Thank you for the opportunity to review “Wildfire-induced disruptions to evapotranspiration, runoff, and water-balance closure across California’s water supply watersheds”. In this paper the authors present a multi-decadal synthesis of wildfire, ET, precipitation, and full natural flow data across key California basins. The results are consistent with growing body of post-wildfire hydrologic response literature, making the topic timely and likely of interest to a broad audience. 

I have several broader conceptual concerns that I believe should be addressed to strengthen the interpretation of the results. First, I am uncertain about the physical interpretation and motivation behind the parameter adjustments (scaling + intercept) applied to precipitation and/or FNF to improve water-balance closure. While these adjustments are presented as diagnostic tools, they risk appearing ad hoc without clearer linkage to quantified uncertainty or process understanding. I think it would strengthen the manuscript to clarify whether these adjustments are intended to identify systematic dataset biases, to approximate unaccounted storage fluxes, or to represent measurement error.  

Second, the water-balance framework assumes that annual changes in storage (ΔS) are negligible when comparing P−ET to FNF. While this generally seems OK at the scales considered here, deviations between P−ET and FNF during fire years could plausibly reflect changes in storage rather than solely disturbance-induced hydrologic “imbalance” or observational uncertainty. I encourage the authors to more explicitly justify the ΔS ≈ 0 assumption, and discuss its limitations.  

Finally, burn severity and vegetation controls are repeatedly invoked as key determinants of ET suppression and recovery, yet it is not fully clear how burn severity metrics are incorporated into the analysis. The methods primarily describe burned perimeters, and additional detail on whether severity (e.g., dNBR or similar indices) was used would improve clarity. Similarly, because vegetation structure and regrowth are central to much of the discussion of ET recovery trajectories, incorporating quantitative vegetation indices would help connect the mechanistic discussion to the results.  

I’ve included some line-by-line comments below.  

Abstract:  

Line 26: Should “Interannual P” be “annual P”? 

Lines 34-36:  

Introduction: 

L 49: What are the compounding disturbances? Repeated wildfires? Wildfire and drought?  

L57: I’m not sure what “vegetation mortality surplus” means? Here and throughout it might be helpful to add a little more detail about the expected change to individual  ET fluxes. The post-fire signal is most likely driven by decreasing transpiration, but there can be compensatory increases in ground evaporation. It might be worth referencing some of the papers by Collar et. al. 

• Collar, N. M., Ebel, B. A., Saxe, S., Rust, A. J., & Hogue, T. S. (2023). Implications of fire-induced evapotranspiration shifts for recharge-runoff generation and vegetation conversion in the western United States. Journal of Hydrology, 621, 129646. https://doi.org/10.1016/j.jhydrol.2023.129646  

• Collar, N. M., Saxe, S., Rust, A. J., & Hogue, T. S. (2021). A CONUS-scale study of wildfire and evapotranspiration: Spatial and temporal response and controlling factors. Journal of Hydrology, 603, 127162. https://doi.org/10.1016/j.jhydrol.2021.127162 

L 80: and moisture availability? Especially in California, which is likely a moisture limited system?  

L 88: While I generally agree that that this gap exists, there are quite a few papers in this space t(some of which the authors already reference) that do address this gap. For example: 

• Goeking, Sara A.; Tarboton, David G. 2020. Forests and water yield: A synthesis of disturbance effects on streamflow and snowpack in western coniferous forests. Journal of Forestry. 2020: 172-192. 

• Hallema, D.W., Sun, G., Caldwell, P.V. et al. Burned forests impact water supplies. Nat Commun 9, 1307 (2018). https://doi.org/10.1038/s41467-018-03735-6 

• Beyene MT, Leibowitz SG, Pennino MJ. Parsing Weather Variability and Wildfire Effects on the Post-Fire Changes in Daily Stream Flows : A Quantile-Based Statistical Approach and its Application. Water Resour Res. 2021 Aug 31;57(10):1-20. PMID: 34898727; PMCID: PMC8654146. 

L118 – Some recent work has identified aridity as an important driver of post-wildfire hydrologic response. Is there an aridity gradient across your watersheds? It might be worth including in Table 1 

• Baudena M, Santana VM, Baeza MJ, Bautista S, Eppinga MB, Hemerik L, Garcia Mayor A, Rodriguez F, Valdecantos A, Vallejo VR, Vasques A, Rietkerk M. Increased aridity drives post-fire recovery of Mediterranean forests towards open shrublands. New Phytol. 2020 Feb;225(4):1500-1515. doi: 10.1111/nph. 

Data section. 

As a reader who is not familiar with these particular hydrometeorological datasets it would be helpful to include a litter more detail describing how they are calculated. For example from the spatial resolution I assume that the ET data is derived from an energy balance model built on Landsat imagery, but maybe that’s incorrect? Does the ET model make assumptions over burned areas that could influence the ET estimates? Is P derived from the same model? Does it incorporate any other precipitation datasets?  

Similarly with the FNF data. Do these data account for diversions and reservoir operations? It might be helpful to include a little more detail since you reference reservoir effects a few times in the discussion. 

L 160-161: Can you clarify that this is mean annual ET? And is the post-fire ET just a single year average?  

L 186-196: I appreciate the discussion around uncertainty and challenges it could pose for interpretation. It seems like these are real challenges when considering the interacting effects of P and ET in a post-fire setting. I’m not quite sure I follow the motivation of your proportional adjustments approach though. Perhaps this an attempt to uncover systematic biases in the datasets? Is the assumption that d_S is really zero? Doesn’t a land cover disturbance like wildfire kind of inherently violate the assumption of steady state?  

L 203 – 217: Interesting to see the range of recovery trajectories. Are there and vegetation indices that could help explain why some burned areas seem to take so long to recover? You mention vegetation structure as a control on ET recovery a few times in the discussion, but I didn’t see it really built into the results.