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Highlights • Reduction of wind speed was the major driving force for decreasing trends in ET 0. • Actual and potential evapotranspiration exhibited an asymmetric complementary relationship. • Vegetation greening was mediated by elevation. • Non-uniform climate warming imposed opposite impacts on vegetation growth. Abstract This study comprehensively analyzed long-term (1960–2014) variations of potential and actual evapotranspiration (ET) and quantified their inter-annual and seasonal sensitivity and attribution to climate and vegetation growth changes in the upper reaches of the Yellow River Basin (UYRB). Satellite-derived vegetation greenness and in situ measured hydrometeorological datasets were used. Average annual reference evapotranspiration (ET 0) showed significant decreasing trend (p < 0.05) by 0.32 mm year−1 over the past 55 years. Results obtained from recovered stationary series and sensitivity analyses showed that reduction of wind speed was the major driving force for decreasing trends in annual and seasonal ET 0. Water budget-derived actual evapotranspiration (ET a) increased dramatically during the study period, whereas potential evapotranspiration (ET p) calculated from Penman equation and pan evaporation (ET pan) decreased significantly, suggesting the existence of evaporation paradox over the UYRB. ET a and ET p or ET pan exhibited complementary behavior, while the complementary relationship was asymmetric. During the period 1982–2014, vegetation greening occurred in most areas (65.6%) of the UYRB and was mediated by elevation. Interestingly, non-uniform climate warming imposed opposite impacts on vegetation growth, namely inter-annual and seasonal NDVI was stimulated by daytime temperature but suppressed by nighttime temperature. Furthermore, the positive impacts imposed by daytime temperature on NDVI was much larger in spring than in autumn and summer. Large-scale coherent vegetation greening would be the primary factor affecting inter-annual ET a in comparison with climate factors. These results help in deep understanding the hydrological response to climate change in cold mountain regions. [ABSTRACT FROM AUTHOR]

Accurate estimates of canopy conductance ( g c ) are essential for quantifying the carbon, water and energy fluxes of ecosystem and understanding the patterns of water utilization of vegetation in arid regions. To this end, g c of Haloxylon ammodendron community, dominated by three desert shrub species, was calculated using the inversed Penman-Monteith equation from measurements of sap flow and concurrent microclimate over two main growing seasons (2014–2015). Then, it was used to examine the Jarvis-Stewart (JS) models which comprised different response functions and the simplified process-based model (BTA) to select the best one for our study species and climate. Photosynthetically active radiation and vapor pressure deficit typically covary throughout the day and are known have opposite effects on g c . When this effects was taken into account, both the JS model and the BTA model produced better g c fittings. Selection of proper vapor pressure deficit function and air temperature function significantly improved the performance of the JS model. The best JS model given a correlation coefficient of 0.89, RMSE of 1.99 mm s −1 and average percent error of 19% in comparison with the PM-calculated g c , while the best BTA model outperformed this model, reflected by higher correlation coefficient (0.90), and lower RMSE (1.93 mm s −1 ) and average percent error (9%). The average decoupling coefficient was 0.28, indicating canopies of H. ammodendron community were well coupled from the atmosphere. These findings addressed the importance of selection of stress function and consideration of air temperature for improving g c estimation in arid region, and gain new knowledge on the environmental control on canopy conductance. [ABSTRACT FROM AUTHOR]

• 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]

• Permafrost extent and ALT changes on the TP were evaluated. • The SOC stocks and storage in TP permafrost areas were estimated. • Thawed and perennially frozen state of SOC in permafrost areas is distinguished. • Dynamics of thawed SOC in TP permafrost areas from 1901−2020 were assessed. Large amounts of frozen carbon stored in the permafrost of the Tibetan Plateau (TP) are gradually thawing due to climate warming. The thaw of frozen carbon allows more active soil organic carbon (SOC) on the TP to participate in the global carbon cycle, which has usually been neglected in previous studies of permafrost carbon. This paper assesses the thawed SOC stock and its historical dynamics in TP permafrost areas based on a data-driven scheme. The results show that the current permafrost area of the TP is 1.14 × 106 km2, and the SOC stock in the top 10 m of permafrost areas is 47.36 Pg. The active layer of the TP permafrost has a regional average thickness of 2.37 m during the baseline period (2000−2020), storing 18.19 Pg of SOC, accounting for about 38.4 % of the total SOC stock in the top 10 m, with the remaining more than 60 % perennially frozen in permafrost. The dynamics of thawed SOC are calculated based on baseline period SOC pools. Despite significant fluctuations, there is a general trend of 0.074 Pg SOC thaw per decade over 1901−2020 as the active layer has deepened. Significantly, the thaw trend of frozen SOC after 1976 is more prominent, reaching 0.420 Pg decade−1. Moreover, this paper reconstructs the SOC pool at the beginning of the last century by incorporating historical deep carbon emissions (1 − 10 m) in the current SOC pool. It recalculates the thaw trend of frozen carbon based on this and finds that the general thaw trend of SOC from 1901−2020 is more significant, with a rate of 0.092 Pg decade−1. Additionally, the dynamics of SOC pools in surface soils (0 − 1 m) of TP permafrost areas are also discussed. Our study highlights the importance of permafrost carbon thaw and provides valuable information for TP carbon studies. [ABSTRACT FROM AUTHOR]

Rice growth is significantly influenced by the ongoing climatic change and subjected to water shortages. Projection on the changes of rice productivity growth and water resources utilization under future climates is of great importance for food security and water resources sustainable management. Climate model outputs in combination with physical-based crop model is an effective way to modeling the crop productivity and water consumption response, but uncertainties associated with climate models remain a major challenge. In this study, we introduce a Bayesian model averaging (BMA) method to provide the multi-model ensemble projections by merging 4 climate models under four emissions scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) from phase five of the Coupled Model Intercomparsion Project (CMIP5). The comprehensive investigation on how the rice yield, water consumption (ET), irrigation water requirement (IR), water use efficiency (WUE) and irrigation water use efficiency (IWUE) response to future climate scenarios with taking account of CO 2 concentration enrichment in three typical sites (Kunshan and Nanjing in the Yangtze River Basin, and Kaifeng in the Yellow River Basin) in rice plantation region of China was conducted by driving a well-validated rice crop model ORYAZ2000 with merging multi-model ensemble projected climate outputs. There are some obvious uncertainties for climate models projections in climatic variables with wide model spread, especially for solar radiation and wind speed. The BMA method is most competent to produce the ensemble with the lowest bias in comparison with simple model averaging (SA) method and individual climate model. In despite of the distinct response of the growth duration to future climate change for the three stations, the rice yield would be reduced significantly under the climate warming. IR would present more remarkable increase compared with the ET, especially for Nanjing and Kunshan stations, due to the decrease in precipitation during the rice growth period. The significant reduction in rice production together with enlargement in ET and IR, resulted in the generally depressed the WUE and IWUE. In addition, despite that the CO 2 fertilization effect cannot compensate the negative effect of temperature increase, the increase of CO 2 concentration can promote the overall level of yield and consequently improve the water use efficiencies of rice. [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]