the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Aug 2023
Agronomic and edaphic drought relations. A semiarid rangeland case
Abstract. The dynamic of rangelands results from complex interactions between vegetation, soil, climate, and human activity. In arid and semiarid areas, rainfall coefficients of variability are over 30 %. This scenario makes rangeland's condition challenging to monitor, and degradation assessment should be carefully considered to study grazing pressures. In the present work, we study the interaction of vegetation and soil moisture in arid rangelands, using vegetation and soil moisture indexes. We aim to study the feasibility of using water soil moisture (soil drought) as a warning index for vegetation drought. An arid agricultural region in the southeast of Spain, in the province of Almeria (Los Vélez), was selected for this study.
MODIS images, with 250 and 500 m spatial resolution, from 2002 to 2019, were acquired to calculate the anomaly (Z-score) for the Vegetation Condition Index (ZVCI) and the Water Condition Index (ZWCI). ZVCI was calculated using the Normalised Difference Vegetation Index (NDVI). Soil moisture component (W) was obtained using the Optical Trapezoid Model (OPTRAM). The probability of coincidence of their negative anomalies between ZVCI and ZWCI, with lags between them, was calculated. The results show that for specific seasons, the anomaly of the water content index had a strong probability of informing in advance where the negative anomaly of VCI will decrease. Soil water content and vegetation indices show more similar dynamics in the months with lower temperatures (from autumn to spring). In these months, given the low temperatures, precipitation leads the vegetation growth. In the following months, water availability depends on evapotranspiration and vegetation type as the temperature rises and the precipitation falls. The stronger relationship between precipitation and vegetation from autumn to the beginning of spring is reflected in the feasibility of ZWCI to aid the prediction of vegetation index anomalies. During these months, using ZWCI and ZVCI as warning indices are possible for two Spanish semiarid rangeland areas: Los Vélez (Almería) and Bajo Aragón (Teruel). Particularly, November to January showed an average increase of 20–30 % in the predictability of vegetation index anomalies. We find other periods of relevant increment in the predictability as March and April for Los Vélez, and July, August and September for Bajo Aragón.
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CC1: 'Comment on nhess-2023-145', Borko Stosic, 15 Nov 2023
In this work the authors explore the feasibility of using water soil moisture (soil drought) as a warning index for vegetation drought. To this end they perform a study for two arid regions in Spain, for the period 2002-2019, with a 10-day temporal ad 250-500m spatial resolution. The conditional probability of the normalized Vegetation Condition Index (ZVCI) and Water Condition Index (ZWCI) with a 40-day lag is used to demonstrate that ZWCI can aid the prediction of vegetation anomalies ZVCI, particularly in the cooler months when vegetation growth is mainly driven by precipitation.
The paper is clear and well written, it employs simple and sound methodology, and I believe that it represents an important contribution to the field of study. Apart from correcting a few typos e.g. “(Appendix 1- PONER ALGO MAS?)” on line 110, I would suggest to the authors to increase the figure labels as they are very hard to read.
Regarding the fact that both temperature and precipitation drive vegetation growth (as discussed along the paper), is there a way that temperature anomalies could also be taken into account explicitly in such a study?
Citation: https://doi.org/10.5194/nhess-2023-145-CC1 -
AC4: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
Citation: https://doi.org/10.5194/nhess-2023-145-AC4 -
AC5: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC6: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC4: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
-
CC2: 'Comment on nhess-2023-145', Jose Luis Valencia, 17 Nov 2023
- In line 110, there is extra text. "Anexo 1- poner algo mas?" . You need to eliminate it
- In Figure 2, it is mentioned that it is used for the model in Equation 12 to estimate parameters. I believe it should say Equation 3.
- What is the motivation for reducing the value of w to 0-1 by replacing values of w above 1? If later a index (WCI that will range between 0 and 1) is used?
- Where does Equation 3 come from (there is no reference, although it seems that it could be found in Sadaghi 2017 from Figure 2)? I think either a reference should be provided, or the foundation and interpretation of this index should be explained, or both.
