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Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/gi-2017-44
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
01 Dec 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Instrumentation, Methods and Data Systems (GI).
Evaluating four gap-filling methods for eddy covariance measurements of evapotranspiration over hilly crop fields
Nissaf Boudhina1,2, Rim Zitouna-Chebbi3, Insaf Mekki3, Frédéric Jacob1,3, Nétij Ben Mechlia2, Moncef Masmoudi2, and Laurent Prévot4 1Institut de Recherche pour le Développement (IRD) – UMR LISAH (IRD, INRA, Montpellier SupAgro), Montpellier, France
2Institut National Agronomique de Tunisie (INAT)/Carthage University, Tunis, Tunisia
3Institut National de Recherche en Génie Rural, Eaux et Forêts (INRGREF)/Carthage University, Ariana, Tunisia
4Institut National de la Recherche Agronomique (INRA) – UMR LISAH (IRD, INRA, Montpellier SupAgro), Montpellier, France
Abstract. Estimating evapotranspiration in hilly watersheds is paramount for managing water resources, especially in semi-arid regions. 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 dysfunctions 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 beforehand splitting the LE time series 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 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 method, the obtained accuracies on LE estimates after gap filling were close to instrumental accuracies, and 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 beforehand split 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.

Citation: Boudhina, N., Zitouna-Chebbi, R., Mekki, I., Jacob, F., Ben Mechlia, N., Masmoudi, M., and Prévot, L.: Evaluating four gap-filling methods for eddy covariance measurements of evapotranspiration over hilly crop fields, Geosci. Instrum. Method. Data Syst. Discuss., https://doi.org/10.5194/gi-2017-44, in review, 2017.
Nissaf Boudhina et al.
Nissaf Boudhina et al.
Nissaf Boudhina et al.

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