the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Oct 2025
Technical note: Including non-evaporative fluxes enhances the accuracy of isotope-based soil evaporation estimates
Abstract. Accurately estimating soil water evaporation is essential for quantifying terrestrial water and energy. Isotope-based methods are useful but often rely on steady-state (SS) soil water storage assumptions or non-steady-state (NSS) models that ignore non-evaporative fluxes (such as infiltration and transpiration), leading to mass balance errors. Here, we introduce a new framework, named ISONEVA (ISOtope based soil water evaporation estimation considers dynamic soil water storage and Non-EVAporative fluxes), adapted from lake evaporation models to account for both evaporative and non-evaporative fluxes in soils under dynamic soil water storage. Validation under virtual and field scenarios demonstrated that ISONEVA improved evaporation estimates by 54.1%–83.6% (virtual) and 54.5%–92.4% (field) compared to traditional SS and NSS models. Furthermore, ISONEVA estimated a plausible upper limit of the E/ET ratio (0.139), encompassing the observed value (0.126), whereas SS and NSS methods severely underestimated (0.037) or were unable to produce a limit under field validation. These results highlight the critical role of dynamic soil water storage and non-evaporative fluxes in isotope-based soil water evaporation estimates, offering a robust framework for long-term assessments and informing future coupled land surface modeling efforts.
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Status: open (until 01 Dec 2025)
- RC1: 'Comment on egusphere-2025-4614', Anonymous Referee #1, 04 Nov 2025 reply
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RC2: 'Comment on egusphere-2025-4614', Anonymous Referee #2, 14 Nov 2025
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General Comments
This study addresses key challenges in estimating soil evaporation using isotopic methods by proposing the ISONEVA framework. The research incorporates dynamic soil moisture storage and non-evaporation fluxes (such as infiltration and transpiration), representing a theoretical improvement over traditional steady-state (SS) and non-steady-state (NSS) methods. ISONEVA requires minimal data (primarily soil moisture content, isotopic composition, and basic meteorological data), making it more suitable for large-scale applications compared to methods like eddy covariance and sap flow. The study provides a conservative upper limit estimation method for the evapotranspiration (E/ET) ratio, offering valuable insights for water resource management. From this perspective, I find this research highly interesting. However, some scientific concerns prevent me from supporting publication at the current paper stage, though I encourage the authors to refine it further.
The fundamental contradiction between theoretical assumptions and mass balance principles. Problem identification: The author assumes that the isotopic composition of infiltration water matches that of surface soil water. This assumption exhibits significant physical inconsistencies. In real soil systems, after precipitation infiltration, new water mixes with existing soil water in an uneven process. The isotopic composition of infiltration water should be a product of mixing precipitation and soil water, not simply equal to surface soil water. Particularly after rainfall events, infiltration water should more closely resemble the isotopic characteristics of precipitation. While the author emphasizes "ensuring soil water and isotopic mass balance," this assumption inherently violates the principle of isotopic mass conservation. Such a flawed premise leads to systematic overestimation or underestimation of infiltration-induced isotopic loss after rainfall events, thereby compromising the accuracy of the E/P ratio. The positive results from virtual experiments may stem from MOIST model's adoption of identical assumptions rather than the validity of this particular hypothesis.
In the virtual experiment section, simulated data were generated using the MOIST model to validate the ISONEVA method. The ISONEVA and MOIST models may share similar physical assumptions (such as the treatment of infiltration isotope ratios), resulting in what essentially becomes self-validation. The soil's initial isotopic uniformity in the virtual experiment was set at 0‰ (an idealized condition absent in natural environments). Precipitation isotopic values were artificially assigned between-50‰ and-10‰, with insufficient consideration for natural variability. This validation design fails to properly assess the method's applicability under real-world complex conditions and may significantly overestimate ISONEVA's accuracy. The "superiority" demonstrated in Figures 4 and 5 likely reflects differences in methodological assumptions rather than actual precision.
The field validation process inadequately addressed critical data gaps and uncertainties. For atmospheric water vapor isotope data, the study employed substitute data from Vienna. Although sensitivity tests were conducted in Appendix B, these analyses only examined variations within Vienna's measurement range. Despite geographical proximity, the Swiss EPFL and Vienna differ in atmospheric circulation patterns, water vapor sources, and seasonal characteristics. The atmospheric water vapor isotope composition is critical for the Craig-Gordon model, and this substitution may introduce systematic bias. ISONEVA's Mean Absolute Error (MAE) of 0.04 might be inflated due to inherent uncertainties in input data. The "slight underestimation" of the E/ET ratio (0.103 versus observed 0.126) could partly stem from atmospheric isotope data deviations. Appendix B's sensitivity analysis (Table B1) shows E/P estimates fluctuating between-0.1 and-0.12, indicating method sensitivity to atmospheric isotope data. However, this uncertainty was not properly incorporated into the final error estimates. Beyond these three major issues, the study should address: 1) The optimization process's uncertainties may significantly outweigh methodological differences, yet results are presented as "mean ± standard deviation" without adequately discussing algorithm limitations; 2) Lack of systematic analysis of optimal thickness variations under different soil textures, precipitation patterns, and vegetation conditions. This limitation restricts the method's universal applicability, making it difficult for users to determine appropriate sampling depth for their specific research areas. The assumption that "surface soil root water uptake dominates non-evaporation flux Q" does not hold in many ecosystems, significantly reducing ISONEVA's practicality as an ET allocation tool. Consequently, the "upper limit" estimates may substantially deviate from actual values in numerous scenarios.
Therefore, the manuscript has several significant shortcomings in methodological clarity, validation rigor, data interpretation, and presentation. The derivations and assumptions are sometimes opaque, the virtual and field validations lack sufficient sensitivity analyses, and key limitations (e.g., scalability and parameter uncertainties) are not adequately addressed. These issues undermine the reproducibility and broader applicability of ISONEVA. While the concept is promising, substantial revisions are needed to strengthen the scientific foundation and ensure the method's robustness for practical use. The manuscript is not suitable for publication in its current form but could be reconsidered after major revisions.
Citation: https://doi.org/10.5194/egusphere-2025-4614-RC2
Model code and software
ISONEVA codes with virtual and field dataset Han Fu https://doi.org/10.5281/zenodo.17119369
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This technical note presents a new isotope-based framework (ISONEVA) that accounts for dynamic soil water storage and non-evaporative fluxes (e.g., infiltration, transpiration) in estimating soil evaporation. The study clearly identifies and addresses a long-standing issue in isotope-based evaporation methods, which is mass balance errors from neglecting non-evaporative fluxes. Based on a conceptual structure from lake evaporation modelling, the proposed model incorporates more hydrological components. The topic is highly relevant to hydrology, ecohydrology, and isotope applications, and it fits well within the scope of Hydrology and Earth System Sciences.
Overall, I find this to be a novel, clearly written, and methodologically sound contribution. The technical note successfully demonstrates that ISONEVA improves the realism and accuracy of isotope-based soil water evaporation estimates. The framework could have broad implications and a strong contribution to the isotope hydrology community.
General comments:
Figures and appendix:
Figure 1: Please clarify what dash arrows refer to?
Figure 3: Please make the font larger. Additionally, the color contrast between model results and observations could be enhanced for clarity.
Figure 6: Why the beginning and ending data points are missing in the NSS curve.
Appendix A: The derivation of ISONEVA are pure equations. Adding explanations would be helpful for readers to understand.