented weighted ensemble Kalman filter (UWEnKF) and a one-dimensional vertical water flow model at the ELBARA field site in the Maqu monitoring network in the upper reaches of the Yellow River, China. The experiments showed that soil properties had little effect on model parameters (e.g., saturated soil moisture content, saturated soil hydraulic conductivity, saturated soil matric potential) in either the horizontal or vertical direction using the model numerical solving scheme adopted, and thus had little effect on soil moisture estimation. Using only the observed K sat may lead to better soil moisture predictions. Reducing the simulation time step has limited impact on soil moisture estimation. The effects of precipitation on soil moisture estimations varied due to overestimation or underestimation of soil moisture content in different soil layers, and differences in soil layer thicknesses led to uncertainty in soil moisture estimation. The model accurately predicted the change trend of soil moisture if the initial values were reasonable. UWEnKF performed well in terms of improving soil moisture estimations despite the uncertainty of many factors in data assimilation system, and performed better with high assimilation frequency (i.e., small assimilation interval). Thus, UWEnKF is an effective and practical technique for soil moisture assimilation whatever the uncertainty of multiple factors is. [ABSTRACT FROM AUTHOR]

• Magnitude of the sub-diurnal AET - VPD hysteresis varies with biomes and climates. • Variation of the hysteresis is mostly attributable to evaporative demand limitation. • Soil moisture supply limitation amplifies the hysteresis during the dry season. • We provide some novel features to diagnose limiting mechanisms of the hysteresis. Hysteresis between sub-diurnal actual evaporation (AET) (or one of its components, transpiration) and vapor pressure deficit (VPD) at the species or individual ecosystem level has been extensively studied, but the global variation and seasonal variability of this hysteresis across biomes and climates is yet to be fully explored and the limiting mechanisms remain unclear. We hypothesize that the sub-diurnal AET - VPD hysteresis results from the interplay between evaporative demand and soil moisture supply limitations. To test our hypothesis, we quantify the sub-diurnal AET - VPD hysteresis across a broad range of biomes and climates based on the observations from the 89 FLUXNET sites (703 site-years) across the globe. We find that the magnitude of hysteresis varies with biomes and climates and is mostly attributable to evaporative demand limitation in all ten sampled biomes. In seasonally dry locations, however, low soil moisture availability amplifies the hysteresis during the dry season. Sensitivity analysis using a hydraulic model suggests that most ecosystems exhibiting seasonal drought display a more isohydric behavior during the dry season, while shift toward a more anisohydric response during the wet season. Our findings have important implications for understanding sub-diurnal dynamics between vegetation and its surrounding environment, reducing uncertainties in AET simulation at fine spatial and temporal scales, and improving understanding of the ecosystem response to hydrologic stress. [ABSTRACT FROM AUTHOR]