Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling

Evapotranspiration (ET) is critical in linking global water, carbon and energy cycles. However, direct measurement of global terrestrial ET is not feasible. Here, we first reviewed the basic theory and state-of-the-art approaches for estimating global terrestrial ET, including remote-sensing-based physical models, machine-learning algorithms and land surface models (LSMs). We then utilized 4 remote-sensing-based physical models, 2 machine-learning algorithms and 14 LSMs to analyze the spatial and temporal variations in global terrestrial ET. The results showed that the ensemble means of annual global terrestrial ET estimated by these three categories of approaches agreed well, with values ranging from 589.6 mm yr−1 (6.56×104 km3 yr−1) to 617.1 mm yr−1 (6.87×104 km3 yr−1). For the period from 1982 to 2011, both the ensembles of remote-sensing-based physical models and machine-learning algorithms suggested increasing trends in global terrestrial ET (0.62 mm yr−2 with a significance level of p0.05), although many of the individual LSMs reproduced an increasing trend. Nevertheless, all 20 models used in this study showed that anthropogenic Earth greening had a positive role in increasing terrestrial ET. The concurrent small interannual variability, i.e., relative stability, found in all estimates of global terrestrial ET, suggests that a potential planetary boundary exists in regulating global terrestrial ET, with the value of this boundary being around 600 mm yr−1. Uncertainties among approaches were identified in specific regions, particularly in the Amazon Basin and arid/semiarid regions. Improvements in parameterizing water stress and canopy dynamics, the utilization of new available satellite retrievals and deep-learning methods, and model–data fusion will advance our predictive understanding of global terrestrial ET

Integration of the Vegetation Phenology Module Improves Ecohydrological Simulation by the SWAT-Carbon Model

Vegetation phenology and hydrological cycles are closely interacted from leaf and species levels to watershed and global scales. As one of the most sensitive biological indicators of climate change, plant phenology is essential to be simulated accurately in hydrological models. Despite the Soil and Water Assessment Tool (SWAT) has been widely used for estimating hydrological cycles, its lack of integration with the phenology module has led to substantial uncertainties. In this study, we developed a process-based vegetation phenology module and coupled it with the SWAT-Carbon model to investigate the effects of vegetation dynamics on runoff in the upper reaches of Jinsha River watershed in China. The modified SWAT-Carbon model showed reasonable performance in phenology simulation, with root mean square error (RMSE) of 9.89 days for the start-of-season (SOS) and 7.51 days for the end-of-season (EOS). Simulations of both vegetation dynamics and runoff were also substantially improved compared to the original model. Specifically, the simulation of leaf area index significantly improved with the coefficient of determination (R2) increased by 0.62, the Nash–Sutcliffe efficiency (NSE) increased by 2.45, and the absolute percent bias (PBIAS) decreased by 69.0 % on average. Additionally, daily runoff simulation also showed notably improvement, particularly noticeable in June and October, with R2 rising by 0.22 and NSE rising by 0.43 on average. Our findings highlight the importance of integrating vegetation phenology into hydrological models to enhance modeling performance

Revisiting the contribution of transpiration to global terrestrial evapotranspiration

Even though knowing the contributions of transpiration (T), soil and open water evaporation (E), and interception (I) to terrestrial evapotranspiration (ET=T+E+I) is crucial for understanding the hydrological cycle and its connection to ecological processes, the fraction of T is unattainable by traditional measurement techniques over large scales. Previously reported global mean T/(E+T+I) from multiple independent sources, including satellite-based estimations, reanalysis, land surface models, and isotopic measurements, varies substantially from 24% to 90%. Here we develop a new ET partitioning algorithm, which combines global evapotranspiration estimates and relationships between leaf area index (LAI) and T/(E+T) for different vegetation types, to upscale a wide range of published site-scale measurements. We show that transpiration accounts for about 57.2% (with standard deviation6.8%) of global terrestrial ET. Our approach bridges the scale gap between site measurements and global model simulations,and can be simply implemented into current global climate models to improve biological CO2 flux simulations

Evapotranspiration estimation considering anthropogenic heat based on remote sensing in urban area

Urbanization influences hydrologic cycle significantly on local, regional even global scale. With urbanization the water resources demand for dense population sharpened, thus it is a great challenge to ensure water supply for some metropolises such as Beijing. Urban area is traditionally considered as the area with lower evapotranspiration (ET) on account of the impervious surface and the lower wind speed. For most remote sensing models, the ET, defined as latent heat in energy budget, is estimated as the difference between net radiation and sensible heat. The sensible heat is generally higher in urban area due to the high surface temperature caused by heat island, therefore the latent heat (i.e. the ET) in urban area is lower than that in other region. We estimated water consumption from 2003 to 2012 in Beijing based on water balance method and found that the annual mean ET in urban area was about 654 mm. However, using Surface Energy Balance System (SEBS) model, the annual mean ET in urban area was only 348 mm. We attributed this inconsistence to the impact of anthropogenic heat and quantified this impact on the basis of the night-light maps. Therefore, a new model SEBS-Urban, coupling SEBS model and anthropogenic heat was developed to estimate the ET in urban area. The ET in urban area of Beijing estimated by SEBS-Urban showed a good agreement with the ET from water balance method. The findings from this study highlighted that anthropogenic heat should be included in the surface energy budget for a highly urbanized area

Grassland greening and water resource availability may coexist in a warming climate in Northern China and the Tibetan Plateau

