1,088 research outputs found

    Calibration-free complementary relationship estimates terrestrial evapotranspiration globally

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

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    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

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    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

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    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

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

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    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

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    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
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