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Evaluating four gap-filling methods for eddy covariance measurements of evapotranspiration over hilly crop fields

机译:评估丘陵作物田蒸发蒸腾涡度协方差测量的四种缺口填补方法

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Estimating evapotranspiration in hilly watersheds is paramount for managing water resources, especially in semiarid/subhumid regions. The eddy covariance (EC) technique allows continuous measurements of latent heat flux (LE). However, time series of EC measurements often experience large portions of missing data because of instrumental malfunctions or quality filtering. Existing gap-filling methods are questionable over hilly crop fields because of changes in airflow inclination and subsequent aerodynamic properties. We evaluated the performances of different gap-filling methods before and after tailoring to conditions of hilly crop fields. The tailoring consisted of splitting the LE time series beforehand on the basis of upslope and downslope winds. The experiment was setup within an agricultural hilly watershed in northeastern Tunisia. EC measurements were collected throughout the growth cycle of three wheat crops, two of them located in adjacent fields on opposite hillslopes, and the third one located in a flat field. We considered four gap-filling methods: the REddyProc method, the linear regression between LE and net radiation (Rn), the multi-linear regression of LE against the other energy fluxes, and the use of evaporative fraction (EF). Regardless of the method, the splitting of the LE time series did not impact the gap-filling rate, and it might improve the accuracies on LE retrievals in some cases. Regardless of the method, the obtained accuracies on LE estimates after gap filling were close to instrumental accuracies, and they were comparable to those reported in previous studies over flat and mountainous terrains. Overall, REddyProc was the most appropriate method, for both gap-filling rate and retrieval accuracy. Thus, it seems possible to conduct gap filling for LE time series collected over hilly crop fields, provided the LE time series are split beforehand on the basis of upslope–downslope winds. Future works should address consecutive vegetation growth cycles for a larger panel of conditions in terms of climate, vegetation, and water status.
机译:估算丘陵流域的蒸散量对于管理水资源至关重要,尤其是在半干旱/半湿润地区。涡流协方差(EC)技术允许连续测量潜热通量(LE)。但是,由于仪器故障或质量过滤,EC测量的时间序列通常会遇到大部分丢失的数据。由于气流倾角的变化和随后的空气动力学特性,现有的填隙方法在丘陵作物田上是有问题的。在评估丘陵农田条件之前和之后,我们评估了不同间隙填充方法的性能。剪裁包括根据上坡和下坡风事先划分LE时间序列。实验是在突尼斯东北部的农业丘陵流域内进行的。 EC测量是在三种小麦作物整个生长周期中收集的,其中两种位于相对的山坡上的相邻田地中,第三种位于平坦的田地中。我们考虑了四种间隙填充方法:REddyProc方法,LE和净辐射之间的线性回归(Rn),LE对其他能量通量的多线性回归以及使用蒸发分数(EF)。不管采用哪种方法,LE时间序列的分割都不会影响缺口填充率,并且在某些情况下可能会提高LE检索的准确性。无论采用哪种方法,在填空后获得的LE估计值的精度都接近仪器精度,并且与先前在平坦和多山地形上的研究报告的精度相当。总体而言,对于缝隙填充率和检索精度而言,REDdyProc是最合适的方法。因此,如果LE时间序列是根据上坡-下坡风预先划分的,则似乎可以对丘陵作物田上收集的LE时间序列进行间隙填充。未来的工作应该针对气候,植被和水状况方面的更大范围的条件解决连续的植被生长周期。

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