the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Nov 2025
Hydraulic Redistribution Decreases with Precipitation Magnitude and Frequency in a Dryland Ecosystem: A Data-Model Fusion Approach
Abstract. Hydraulic redistribution (HR), the movement of water via plant root systems that connect soil compartments with different water potential, should influences soil moisture dynamics particularly in water-limited ecosystems. Realistic representation of HR in ecosystem models is essential to improve the ability of these models to predict ecosystem function in dryland regions. In this study, we integrated HR into the Terrestrial ECOsystem model and employed a Bayesian Markov Chain Monte Carlo technique to optimize soil hydraulic parameters and root conductance using four years of soil moisture observations from a piñon-juniper woodland. We found that (i) integrating HR generally improved model prediction of soil moisture during dry periods, particularly in the top 30 cm of the soil profile, where more than 50 % of root biomass exists, mostly during dry periods; (ii) HR increased surface soil moisture by up to 60 % during dry periods; (iii) HR decreased with increasing precipitation magnitude and frequency, however, the length of dry spells between rainfall events also influenced HR rates; and (iv) upward HR in the top 60 cm soil profile became more pronounced as dry conditions progressed, with rates ranging from 0.10 to 0.50 mm d⁻¹. These findings highlight that HR plays a likely role in sustaining soil moisture during extended dry periods and has a limited effect during precipitation events. Future research should investigate the effect of HR on other ecosystem processes, such as net ecosystem exchange of carbon and evapotranspiration under varying climatic conditions.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-4608', Anonymous Referee #1, 28 Nov 2025
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RC2: 'Comment on egusphere-2025-4608', Anonymous Referee #2, 29 Nov 2025
This study integrated the hydraulic redistribution into a process-based ecosystem model (TECO) and found that the TECO with HR greatly improved model prediction of soil moisture during dry periods in a pinon-juniper woodland. The authors also found that the HR decreased with increasing precipitation magnitude and frequency and that upward HR in the top 60 cm was more pronounced as dry conditions progressed. This is a very interesting and meaningful study. As soil moisture is a key factor regulating ecosystem processes, this work provided an important foundation for further improving the capacity of ecosystem models to predict carbon and water cycles. I only had a few minor comments, which could help further enhance the clarity of the manuscript. Please see the comments below.
L47: Altered precipitation
L152–154 Please specify the total depth of the soil profile, which would save readers the effort of summing the individual soil layers. In addition, it appeared that the data assimilation was applied only to the upper four soil layers, whereas the remaining deeper layers were not considered, despite the soil profile being divided into ten layers. Please clarify this point.
L188 Please explain what the subscript j represents, as this would help clarify the meaning of Rj and soil matric potential associated with index j.
L204–205 Please specify then number of parameters that were optimized in the model.
L233–235 During the spin-up period, did you use the default TECO model?
L255–256 Please explain the rationale for using these two different metrics to evaluate model performance.
L285 “Vertical bars indicate”: Missing information here. It is hard to see any vertical bars in the figure. Also, please indicate what the different colors represent in the figure legend.
Figure 2 Please include a sentence in the figure legend to indicate that smaller values of the metrics correspond to better model performance. Please include the unit for the x-axis label.
L358–360 Only after reading this section did I realize why the bottom five layers were shown in Fig. 3. Including this information in the Methods section would help prevent reader confusion.
Fig. 5 While I understood that log10(days+1) was used on the x-axis to deal with zero values, it would be helpful to indicate this clearly in the figure legend.
L417 Correct “Xing Ming Hao et al.” to “Hao et al.”.
L426–433 It seemed that Figs. 1 and 6 were based on the same dataset, but presented differently. Is my understanding correct? If so, I would suggest considering combining Fig. 6 with Fig. 1 to avoid redundancy. Additionally, the content in this paragraph seems more appropriate for the Results rather the Discussion section.
L450 Please correct to “Ryel et al. (2002)”.
L458 “(typically from November to May)”
L459 “(usually from June to October)”
L471–472 “reported by Howard et al. (2009) and Neumann et al. (2014), which could…”?
L481–484 Please rewrite this sentence so that the two subsequent clauses convey consistent meanings.
