Globally, 60% of the evaporation from land returns as precipitation over land and a fifth of annual precipitation over land is directly dependent on the presence of vegetation-supplied moisture. In many regions, particularly in dry seasons, a majority of the precipitation relies on moisture from vegetation and is therefore vulnerable to changes in upwind land use that modify water moisture supply to the atmosphere. The benefits of precipitation for societies are invaluable, ranging from food production to carbon sequestration, and the role of ecosystems for supplying moisture for rainfall can be therefore be considered an important, albeit under-appreciated, ecosystem service. Our research shows that loss of moisture-supplying ecosystems, such as deforestation in the Amazon, can disrupt such moisture supplies, thereby reducing precipitation and negatively impacting crop yield, wetlands, and forest resilience in downwind regions. Conversely, some human activities, such as afforestation and irrigation, bring untapped subsoil water resources into the atmosphere and can help mitigate dry spells both locally and remotely. While they can have the potential to bring moisture-supplying benefits similar to moisture-supplying ecosystems, they also carry the risk of depleting local surface and groundwater resources and bringing about other adverse trade-offs. The past decade has seen rapid developments in moisture tracking models and data, which have brought to light previously ignored long-distance moisture flow relationships among different land areas, land users, and land-use decisions. These scientific advances mean that it is now possible to map out the ecosystem service of vegetation-supplied precipitation at a global scale in great detail, as well as to track their dependencies and interdependencies. We argue that the time is ripe for moisture-supplying ecosystems to be widely considered in land management and governance contexts. Nevertheless, a few important challenges remain. Particularly, future research needs to better constrain the uncertainties of moisture recycling relationships under climate change and atmospheric circulation change; to understand the effects of ecosystem adaptation, regime shifts, and social-ecological feedbacks; as well as to quantify the multiple benefits and trade-offs of the ecosystem service of vegetation-supplied precipitation. A better understanding of the relationships between moisture supply, drought mitigation, ecosystem resilience, and terrestrial carbon is especially relevant under the current UN Decade of Ecosystem Restoration as well as for achieving the Paris Agreement temperature target.

The Loess Plateau in China has experienced a remarkable greening trend due to vegetation restoration efforts in recent decades. However, the response of precipitation to this greening remains uncertain. In this study, we identified and evaluated the main moisture source regions for precipitation over the Loess Plateau from 1982 to 2019 using a moisture tracking model, the modified WAM-2layers model, and the conceptual framework of the precipitationshed. By integrating multiple linear regression analysis with a conceptual hydrologically weighting method, we quantified the effective influence of different environmental factors for precipitation, particularly the effect of vegetation. Our analysis revealed that local precipitation has increased on average by 0.16 mm yr-1 and evaporation by 5.17 mm yr-1 over the period 2000-2019 after the initiation of the vegetation restoration project. Regional greening including the Loess Plateau contributed to precipitation for about 0.83 mm yr-1, among which local greening contributed for about 0.07 mm yr-1. Local vegetation contribution is due to both an enhanced local evaporation as well as an increased local moisture recycling (6.9% in 1982-1999; 8.3% in 2000-2019). Thus, our study shows that local revegetation had a positive effect on local precipitation, and the primary cause of the observed increase in precipitation over the Loess Plateau is due to a combination of local greening and circulation change. Our study underscores that increasing vegetation over the Loess Plateau has exerted strong influence on local precipitation and supports the positive effects for current and future vegetation restoration plans toward more resilient water resources managements.

