Modeling and Partitioning of Regional Evapotranspiration Using a Satellite-Driven Water-Carbon Coupling Model

Hu, Zhongmin; Wu, Guojiang; Zhang, Liangxia; Li, Shenggong; Zhu, Xianjin; Zheng, Han; Zhang, Leiming; Sun, Xiaomin; Yu, Guirui

doi:10.3390/rs9010054

Cited by 34 publications

(20 citation statements)

References 55 publications

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“…Only the site‐specific parameterization performance is used for fair comparison as given in Table . On average, the R 2 and RMSE of ET are better or about the same with that obtained by Hu et al () and Yebra et al (), and GPP is closely comparable or better than the simulation yield by Hu et al () and Yebra et al () using their coupled model. This gives us confidence that the PML_V2 model proposed here is relatively simple yet reliable to estimate ET and GPP.…”

Section: Discussionsupporting

confidence: 78%

“…The GPP calculated from this algorithm was used as the observed GPP obs for model use. The daily data set is further aggregated to obtain 8‐day average values in accordance with the temporal resolution of remote sensed LAI (Hu et al, ; Papale & Valentini, ; Shi et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…Numerous models have been developed to estimate ET (Bastiaanssen, Menenti, et al, ; Bastiaanssen, Pelgrum, et al, ; Cleugh, Leuning, Mu, & Running, ; Guerschman et al, ; Leuning, Zhang, Rajaud, Cleugh, & Tu, ; Long & Singh, ; McVicar & Jupp, ; Mu, Heinsch, Zhao, & Running, ; Norman, Kustas, & Humes, ; Yang, Long, & Shang, ; Zhang, Chiew, Zhang, & Li, ) and GPP (Hu et al, ; Ma et al, ; Running et al, ; Yang, Donohue, McVicar, & Roderick, ; Yebra et al, ) from stand to regional and global scale during the past few decades. On the one hand, the Penman–Monteith (PM) equation (Monteith, )‐based ET models have been proven as biophysically solid, which is often applied in combination with land surface information (e.g., radiation and vegetation) derived from remotely sensed imageries (Cleugh et al, ; Leuning et al, ; Mallick et al, ; Morillas et al, ; Mu, Zhao, & Running, ; Zhang et al, ; Zhang et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems

et al. 2018

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Accurate quantification of terrestrial evapotranspiration and ecosystem productivity is of significant merit to better understand and predict the response of ecosystem energy, water, and carbon budgets under climate change. Existing diagnostic models have different focus on either water or carbon flux estimates with various model complexity and uncertainties induced by distinct representation of the coupling between water and carbon processes. Here, we propose a diagnostic model to estimate evapotranspiration and gross primary production that is based on biophysical mechanism yet simple for practical use. This is done by coupling the carbon and water fluxes via canopy conductance used in the Penman–Monteith–Leuning equation (named as PML_V2 model). The PML_V2 model takes Moderate Resolution Imaging Spectrometer leaf area index and meteorological variables as inputs. The model was tested against evapotranspiration and gross primary production observations at 9 eddy‐covariance sites in Australia, which are spread across wide climate conditions and ecosystems. Results indicate that the simulated evapotranspiration and gross primary production by the PML_V2 model are in good agreement with the measurements at 8‐day timescale, indicated by the cross site Nash–Sutcliffe efficiency being 0.70 and 0.66, R2 being 0.80 and 0.75, and root mean square error being 0.96 mm d−1 and 1.14 μmol m−2 s−1 for evapotranspiration and gross primary production, respectively. As the PML_V2 model only requires readily available climate and Moderate Resolution Imaging Spectrometer vegetation dynamics data and has few parameters, it can potentially be applied to estimate evapotranspiration and carbon assimilation simultaneously at long‐term and large spatial scales.

