Peer review report 1 On “Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI”

2016 ◽  
Vol 217 ◽  
pp. 167
Author(s):  
Alfredo R. Huete
Keyword(s):  
Primary Production ◽  
Water Use Efficiency ◽  
Peer Review ◽  
Water Use ◽  
Gross Primary Production ◽  
Light Use Efficiency ◽  
Modis Evi ◽  
Use Efficiency

scholarly journals Primary production in forests and grasslands of China: contrasting environmental responses of light- and water-use efficiency models

2012 ◽  
Vol 9 (4) ◽  
pp. 4285-4321 ◽  
Author(s):  
H. Wang ◽  
I. C. Prentice ◽  
J. Ni
Keyword(s):  
Primary Production ◽  
Water Use Efficiency ◽  
Water Use ◽  
South China ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Stomatal Closure ◽  
Co2 Response ◽  
Data Set ◽  
Use Efficiency

Abstract. An extensive data set on net primary production (NPP) in China's forests is analysed with two semi-empirical models based on the light use efficiency (LUE) and water use efficiency (WUE) concepts, respectively. Results are shown to be broadly consistent with other data sets (grassland above-ground NPP; globally extrapolated gross primary production, GPP) and published analyses. But although both models describe the data about equally well, they predict notably different responses to [CO2] and temperature. These are illustrated by sensitivity tests in which [CO2] is kept constant or doubled, temperatures are kept constant or increased by 3.5 K, and precipitation is changed by ±10%. Precipitation changes elicit similar responses in both models. The [CO2] response of the WUE model is much larger but is probably an overestimate for dense vegetation as it assumes no increase in runoff; while the [CO2] response of the LUE model is probably too small for sparse vegetation as it assumes no increase in vegetation cover. In the LUE model warming reduces total NPP with the strongest effect in South China, where the growing season cannot be further extended. In the WUE model warming increases total NPP, again with the strongest effect in South China, where abundant water supply precludes stomatal closure. The qualitative differences between the two formulations illustrate potential causes of the large differences (even in sign) in the global NPP response of dynamic global vegetation models to [CO2] and climate change. As it is not clear which response is more realistic, the issue needs to be resolved by observation and experiment.

Variation of gross primary production, evapotranspiration and water use efficiency for global croplands

2020 ◽  
Vol 287 ◽  
pp. 107935
Author(s):  
Zhipin Ai ◽  
Qinxue Wang ◽  
Yonghui Yang ◽  
Kiril Manevski ◽  
Shuang Yi ◽  
...  
Keyword(s):  
Primary Production ◽  
Water Use Efficiency ◽  
Water Use ◽  
Gross Primary Production ◽  
Use Efficiency

The role of Evapotranspiration and Water Use Efficiency in Agriculture in Portugal

2020 ◽  
Author(s):  
José Vaz ◽  
Célia M. Gouveia ◽  
Isabel F. Trigo
Keyword(s):  
Climate Variability ◽  
Primary Production ◽  
Water Use Efficiency ◽  
Water Use ◽  
Reference Evapotranspiration ◽  
Gross Primary Production ◽  
Growth Monitoring ◽  
Climate Variability And Change ◽  
Wine Production ◽  
Use Efficiency

<p>Understanding climate variability and change and its impacts on natural systems is becoming more and more important as changes in earth surface condition near surface air temperature and precipitation. Over Portugal, the observed warming trends have been found to be asymmetric with respect to seasonal and diurnal cycles, with greatest warming occurring for the minimum temperature and during winter and spring. These observed trends exert strong influences on agriculture systems, affecting production viability through changes in winter hardening, frost occurrence, growing season lengths and heat accumulation for ripening potential.</p><p>Remote sensing technology has been developing steadily and its products can provide many applications in agriculture, namely crop identification, crop growth monitoring and yield prediction. Recently the LSA SAF team set up a strategy to generate long term data records from Meteosat Second Generation satellite series (2004 to present), releasing Land Surface Temperature (LST), Reference Evapotranspiration (ETREF) and Vegetation parameters (FAPAR, LAI and FVC) using a stable set of input data and algorithm, which would be suitable for climate variability and change detection studies. On the other hand, a new product to characterize the ecosystem processes, the Gross Primary Production (GPP), is under production since 2018.</p><p>In this work we propose to computed Water Use Efficiency (WUE), as the ratio between Gross Primary Production (GPP) and Reference Evapotranspiration (ETREF), using LSA-SAF Products. WUE translates the exchanges of carbon and water gross fluxes, between natural ecosystem and the atmosphere, allowing to monitor the adaptability of the ecosystems to climate change. The role played by Evapotranspiration and Water Use Efficiency for different crops in Portugal is evaluated, namely on Wine Production for Douro Region. Results for 2018 and 2019 highlights the vulnerability of the different sectors of Douro Region to dry and wet conditions, namely helping to analyze the impact of droughts on Douro wine production.</p><p>Acknowledgements: This study was performed within the framework of the LSA-SAF, co-funded by EUMETSAT This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under projects CLMALERT (ERA4CS/0005/2016).</p>

scholarly journals Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data

2018 ◽  
Vol 10 (9) ◽  
pp. 1346 ◽  
Author(s):  
Joanna Joiner ◽  
Yasuko Yoshida ◽  
Yao Zhang ◽  
Gregory Duveiller ◽  
Martin Jung ◽  
...  
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Satellite Data ◽  
Gross Primary Production ◽  
Satellite Observation ◽  
Data Driven ◽  
Spatial And Temporal Variability ◽  
Light Use Efficiency ◽  
High Productivity ◽  
Use Efficiency

We estimate global terrestrial gross primary production (GPP) based on models that use satellite data within a simplified light-use efficiency framework that does not rely upon other meteorological inputs. Satellite-based geometry-adjusted reflectances are from the MODerate-resolution Imaging Spectroradiometer (MODIS) and provide information about vegetation structure and chlorophyll content at both high temporal (daily to monthly) and spatial (∼1 km) resolution. We use satellite-derived solar-induced fluorescence (SIF) to identify regions of high productivity crops and also evaluate the use of downscaled SIF to estimate GPP. We calibrate a set of our satellite-based models with GPP estimates from a subset of distributed eddy covariance flux towers (FLUXNET 2015). The results of the trained models are evaluated using an independent subset of FLUXNET 2015 GPP data. We show that variations in light-use efficiency (LUE) with incident PAR are important and can be easily incorporated into the models. Unlike many LUE-based models, our satellite-based GPP estimates do not use an explicit parameterization of LUE that reduces its value from the potential maximum under limiting conditions such as temperature and water stress. Even without the parameterized downward regulation, our simplified models are shown to perform as well as or better than state-of-the-art satellite data-driven products that incorporate such parameterizations. A significant fraction of both spatial and temporal variability in GPP across plant functional types can be accounted for using our satellite-based models. Our results provide an annual GPP value of ∼140 Pg C year - 1 for 2007 that is within the range of a compilation of observation-based, model, and hybrid results, but is higher than some previous satellite observation-based estimates.

scholarly journals Tracking Ecosystem Water Use Efficiency of Cropland by Exclusive Use of MODIS EVI Data

2015 ◽  
Vol 7 (9) ◽  
pp. 11016-11035 ◽  
Author(s):  
Xuguang Tang ◽  
Hengpeng Li ◽  
Tim Griffis ◽  
Xibao Xu ◽  
Zhi Ding ◽  
...  
Keyword(s):  
Water Use Efficiency ◽  
Water Use ◽  
Modis Evi ◽  
Ecosystem Water Use Efficiency ◽  
Use Efficiency
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