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Drought stress detection with a coupled AgroC-SCOPE model

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<p>Photosynthesis is the cornerstone of all life on earth. Light energy, captured by chlorophyll, fuels photosynthesis. As an excess of absorbed light leads to harmful products, the excess light is either dissipated as heat or it is re-emitted in the atmosphere. The latter pathway results in a weak, but very specific spectral signal, right from the heart of the photosynthetic apparatus, called chlorophyll fluorescence. Recent advancements in spectrometry have allowed the retrieval of fluorescence with remote sensing. Given its close link to photosynthesis, it has the potential of informing crop growth models. The aim of this study is to estimate the stress parameter of the crop growth model AgroC by incorporating remotely-sensed sun-induced chlorophyll fluorescence (SIF) data. The radiative transfer model SCOPE converts the leaf-level fluorescence obtained from AgroC to canopy-scale SIF. In case of a stress, the SIF at 760 nm decreases, while the SIF at 687 nm shows a more complex relationship to stress. Comparing the modelled canopy-scale and observed SIF provides information on the plant water stress status, allowing a more precise estimate of the photosynthetic activity. Downstream, this leads to a better estimation of the plant growth, as well as a better estimation of the carbon and water fluxes. A field campaign is conducted over a sugar beet field in Merzenhausen, Germany, in which the fluorescence was measured alongside the water and carbon fluxes. As the fluorescence provides an additional constraint on the photosynthesis, the AgroC-SCOPE model is expected to provide significantly better estimates of the carbon fluxes compared to the AgroC model. The results of the coupled AgroC-SCOPE model will be presented at this meeting. This study provides information on the link between drought stress and fluorescence. An approach similar to the one proposed in this study will allow detecting drought stress at the regional to global scale with FLEX data.</p>
Title: Drought stress detection with a coupled AgroC-SCOPE model
Description:
<p>Photosynthesis is the cornerstone of all life on earth.
Light energy, captured by chlorophyll, fuels photosynthesis.
As an excess of absorbed light leads to harmful products, the excess light is either dissipated as heat or it is re-emitted in the atmosphere.
The latter pathway results in a weak, but very specific spectral signal, right from the heart of the photosynthetic apparatus, called chlorophyll fluorescence.
Recent advancements in spectrometry have allowed the retrieval of fluorescence with remote sensing.
Given its close link to photosynthesis, it has the potential of informing crop growth models.
The aim of this study is to estimate the stress parameter of the crop growth model AgroC by incorporating remotely-sensed sun-induced chlorophyll fluorescence (SIF) data.
The radiative transfer model SCOPE converts the leaf-level fluorescence obtained from AgroC to canopy-scale SIF.
In case of a stress, the SIF at 760 nm decreases, while the SIF at 687 nm shows a more complex relationship to stress.
Comparing the modelled canopy-scale and observed SIF provides information on the plant water stress status, allowing a more precise estimate of the photosynthetic activity.
Downstream, this leads to a better estimation of the plant growth, as well as a better estimation of the carbon and water fluxes.
A field campaign is conducted over a sugar beet field in Merzenhausen, Germany, in which the fluorescence was measured alongside the water and carbon fluxes.
As the fluorescence provides an additional constraint on the photosynthesis, the AgroC-SCOPE model is expected to provide significantly better estimates of the carbon fluxes compared to the AgroC model.
The results of the coupled AgroC-SCOPE model will be presented at this meeting.
This study provides information on the link between drought stress and fluorescence.
An approach similar to the one proposed in this study will allow detecting drought stress at the regional to global scale with FLEX data.
</p>.

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