Compound drought and heatwaves (CDH) have garnered increasing attention because concurrent extreme events can exacerbate the harmful impacts caused by univariate extremes. However, various severities in CDH events and their relationships with sea surface temperature (SST) variations in China remain little understood. Here, we accurately identify CDH events and multi-aspect of characteristics using the standardized precipitation evapotranspiration index (SPEI) and the excess heat factor (EHF) during the extended summer (May–September) of 1961–2017. The evolution of multifaceted characteristics of CDH and their association with SST variation are further explored. The results suggest that the number, frequency, duration and intensity of regional CDH events show heterogeneous spatial patterns, with a significant increasing trend. A consistent abrupt transition in CDH characteristics averaged over China occurred in the period of 1993–1996. Mild and moderate CDHs occur more commonly in Northwest and North China, whereas severe CDHs are mainly found in central and eastern regions. Mild and moderate CDHs are more susceptible to SST modes than severe CDH, and there are strong positive correlations between mild and moderate CDH characteristics and SST variations in the northwest and northern regions. Compared to El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) plays a dominant role in the intensifications of mild and moderate CDH events. Regionally, the northwest and north have experienced longer, more frequent and severe CDH events during the positive phase of IOD. These findings reveal the divergent evolutions in CDH characteristics with various severities and inconsistent impacts of different SST modes on the compound events.

Evapotranspiration (ET) partitioning distinguishes the soil evaporation (E) and plant transpiration (T) components and is crucial for understanding the land-atmosphere interactions and ecosystem water budget. However, the mechanism and controls of ET partitioning for subtropical forests in heterogeneous environments remain poorly understood. Here, we present delta 18O and delta 2H of about 1,527 isotope samples including atmospheric water, soil and plant water during different seasons in 2 years of 2020-2021 from a coniferous forest across Southeast China. We used the isotopic mass balance of ecosystem water pools, the Craig-Gordon model and the Keeling-Plot method to partition T from ET (T/ET) and quantify the controls on T/ET. Results indicated that the uncertainty in the T/ET was principally from the soil water evaporation (delta E) value, about 20-30 cm was found to be a reasonable evaporating front depth for estimating delta E in this coniferous forest. T/ET presented a "U" shape diurnal pattern and varied from 66.7% to 89.9%. Isotope-based T/ET in autumn with high temperatures and little rain was higher than those in the summer and winter seasons. Relative humidity (or vapour pressure deficit) dominated the diurnal T/ET variations (relative contributions of > 40%) in summer and autumn, while air temperature and soil water content were the main controls in winter. Our study also showed that delta 18O-derived T/ET was consistent with that of delta 2H, although delta 2H was found to be more stable in ET partitioning, the dual stable isotope approach should be employed in future studies for the uncertainties brought by samplings or measurements. The agreement between the isotope-based T/ET and ET partitioning approach that uses eddy covariance and sap flux data was stronger at midday. These isotope-inferred ET partitioning can inform land surface models and provide more insights into water management in subtropical forests.

Understanding future variations and trends of heatwave events has critical implications for the ecosystem and human health. However, the diverse metrics of heatwave affect the comparable assessment of heatwave evolution at regional scales. The inadequate consideration of the enhanced warming trend and local antecedent heat conditions at different climate zones undermines the comprehensive understanding of future heatwave changes. Here, we systematically assess variations and trends in duration, frequency, and intensity of heatwave events in China from 1961 to 2100, using historical observations and climate model simulations from Coupled Model Intercomparison Project Phase 6. The increased rates and trends in the duration and frequency are more evident than those in intensity and severe heatwave days. Regionally, the northern and western regions are projected to suffer longer and more frequent consecutive heatwaves, while southern regions are likely at greater risk of severe heatwave days. A comparison among four scenarios shows that the future heatwave characteristics projected by the high forcing Shared Socioeconomic Pathway (SSP5-8.5) exhibit substantial intensification than those in other three experiments, imposing intractable dangers to numerous organisms and ecosystems. Under the SSP1-2.6, the acceleration of all heatwave characteristics is projected to slow down in all regions after 2040. In addition to maximum temperature, temperature advections are projected to contribute to heatwave intensification in western regions. Our results provide a comprehensive assessment of future variations and trends in heatwave events. The comparable future changes across unevenly developed regions are necessary for improving regional adaptive capacity to extreme heat risk.

