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首页> 外文期刊>Agricultural and Forest Meteorology >Incorporation of a soil water modifier into MODIS predictions of temperate Douglas-fir gross primary productivity: initial model development.
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Incorporation of a soil water modifier into MODIS predictions of temperate Douglas-fir gross primary productivity: initial model development.

机译：将土壤水分改良剂纳入MODIS预测的温带花旗松冷杉总初级生产力：初始模型开发。

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The moderate resolution imaging spectroradiometer (MODIS) is being used to monitor gross primary production (GPP), both spatially and temporally, routinely from space. However, estimates of GPP at various flux stations indicate that the MODIS algorithm may (i) over-predict GPP at sites where limitation to growth by low-soil water content is not adequately captured by the reduction in stomatal conductance by vapor pressure and (ii) under-predict GPP in highly productive, evergreen, needle leaf forests, due to a reduced radiation-use-efficiency term. The objective of this paper is to determine if any systematic bias exists in the MODIS algorithm relative to eddy covariance (EC) estimates of GPP made over an evergreen, needle leaf temperate rainforest on Vancouver Island, Canada, which is routinely water-stressed in summer months. Results indicate that 8-day GPP as predicted by the standard MODIS algorithm, with appropriate parameters for evergreen needle leaf forest, was highly correlated to EC-measured GPP (r2=0.89, p<0.001, S.E.=0.9 g C m-2 day-1), however with significant bias, under predicting GPP by as much as 30%. Increasing the radiation-use-efficiency term epsilon < sub>max (g C MJ-1) from the MODIS lookup value to the maximum observed at the site resulted in a reduced bias in the predicted GPP, however estimates were 8% higher than EC measurements. To account for soil water stress on plant growth, we implemented a soil water modifier initially proposed by Leuning et al. [Leuning, R., Cleugh, H., Zegelin, S., Hughes, D., 2005. Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: measurements and comparison with MODIS remote sensing estimates. Agric. For. Meteorol. 129, 151-173] that accounts for rainfall and potential evaporation in the antecedent 3 months, a surrogate for soil water availability. Results confirm that field observations of relative available soil water content in the 0-60 cm layer matched the proposed soil water modifier closely with the relationship between the modified MODIS algorithm GPP and the EC-measured GPP remaining highly significant (r2=0.91, p<0.001, S.E.=1.1 g C m-2 day-1) with no significant bias. Whilst broad scale implementation of such a soil water modifier into the MODIS algorithm is still limited due to lack of rainfall data, at least in the short-term, the modifier does provide an alternative for researchers and land mangers, interested in applying the MODIS GPP products over regional areas, but who may have, or are observing, over-estimated production estimates due to the lack of inclusion of soil water modification to growth.
机译：中分辨率成像光谱仪（MODIS）被用于常规地从空间上和时间上监测总的初级生产（GPP）。但是，在各种通量站处的GPP估算值表明，MODIS算法可能会（i）在通过蒸汽压降低气孔电导率不能充分捕获低土壤水分对生长的限制的站点上过度预测GPP，并且（ii ）由于降低了辐射使用效率，因此在高产常绿针叶林中对GPP的预测不足。本文的目的是确定相对于加拿大温哥华岛常绿，针叶温带雨林的GPP的涡流协方差（EC）估计，MODIS算法中是否存在任何系统性偏差，夏季通常用水胁迫个月。结果表明，标准MODIS算法预测的8天GPP具有常绿针叶林的适当参数，与EC测得的GPP高度相关（r2 = 0.89，p <0.001，SE = 0.9 g C m-2天-1），但是在预测GPP的情况下偏差高达30％。从MODIS查找值将辐射使用效率项epsilon max （g C MJ-1）增加到现场观察到的最大值，导致预测的GPP偏差减小，但是估计值为8比EC测量值高％。为了解决土壤水分对植物生长的压力，我们实施了Leuning等人最初提出的土壤水分改良剂。 [Leuning，R.，Cleugh，H.，Zegelin，S.，Hughes，D.，2005。澳大利亚温带桉树森林和热带湿/干稀树草原的碳和水通量：测量值和与MODIS遥感估计值的比较。农业对于。陨石[129，151-173]解释了前三个月的降雨和潜在的蒸发，这是土壤水可利用量的替代物。结果证实，0-60 cm层中相对可用土壤水分的现场观测与拟议的土壤水分改良剂紧密匹配，而改良的MODIS算法GPP与EC测量的GPP之间的关系仍然非常显着（r2 = 0.91，p < 0.001，SE = 1.1 g C m-2 day-1），无明显偏差。尽管由于缺乏降雨数据，这种土壤水分改良剂在MODIS算法中的大规模实施仍然受到限制，但至少在短期内，该改良剂的确为研究人员和土地管理者提供了另一种选择，他们有兴趣应用MODIS GPP区域范围内的产品，但由于缺乏将土壤水分改良剂包括在生长中，因此可能已经或正在观测的生产估计值被高估了。

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