IAHS-AISH Scientific Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Advantages and opportunities in using multisensor remote sensing data for evapotranspiration retrieval as well as better partitioning between evaporation and transpiration

Gilles Boulet1, Samuel Mwangi1, Albert Olioso2, Valérie Le Dantec1, Olivier Merlin1, Jerôme Demarty3, Kanishka Malick4, Eswar Rajasekaran5, Athira Karal Valiyaparambath5, Zouhair Rafi6, and Salah Er-raki7
Gilles Boulet et al.
  • 1CESBIO, Université de Toulouse, CNES, CNRS, INRAE, IRD, UT3, Toulouse, France (gilles.boulet@ird.fr)
  • 2EMMAH, INRAE-Avignon Université, Avignon, France
  • 3HSM, IRD, CNRS, Université de Montpellier, Montpellier, France
  • 4Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
  • 5Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, India
  • 6Mohammadia School of Engineer, Rabat, Morocco
  • 7UCAM, LP2M2E- FST, Marrakech, Morocco

Quantification of evapotranspiration is crucial for a sustainable management of scarce water resources. Surface energy balance models driven by remotely sensed surface temperatures observations enable to estimate total evapotranspiration and average (surface) water stress conditions. For improved agricultural water management as well as ecosystem health monitoring, it is also important to provide an estimate of evapotranspiration components, i.e. transpiration and soil evaporation, and target the water status of the plant. This is possible through the use of dual-source energy balance models because they solve separate energy budgets for the soil and vegetation. However, the dual-source models rely on specific assumptions on plant water stress to get both components out of the sole surface temperature information. Additional information are thus required, either specifically related to evaporation (such as surface water content, as it can be derived from active microwave information) or transpiration (such as physiological indices derived from specific optical bands). Present work evaluates the ability of the SPARSE dual-source energy balance model to compute not only total evapotranspiration, but also water stress and transpiration/evaporation components, exploiting the complementarities of multiple data sources, including those acquired at lower spatial resolution or from a different view angle. Flux datasets including available sapflow and lysimeter measurements acquired over rainfed and irrigated crops in temperate, Mediterranean and semi-arid regions are used to evaluate the retrieval performances of the evaporation and transpiration components. More than a systematic increase of retrieval performance, the main positive outcome of combining those different sources of data, as well as rightfully accounting for their specific signature (direction, resolution...), seems to be an increased robustness and a better realism of the subcomponents that are retrieved.

How to cite: Boulet, G., Mwangi, S., Olioso, A., Le Dantec, V., Merlin, O., Demarty, J., Malick, K., Rajasekaran, E., Karal Valiyaparambath, A., Rafi, Z., and Er-raki, S.: Advantages and opportunities in using multisensor remote sensing data for evapotranspiration retrieval as well as better partitioning between evaporation and transpiration, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-194, https://doi.org/10.5194/iahs2022-194, 2022.