- In my opinion, the explanation of Equation 6 is unnecessary; I believe conditional probability should be well-known to everyone.
- In line 173, it is indicated how the phases are generated. To impose the limits of these phases, it seems like the median is used, although it is not explicitly stated. In my view, representing it with a Box-Cox diagram would allow a discussion of these points since the third quartile would suggest that phase 2 begins some weeks later, especially in Los Velez. Wouldn't it be clearer to exclusively represent a line connecting the medians of each ten-day period for greater clarity?
- Figure 4 is not clear, especially regarding rainfall. It is difficult to distinguish those "abundant rains" in phase 3 (at least when comparing them with phase 2 where the extreme points are higher). There is also a contradiction stated in lines 188-189 regarding the explanation of Figure 4, as it indicates that there is more rain in phase 2.
- I suggest using more distinct colors to better distinguish the series in Figure 5 (for example, red and blue).
- In line 192, it is mentioned that there is a smoother profile of the ZVCI series; perhaps a cause explaining this should be suggested.
- Although providing probabilities in percentages may not be the most appropriate, it is understandable given the calculation method. However, I am more in favor of indicating the value between 0 and 1 when discussing probabilities.
- Mentioning expected probabilities on standardized data could be considered. For example, if the indices followed normal distributions (which may not be the case), for ZWCI and ZVCI, the probabilities would be P(Index<-0.5)=0.309, P(Index<-0.7)=0.242, and P(Index<-0.1)=0.159.
- The comments about the probability of an index being below the threshold of -0.7 being lower than being below -0.5 seem unnecessary. This is obvious: P(Z<-0.5)=P(Z<-0.7)+P(-0.7<=Z<-0.5) (the same for Z<-1). In any case, the greater the difference, the higher the probability that the index is between [-0.7, -0.5).
- In line 215, why is there now a condition for the threshold of -0.3? I don't understand if there is justification or at least it is not explained.
- In Figures 8, 9, 10, 11, P(VCI<-0.7) is stated. Obviously, this probability is always 0 because the VCI value is in the interval (0,1). It should be P(ZVCI<-0.7).
- In the paragraph between lines 224 and 230, there is no reference to the possibility that the correlation could be negative in the summer months (from late May to September). Additionally, the term "significantly" is used, but based on what criterion or test is it significant?
- In lines 238 and 239, it is said, "as with Los Velez, the lag-4 conditional probabilities for the threshold -1.0 remain above the base probability." It seems incorrect to me; in Los Velez, these probabilities for the summer months were below.
- In line 241, it is said that the probability with a 4-period delay is higher than the base probability, but this also occurs for the probability without a delay.
- I wonder why, with two time series, a transfer function model is not carried out, identifying cross-correlations to determine the delay that best explains one series in terms of the other. It may have been done, but it is not indicated in the article. Why have you chosen 4 lag?
Citation: https://doi.org/10.5194/nhess-2023-145-CC2 -
AC3: 'Reply on CC2', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
RC1: 'Comment on nhess-2023-145', Anonymous Referee #1, 06 Dec 2023
Specific Comments
Ln 14. Can you explain why you are using the term “water soil moisture” in the following phrase “We aim to study the feasibility of using water soil moisture (soil drought)”
Ln 18. Please choose between using ZVCI or ZVCI. You should keep one of those and don’t change through the manuscript.
Ln 22. VCI = ZVCI? Please be consistent with acronyms throughout the manuscript.
English comments
Ln 24. Precipitation leads TO vegetation growth. OR precipitation grows vegetation.
Ln 37. Please use “soil water content”. Please modify all the rest by yourself.
Ln 46. I think a reference is needed for the types of droughts.
Ln 73. In line 46 you mention four types of droughts. Now, you are using a “new term,” edaphic drought. Why is it not mentioned before?.
Ln 101. They use using?. Please correct.
Ln 100. It is not clear why they choose those pixels.
Ln 110. (Appendix 1- PONER ALGO MAS?). This is not the first one, I think this research paper needs to be resubmitted. There are too many typos; see above.
Ln 115. You defined the vegetation condition index with ZVCI in the abstract and have now changed it to VCI.
