The work presented by van Asselen et al. investigates the effects of subsurface infiltration systems in subsoil vertical dynamics. Five study sites in the Dutch peat meadows are considered where the installation of extensometers in parcels with and without Water Infiltration Systems (WIS) enables the continuous measurements of the vertical dynamics. Campaigns of spirit leveling are also employed to measure vertical movements of soil and compared to extensometers. The extensometers have different anchor depths to gain deformation of the soil at different levels.

The main outcome of the study is the correlation between water level fluctuations (from a previous study) and surface vertical movements, showing the capability of WIS to increase the phreatic groundwater level thus reducing seasonal land surface fluctuations.

The paper is well-written and well-organized. The concepts are clearly explained as well as the experimental setup.

I think minor revisions are necessary to clarify/improve/discuss the following points:

• As the author stated, there is a discrepancy between the spirit levelling and the extensometers. Dynamics from the extensometers are often lower than the dynamics measured by the spirit levelling. The authors state that this may be due to the deformation of the top 5 cm of soil which is not taken into account in the extensometers. I am not convinced this is the reason. Could be linked to the anchoring system of the extensometers? How is the horizontal plate anchored to the ground?
• The reader is expected to see the results of the layers deformation at different depths. However, the analysis of these data is postponed to a future study. However, I think this is useful information to understand and unravel the physical processes leading to the reduction of deformation with the WIS implementation.
• Is there any way to relate the soil lithology to the high/low result in decreasing the seasonal soil fluctuation? The lithological data available in the study have not been used to interpret the results.
• The results from observations of vertical land movements are presented in terms of elevation change. To understand the mechanisms driving the reduction of deformation (poroelastic effect, shrinkage/swelling), I think it could be beneficial to plot the deformations from the surface (-0.05 m) to the -0.8 m anchor. Which is the behavior in time? Example from Fig. 11 (ASD reference but also with AWIS). Why the Anchor 0.06 and 0.79 have an overlapping behavior until March 2022 (no deformation from 0.06 to 0.79)?

The manuscript explores the effects of subsurface water infiltration systems (WIS) on vertical soil movement and land subsidence across a collection of peat meadows. The study is data-driven and is based on very detailed experimental campaigns. The sites investigated cover a variety of settings typical of the targeted regional scenario. On one side, I do find the experimental study to be interesting and informative. On the other side, I do think the hydrological component of the study is still not fully developed, the experimental approach and techniques being mostly associated with geotechnical and soil mechanics areas. In this sense, I find the discussion to be focused mostly on the description of the results encapsulated in the figures rather than providing clear interpretations linking fundamental hydrological processes. Hence, I would suggest expanding this element, which is important for the Journal and its readership, and perhaps relegating some more technical and descriptive parts (e.g., local geological/sedimentological settings) to Appendices.

I also found the focus on climate change to support the importance/impact of the study to be too much highlighted and more oriented towards practical applications, rather than uncovering/analyzing fundamental hydrological processes. I would suggest diminishing the emphasis on such element and highlighting more clearly the importance and collocation of the study in the context of the current literature associated with fundamental processes. In essence, the Authors should be clear about whether their contribution is more application-oriented or geared toward providing enhanced understanding of hydrological processes and system functioning. Since I do see a lot of potential in this sense, I would then suggest de-emphasizing the application-oriented aspect.

In terms of quality of results, I did not find too many comments about data uncertainties. For example, I am assuming that groundwater levels are associated with some uncertainties. How are uncertainties associated with all of the data types analyzed impact on potential relationships between processes? Is there a way the Authors can provide some insights on these aspects?

Are some of the results (for example, the results depicted in Figure 14) to be expected? If so, is there a rationale underlying such expectation? Or do they come as unexpected? These are some examples of insights that Authors could provide to enhance the potential impact of their work.

Additionally, are these types of results typical of the context they Authors analyze? Or can they be somehow transferred to other settings?

The Authors attempt providing a fit to the data. Why do they expect a linear trend? Is this simply to identify a trend or can this be employed to do something more, e.g., to provide some interpretive model. In any case, when performing a model calibration, I assume the Authors have also evaluated uncertainties associated with parameter estimates. I was not able to see bounds of uncertainty around the plotted linear trends. I would suggest an in-depth analysis of this element together with a clarification of the actual purpose of providing a linear trend line. This is also in line with the statement made by the Authors regarding obtaining an improved quality fit with more data (the Authors refer to a manuscript which is still in the writing phase). Why should the reader be interested to what the Authors define a better fit? How do the Authors quantify the terminology better fit? Simply in terms of R2? Model parameter uncertainty? Model predictive power? The reader would benefit from this kind of discussion, in my view.

When discussing about temporal data series, did the Author observe any trend/drift associated with measurement accuracy? Any induced correlation among data?

On these bases, I would suggest a series of revisions that I would define as ranging between moderate and major.