the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Feb 2024
Effects of changes in climatic conditions on soil water storage patterns
Abstract. The soil water storage (SWS) defines crop productivity of a soil and varies under differing climatic conditions. Pattern identification and quantification of these variations remains difficult due to the non-linear behaviour of SWS changes over time.
We hypothesize that these patterns can be revealed by applying wavelet analysis to an eight-year time series of SWS, precipitation (P) and actual evapotranspiration (ETa) in similar soils of lysimeters in a colder and drier location and a warmer and wetter location within Germany. Correlations between SWS, P and ETa at these sites might reveal the influence of altered climatic conditions but also from subsequent wet and dry years on SWS changes.
We found that wet and dry years exerted influence on SWS changes by leading to faster or slower response times of SWS changes to precipitation in respect to normal years. Extreme precipitation events were visible in SWS and P wavelet spectra. Time shifts in correlations between ETa and SWS became smaller at the wetter and warmer site over time in comparison to the cooler and drier site where they stayed constant. This could be attributed to an earlier onset of the vegetation period over the years and thus to an earlier ETa peak every year and reflects the direct impact of changing climate on soil water budget parameters.
Long-term observations (>30 years) might reveal similar time shifts for a drier climate. Analysis of the SWS capacity could provide information on how different climatic conditions affect the long-term storage behaviour of soils.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-118', Anonymous Referee #1, 12 Mar 2024
This is a very interesting study to use a wavelet coherency method to show how climate conditions may affect the soil water storage patterns. However, it can be improved before being accepted for publication. My comments are below:
Line 84-112: it’s good to see the brief summary of methods used for analyzing time series of soil water. However, in terms of wavelet method, I think it worths mentioning the extension of wavelet coherence from two variables to multiple variables, including multiple wavelet coherence (doi:10.5194/hess-20-3183-2016) and partial wavelet coherency (https://doi.org/10.5194/hess-25-321-2021).
Line 113: capitalize “w” in “wavelet” please.
Line 170: I might have missed how did you treat the three replicates when you analyzed the data using wavelet? Did you do wavelet coherency for each lysimeter or for the mean values of the three lysimeters.
Line 204-205: I would detail the exact depth of each horizon for each lysimeter. How did the variations in the thickness of various horizons below the Ap horizon affect the SWS and associated correlations with climate (e.g., P, and Eta)?
Line 208: why not keep exact the same. How can you exclude that the different crops in 2014 would not affect the associated relationships?
Line 245: if you are interested in the real correlation between two variables, partial wavelet coherency mentioned above may be a better option. This at least can be discussed in the conclusion.
Line 296: I don’t think that band is green, more like bright sky blue
Line 301, 304, 305: please specify which smaller scales
Line 340: can’t see the small peak in Fig 4b. Do you mean Fig 4d?
Line 350: I did not see the description of rainfall pattern. It shows no annual cycle but big peak at a few hours’ time scales, and this is more obvious at the drier site. Can you please add this result in?
Line 396: Twelve
Line 451-454: can you please explain how ETa responds to the SWS changes after more than 100 days? ETa should not respond to SWS change in a very short time? I know this is related to different time scale, but it seems really hard to understand from the hydrological process point of view. You may need to clarify here.
Line 467: 136 h or day?
Citation: https://doi.org/10.5194/egusphere-2024-118-RC1 - AC1: 'Reply on RC1', Annelie Ehrhardt, 30 Apr 2024
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RC2: 'Comment on egusphere-2024-118', Anonymous Referee #2, 21 Mar 2024
Comments on” Effects of changes in climatic conditions on soil water storage patterns”, by Ehrhardt et al.
General comments: Soil water storage (SWS) is an important indicator for revealing the environmental changes effects on the soil-water-atmosphere continuum. Temporal pattern detection and analysis of these changes is helpful to understand long-term impacts of droughts on plant and crop productivity. Wavelet coherence analysis of SWS components measured by lysimeters were conducted for two sites in the paper, which is helpful to the better understanding of their relationships. In general, this paper proposed an interesting study for soil water storage patterns and their shifts affected by climatic conditions. I have some concerns which is needed to be solved.
Detailed comments:
- This part can be better organized. For example, you mentioned that “Pattern identification and quantification of these variations remains difficult”, you mean the variations in SWS? if so, why not just analyze the measured SWS? Why you believe “these patterns can be revealed by applying wavelet analysis”? What inspired you to conduct such an analysis? Please clarify.
- Also, you concluded in Abstract that ”wet and dry years exerted influence on SWS changes by leading to faster or slower response times of SWS changes to precipitation in respect to normal years.” But why? does that caused by extreme precipitation events? why you believe “Long-term observations (>30 years) might reveal similar time shifts for a drier climate” ?
- I found that the logic in some paragraphs is hard to follow, there are too much plain concepts and descriptions. For example, the paragraph talking about the methods of deriving reoccurring patterns in time series of SWS, all of these methods were fairly detailed in other researches using time series analysis. I believe the advantages of wavelet coherency analysis and the reason for taking the method in this study should be better highlighted.