Ln 118. Eq 1 is dependent on NDVI and Eq. 3 is dependent on NDVI. Do you think this is tricky if you are looking for a correlation between them (WCI and VCI)?
Ln 132. What does the soil water content of one mean?. Is it possible to have soil water content of 0?
Ln 144. Which anomalies? I think it is explained below. Please correct the entire paragraph.
Ln. 151 See acronyms.
Ln 153. Instead of A or B, you should use the acronyms presented before.
Final comments.
Why do you not use a method to evaluate the precision of W computation? Measuring surface soil water content is not difficult. Section 2.4 is not well written and is essential for the manuscript. The methodology does not specify how to verify the results. The methodology is only based on indexes previously published; where is the novelty? On the conditional probability? The manuscript seems to be written carelessly. I suggest rejection
Citation: https://doi.org/10.5194/nhess-2023-145-RC1 -
AC1: 'Reply on RC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC1: 'Reply on RC1', Ana Maria Tarquis, 25 Jan 2024
-
RC2: 'Comment on nhess-2023-145', Anonymous Referee #2, 07 Dec 2023
General comments:
The paper intended to analyze the relationship between agronomic and edaphic drought in a semiarid rangeland area. The use of several remote sensing indexes is the primary source of data to provide this analysis. The paper's general idea is valuable but not novel as vast literature uses this kind of tool to analyze such relationships at different scales and under different biomes. The main novelty of the paper is perhaps not fully addressed in the introduction.
The causal mechanisms behind the soil and vegetation drought expression are not fully addressed, probably because of the limitation of the pixel resolution that restricts the specific vegetation identifications and the lack of soil hydraulic properties or soil moisture spatial information. No ground data is used, severely limiting the robustness of the remote sensing analysis. Maybe the general idea and the title of the manuscript should be more related to comparing the dynamics of physically different remote sensing drought indexes to detect agricultural drought, which is more related to objective 2. If so, the study's outreach is limited but valuable, maybe for a letter paper.
In addition, the documents presented several grammar, format, and presentation flaws that made it difficult to follow some essential ideas.
All these reasons support the decision to reject this paper in its current form. However, I put some specific comments to enhance the document for a possible resubmission.
Abstract: The justification of the problem is not well accomplished; why does the 30% precipitation variability represent a challenge? What is the relation between degradation and rainfall variability?
Introduction:
References are too old; I suggest keeping only references for the last 10 years. At least, it was a singular paper. The manuscript requires an extensive English revision before being resubmitted, and it is hard to follow the ideas in this current form. I suggest including a more comprehensive explanation and justification of how agronomic and edaphic drought relations can be propagated. The literature remains poor; please add more relevant and actual papers on the subject. Also, an explanation of what details about the OPTRAM index should be included. Why could this index detect something different from the NDVI?
It is unclear and not correctly justified why using an arid rangeland could be singular to study these relationships.
The definition of edaphic drought is missing.
Methods:
The rationale for choosing the different remote sensing indexes is completely missing. You can use a diagram to support the text to better explain your procedure's logic.
Scientific names should be put in italics.
A description of root depths and the hydraulic properties of soils should be convenient.
The climate description is poor; please use an international reference based on the Koeppen classification.
The explanation of pixel selection is very unclear; please explain how you merge the information better.
You must put the complete names of the MODIS products used in the study, for instance the NDVI product. How did you deal with clouds? Do you use the Quality Assessment data?
Do you resample the NDVI to the STR resolution or vice versa? please clarify.
A better map of the study area is necessary to understand the context better, please improve the one chosen. A climograph could be added, for example, and the land cover present in the selected area.
Results:
The results are attractive and are the main strength of the paper, however, they are difficult to connect to the main objectives. Maybe you could enhance the idea of early detection of a hazard.
The Discussion sections reflect the poor level of analysis displayed in the document, with only three references to confront the results.
Specifics comments:
Line 11: To communicate the idea of precipitation variability, I suggest using another metric or explaining better what you mean by 30% of the coefficient of variability.
Line 13: what is water soil moisture? Please use a widely used terminology.
