Estimation of Root-Zone Soil Moisture in Semi-Arid Areas Based on Remotely Sensed Data
and Jiaxin Jin 1
Round 1
Reviewer 1 Report
Reviewed manuscript “Estimation of root-zone soil moisture in semi-arid areas based
on remotely sensed data” is an original and interesting study. Authors comprehensively demonstrated/calculated the root-zone soil moisture. Study is very interesting and it would add scientific contribution in literature. Authors collected lot of data with strong reasoning. I would suggest minor revision.
Following are some suggestions for further improvements:
First few lines of the abstract should be about the importance of study.
Lines 55-65: Consider revising the lines.
Figure 1 ,3, 5 and 7 is not so clear, need high resolution.
Lines 256-265: Please rewrite this paragraph.
Lines 302-306: Consider revising the lines.
Introduction and Discussion section needs to further strengthen by latest studies on the subject. Improve the discussion section.
At some places in the text, there are grammatical mistakes that need to be corrected by some native English colleague. Please summarize the conclusion.
To further strengthen introduction, latest studies etc. are suggested to cite for the estimation of root-zone soil moisture in semi-arid areas.
Author Response
Point 1: First few lines of the abstract should be about the importance of study.
Response 1: The first 3 setences has illustrated the importance of estimating spatial RZSM.
Point 2: Lines 55-65: Consider revising the lines.
Response 2: These lines have been modified in the reviesed manuscript.
Point 3: Figure 1 ,3, 5 and 7 is not so clear, need high resolution.
Response 3: Figure 1 ,3, 5 and 7 have been modified.
Point 4: Lines 256-265: Please rewrite this paragraph.
Response 4:The expression has been simplified and modified.
Point 5: Lines 302-306: Consider revising the lines.
Response 5: The expression has been modified.
Point 6: Introduction and Discussion section needs to further strengthen by latest studies on the subject. Improve the discussion section. To further strengthen introduction, latest studies etc. are suggested to cite for the estimation of root-zone soil moisture in semi-arid areas.
Response 6: Reference about the estimation of root-zone soil moisture in semi-arid areas has been added to Introduction. More comments have been added to Discussion section.
Point 7: At some places in the text, there are grammatical mistakes that need to be corrected by some native English colleague. Please summarize the conclusion.
Response 7: The grammatical mistakes have been corrected.
Reviewer 2 Report
Dear authors,
Thank you for the opportunity to review this Manuscript (Estimation of root-zone soil moisture in semi-arid areas based on remotely sensed data). The objective of this paper was to regionalize the parameters of the SMAR model and estimate the RZSM in semiarid areas using the SMAR method. The Xiliaohe River basin was selected as our study area, and SM data collected from different depths (ranging from 10 to 100 cm) at SM sites distributed in the study area were used. The structure of this paper is outlined as follows: Section 2 describes the study area, data, and methodology, Section 3 illustrates the results, and Sections 4 and 5 present the discussion and conclusions, respectively. The manuscript has important results but there is some aspect that should be reviewed by the authors.
PLEASE, THE EDITIONS SHOULD BE ADDED IN THE MANUSCRIPT AND ANSWERED IN THE LETTER
The title is good. However, the authors could describe that there is a biochar treatment.
The abstract is clear and brings all information required. However, it is not clear the Material and Methods. The results should be present in the past
The introduction is good. No suggestions
The goals are clear. However, it is not clear why the authors used arid conditions.
In the “Materials and Methods” and “Results and Discussion” the topics are clear and help to understand and follow the study.
Explain the kind of clay in the soil
Explain the field condition in the study. How is soil used in this area
Results and discussion
Explain the results of the 3.1 topics. The authors describe the results but it is not clear to understand
Explain the data analysis in the calibrate method. How many samples? Figure 4 demonstrates a few pieces of data.
In the discussion (pag. 11) there is a map lost.
Explain the Figures on page 13 “importance”
Author Response
Point 1:The title is good. However, the authors could describe that there is a biochar treatment.
Response 1: This study is mainly about the soil moisture estimation based on remote sensing and data mining technology on a short time scale. Biochar treatment belong to paleoclimatology field and is mostly applied to studies on the scale of the entire history of earth. Therefore this method is not included in the description of this study.
Point 2:The abstract is clear and brings all information required. However, it is not clear the Material and Methods. The results should be present in the past.
Response 2: The supplementary description of the method in the last sentence of the abstract has been moved to the front.
Point 3:The goals in the instruction are clear. However, it is not clear why the authors used arid conditions.