Moisture recycling of local water sources through evaporation allows a region to maintain precipitation in the same region. Many studies have shown that deforestation can reduce evaporation and downwind rainfall, and it has been suggested that reforestation conversely increase evaporation and downwind rainfall. Precipitation has been observed to increase over China’s Loess Plateau over the past two decades, coinciding with the start of the Grain for Green project - the largest active revegetation programme attempted in the world. However, the contribution of revegetation to the increase in precipitation is yet unknown. Here, we aim to quantitatively analyze the relationship between revegetation, evaporation, and locally recycled moisture. Based on the ERA5 reanalysis data, we used the modified Water Accounting model-2 layers (WAM-2layers) to track the recycling moisture over the Loess Plateau. Preliminary results indicate that local recycling moisture (Er) accounted for almost one-tenth of the annual precipitation, and seems to have a decreasing trend, which was more evident after 2000. Meanwhile, the contribution of local evaporation to local precipitation appears to decrease during both 1982-1999 and 2000-2015, while the decreasing trend has been slightly amplified after the revegetation. Spatially, Er over the Loess Plateau showed a decreasing trend from southeast to northwest. Significant increasing trend of Er can be identified in the northern part of the plateau during 1982-1999. However, after the implement of the Green for Grain Project, most area over the Loess Plateau showed a decreasing trend, which is significant in the east. Thus, contrary to popular wisdom, the revegetation appears to have led to a decrease in evaporation and subsequent recycling, and the increase in precipitation seems to have other causes. These results are subject to high data uncertainty, and further research is needed to better understand the hydroclimatic effects of revegetation projects under climate change.

Seasonal variation of vegetation profoundly affects the water cycle. However, the seasonal divergence of evapotranspiration (ET) sensitivity in response to vegetation variations has not been fully understood. Here we derived an analytical solution to examine the impact of seasonal vegetation changes on ET with an extended Budyko framework based on an improved ET algorithm with improved water balance constraints. Results reveal a clear seasonal divergence of ET sensitivity to vegetation coverage changes across climate regimes and biomes. Generally, the high ET sensitivity to vegetation coverage has a clear north-south shift trajectory from spring to winter. For moderate-humid regions (0.7 < aridity index < 1.0), vegetation exhibits higher importance in altering ET in March-September. While for moderate-dry regions (1.0 < aridity index < 1.4), the sensitivity of ET to vegetation changes is the highest in September-November. Moreover, the spatial-temporal pattern of ET sensitivity to seasonal vegetation changes is different between short vegetation cover and forest. Additionally, negative ET sensitivity to vegetation coverage changes was discovered in regions with seasonal precipitation of less than 500 mm and sparse vegetation coverage (predominant land cover types of grassland, scrubland, and savannas). In summary, our study provides an analytical solution to estimate ET sensitivity to seasonal vegetation changes within the extended Budyko framework. The results highlight the difference in hydrological response to vegetation dynamics across seasons and vegetation types.

AimsThe variability of climatic conditions and complexity of underlying surface conditions in the humid regions of southern China have brought difficulties to the measurement and estimation of evapotranspiration.Tree transpiration is the key component of forest evapotranspiration.The monitoring and measurement of sap flow has become the main method to determine transpiration.Cunninghamia lanceolata forest as a representative vegetation in the source area of Xinʼanjiang River, is crucial to soil and water conservation and climate regulation in the area. MethodsIn order to investigate the controlling mechanism of environmental factors on the change of the sap flow rate (J s ) during the growing season of C. lanceolata (April to September 2020), the J s of C. lanceolata were monitored by the sap flow measurement system and environmental observations and soil water content were measured by the meteorological gradient tower in the source area. Important findingsThe J s of C. lanceolata had obvious seasonal variations with the largest in August and the lowest in May.Among the environmental factors, net solar radiation (R n ) and vapor pressure deficit (VPD) were the strongest factors correlating with J s .The results of principal component analysis indicated that the variance contribution rates of the first principal component were 59.1% and 57.9% at the hourly and daily scales, respectively.Furthermore, VPD and R n played a major role in the first principal component and were the main environmental factors affecting the change of the sap flow rate of C. lanceolata in the study area.During the

