Characterization of Hydrologic Sand and Dust Storm Sources in the Middle East

Round 1

Reviewer 1 Report

The hydrological SDS source is one of the main areas where human activity is linked to dust storms. However, few studies seem to be able to quantify the significant impact of changes in this type of SDS on the dust events. This study extracted hydrological SDS in the Middle East and analyzed the spatial and temporal trends in hydrological SDS and their possible impacts in relation to regional water resources changes. This article has important implications for the study of the impact of climate change and human activities on sand and dust events. I suggest this article be published after major revised or reconstruction. From the current context, I have below comments and suggestions.

 

The results indicate that hydrological SDSs account for a small area of the overall dust storm sources, why the emphasis on hydrological dust storm sources in the Middle East and how it compares to other types of SDSs. This premise is very important and it directly determines the significance of this study.

 

It is recommended that the research methodology be further clarified in terms of the steps in the analysis, the corresponding methods used, and the objectives. I would also suggest adding a reasearch framework as a way of highlighting the main line of the study.

 

How do you use remote sensing products to identify SDSs? In general, remote sensing products reflect information about dust aerosols, but the location from which the dust is released does not seem to be reflected by the dust aerosol indicators.

 

How do you determine SDS hotspots by visual interpretation? Please add a description and interpretation flags.

 

I think it is important to know whether the validation points in SDS hotspots were generated by random algorithm sampling or whether they are selected solely by visual interpretation. Also, whether the validation points were validated through fieldwork or other methods? The number of validation points seems to be on the low side, and would generally need to be between one-third and two-thirds of the sample.

 

2.2: This section may need to be described in more detail, including the key indicators and thresholds for each category.

 

3.1: I think it may not be appropriate to describe dust storm thresholds in terms of both dust aerosol indicators and subsurface indicators for the same site, because even if the subsurface at this site meets the conditions for dust emissions, the dust aerosol at this site may originate from dust emissions from tens of kilometres away. At the same time, the combination of local wind speed and subsurface may not be called a hotspot even if the local dust emissions are satisfied, if the dust aerosols emitted are weakly transported.

 

It is suggested that the results of 3.2 and 3.3 swap places, as time is of first importance relative to space.

 

The time scales of analysis are inconsistent. For example, the time period for the acquired remote sensing data is July 11, 2018, to June 01, 2022, but the time ranges analyzed for surface water and groundwater are 1984-2020 and April 2002 to July 2017, respectively. I suggest a more plausible interpretation in the combination of the time periods analyzed.

 

I only found 1 figure in Figure 1 and no subplots (a) and (b) appear.

 

The MERRA2 AOT data used in part 3.3 may need to be described in the methods. For the MERRA2 aerosol reanalysis data product, why was only the indicator dust scattering AOT chosen and what is special about it? In addition, what is the logical link between MERRA2 AOT data and the data previously obtained through the interpretation of remotely sensed data?

 

 

While it is true that drought events are significantly correlated with SDSs, there is still a lack of evidence of correlation from the analysis in this paper. First, drought events are significantly correlated with hydrological dust storm sources, but we do not know the contribution of dust emissions from hydrological dust storm sources across the region. At the same time, the correlation between hydrological indicators and regional dust aerosol indicators may stem from the combined effects of climate change. Therefore, the causal relationship between drought causing the expansion of hydrological dust storm sources and the consequent impact on dust storm occurrence cannot be demonstrated in this paper.

Author Response

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Reviewer 2 Report

1. The authors should include a detailed description of the mask modeling applied in the research i.s., it is necessary to add the working and background of the mask in order to get easy understanding. 

2. As well, it is recommended a comparison to other methods in the literature. 

3. The overall accuracy of 82.6%, how  can it be improved? it is recommended to mention the facts which are generating uncertainties in the presented method. 


4. Could this methodology be implemented for other regions of the world? Please, mention the scientific challenge.

5. ANOVA is an  alternative to determine the influence  of drought and human interventions. Also, a numerical analysis  data-driven model will be recommended at the mean term.

6. Plase, the authors should mention the future work of this research.

Author Response

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Round 2

Reviewer 1 Report

The manuscript has been greatly improved, congratulations!