Response 3: The illustration of the reason for using arid conditions has been added in the last 2 paragraphs of the instruction.
Point 4:Explain the kind of clay in the soil.
Response 4: The meanings of the sand, silt and clay are explained in the second paragraph of the Section 2.4.
Point 5:Explain the field condition in the study. How is soil used in this area.
Response 5: Data about soil properties is serely utilized as auxiliary data for predicting SMAR parameters in this study, so that the the field condition about soil is not discribed.
Point 6:Explain the results of the 3.1 topics. The authors describe the results but it is not clear to understand.
Response 6: The expressions and phrasing in Section 3.1 have been modified.
Point 7: Explain the data analysis in the calibrate method. How many samples? Figure 4 demonstrates a few pieces of data.
Response 7: Figure 4 shows comparison between calibrated values and predicted values of all SMAR parameters. There are 21 samples on training RF model to predict spatial SMAR parameters.
Point 8: In the discussion (pag. 11) there is a map lost.
Response 8: The figures are matched to the text in 4. Discussion and the figure3 a-b is in Section 3.1.
Point 9:Explain the Figures on page 13 “importance”.
Response 9: The “importance” in page 13 means the degree of contribution of the explanatory variables in the random forest model and the specific explanation could be found in the added reference [29] in Section 2.7.
Reviewer 3 Report
Review of the article “Estimation of root-zone soil moisture in semi-arid areas based on remotely sensed data”.
The paper fits the theme of the journal “Remote sensing”.
The paper proposes a method for restoring soil moisture in the root zone (0-60 cm) based on remote assessing soil moisture in the surface soil layer (0-5 cm). The article has a scientific novelty; its topic is relevant. Remote sensing data are compared with ground-based measurements of soil moisture.
By remote sensing data, the reliable determination of soil moisture in the 0-60 cm layer largely depends on the grad(W).
Some questions and comments:
1. Line 182. Please, explain the physical meaning of “a, b in Eq. (2). Are these empirical adjustable parameters?
2. Line 185. Where is Eq. 9? Probably it is (2)?
3. Line 227 and Figure 2. Where is the definition of R?
(Line 152. Is R the reflectance values in the red band?)
4. Figure 4. Is R2 the correlation coefficient? They should be determined.
R2 values are low. What about the reliability of the Model?
5. Figure 4c-d. The dependency is not evident.
Comments for author File: 
Comments.docx
Author Response
Point 1: Line 182. Please, explain the physical meaning of “a, b in Eq. (2). Are these empirical adjustable parameters?
Response 1: a in Eq. (2) represents the ‘water loss efficient’ and b in Eq. (2) represents the ‘diffusion efficient’ in the SMAR method which is described in section 2.5. They are parameters in the SMAR model that is optimized or calibrated by the genetic algorithm as well as sfc and sw2.
Point 2: Line 185. Where is Eq. 9? Probably it is (2)?
Response 2: The ‘Eq. 9’ has been modified as ‘Eq. 2’.
Point 3:Line 227 and Figure 2. Where is the definition of R?(Line 152. Is R the reflectance values in the red band?)
Response 3: R in the Line 152 means the reflectance values in the red band. R in Line 227 and Figure 2 means the correlation coefficient between the RZSM observed in the in-situ field and the RZSM estimated by SMAR model. The definition of the correlation coefficient R has been added in the formula 4 and line 227 and the corresponding application in the context has been declared in the title of figure 2 and line 227.
Point 4:Figure 4. Is R2 the correlation coefficient? They should be determined. R2 values are low. What about the reliability of the Model?
Response 4: R2 is the determination efficient of the calibrated parameters and the predicted parameters which illustrated the goodness of random forest method on predicting SMAR model parameter. R2 values are low means that the performance of RF to fit parameters is unsatisfactory. However, the performance of the whole process or method is assessed by the comparison of RZSM observations anf RZSM estimations as discribed in Section 3.3——‘Root-zone soil moisture estimated by regional SMAR’.
Point 5:Figure 4c-d. The dependency is not evident.
Response 5: Figure 4c-d indeed show that the dependency of predicted parameters on the calibrated parameters is not evident. However, as explained in response 4, the goal of this method is to estimate spatial RZSM rather than SMAR model parameters. Therefore, although there is no good agreement between the predicted and calibrated parameters for the ‘homogenization’ tendency of RF method on SMAR paramters prediction, the whole method that this study proposed can still be recognized effective for the good agreement batween RZSM observations and estimations showed in Section 3.3.
