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

摘要

Estimating evapotranspiration in hilly watersheds is paramount for managingwater 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 ofmissing data because of instrumental malfunctions or quality filtering.Existing gap-filling methods are questionable over hilly crop fields becauseof changes in airflow inclination and subsequent aerodynamic properties. Weevaluated the performances of different gap-filling methods before and aftertailoring to conditions of hilly crop fields. The tailoring consisted of splitting the LE time seriesbeforehand on the basis of upslope and downslopewinds. The experiment was setup within an agricultural hilly watershed innortheastern Tunisia. EC measurements were collected throughout the growthcycle of three wheat crops, two of them located in adjacent fields onopposite hillslopes, and the third one located in a flat field. We consideredfour gap-filling methods: the REddyProc method, the linear regression betweenLE and net radiation (Rn), the multi-linear regression of LE against the otherenergy 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, andit might improve the accuracies on LE retrievals in some cases. Regardless ofthe method, the obtained accuracies on LE estimates after gap filling were closeto instrumental accuracies, and they were comparable to those reported inprevious studies over flat and mountainous terrains. Overall, REddyProc wasthe most appropriate method, for both gap-filling rate and retrievalaccuracy. Thus, it seems possible to conduct gap filling for LE time seriescollected over hilly crop fields, provided the LE time series are split beforehandon the basis of upslope–downslope winds. Future works should addressconsecutive vegetation growth cycles for a larger panel of conditions interms of climate, vegetation, and water status.