EGU24-13113, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-13113
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multimodel – multidata simulations for mapping evapotranspiration and its uncertainty of estimation from remote sensing data

Albert Olioso1,2, Samuel Mwangi1, Hugo Desrutins2, José Sobrino3, Drazen Skoković3, Simon Carrière4, Nesrine Farhani5, Jordi Etchanchu5, Jérôme Demarty5, Tian Hu6, Kanishka Mallick6, Aolin Jia6, Samuel Buis2, Marie Weiss2, Chloé Ollivier5, and Gilles Boulet7
Albert Olioso et al.
  • 1Unité de Recherche écologie des Forêts Méditerranéennes (URFM), INRAE, Avignon, France (albert.olioso@inrae.fr)
  • 2UMR EMMAH, INRAE- Avignon Université, Avignon, France
  • 3Global Change Unit, Image Processing Laboratory, University of Valencia, Valencia, Spain
  • 4UMR METIS, Sorbonne Université-UPMC-CNRS-EPHE, Paris, France
  • 5UMR HSM, IRD-CNRS-Université de Montpellier, Montpellier, France
  • 6Department of Environment Research and Innovation, LIST, Belvaux, Luxembourg
  • 7UMR CESBIO, UPS-CNRS-CNES-IRD, Toulouse, France;

Evapotranspiration (ET) is a fundamental element of the hydrological cycle which plays a major role on surface water balance and surface energy balance. At local scale, ET can be estimated from detailed ground observations, for example using flux towers, but these measurements are only representative of very limited homogeneous area. When regional information is required, e.g.  for monitoring ground water resources, ET can be mapped using thermal infrared and spectral reflectance data. Various ET models have been developed but there was no competitive evaluation of them over a large range of situations, so that it is not possible to evaluate the intrinsic performance of one model compared to another. In such situation, ensemble model averaging may provide a coherent estimation of ET with an increased overall accuracy. In this work the ensemble modelling approach is extended to a multi-model – multi-data framework that provides ET estimations together with an uncertainty of estimation.

We developed the EVASPA framework for estimating ET through ensemble averaging with the objective of providing estimates of ET together with an estimation uncertainty. In this presentation we present a full analysis of the uncertainties of ET estimation in relation to uncertainties in input variables and models. Airborne remote sensing data were acquired over the Grosseto area in Italy in the frame of the ESA SurfSense experiment (high spatio-temporal Resolution Land Surface Temperature Experiment) in support of the LSTM mission project (Copernicus Land Surface Temperature Monitoring). Evapotranspiration was computed using two different types of models considering: -1) the evaporative fraction (EF) computed from the variability of surface temperature versus vegetation amount (fraction cover) or albedo over the investigated areas ('triangle' approach) and -2) the residual aerodynamic equation. Two types of uncertainties were computed: the ‘novice user’ uncertainty and the ‘expert user’ uncertainty which differed by the previous knowledge on the accuracy of input data and on the performances of models that was available to users. Evapotranspiration uncertainties ranged between 0.8 mm.d-1 (EF model, expert case) and 2.7 mm.d-1 (aerodynamic model, novice case). The analysis showed that the main uncertainty sources were related to model formulations (evaporative fraction calculation and ground heat flux calculation for both types of models) and to solar radiation (both types of models), wind speed and air temperature (aerodynamic model).

The EVASPA framework is presently used for the definition of the ET product in the frame of the TRISHNA thermal infrared space mission (CNES/ISRO).

How to cite: Olioso, A., Mwangi, S., Desrutins, H., Sobrino, J., Skoković, D., Carrière, S., Farhani, N., Etchanchu, J., Demarty, J., Hu, T., Mallick, K., Jia, A., Buis, S., Weiss, M., Ollivier, C., and Boulet, G.: Multimodel – multidata simulations for mapping evapotranspiration and its uncertainty of estimation from remote sensing data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13113, https://doi.org/10.5194/egusphere-egu24-13113, 2024.