Evaluating four gap-filling methods for eddy covariance measurements of evapotranspiration over hilly crop fields
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...
| Հիմնական հեղինակներ: | , , , , , , |
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| Ձևաչափ: | Հոդված |
| Լեզու: | English |
| Հրապարակվել է: |
Copernicus Publications
2018-06-01
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| Շարք: | Geoscientific Instrumentation, Methods and Data Systems |
| Առցանց հասանելիություն: | https://www.geosci-instrum-method-data-syst.net/7/151/2018/gi-7-151-2018.pdf |
| Ամփոփում: | 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. |
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| ISSN: | 2193-0856 2193-0864 |