| 20 Oct 2025
Uncertainties in long-term ensemble estimates of contextual evapotranspiration over Southern France
Abstract. Estimating evapotranspiration (ET) beyond the local or point scale is critical for water resources and ecosystem studies. Remote sensing offers a unique advantage by enabling ET monitoring at larger spatial scales than in-situ instruments. By leveraging relationships between surface biophysical parameters and terrestrial thermal emission, continuous ET can be retrieved across diverse landscapes. Herein, we apply the EVapotranspiration Assessment from SPAce (EVASPA) contextual tool over southern France, using MODIS-derived land surface temperature / emissivity (LST/E), NDVI and albedo products. The dataset spans 2004–2024, yielding 972 instantaneous ET estimates. The EVASPA ensemble integrates multiple member outputs generated from: 1) alternative formulations of the evaporative fraction (EF) and ground heat flux (G), and 2) different LST and radiation inputs. Evaluation against flux tower data shows that even a simple ensemble average provides reasonable agreement, though individual member performance varies substantially. Uncertainty analyses were also performed where we looked at how each of the distinct variables (i.e., LST, radiation, evaporative fraction (EF), and ground heat flux (G) methods) influenced the modelled ET. The analyses reveal that LST inputs and EF formulations are the dominant sources of variability, with seasonal dependence–uncertainties peak during summer (tending to follow the annual cycle of radiation) and are partly influenced by satellite characteristics. Generally the satellite's overpass time introduces more incertitude to the gap filled daily ET estimates compared to the LST/LSE separation methods; as such, the uncertainties in LST could, by extension, be partially attributed to uncertainties in the radiations during the acquisition time. Radiation inputs also contribute to the variations in the ensemble, while G flux methods exert comparatively minor influence, especially for estimates derived from TERRA morning overpasses. Overall, our results demonstrate that ensemble-based contextual modelling can provide both reliable flux estimates and a meaningful uncertainty spread. By allowing optimal member selection according to surface and climatic conditions, ensemble modelling using EVASPA enhances ET retrieval robustness thus providing more resilient and informative estimates. Such ensemble frameworks are especially valuable for forthcoming missions like TRISHNA, where consistent and accurate, high-resolution ET monitoring will be crucial for operational water and ecosystem management.
General assessment
This manuscript presents a scientifically robust and timely contribution. The ensemble-based EVASPA framework, combining multiple LST, radiation, EF and G datasets, provides a valuable foundation for analysing uncertainties in contextual evapotranspiration (ET) modelling. The methodological implementation is technically sound, and the topic is highly relevant for the remote-sensing and ET communities, especially in the context of upcoming missions such as TRISHNA.
My comments concern almost exclusively the readability and organisation of the manuscript, not the scientific validity, which appears strong. The manuscript is dense, and the large amount of information sometimes makes it challenging to identify the central messages. A clearer narrative and more guidance for the reader would significantly increase the accessibility and impact of the work.
Major comments
1. Readability and narrative flow
The manuscript contains extensive information, often presented in long paragraphs with multiple embedded ideas. This makes it difficult for readers to extract the main points and to follow the progression of the results. A clearer hierarchy of information, distinguishing essential findings from detailed descriptions, would be highly beneficial.
Example: In parts of Section 4.3, very long multi-clause sentences make it difficult to isolate the key conclusions.
2. Clarity of objectives and role of each analysis
The study combines input-data variability analysis, performance evaluation against flux towers, ensemble-based uncertainty quantification, and similarity clustering. All of these components are relevant, but the manuscript does not always clearly articulate how each one contributes to the overarching objective. Briefly restating the purpose of each major section would help maintain coherence.
3. Interpretation and introduction of figures
The figures are well designed, but several require more explanation to be fully interpretable. In some cases, it is not clear how values were aggregated or what specific elements represent.
Examples:
- For Figure 3, the method used to compute the distributions (means and standard deviations) is not entirely clear, particularly the number of pixels and temporal samples considered.
- Figure 5 would benefit from a clearer explanation of what each column corresponds to in terms of ensemble subsets.
Providing more explicit introductions to figures would greatly help readers understand what to focus on.
4. Spatial representativeness
Most analyses are based on the eight 1-km pixels corresponding to the flux-tower sites. This setup is fully appropriate for a site-based uncertainty assessment, but it does limit spatial generalisation. A brief acknowledgement of this limitation would help clarify the scope of the conclusions.
5. Emphasis on key insights
Some of the most important conclusions - such as the dominant role of LST (particularly overpass time), the notable influence of EF methods, and the different impact of radiation in gap-filling versus instantaneous estimates - are present but sometimes buried within dense text. Highlighting these insights more explicitly would strengthen the communication of the study’s main contributions.
Minor comments
- Some sentences are particularly long and could be split for clarity.
- Acronyms may be reintroduced when they reappear after long intervals.
- The introduction could converge more directly toward the specific objectives of the study.
- The conclusion is informative, but a more concise synthesis of the central messages would improve its effectiveness.
Final recommendation
The science is solid and the manuscript has clear potential. Once clarified and streamlined, it will make a strong contribution. I recommend major revisions, focusing mainly on the readability, structure, and presentation rather than on the scientific methodology.