Thank you for giving me the opportunity to review this article.

General comments:

The paper: "Evaluation of remote sensing and reanalysis-based precipitation products for agro-hydrological studies in semi-arid tropics of Tamil Nadu" addresses a very innovative topic, especially in the era of remote sensing where satellite products must be rigorously validated before any hydrological application. The study focuses on the reliability of these products in the semi-arid environment of Tamil Nadu.

"Hydrology and Earth System Sciences" is indeed an appropriate journal for the article.

Specific comments :

Line 87. When you mention GPM, are these IMERG data? GPM-IMERG is generally used.

Line 140. Are the rain gauges (69 rain gauges) used for validation included in the GPCC? If not, please specify.

In Table 2, IMERG-GPM can go up to hourly.

Why is there redundancy on the study regions in the methodology and study area in part 2?

Figure 1. It's a bit strange that the ground stations are very aligned. How is this possible? There are rain gauges in the mountains even though the area is supposed to be difficult to access.

Line 253. Doesn't this already introduce a large bias for the data used for validation? In other studies, "point-gridded" is used. Because the location of rain gauges most often does not coincide with gridded precipitation products (GPP) grid centroids, a second strategy was implemented: the point-gridded approach. In practice, a cell is delineated around each rain gauge (cell size of 0.04, 0.05, or 0.1°… depending on the GPP; Table. 2). Then, the rainfall value in those new cells was estimated as the area-weighted mean (max. 4) of the GPP grid cells overlapping with the new cell.

Results.

Grid scale/district scale method are not really mentioned in the methodology part.

Monsoon/Non-Monsoon not clear in the methodology.

Discussion

The first paragraph seems out of place and confuses the reader. Start directly by discussing the results.

Line 665. Why are ERA-5 Land and MSWEP performing better than others? Algorithms used? Reanalyzed products? Is this the case for other studies?

Line 687. From what rainfall intensity does ERA-5 Land struggle to detect?

Line 694 – 704. The entire paragraph should be dispatched into other paragraphs to properly explain the reasons for the performance of precipitation products compared to others."

Technical comments :

Line 266. What do all the terms mean? *Pi, …*

Line 283. Equation 7 not mentioned in the text.

Same for Eq. 8, 9, 10

Line 290. Equation 11 instead of Equation 7.

Equation 12 not mentioned in the text.

Line 302. Equation 13 instead of Equation 9.

Review all Equation numbers.

The authors present a validation exercise for different precipitation products in several regions of India.

The topic is suitable for HESS, but I have some methodological concerns that need to be addressed before publications

General comments:

Station to grid comparison: The authors assert that station to grid comparisons are difficult and conduct 'linear interpolation' from station to grid and from product grid to a common 0.1x0.1 degree comparison. I find the overall description of this vague and am also not entirely convinced that this solves the problem given that a lot of the variability within each grid-cell is due to topography and localized patterns that don't change linearly. I am also concerned/ confused that the authors ony consider stations within the district for the regional/ district comparison. Given the irregular shape additional stations outside the region should also be considered. 

Choice of regions: I might have missed that, but why are only some regions compared and not India as a whole? 

Reliance on Tables and many figures to compare: Apart from the Taylor diagrams, the authors have many tables and many figures with subplots that compare values between the products. It is very difficult to keep track of all of these comparisons. It would be good to think about a better way to integrate and present results. 

Specific comments:

Section 2.2. This section could probably be shortenened to focus on the most important information here. 

L153: Climate Data Guide, 2024 is not an appropriate citation for the datasets since the CDG is not the primary source of the data, but a guide for data users by UCAR. 

Figure 1: The regular gridded station distribution seems to be an error in the figure? 

L240: " For quality reasons, the years 2005 and 2010 were excluded from the present study" > Please explain

L253: "The interpolated 0.1degree station dataset was used as ground truth to evaluate all the other precipitation products" > See my general comment. Also, it would be really good if the authors could come up with a way to provide any kind of quality measure for this. For example, the authors could have reserved some stations for verification of that methodolody. Or conduct a leave-one-out cross-validation to assess how well the interpolated data reflects actual precipation in that location. 

L320: It would be good to also provide MAE as a percentage value of mean precipitation. 

Figure 2: I am a bit confused with this figure because alls of these lines seem to be perfectly straigt on a log-log plot and that is something that I would not have expected. It is also not possible to always see all lines. 

Figures 3-6: I was initailly confused by these figures. I guess the key message here would be, how the errors compare between monosson and non-monsoon season, but for that, the reader has to do their own math. 

Figure 8-11: These should contain the station locations to get a better sense of the interpolation.

L490: "ERA5-Land produced the closest approximation to the station data (Fig. 8). " > It would be good to back this up with some quantittative quality measure rather than a qualitative comparison. 

Section 5: This should start with a discussion of results including general patterns and limitations of the study. Then followed by 

The manuscript is highly relevant, as data scarcity is a major constraint in both hydrological and agricultural modeling. Providing reliable information about alternative data sources can aid modelers and support decision-makers. However, some sections of the manuscript need restructuring. Detailed comments are provided in the attached PDF. The manuscript can be accepted after minor revision.