Line 17: Please explain why you selected two MODIS resolutions.
Line 21. What specific season?
Line 34, I suggest explaining that plant growth can be related to NDVI. The Normalized Difference Vegetation Index must be described with its entire name.
Line 35 Farrat et al., 1994 studied the relationship between NDVI, rainfall, and soil moisture. This is a very old reference, please provide more actual references.
Line 37 what are the main findings of the papers you referred to?
Line 39 and 40: is very difficult to follow the idea, strong correlation of what? The soil moisture between soil surface and lower layers?
Line 42. Please check English grammar.
Lines 46 to 49 please use references to support the drought definitions.
Citation: https://doi.org/10.5194/nhess-2023-145-RC2 -
AC2: 'Reply on RC2', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC2: 'Reply on RC2', Ana Maria Tarquis, 25 Jan 2024
Status: closed
-
CC1: 'Comment on nhess-2023-145', Borko Stosic, 15 Nov 2023
In this work the authors explore the feasibility of using water soil moisture (soil drought) as a warning index for vegetation drought. To this end they perform a study for two arid regions in Spain, for the period 2002-2019, with a 10-day temporal ad 250-500m spatial resolution. The conditional probability of the normalized Vegetation Condition Index (ZVCI) and Water Condition Index (ZWCI) with a 40-day lag is used to demonstrate that ZWCI can aid the prediction of vegetation anomalies ZVCI, particularly in the cooler months when vegetation growth is mainly driven by precipitation.
The paper is clear and well written, it employs simple and sound methodology, and I believe that it represents an important contribution to the field of study. Apart from correcting a few typos e.g. “(Appendix 1- PONER ALGO MAS?)” on line 110, I would suggest to the authors to increase the figure labels as they are very hard to read.
Regarding the fact that both temperature and precipitation drive vegetation growth (as discussed along the paper), is there a way that temperature anomalies could also be taken into account explicitly in such a study?
Citation: https://doi.org/10.5194/nhess-2023-145-CC1 -
AC4: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
Citation: https://doi.org/10.5194/nhess-2023-145-AC4 -
AC5: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC6: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC4: 'Reply on CC1', Ana Maria Tarquis, 25 Jan 2024
-
CC2: 'Comment on nhess-2023-145', Jose Luis Valencia, 17 Nov 2023
- In line 110, there is extra text. "Anexo 1- poner algo mas?" . You need to eliminate it
- In Figure 2, it is mentioned that it is used for the model in Equation 12 to estimate parameters. I believe it should say Equation 3.
- What is the motivation for reducing the value of w to 0-1 by replacing values of w above 1? If later a index (WCI that will range between 0 and 1) is used?
- Where does Equation 3 come from (there is no reference, although it seems that it could be found in Sadaghi 2017 from Figure 2)? I think either a reference should be provided, or the foundation and interpretation of this index should be explained, or both.
- In my opinion, the explanation of Equation 6 is unnecessary; I believe conditional probability should be well-known to everyone.
- In line 173, it is indicated how the phases are generated. To impose the limits of these phases, it seems like the median is used, although it is not explicitly stated. In my view, representing it with a Box-Cox diagram would allow a discussion of these points since the third quartile would suggest that phase 2 begins some weeks later, especially in Los Velez. Wouldn't it be clearer to exclusively represent a line connecting the medians of each ten-day period for greater clarity?
- Figure 4 is not clear, especially regarding rainfall. It is difficult to distinguish those "abundant rains" in phase 3 (at least when comparing them with phase 2 where the extreme points are higher). There is also a contradiction stated in lines 188-189 regarding the explanation of Figure 4, as it indicates that there is more rain in phase 2.
- I suggest using more distinct colors to better distinguish the series in Figure 5 (for example, red and blue).
- In line 192, it is mentioned that there is a smoother profile of the ZVCI series; perhaps a cause explaining this should be suggested.
- Although providing probabilities in percentages may not be the most appropriate, it is understandable given the calculation method. However, I am more in favor of indicating the value between 0 and 1 when discussing probabilities.
