论文标题
遥控太阳能诱导的叶绿素荧光的旱地蒸散量:在两源能量平衡模型中限制最佳气孔模型
Dryland evapotranspiration from remote sensing solar-induced chlorophyll fluorescence: constraining an optimal stomatal model within a two-source energy balance model
论文作者
论文摘要
蒸散(ET)代表了旱地中最大的水分流量,但是ET及其分配到植物蒸腾作用(T)和土壤蒸发(E)的量化很差,尤其是在精细的时间尺度上。基于物理的遥感模型依赖于合理的热通量估计值,例如两源能量平衡模型,可以从更明确地考虑气孔调节对Dryland ET的关键影响中受益。这项研究的目的是评估太阳能诱导的叶绿素荧光(SIF)的价值(SIF),即光合作用的代理,以限制在旱地的两源能量平衡模型中最佳气孔模型的冠层电导(GC)。我们评估了使用原位涡流协方差GPP作为基准测试的ET估计,并与使用连续的太阳能诱导的叶绿素荧光(CSIF)遥感产物而不是GPP的结果进行了比较,而有无根区域对GC的根部区域。估计的ET在四个草原和两个树草的旱地生态系统中非常强大。 ET模拟与原位GPP的比较得出的平均R2为0.73(0.86),RMSE在半小时(每日)时间尺度时为0.031(0.36)mm。包括明确的土壤水分对GC的影响,将R2提高到0.76(0.89)。对于CSIF模型,ET估计值的平均R2在包括土壤水分的影响时也有所改善:从0.65(0.79)到0.71(0.84),RMSE在0.023(0.22)和0.043(0.54)之间,取决于现场。我们的结果表明,在非常低的ET条件下,SIF估算了下天和每日通量的能力。 SIF可以提供有效的植被信号,以将气孔电导限制为旱地中的T和E分为T和E。使用遥感SIF估计值,例如CSIF,Tropomi-SIF或即将到来的Flex任务等,可以扩展该方法以进行区域估算。
Evapotranspiration (ET) represents the largest water loss flux in drylands, but ET and its partition into plant transpiration (T) and soil evaporation (E) are poorly quantified, especially at fine temporal scales. Physically-based remote sensing models relying on sensible heat flux estimates, like the two-source energy balance model, could benefit from considering more explicitly the key effect of stomatal regulation on dryland ET. The objective of this study is to assess the value of solar-induced chlorophyll fluorescence (SIF), a proxy for photosynthesis, to constrain the canopy conductance (Gc) of an optimal stomatal model within a two-source energy balance model in drylands. We assessed our ET estimation using in situ eddy covariance GPP as a benchmark, and compared with results from using the Contiguous solar-induced chlorophyll fluorescence (CSIF) remote sensing product instead of GPP, with and without the effect of root-zone soil moisture on the Gc. The estimated ET was robust across four steppes and two tree-grass dryland ecosystem. Comparison of ET simulated against in situ GPP yielded an average R2 of 0.73 (0.86) and RMSE of 0.031 (0.36) mm at half-hourly (daily) timescale. Including explicitly the soil moisture effect on Gc, increased the R2 to 0.76 (0.89). For the CSIF model, the average R2 for ET estimates also improved when including the effect of soil moisture: from 0.65 (0.79) to 0.71 (0.84), with RMSE ranging between 0.023 (0.22) and 0.043 (0.54) mm depending on the site. Our results demonstrate the capacity of SIF to estimate subdaily and daily ET fluxes under very low ET conditions. SIF can provide effective vegetation signals to constrain stomatal conductance and partition ET into T and E in drylands. This approach could be extended for regional estimates using remote sensing SIF estimates such as CSIF, TROPOMI-SIF, or the upcoming FLEX mission, among others.