the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessment of Upscaling Methodologies for Daily Crop Transpiration using Sap-Flows and Two-Source Energy Balance Models in Almonds under Different Water Status and Production Systems
Abstract. The daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies to retrieve Td in almond trees with different production systems and water status. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th-TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo) and potential evapotranspiration (ETp). These approaches were firstly evaluated with in situ sap flow (T-SF) data and then applied to the Th-TSEB. Daily T-SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T-SF, and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water stressed trees. However, the daily upscaling approaches applied in the TSEB (Td-TSEB) failed to detect differences between production systems. The lack of sensibility of Td-TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The improvement of ETp estimations or more sophisticated ETp models could solve this issue.
- Preprint
(2308 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 08 May 2024)
-
RC1: 'Comment on hess-2024-5', Anonymous Referee #1, 23 Apr 2024
reply
This paper investigates the temporal upscaling from snapshot (airborne or satellite overpass) to daily transpiration using both sap flow observations and the dual source TSEB model, over an almond orchard. This scaling, which might be very different for woody and herbaceous species, has to my knowledge not been looked at previously, and this paper casts some light on how the stomatal and ecophysiological regulation might affect this temporal extrapolation. The analysis is based on 2 summer UAV flights over a field with contrasted structural (3) and water treatment (3) levels.
Main concern is that the outcomes are only based on those 2 dates, therefore on a very limited meteorological forcing conditions. I wonder why in-situ TIR radiometers or cheap TIR imaging cameras have not been used to continuously monitor the 3*3 conditions at representative places to complement the study and offer a longer timeseries.
Second concern is that the upscaling using the measured and simulated reference transpiration rates are treated differently just based on a performance, I think it would be useful to see how the performance degradation at other times of the day impact the reconstruction (and not only using 2PM, line 490). If the ref. T is at 10AM for instance, does the TSEB-based extrapolated diurnal transpiration show the same pattern as when using the observed T as a ref ?
Minor comments:
- Line 49: this is partially true for evapotranspiration ET, not for evaporation E and transpiration T, because the system is often underdetermined (one constraint brought by Land Surface Temperature, whereas there are 2 unknowns, E and T, cf Boulet et al., 2018) except when using TSEB_2T; please comment
- Line 70: add both Van Niel et al. (2011) paper on the topic and take their outcomes into consideration (convex/concave up shapes of EF for instance)
- Line 129: “two laterals” what does that mean ? Please explain the technical terms on irrigation and horticultural practices, not everyone is familiar with “open vase” etc.
- Line 230 and Line 535: how did you take into account the shadows for the soil and canopy temperatures ? (cf. Mwangi et al., 2023). What is the impact of the shadows actually ? (needs more analysis and comment than what is written in line 535 to 539)
- Line 285: how did you choose the minimum surface resistance for the PM equation ?
- Table 1 and 2: review the column heads which are not self understandable; there is an error in the header of the fourth col. Of Table 2 (twice fc)
- I find the ANOVA analysis not very conclusive and little insightful, maybe worth trying to gain info from a temporal analysis for modelled reference as suggested above, not only 2PM ?
- Line 599 “hinting at a potential enhancement to address the observed underestimation”: this is simply impossible to understand, please rephrase and clarify !
Refs:
Boulet, G., Delogu, E., Saadi, S., Chebbi, W., Olioso, A., Mougenot, B., Fanise, P., Lili-Chabaane, Z., and Lagouarde, J. P.: Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands, Proc. IAHS, 380, 17-22, https://www.proc-iahs.net/380/17/2018/
Samuel Mwangi, Gilles Boulet, Michel Le Page, Jean Philippe Gastellu-Etchegorry, Joaquim Bellvert, et al.. Observation and Assessment of Model Retrievals of Surface Exchange Components Over a Row Canopy Using Directional Thermal Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023, 16, pp.7343-7356. 10.1109/JSTARS.2023.3297709.
Van Niel, T.G.; McVicar, T.R.; Roderick, M.L.; van Dijk, A.I.J.M.; Renzullo, L.J.; van Gorsel, E. Correcting for systematic error in satellite-derived latent heat flux due to assumptions in temporal scaling: Assessment from flux tower observations. J. Hydrol. 2011, 409, 140–148.
Citation: https://doi.org/10.5194/hess-2024-5-RC1
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
174 | 36 | 12 | 222 | 17 | 10 |
- HTML: 174
- PDF: 36
- XML: 12
- Total: 222
- BibTeX: 17
- EndNote: 10
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1