- Mentioning expected probabilities on standardized data could be considered. For example, if the indices followed normal distributions (which may not be the case), for ZWCI and ZVCI, the probabilities would be P(Index<-0.5)=0.309, P(Index<-0.7)=0.242, and P(Index<-0.1)=0.159.
- The comments about the probability of an index being below the threshold of -0.7 being lower than being below -0.5 seem unnecessary. This is obvious: P(Z<-0.5)=P(Z<-0.7)+P(-0.7<=Z<-0.5) (the same for Z<-1). In any case, the greater the difference, the higher the probability that the index is between [-0.7, -0.5).
- In line 215, why is there now a condition for the threshold of -0.3? I don't understand if there is justification or at least it is not explained.
- In Figures 8, 9, 10, 11, P(VCI<-0.7) is stated. Obviously, this probability is always 0 because the VCI value is in the interval (0,1). It should be P(ZVCI<-0.7).
- In the paragraph between lines 224 and 230, there is no reference to the possibility that the correlation could be negative in the summer months (from late May to September). Additionally, the term "significantly" is used, but based on what criterion or test is it significant?
- In lines 238 and 239, it is said, "as with Los Velez, the lag-4 conditional probabilities for the threshold -1.0 remain above the base probability." It seems incorrect to me; in Los Velez, these probabilities for the summer months were below.
- In line 241, it is said that the probability with a 4-period delay is higher than the base probability, but this also occurs for the probability without a delay.
- I wonder why, with two time series, a transfer function model is not carried out, identifying cross-correlations to determine the delay that best explains one series in terms of the other. It may have been done, but it is not indicated in the article. Why have you chosen 4 lag?
Citation: https://doi.org/10.5194/nhess-2023-145-CC2 -
AC3: 'Reply on CC2', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
RC1: 'Comment on nhess-2023-145', Anonymous Referee #1, 06 Dec 2023
Specific Comments
Ln 14. Can you explain why you are using the term “water soil moisture” in the following phrase “We aim to study the feasibility of using water soil moisture (soil drought)”
Ln 18. Please choose between using ZVCI or ZVCI. You should keep one of those and don’t change through the manuscript.
Ln 22. VCI = ZVCI? Please be consistent with acronyms throughout the manuscript.
English comments
Ln 24. Precipitation leads TO vegetation growth. OR precipitation grows vegetation.
Ln 37. Please use “soil water content”. Please modify all the rest by yourself.
Ln 46. I think a reference is needed for the types of droughts.
Ln 73. In line 46 you mention four types of droughts. Now, you are using a “new term,” edaphic drought. Why is it not mentioned before?.
Ln 101. They use using?. Please correct.
Ln 100. It is not clear why they choose those pixels.
Ln 110. (Appendix 1- PONER ALGO MAS?). This is not the first one, I think this research paper needs to be resubmitted. There are too many typos; see above.
Ln 115. You defined the vegetation condition index with ZVCI in the abstract and have now changed it to VCI.
Ln 118. Eq 1 is dependent on NDVI and Eq. 3 is dependent on NDVI. Do you think this is tricky if you are looking for a correlation between them (WCI and VCI)?
Ln 132. What does the soil water content of one mean?. Is it possible to have soil water content of 0?
Ln 144. Which anomalies? I think it is explained below. Please correct the entire paragraph.
Ln. 151 See acronyms.
Ln 153. Instead of A or B, you should use the acronyms presented before.
Final comments.
Why do you not use a method to evaluate the precision of W computation? Measuring surface soil water content is not difficult. Section 2.4 is not well written and is essential for the manuscript. The methodology does not specify how to verify the results. The methodology is only based on indexes previously published; where is the novelty? On the conditional probability? The manuscript seems to be written carelessly. I suggest rejection
Citation: https://doi.org/10.5194/nhess-2023-145-RC1 -
AC1: 'Reply on RC1', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC1: 'Reply on RC1', Ana Maria Tarquis, 25 Jan 2024
-
RC2: 'Comment on nhess-2023-145', Anonymous Referee #2, 07 Dec 2023
General comments:
The paper intended to analyze the relationship between agronomic and edaphic drought in a semiarid rangeland area. The use of several remote sensing indexes is the primary source of data to provide this analysis. The paper's general idea is valuable but not novel as vast literature uses this kind of tool to analyze such relationships at different scales and under different biomes. The main novelty of the paper is perhaps not fully addressed in the introduction.