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Section: Discussionsupporting

confidence: 78%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems

et al. 2018

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“…The T/ET can vary between 20% and 95% across ecosystems (Berkelhammer et al, 2016). T/ET studies across a wide spectrum of scales and ecosystems have become a hot spot in ecohydrology and related disciplines (Hu et al, 2017;Velpuri & Senay, 2017;Zhou et al, 2016) to improve the prediction of ecosystem responses to climate change.…”

Section: Introductionmentioning

confidence: 99%

Seasonality of the Transpiration Fraction and Its Controls Across Typical Ecosystems Within the Heihe River Basin

Tong

Wang

et al. 2019

JGR Atmospheres

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Understanding the seasonality of the transpiration fraction (T/ET) of total terrestrial evapotranspiration (ET) is vital for coupling ecological and hydrological systems and quantifying the heterogeneity among various ecosystems. In this study, a two‐source model was used to estimate T/ET in five ecosystems over the Heihe River Basin. In situ measurements of daily energy flux, sap flow, and surface soil temperature were compared with model outputs for 2014 and 2015. Agreement between model predictions and observations demonstrates good performance in capturing the ecosystem seasonality of T/ET. In addition, sensitivity analysis indicated that the model is insensitive to errors in measured input variables and parameters. T/ET among the five sites showed only slight interannual fluctuations while exhibited significant seasonality. All the ecosystems presented a single‐peak trend, reaching the maximum value in July and fluctuating day to day. During the growing season, average T/ET was the highest for the cropland ecosystem (0.80 ± 0.13), followed by the alpine meadow ecosystem (0.79 ± 0.12), the desert riparian forest Populus euphratica (0.67 ± 0.07), the Tamarix ramosissima Ledeb desert riparian shrub ecosystem (0.67 ± 0.06), and the alpine swamp meadow (0.55 ± 0.23). Leaf area index exerted a first‐order control on T/ET and showed divergence among the five ecosystems because of different vegetation dynamics and environmental conditions (e.g., water availability or vapor pressure deficits). This study quantified transpiration fraction across diverse ecosystems within the same water basin and emphasized the biotic controls on the seasonality of the transpiration fraction.

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“…In recent years, a variety of physical process models have been developed to estimate the spatial distribution of evapotranspiration (ET) and gross primary production (GPP) at various scales ranging from the stand scale to global (Li et al, 2009). Although much progress has been made in understanding the details of physical processes incorporated into ecosystem models and their applications on regional scales, there are still large uncertainties in model estimates of the water and carbon balance (Hu et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Incorporating Spatial Variations in Parameters for Improvements of an Evapotranspiration Model

Keenan

et al. 2020

JGR Biogeosciences

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Ecosystem models are important tools for exploring the temporal and spatial patterns of ecosystem processes and their responses to climate change. However, the implications of uncertainty in model parameters are often overlooked, especially in regional ecosystem model simulations. Here, we use eddy-covariance observations to estimate parameters in an ecosystem model, which was developed from Shuttleworth-Wallace model, and examine the effect on estimates of evapotranspiration (ET). Using a simple ecosystem model as an example, we use Monte Carlo techniques to optimize key model parameters using eddy covariance (EC) data from 163 FLUXNET sites. The optimization process revealed a strong spatial correlation between key parameters and environmental variables, particularly leaf area index (LAI) and soil characteristics (e.g., clay fraction). The optimization of parameters related to canopy conductance and soil surface resistance greatly improved model performance, particularly when incorporating the identified spatial variation of parameters. The improved model agreed well with the measurements with an increase in the coefficient of determination (R 2) from 73% to 80% in the 8-day averaged ET estimation and a decrease in the root mean square error (RMSE) from 130.2 to 104.3 mm year −1 compared with the original model. The results suggest the potential of eddy-covariance flux observations to identify predictable spatial variations of key parameters, which can be used to better constrain ecosystem models. And in this case, a universal and efficient method for reducing the uncertainties in key parameters across different PFTs and ecosystem applications is suggested.

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Modeling and Partitioning of Regional Evapotranspiration Using a Satellite-Driven Water-Carbon Coupling Model

Cited by 34 publications

References 55 publications

Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems

Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems

Seasonality of the Transpiration Fraction and Its Controls Across Typical Ecosystems Within the Heihe River Basin

Incorporating Spatial Variations in Parameters for Improvements of an Evapotranspiration Model

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