Trend Analyses of Percolation of Atmospheric Precipitation Due to Climate Change: Case Study in Lithuania
Round 1
Reviewer 1 Report
This manuscript analyzed the trend of percolation of atmospheric precipitation in Lithuania. Overall, the results are clear and the increase in percolation is mainly due to changes in air temperature (especially in winter). I suggest that the manuscript should be presented more concisely. The main comments are as follows:
1. Line 31: The authors should declare more about the reasonability and representativeness of the data. For example, the lysimetric data were collected from the lysimetric equipment with a surface area of 1.75 m2, how many lysimetric equipment were used? The precipitation amount was calculated according to the data of Vilnius Meteorological Station, is there any other meteorological station?
2. Line 156: Error! Reference source not found.
3. Line 168: … was 34 mm higher at 686 mm …
4. Line 209: As described in the text, relative Frequency (RF) was calculated using the formula RF = f / n, where f is the number of times the data occurred in an observation, n − the total number of events occurring in a given observation. So, is percolation most likely to occur or fail in June, with the relative frequency of percolation equaling to 0.70?
5. How about the change of land use of Lithuania in the past three decades, as you described that '... when part of the agricultural land is not covered by vegetation (Line 445)'. Does the area of agricultural land increase or not in Lithuania?
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
The study presented in the manuscript analyzes long-term lysimetric data in eastern Lithuania in order to identify trends in changes of precipitation percolation and investigates potential causes. The study is interesting and provides meaningful results and conclusions.
Although the manuscript is well written and it is easy to follow, it could benefit by:
1) improving the Abstract. Sentence “data of periods 1989-1998 and 2011-2020 was used” should be changed because these were not only data used in the study. It should be clarified that data from these periods were compared, but longer period data were analyzed (1987-2022), as stated in the previous sentence. Data in sentence “Since 1961... ” are obsolete for the abstract and inconsistent with other findings across the manuscript (the period “since 1961” is not precise enough and does not match with the studied period). I recommend stating only mean annual temperature increase for the analyzed periods and general comment on changing temperatures across the seasons. For precipitation in the following sentence, please also add comment on seasonal precipitation changes, since it is the way the changes in percolation are presented. Information on changes in precipitation intensity (frequency of dry days and frequency of heavy precipitation days) would also be valuable here.
2) adding the monthly analysis of the precipitation intensity, which is also important for the percolation. It could be a simple change in mean monthly numbers of days without precipitation (less than 1 mm) and number of days with heavy precipitation (above some threshold which is determined by climate characteristics).
Minor comments:
Lines 17 and 19: February is found to be a month with decreasing mean temperature, which contradicts this sentence.
Line 20: Sentence is not clear enough. Maybe it should be “melting of snow in a shorter period”?
Lines 52-54: In the sentence “Compared to...” spring temperature increase is stated twice with different numbers (1.6 and 1.4°C), please correct.
Sentence in lines 54-57 could be written more clearly and maybe separated into two sentences.
Across the Results references for Figures and Tables are missing.
Figure 1: please add numbers to the y-axis
Lines 166/167: in the first part of the sentence periods 1961-1990 and 1991-2020 are stated, but are not used in the analysis. Please correct.
Table 1: How was the mean temperature calculated? Please check the calculation for January at least. It is unusual to have an increase in minimum (+1°C) and maximum temperature (+0.6°C), but at the same time decrease in mean temperature (-0.7°C) – numbers are from Table 1 for January.
Author Response
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Author Response File: Author Response.docx
