We would like to thank Dr Bo Huang for his helpful comments on our manuscript. Below please find responses to each comment, which we hope help clarify some of the points raised.

Here we will provide responses to points 4-7 raised by Dr Huang, points 1-3 are addressed in the attached supplement as the internal HESS response platform does not allow for easy presentation of equations needed to address the issues raised. 

4. Figures 7 and 9 present soil moisture distributions, but the frequency ranges differ significantly between the two. What explains this discrepancy? Additionally, Figure 9 is described as including green and red dashed lines in the caption, but these are not visible in the figure as provided. Please resolve this inconsistency.

Discrepancies between soil moisture distributions reflect soil properties at each site, total rainfall, rainfall characteristics, and PET. For example, at our more arid sites (Sites A and HA) soil moisture is limited to 30-50% saturation, whereas Sites SA and HU see soil moisture saturations reach greater than 80%. This is likely due to the higher total rainfall and lower PET at these sites compared to our more arid locations. However, there are also differences in soil moisture distributions between Site A and Site HA, with soil moisture on average being higher at our hyper-arid site. This may appear counter-intuitive given these is our most arid location, but soil moisture is also sensitive to root water uptake. At Site A shrubs are present throughout the profile, and take up 12-21% of infiltration, while Site HA is bare soil. We have also shown that soil moisture is sensitive to rainfall characteristics, at Site HA more rainfall is delivered via heavy events (30-82% vs 12-49%) and the magnitude of extreme (99^th percentile) rainfall is also higher (17.9 vs 11.2 mm/h). You can see the deeper penetration of wetting fronts at Site HA in fig 8.

Apologies - the caption of Figure 9 needs updating. The correct caption should read: Soil Moisture Distributions with Wilting Points. Modelled distribution of soil moisture at 1.2 mbgl at Site SA (a) and A (b) using P25 (blue) and CP4A (red) rainfall and PET. The dashed orange line represents the wilting point range for Acacia shrubs, based on taking the upper and lower Feddes’ parameters given in Table A2 (wilting point = P2H) (Sela et al, 2015).

5. Figure 10 is labeled as depicting rainfall and PET but does not include these variables in the presented panels. Please revise the caption to accurately reflect the displayed data.Figure 10 is labeled as depicting rainfall and PET but does not include these variables in the presented panels. Please revise the caption to accurately reflect the displayed data.

We apologise for this error. The plot previously included rainfall and PET but they were removed as it made visualising the other variables more challenging. Cumulative rainfall and PET are given in Table 1. Additionally, infiltration largely follows cumulative rainfall, with differences between P25 and CP4A Hydrus simulations largely due to the infiltration partitioning between different stores. If it would improve clarity, we can add rainfall and PET to Figure 10.

If rainfall and PET is removed, the Figure 10 caption will read: Cumulative Infiltration Runoff, Evaporation, Transpiration, and Deep Infiltration. Modelled components of the water balance using CP4A (solid lines) and P25 (dashed lines) rainfall/PET as input for Hydrus 1-D. Plots show the 500 infiltration (a), surface run-off (b), bottom drainage (c), evapotranspiration (d), evaporation (e), and transpiration (f) at our semi-arid, arid, and hyper-arid locations.

6. The symbol “θs” is used extensively without definition, which may confuse readers unfamiliar with soil moisture notation. Please explicitly define “θs” or use a reader friendly abbreviation.

On first use in the manuscript θs is defined – please see line 419: Fig. 7a-d show histograms of depth-integrated θs (% soil saturation in entire 300 cm of the soil profile). But to increase clarity we can more explicitly define θs in 2.4.3 (Hydrological Model Set Up, Data, and Sensitivity). The revised text could read: Throughout this manuscript we will express soil moisture as a saturation percentage (given the symbol θs), which reflects the proportion of pore spaces that are filled with water relative to if all pore space is saturated (eg 100% means all pore space is filled with water, 0% mean all pores are filled with air). Pore space differs by soil properties hence a relative metric is used to compare our hydrological sites.

7. Duplicate scenario name in Table A1, consider to re-name these scenarios.

Table A1 details the soil parameters used in our Hydrus simulations, to establish whether relative biases in hydrological outcomes when driving Hydrus using CP4A/P25 remained regardless of soil parameters, we utilised three soil parameters sets (as stated in section 2.4.3 and Appendix A).

These parameters were based calculated using the Genuchten-Mualem (Van Genuchten, 1980) equations with soil texture values taken from the iSDAsoil database (Hengl et al, 2021). iSDA provides a lower and upper bound of sand, silt, and clay percentages, our default (‘def’) parameter set was estimated using the mid-point of these lower and upper bounds. To create our low (‘lowK’) and high hydraulic conductivity (‘highK’) soil parameters, we used the lower and upper bound of the sand percentage respectively. We then proportionally adjusted the silt and clay percentage to ensure values equalled 100. We used the same labelling for each site as they follow the same methodology and are designed to be comparable across sites. Of course, soil parameters will differ based on the relative proportion of sand, silt, and clay at each site.

References

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Singer, M.B., Asfaw, D.T., Rosolem, R., Cuthbert, M.O., Miralles, D.G., MacLeod, D., Quichimbo, E.A. and Michaelides, K., 2021. Hourly potential evapotranspiration at 0.1 resolution for the global land surface from 1981-present. Scientific Data, 8(1), p.224.

Zomer, R., Trabucco, A., van Straaten, O., and Bossio, D.: Carbon, land and water: A global analysis of the hydrologic dimensions of climate change mitigation through afforestation/reforestation, IWMI, Vol. 101, 2007.

Mirzabaev, A., et al.: Desertification, in: Climate Change and Land: an IPCC special report on climate change, desertification, land 880 degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, IPCC, 2019.

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We would like to thank Dr Gómez-Delgado for his very detailed and thoughtful review. His comments are very helpful and we are glad to have the opportunity to elaborate on some of the issues raised. Please find attached our response to his very detailed review. We are more than happy to provide any further clarifications or details where required.