Regional‐Scale Wilting Point Estimation Using Satellite SIF, Radiative‐Transfer Inversion, and Soil‐Vegetation‐Atmosphere Transfer Simulation: A Grassland Study
Regional‐Scale Wilting Point Estimation Using Satellite SIF, Radiative‐Transfer Inversion, and Soil‐Vegetation‐Atmosphere Transfer Simulation: A Grassland Study
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DOI：
10.1029/2022jg007074
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发表时间：
2023-04
期刊：
影响因子：
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通讯作者：
T. Kiyono;H. Noda;T. Kumagai;H. Oshio;Y. Yoshida;T. Matsunaga;K. Hikosaka
中科院分区：
文献类型：
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作者：
T. Kiyono;H. Noda;T. Kumagai;H. Oshio;Y. Yoshida;T. Matsunaga;K. Hikosaka
虽然水的供应强烈控制总初级生产（GPP），土壤水分含量（SMC）（萎蔫点）的影响是很差的量化在区域和全球范围内。在这项研究中，我们使用了10年的温室气体观测卫星（GOSAT）的太阳诱导叶绿素荧光（SIF）观测，以估计蒙古高原半干旱草原的枯萎点。依次进行辐射传输模型反演和土壤植被大气传输模拟，以区分干旱对植物生理的影响和叶冠光学特性的变化。我们修改了现有的反演算法和广泛使用的土壤冠层光合作用和能量通量观测模型，以充分评估旱地特征，例如稀疏的冠层和强对流。修改后的模型，检索参数和校准GOSAT的SIF，预测现实的全球初级生产力值。我们发现，（a）GOSAT估算的SIF产量与干旱呈明显的S形关系，估算的萎蔫点与文献中SMC的地面观测值在0.01 m3 m−3以内相匹配，（B）在考虑了叶冠光学特性的变化后，调整最大羧化速率改善了SIF预测，这意味着GOSAT检测到了叶水平光合作用中的干旱胁迫，以及（c）地表能量平衡显著影响草地的SIF;修改后的模型很好地再现了观测到的SIF（夏季平均偏差= 0.004 mW m−2 nm−1 sr−1），而原始模型在弱水平风条件下预测的值相当低。SIF中的一些模型-观察不匹配表明，需要对荧光参数化进行更多的研究（例如，光抑制）和额外的观察约束。
Although water availability strongly controls gross primary production (GPP), the impact of soil moisture content (SMC) (wilting point) is poorly quantified on regional and global scales. In this study, we used 10 years of observations of solar‐induced chlorophyll fluorescence (SIF) from the Greenhouse gases Observing Satellite (GOSAT) satellite to estimate the wilting point of a semiarid grassland on the Mongolian Plateau. Radiative‐transfer model inversion and soil‐vegetation‐atmosphere transfer simulation were sequentially conducted to distinguish the drought impacts on plant physiology from the changes in the leaf‐canopy optical properties. We modified an existing inversion algorithm and the widely used Soil‐Canopy Observation of Photosynthesis and Energy fluxes model to adequately evaluate dryland features, for example, sparse canopy and strong convection. The modified model, with retrieved parameters and calibration to GOSAT SIF, predicted realistic GPP values. We found that (a) the SIF yield estimated from GOSAT showed a clear sigmoidal pattern in relation to drought, and the estimated wilting point matched ground‐based observations in the literature within ∼0.01 m3 m−3 for the SMC, (b) tuning the maximum carboxylation rate improved the SIF prediction after considering the changes in the leaf‐canopy optical properties, implying that GOSAT detected drought stress in leaf‐level photosynthesis, and (c) the surface energy balance significantly impacted the grassland's SIF; the modified model reproduced observed SIF well (mean bias = 0.004 mW m−2 nm−1 sr−1 in summer), whereas the original model predicted substantially low values under weak horizontal wind conditions. Some model‐observation mismatches in the SIF suggest that more research is needed for fluorescence parametrization (e.g., photoinhibition) and for additional observation constraints.