Greening of Northern China and the Tibetan Plateau (NCTP) has been observed by increases in the remotely sensed leaf area index (LAI), driven primarily by CO2 fertilization effects, anthropogenic warming, and the implementation of ecological restoration programs. Continued growth of LAI throughout the 21st century is also projected by the Coupled Model Intercomparison Project Phase 6 (CMIP6) scenarios. However, the question of whether local water resources can sustain ongoing grassland greening has not been adequately investigated. Here we assessed the sustainability of water resources under grassland greening across NCTP under various climate scenarios using water yield (WY, defined as precipitation minus actual evapotranspiration) as the key metric. Unexpectedly, we observe the coexistence of increases in LAI and WY in most of NCTP. In a warming climate with increasing precipitation and CO2, we find that grasses maintain high water use efficiency to sustain their growth, contributing to continued local water resource availability. Thus, livestock production may also continue to increase under the simultaneous growth of LAI and WY in the future

Evaluation of six satellite-based terrestrial latent heat flux products in the vegetation dominated Haihe river basin of north China

In this study, six satellite-based terrestrial latent heat flux (LE) products were evaluated in the vegetation dominated Haihe River basin of North China. These LE products include Global Land Surface Satellite (GLASS) LE product, FLUXCOM LE product, Penman-Monteith-Leuning V2 (PML_V2) LE product, Global Land Evaporation Amsterdam Model datasets (GLEAM) LE product, Breathing Earth System Simulator (BESS) LE product, and Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD16) LE product. Eddy covariance (EC) data collected from six flux tower sites and water balance method derived evapotranspiration (WBET) were used to evaluate these LE products at site and basin scales. The results indicated that all six LE products were able to capture the seasonal cycle of LE in comparison to EC observations. At site scale, GLASS LE product showed the highest coefficients of determination (R2) (0.58, p 2), followed by FLUXCOM and PML products. At basin scale, the LE estimates from GLASS product provided comparable performance (R2 = 0.79, RMSE = 18.8 mm) against WBET, compared with other LE products. Additionally, there was similar spatiotemporal variability of estimated LE from the six LE products. This study provides a vital basis for choosing LE datasets to assess regional water budget

Integrating in-situ measurements, land surface models and satellite remote sensing to understand impacts of environmental changes on terrestrial ecosystem processes at multiple scales

How terrestrial ecosystems respond to environmental changes affects the well-being of human society. Thus, extreme climate events, increasing the atmospheric concentration of CO₂, and drastic changes in temperature are sources of major concern. However, our current capacity to understand and predict these responses is still limited because a myriad of physical, chemical, and biological processes are involved. While many mechanistic-based land surface models have been developed, their performances remain relatively poor and require continuous improvement. While ground-based and space-based observational datasets of the surface of the Earth have been available for a long time, their linkages to the functional aspects of the processes in terrestrial ecosystems often are weak. In this study, I used the approach of integrating in-situ measurements, land surface models, and remote sensing by satellites. I hypothesized that, through such integration, the impacts of environmental changes on terrestrial processes at multiple scales could be better understood and even predicted, especially the impacts related to the functions of important ecosystems. I tested this hypothesis at the local, regional, and global scales. At the local scale, i.e., at a Midwest forest site known as the isoprene volcano of the world, I examined the effects of droughts on the emissions of isoprene, which is the most abundant, non-methane, biogenic volatile organic compound. I compared flux tower observations with simulations performed by a state-of-the-art land model (CLM) coupled with the model of emissions of gases and aerosols from Nature version 2.1 (MEGAN2.1), and I used these observations to develop an understanding of how the amount of moisture in the soil and the ambient temperature affect the prediction of isoprene emissions during droughts. I found that temperature had a delaying effect on isoprene emissions, which are sensitive to variations in the moisture content of the soil. Thus, during drought conditions, both the delaying effect and the sensitivity to moisture are overlooked by the model. A better model that does not have these two shortcomings is required for realistic predictions of isoprene emissions. At the regional scale, I investigated the potential of using sun-induced chlorophyll fluorescence (SIF) retrieved from a satellite to monitor vegetation activities in an arid region and a semi-arid region in Australia. I chose these two types of regions for this investigation because the ecosystems in such regions have important effects on the global carbon cycle, while their contributions are poorly constrained in global carbon budgets. I found that SIF was synchronized better with the activity of vegetation than other indices that are commonly used for this purpose. I quantified the relationships between the various activities of plants and the amount and frequency of precipitation, and I was able to demonstrate that, over the region being studied, SIF represented the activity of vegetation in response to the availability of water better than other, remotely-sensed variables. At the global scale, I used multiple model ensembles to determine the climatic and anthropogenic controls on the terrestrial evapotranspiration trends from 1982 to 2010. After climatic influences, increases in CO₂ were found to be the second-most dominant factor that affected the trend of ET. CO₂ causes a decreasing trend in the canopy’s transpiration and ET, and this is especially of concern for tropical forests and high-latitude shrub lands. The increased deposition of nitrogen amplifies the global ET slightly due to enhanced growth of plants. On a global scale, land-use-induced ET responses are minor, but they can be significant locally, particularly over regions with intensive changes in the land-cover. The results of my studies demonstrated that integrating in-situ measurements, models of the surface on the land, and remote sensing using satellites can provide insights regarding the impacts of environmental changes on terrestrial processes at multiple scales. This approach is particularly important when models are imperfect and observations are lacking. My findings indicated ways that future models can be improved and identified key observational needs for the functions of terrestrial ecosystems.Geological Science