- In line 77, you mentioned “the effect of a change in climatic conditions on SWS has scarcely been reported to date.” But in lines 57-65, several papers were cited, please explain more.
- Line 113, capitalize the first letter.
- Lines 128-129. The authors mentioned: “When analyzing the effect of climate variability on SWS it is plausible to compare time series of similar soils under different climatic conditions”, why similar soils? In my opinion, soil is also part of results in a given climatic condition, so what is the practical meaning of this experiment? Needing further explain.
- Lines 157-158. you hypothesized that “similar to grassland soils the phase shift between ETa and SWS is smaller under drier as compared to wetter conditions”. but why? As we know the crop land has totally different hydrological characteristics from grasslands, why you believe the SWS variation patterns of them are similar?
- Figure 1, scales of the two enlarged maps are obviously different, and unify scales are recommended, latitude and longitude also need to be included. Besides, the text was too small and not easy to read.
- Explanatory text in Figure 1 was not accurate enough (only mentioned the average monthly precipitation (P) sums and average monthly temperature) and thus need to further clarified.
- How about the influence of amount of precipitation during the vegetation period as your record in Table 2?
- Section 2.2, as you said in line 195, “the average monthly temperatures and precipitation were obtained from automated weather stations”, and in line 218, “Missing data were gap-filled on aggregated hourly basis within the post-processing scheme”, considering the 1-min resolution collection in lysimeters, how did you ensure the accuracy of precipitation data post-processed？Are there any uncertainties from this processing?
- Equation 1, P was from automated weather stations, Qnet from lysimeters, but where did ETa come from? You didn’t give explicit data source.
- Figure 2, legend “dd” and “sel”, while “DD” and “SE” in Figure 8, it is better to be consistent.
- In line 294, “They related these fluctuations to seasonal variations due to water consumption by plants (transpiration) and soil evaporation.” Is that the same reason for the changes reported in your study?
- Line 332, “the periodicities at the daily scale were significant throughout the vegetation period at both sites”, in the current drawing forms, the daily scale periodicities were not obvious to obtain.
- Line 339, “In contrast to Dedelow, a small peak around a period of approximately 16500 hours was found in Selhausen”, similar to comment 8, not obviously.
- As you said in line 486, “the end of the vegetation period for crops is determined by the harvest and not by the actual drop in temperatures”, while calculations were executed according to Ernst and Loeper (1976) with hourly temperature data in Figure 8, please clarify.
- Most importantly, the study areas in your paper were located in Selhausen (51°52’7’’N, 6°26’58’’E) and Dedelow (53°23’2’’N, 13°47’11’’E), is the climatic discrepancy between them significant enough to call them “different climatic conditions” as section 3.1 and your title？
- The tables need to be better organized.
- Discussion is not sufficient in section 3.2. The reason for time shifts is lacking, and the implication of these results needs be illustrated better.
Citation: https://doi.org/10.5194/egusphere-2024-118-RC2 - AC2: 'Reply on RC2', Annelie Ehrhardt, 30 Apr 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-118', Anonymous Referee #1, 12 Mar 2024
This is a very interesting study to use a wavelet coherency method to show how climate conditions may affect the soil water storage patterns. However, it can be improved before being accepted for publication. My comments are below:
Line 84-112: it’s good to see the brief summary of methods used for analyzing time series of soil water. However, in terms of wavelet method, I think it worths mentioning the extension of wavelet coherence from two variables to multiple variables, including multiple wavelet coherence (doi:10.5194/hess-20-3183-2016) and partial wavelet coherency (https://doi.org/10.5194/hess-25-321-2021).
Line 113: capitalize “w” in “wavelet” please.
Line 170: I might have missed how did you treat the three replicates when you analyzed the data using wavelet? Did you do wavelet coherency for each lysimeter or for the mean values of the three lysimeters.
Line 204-205: I would detail the exact depth of each horizon for each lysimeter. How did the variations in the thickness of various horizons below the Ap horizon affect the SWS and associated correlations with climate (e.g., P, and Eta)?
Line 208: why not keep exact the same. How can you exclude that the different crops in 2014 would not affect the associated relationships?
Line 245: if you are interested in the real correlation between two variables, partial wavelet coherency mentioned above may be a better option. This at least can be discussed in the conclusion.
Line 296: I don’t think that band is green, more like bright sky blue
Line 301, 304, 305: please specify which smaller scales
Line 340: can’t see the small peak in Fig 4b. Do you mean Fig 4d?
Line 350: I did not see the description of rainfall pattern. It shows no annual cycle but big peak at a few hours’ time scales, and this is more obvious at the drier site. Can you please add this result in?
Line 396: Twelve
Line 451-454: can you please explain how ETa responds to the SWS changes after more than 100 days? ETa should not respond to SWS change in a very short time? I know this is related to different time scale, but it seems really hard to understand from the hydrological process point of view. You may need to clarify here.