Accurate estimation of global evapotranspiration (ET) is critical to understand the water and energy cycles in the Earth system. Satellite-driven ET algorithms serve as an effective way to estimate the global ET. However, many algorithms have been designed independently of water balance constraints, which potentially limit their ability to estimate ET in water-limited and high interception regions. As ET remains one of the most uncertain terms in the global water budgets, incorporating water balance constraints into algorithms should improve the performance of ET estimates. In this study, we developed a general solution (denoted PEW) based on the proportionality hypothesis to incorporate available water control into the widely used Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) ET algorithm. Simulated performances of the PEW model and PT-JPL algorithm were evaluated against 106 FLUXNET eddy covariance (EC) towers data at the site scale. Meanwhile, model results were compared at the global scale with the means of the widely used ET products. We found that the PEW model has smaller errors than the original PT-JPL algorithm, with the greatest improvements in water-limited regions and areas characterized by the high interception. Moreover, by incorporating the water balance constraints into the ET algorithm, the PEW model has the ability to distinguish variations in ET affected by El Nino-Southern Oscillation. In summary, our study offers a convincing evidence regarding the incorporation of water balance constraints into remote sensing algorithms for more accurately mapping global terrestrial ET with an enhanced understanding of ET variation under climate change. This model is the first of its kind among remote-sensing models to provide global land ET estimation with the proportionality hypothesis-based water balance constraints.

Since evapotranspiration (ET) is the intrinsic link between global energy and water cycle, remote sensing-based models have been developed for regional and global scale ET on heterogeneous land surface over the past four decades. In view of the significantly different physical mechanisms and mathematical expressions among remote sensing ET models as well as data availability and quality control process among the model input products, it is necessary to investigate the uncertainties of the multiple sources in actual ET estimation. Here, three remote sensing ET models, including the PT-DTsR model, the PM-mod model and the PML model, were simultaneously driven by three meteorological reanalysis products, resulting in nine calculation schemes to analyze the combined effect of the models and the input datasets. The Sobol' sensitivity method was also adopted for identifying the influential model parameters and in turn understanding the model process. The results indicated that estimates from nine calculation schemes showed great differences in the magnitude and temporal variation, explaining 20-50% of ET variability over all sites. Additionally, schemes compared with both uncorrected and corrected energy balance observations, as well as schemes using meteorological variables from three reanalysis products and Eddy Covariance tower observations, verified that the uncertainties in latent heat flux data observations caused by the energy budget mis-closure problem and spatial scale mismatch have propagated into the ET estimation. Our study is a beneficial reference for the uncertainties in remote sensing-based methods, and thus can provide guidance for the future development of ET models.

Although soil moisture (SM) is an important constraint factor of evapotranspiration (ET), the majority of the satellite-driven ET models do not include SM observations, especially the SM at different depths, since its spatial and temporal distribution is difficult to obtain. Based on monthly three-layer SM data at a 0.25° spatial resolution determined from multi-sources, we updated the original Priestley Taylor–Jet Propulsion Laboratory (PT-JPL) algorithm to the Priestley Taylor–Soil Moisture Evapotranspiration (PT-SM ET) algorithm by incorporating SM control into soil evaporation (Es) and canopy transpiration (T). Both algorithms were evaluated using 17 eddy covariance towers across different biomes of China. The PT-SM ET model shows increased R2, NSE and reduced RMSE, Bias, with more improvements occurring in water-limited regions. SM incorporation into T enhanced ET estimates by increasing R2 and NSE by 4% and 18%, respectively, and RMSE and Bias were respectively reduced by 34% and 7 mm. Moreover, we applied the two ET algorithms to the whole of China and found larger increases in T and Es in the central, northeastern, and southern regions of China when using the PT-SM algorithm compared with the original algorithm. Additionally, the estimated mean annual ET increased from the northwest to the southeast. The SM constraint resulted in higher transpiration estimate and lower evaporation estimate. Es was greatest in the northwest arid region, interception was a large fraction in some rainforests, and T was dominant in most other regions. Further improvements in the estimation of ET components at high spatial and temporal resolution are likely to lead to a better understanding of the water movement through the soil–plant–atmosphere continuum.