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

Journal metrics

Journal metrics

  • IF value: 1.319 IF 1.319
  • IF 5-year value: 1.299 IF 5-year 1.299
  • CiteScore value: 1.27 CiteScore 1.27
  • SNIP value: 0.740 SNIP 0.740
  • SJR value: 0.598 SJR 0.598
  • IPP value: 1.21 IPP 1.21
  • h5-index value: 12 h5-index 12
  • Scimago H index value: 6 Scimago H index 6
Volume 7, issue 2 | Copyright
Geosci. Instrum. Method. Data Syst., 7, 151-167, 2018
https://doi.org/10.5194/gi-7-151-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 Jun 2018

Research article | 07 Jun 2018

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 Prévot3 Nissaf Boudhina et al.
  • 1LISAH, IRD, INRA, Montpellier SupAgro, University of Montpellier, 34060 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

Abstract. 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.

Publications Copernicus
Download
Short summary
To provide reliable time series of evapotranspiration, we evaluated the performances of four different gap-filling methods when tailored to conditions of hilly crop fields. The tailoring consisted of splitting the time series beforehand on the basis of upslope and downslope winds. The obtained accuracies on evapotranspiration after gap filling were comparable to those previously reported over flat and mountainous terrains, and they were better with the most widely used gap-filling method.
To provide reliable time series of evapotranspiration, we evaluated the performances of four...
Citation
Share