Line 467: 136 h or day?
Citation: https://doi.org/10.5194/egusphere-2024-118-RC1 - AC1: 'Reply on RC1', Annelie Ehrhardt, 30 Apr 2024
-
RC2: 'Comment on egusphere-2024-118', Anonymous Referee #2, 21 Mar 2024
Comments on” Effects of changes in climatic conditions on soil water storage patterns”, by Ehrhardt et al.
General comments: Soil water storage (SWS) is an important indicator for revealing the environmental changes effects on the soil-water-atmosphere continuum. Temporal pattern detection and analysis of these changes is helpful to understand long-term impacts of droughts on plant and crop productivity. Wavelet coherence analysis of SWS components measured by lysimeters were conducted for two sites in the paper, which is helpful to the better understanding of their relationships. In general, this paper proposed an interesting study for soil water storage patterns and their shifts affected by climatic conditions. I have some concerns which is needed to be solved.
Detailed comments:
- This part can be better organized. For example, you mentioned that “Pattern identification and quantification of these variations remains difficult”, you mean the variations in SWS? if so, why not just analyze the measured SWS? Why you believe “these patterns can be revealed by applying wavelet analysis”? What inspired you to conduct such an analysis? Please clarify.
- Also, you concluded in Abstract that ”wet and dry years exerted influence on SWS changes by leading to faster or slower response times of SWS changes to precipitation in respect to normal years.” But why? does that caused by extreme precipitation events? why you believe “Long-term observations (>30 years) might reveal similar time shifts for a drier climate” ?
- I found that the logic in some paragraphs is hard to follow, there are too much plain concepts and descriptions. For example, the paragraph talking about the methods of deriving reoccurring patterns in time series of SWS, all of these methods were fairly detailed in other researches using time series analysis. I believe the advantages of wavelet coherency analysis and the reason for taking the method in this study should be better highlighted.
- In line 77, you mentioned “the effect of a change in climatic conditions on SWS has scarcely been reported to date.” But in lines 57-65, several papers were cited, please explain more.
- Line 113, capitalize the first letter.
- Lines 128-129. The authors mentioned: “When analyzing the effect of climate variability on SWS it is plausible to compare time series of similar soils under different climatic conditions”, why similar soils? In my opinion, soil is also part of results in a given climatic condition, so what is the practical meaning of this experiment? Needing further explain.
- Lines 157-158. you hypothesized that “similar to grassland soils the phase shift between ETa and SWS is smaller under drier as compared to wetter conditions”. but why? As we know the crop land has totally different hydrological characteristics from grasslands, why you believe the SWS variation patterns of them are similar?
- Figure 1, scales of the two enlarged maps are obviously different, and unify scales are recommended, latitude and longitude also need to be included. Besides, the text was too small and not easy to read.
- Explanatory text in Figure 1 was not accurate enough (only mentioned the average monthly precipitation (P) sums and average monthly temperature) and thus need to further clarified.
- How about the influence of amount of precipitation during the vegetation period as your record in Table 2?
- Section 2.2, as you said in line 195, “the average monthly temperatures and precipitation were obtained from automated weather stations”, and in line 218, “Missing data were gap-filled on aggregated hourly basis within the post-processing scheme”, considering the 1-min resolution collection in lysimeters, how did you ensure the accuracy of precipitation data post-processed？Are there any uncertainties from this processing?
- Equation 1, P was from automated weather stations, Qnet from lysimeters, but where did ETa come from? You didn’t give explicit data source.
- Figure 2, legend “dd” and “sel”, while “DD” and “SE” in Figure 8, it is better to be consistent.
- In line 294, “They related these fluctuations to seasonal variations due to water consumption by plants (transpiration) and soil evaporation.” Is that the same reason for the changes reported in your study?
- Line 332, “the periodicities at the daily scale were significant throughout the vegetation period at both sites”, in the current drawing forms, the daily scale periodicities were not obvious to obtain.
- Line 339, “In contrast to Dedelow, a small peak around a period of approximately 16500 hours was found in Selhausen”, similar to comment 8, not obviously.
- As you said in line 486, “the end of the vegetation period for crops is determined by the harvest and not by the actual drop in temperatures”, while calculations were executed according to Ernst and Loeper (1976) with hourly temperature data in Figure 8, please clarify.
- Most importantly, the study areas in your paper were located in Selhausen (51°52’7’’N, 6°26’58’’E) and Dedelow (53°23’2’’N, 13°47’11’’E), is the climatic discrepancy between them significant enough to call them “different climatic conditions” as section 3.1 and your title？
- The tables need to be better organized.
- Discussion is not sufficient in section 3.2. The reason for time shifts is lacking, and the implication of these results needs be illustrated better.
Citation: https://doi.org/10.5194/egusphere-2024-118-RC2 - AC2: 'Reply on RC2', Annelie Ehrhardt, 30 Apr 2024
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Annelie Ehrhardt
Jannis S. Groh
Horst H. Gerke
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2659 KB) - Metadata XML