The causal mechanisms behind the soil and vegetation drought expression are not fully addressed, probably because of the limitation of the pixel resolution that restricts the specific vegetation identifications and the lack of soil hydraulic properties or soil moisture spatial information. No ground data is used, severely limiting the robustness of the remote sensing analysis. Maybe the general idea and the title of the manuscript should be more related to comparing the dynamics of physically different remote sensing drought indexes to detect agricultural drought, which is more related to objective 2. If so, the study's outreach is limited but valuable, maybe for a letter paper.
In addition, the documents presented several grammar, format, and presentation flaws that made it difficult to follow some essential ideas.
All these reasons support the decision to reject this paper in its current form. However, I put some specific comments to enhance the document for a possible resubmission.
Abstract: The justification of the problem is not well accomplished; why does the 30% precipitation variability represent a challenge? What is the relation between degradation and rainfall variability?
Introduction:
References are too old; I suggest keeping only references for the last 10 years. At least, it was a singular paper. The manuscript requires an extensive English revision before being resubmitted, and it is hard to follow the ideas in this current form. I suggest including a more comprehensive explanation and justification of how agronomic and edaphic drought relations can be propagated. The literature remains poor; please add more relevant and actual papers on the subject. Also, an explanation of what details about the OPTRAM index should be included. Why could this index detect something different from the NDVI?
It is unclear and not correctly justified why using an arid rangeland could be singular to study these relationships.
The definition of edaphic drought is missing.
Methods:
The rationale for choosing the different remote sensing indexes is completely missing. You can use a diagram to support the text to better explain your procedure's logic.
Scientific names should be put in italics.
A description of root depths and the hydraulic properties of soils should be convenient.
The climate description is poor; please use an international reference based on the Koeppen classification.
The explanation of pixel selection is very unclear; please explain how you merge the information better.
You must put the complete names of the MODIS products used in the study, for instance the NDVI product. How did you deal with clouds? Do you use the Quality Assessment data?
Do you resample the NDVI to the STR resolution or vice versa? please clarify.
A better map of the study area is necessary to understand the context better, please improve the one chosen. A climograph could be added, for example, and the land cover present in the selected area.
Results:
The results are attractive and are the main strength of the paper, however, they are difficult to connect to the main objectives. Maybe you could enhance the idea of early detection of a hazard.
The Discussion sections reflect the poor level of analysis displayed in the document, with only three references to confront the results.
Specifics comments:
Line 11: To communicate the idea of precipitation variability, I suggest using another metric or explaining better what you mean by 30% of the coefficient of variability.
Line 13: what is water soil moisture? Please use a widely used terminology.
Line 17: Please explain why you selected two MODIS resolutions.
Line 21. What specific season?
Line 34, I suggest explaining that plant growth can be related to NDVI. The Normalized Difference Vegetation Index must be described with its entire name.
Line 35 Farrat et al., 1994 studied the relationship between NDVI, rainfall, and soil moisture. This is a very old reference, please provide more actual references.
Line 37 what are the main findings of the papers you referred to?
Line 39 and 40: is very difficult to follow the idea, strong correlation of what? The soil moisture between soil surface and lower layers?
Line 42. Please check English grammar.
Lines 46 to 49 please use references to support the drought definitions.
Citation: https://doi.org/10.5194/nhess-2023-145-RC2 -
AC2: 'Reply on RC2', Ana Maria Tarquis, 25 Jan 2024
We have responded to each question and suggestion you posted. Thank you very much for your time and work.
Please see the attached file.
We have changed the title to be more in agreement with our study:
Relationship between Vegetation and Soil Moisture anomalies based on remote sensing data. A semiarid rangeland case.
-
AC2: 'Reply on RC2', Ana Maria Tarquis, 25 Jan 2024
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