Citation: https://doi.org/10.5194/egusphere-2025-4608-RC2 -
EC1: 'Comment on egusphere-2025-4608', Benjamin Stocker, 08 Jan 2026
Dear authors,I have received a third review which could not be posted in our portal as the deadline for posting reviews had been closed shortly before. This review was therefore sent by email (06.01.2026) - the same day as the open discussion phase was closed. I take the liberty to ask authors to take their inputs into consideration, too, and thank you for your understanding. The review text is pasted in below.Beni Stocker--- review text below ---This study uses a modeling approach to investigate the impacts of hydrologic redistribution (HR) on soil moisture dynamics in semi-arid woodland ecosystems. The authors incorporated HR into the TECO model and optimized model parameters using Bayesian MCMC techniques constrained by field soil moisture observations. The enhanced model substantially improved soil moisture simulations, particularly for surface soils during dry periods. The results indicate that HR increases surface soil moisture, with both its rate and magnitude closely linked to dry conditions.Overall, this is a well-designed and interesting study with important implications, as soil moisture plays a dominant role in regulating the structure and functioning of dryland ecosystems. Incorporating HR into ecosystem models has strong potential to improve predictions of plant growth as well as ecosystem water and carbon cycling. The TECO model has been widely and successfully applied to dryland systems, and the Bayesian optimization framework used here has been shown to be effective. The impacts of HR are clearly presented, particularly with respect to depth-dependent responses, diurnal and seasonal dynamics, and relationships with precipitation events. Potential limitations of the study are appropriately discussed. The manuscript is generally well written and easy to follow. I have no major concerns and recommend minor revision.Specific comments:
- L31: Consider deleting “mostly during dry periods,” as this is already stated in L29.
- L35: “Likely role” seems tentative. Since this study explicitly demonstrates the role of HR, consider using more definitive wording.
- L69, L417: For “Xing-Ming Hao,” consider deleting “Xing-Ming” and using “Hao et al.” for consistency.
- L70: Citation appears as “{Hultine, 2003 #211}”; please correct formatting.
- L74: Replace “understood” with “limited.”
- L86: Clarify “plant availability” (e.g., “availability for plant uptake”).
- L134–135: Please revise this sentence for clarity.
- L174: Please clarify how parameter m was determined.
- Fig. 1: While TECO+HR generally simulates SWC well, some model–observation mismatches may reflect measurement issues. For example, at 5 cm depth, a soil moisture peak occurs prior to 2020 without a corresponding precipitation event, and in 2021 soil moisture shows a smooth decline that may indicate limited sensor sensitivity to precipitation.
- Fig. 6: The figure requires clearer explanation. The impacts of HR are not easy to discern from the current presentation. In addition, the color gradient is confusing, as similar colors appear to represent both low and high values, making it difficult to interpret the magnitude and direction of HR effects.
- L446: Please check citation formatting (e.g., “Hao et al., 2013”) and ensure consistency elsewhere (e.g., L450).
- L471: Please change to “Howard et al. (2009) and Neumann et al. (2014)”
Citation: https://doi.org/10.5194/egusphere-2025-4608-EC1
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- 1
General comments:
The manuscript "Hydraulic Redistribution Decreases with Precipitation Magnitude 1 and Frequency in a Dryland Ecosystem: A Data-Model Fusion Approach" tested the incorporation of algorithms that represent hydraulic redistribution in a terrestrial ecosystem model for improved estimates of hydrological processes, which are also used to inform mechanistic understanding of hydraulic redistribution in a dryland ecosystem under different climate conditions. This is a timely and novel contribution because limited mechanistic understanding and limited modeling of hydraulic redistribution can lead to large uncertainty in estimates of hydrological processes. However, the presentation of the work can be improved to better illustrate the importance and implications of the study, and I have the following suggestions for consideration:
1. Consider starting the introduction with soil moisture, since most readers are more familiar with that topic. Introduce matric potential and other narrower concepts before discussing hydraulic redistribution and model details. The current introduction does not flow from broad to narrow and it uses terms such as water potential before those terms receive a clear definition later on.
2. Consider providing more justification for model improvements and give a more detailed review of existing models and their gaps to place this study in the current literature. Connect the detailed hypotheses more clearly to the modeling activities.
3. State quality control procedures for the soil moisture data, and give the exact depth and time step of the soil moisture records used for parameterization. Those details are currently unclear in the methods and can only be inferred from the results.
4. Consider using an antecedent precipitation index or a similar metric to represent cumulative precipitation effects, because precipitation often produces lagged responses in hydrological processes.
5. Consider reducing repetition between the discussion and the results. Also consider comparing this study with similar work, expanding mechanistic explanations where needed, and discussing future implications more thoroughly to strengthen the discussion section.
Specific comments:
L21: "Dryland" should be emphasized in the abstract.
L52-54: Is it necessary to have the lumped citations for this concept?
L59: Try to be more specific about how often HR is ignored in models. Also consider discussing this later in the introduction to make the logic flow better.
L83. Water potential was used previously before being introduced and defined here. See my suggestions about rearrangement.
L141. Is there quality control to remove data from the freezing point?
Table 1: What sources are used to inform the priors for the first six parameters?
L271: Is the "balanced results" expected because of the method used? If so is this more for methods than results?
Figure 2: State how many days or percentage of days are in the "dry" and "wet" periods, respectively. If the data size is very different they may influence the interpretation of error metrics.
L426. This paragraph seems more like results than discussion.
Technical comments:
L44: Remove the comma after "drylands".
L70. Fix the broken citation.
L132. Spell out abbreviations at their first appearances.
L135. "Storing" and "store" seem repetitive.
L417 and L446. The citation does not seem correct since it has the full name of an author.