Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States

Mishra, Vikalp; Cruise, James F.; Hain, Christopher R.; Mecikalski, John R.; Anderson, Martha C.

doi:https://doi.org/10.5194/hess-22-4935-2018

Articles | Volume 22, issue 9

https://doi.org/10.5194/hess-22-4935-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-22-4935-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 9

Research article

|

25 Sep 2018

Research article |

| 25 Sep 2018

Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States

Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson

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Final revised paper (published on 25 Sep 2018)
Preprint (discussion started on 25 Jul 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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AC1: 'Correction of table-2', Vikalp Mishra, 07 Sep 2017
RC1: 'Development of Soil Moisture Profiles Through Coupled Microwave-Thermal Infrared Observations in the Southeastern United States', Anonymous Referee #1, 23 Oct 2017
- AC2: 'Reply to Anonymous Reviewer#1', Vikalp Mishra, 07 Dec 2017
RC2: 'Review of manuscript “Development of Soil Moisture Profiles Through Coupled Microwave-Thermal Infrared Observations in the Southeastern United States” by V. Mishra et al.', Anonymous Referee #2, 01 Nov 2017
- AC3: 'Reply to Anonymous Reviewer#2', Vikalp Mishra, 07 Dec 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (22 Dec 2017) by Theresa Blume

AR by Vikalp Mishra on behalf of the Authors (31 Jan 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (08 Feb 2018) by Theresa Blume

RR by Salvatore Manfreda (28 Feb 2018)

Suggestions for revision or reasons for rejection

The manuscript introduces a challenging research topic still unsolved.
The manuscript is well organized and authors have put great effort on the review of the manuscript. I had the opportunity to read both the manuscript, the rebuttal letter and also the manuscript with track of changes. I have to admit that the manuscript has been improved significantly, but according to my perspective there are still a number of open questions.

I have some comments that have been written with the aim to improve the final quality of the manuscript:

1. The authors use the relationship between relative saturation and evapotranspiration to derive an estimate of the available water content. I would like to stress this point because the ET can certainly provide good indications on the available water content, but when the relative saturation exceeds the field capacity, this method is unable to properly identify the state of the soil. Therefore, ALEXI SM is an estimate of the available water content not soil moisture.

2. Given the above consideration I wonder if such limitation may be reasonable of some of the errors observed may be due to such an assumption.

3. Looking at the results, it seems that the proposed model leads to results similar to those by Noah LSM. The argument of the authors is that POME tends to be better in the lower soil layer, but this result is imposed by calibrating the lower limit of relative saturation profile. As stated by the authors the lower boundary condition is imposed equal to 0.55. In fact, all time series in the lower layer (40-100cm) show a similar dynamics with small variability around a relative value close to 0.55. Therefore, this is not an evidence of model reliability in my personal opinion.

4. Referee 2 comment 3. I think that the discrepancies between soil moisture measurements in the top layer and the POME predictions may be due to the ALEXI SM estimates that are probably rescaled according to the relative soil porosity.

5. In my experience, the soil moisture signal tend to be smoothed moving to the lower layers (see Manfreda et al., HESS - 2014), but the time series 2115, 2113, 2013 (figure 5) show an amplification of soil moisture changes over time. This may be due to the presence of a phreatic surface interfering with the unsaturated zone. I suspect that these point are not coherent with the modeling scheme adopted.

6. In general, I admit that the authors are working on a challenging topic, but the overall presentation of the results does not fully convince about the advantages and potential of the proposed method. The fact that POME is superior to Noah LSM only on 50% of the stations and the fact that the better performances in the lower layers, claimed by the authors as an advantage of the proposed method, may be an outcome of a calibration is a bit weak to justify its use in future applications. I would like to have more arguments about the potential of these model, how and where it can be used.

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RR by Anonymous Referee #4 (14 Mar 2018)

RR by Anonymous Referee #5 (02 Apr 2018)

Suggestions for revision or reasons for rejection

Review HESS-2017-351
First of all I would like to make clear that I have not been a reviewer on this manuscript before. I studied the response to the reviewers and the revised manuscript and I think the authors responded well to most of these comments, but being a new reviewer for this manuscript I cannot avoid having some questions. I found the manuscript extremely interesting, and the approach without a-priori assumptions at the scale of LSM models is very useful to the community of HESS. At present however, the manuscript is somewhat impenetrable to me, and therefore I assume to other readers of HESS as well (comments below). Which readership did the authors have in mind: the well-informed LSM or remote sensing community that is certainly present in HESS, or the broader hydrologic community with an interest in remotely sensed applications?
1. The objective of the paper evolves around the POME model by using SM profiles developed from remotely sensed data only. Although I am sure everyone knows about entropy, the explanation of POME is rather short, as mentioned by one other reviewer as well. The reader is referred to several previous publications that employ the POME model. I suggest to include a more extensive description of the POME results instead of referring to whom applied it. This would help out the interested non-expert HESS readership to get to a level of insight that helps to appreciate this manuscript.
2. For ALEXI field capacity and wilting point are employed in Eq. 1. Which values were used for the different soil types?
3. Line 250-253: Can the authors explain a bit more about the varying spatial scales and locations instead of only giving r and RMSE/RMSD/ubRMSD for various authors? For scientists unfamiliar with SEE disaggregation this part could be more informative, also because it is important for the approach used in this study.
4. What was the rationale/advantage for using surface and potential evaporation instead of the SEE definition given in line 275? Not clear now, only clear it changes the definition. Would be good to know as the change in definition seems to limit its applicability to water rich environments?
5. One of the assumptions needed for POME is due to non-monotonic behavior of SM. This necessitates the assumption of an inflection point. In the present study, only for 9% of the profiles generated such an assumption was needed. So, although POME is assumption free, the application of POME may not be (still better than LSM regarding number of assumptions). Can the authors reflect on the applicability of POME for other studies? If POME was not applied on SM but instead on the soil water potential (SWP) non-monotonic behaviour across a profile is no longer a concern. This would of course require a relation between SWP and SM, but increasingly assumption free relations are being developed to do so, they only at present take a lot of computational time.
6. Restricting ALEXI and POME by soil moisture at field capacity means that comparison with in situ data misses out on the field capacity to saturated soil moisture range, especially in the water rich environments of the present study. Can the authors reflect on this?
7. Looking at Fig 4 the correlation for 6 out of 10 sites decreases with depth. What could cause this? The most dynamic SM can be expected at the soil surface if no preferential flow path are present in the profile. In figure 5 most dynamics can be seen at the 40-100 layer at some sites, indicating preferential flow paths (unless a dynamic shallow groundwater table is present). Some of the sites have a clay type soil which may form cracks and thus provide preferential flow conduits. This might perhaps also explain the decrease in correlation at greater depth, because such flow conduits will only be active under very wet conditions. These may are not accounted for in the POME approach as this is limited to field capacity or is this the result of the overpass time?
8. The conclusions puzzle me regarding the comparison between Noah, POME and SCAN. I have fig 5 and 6 for Noah, and fig 4, 5 and 6 for POME. Why is there only one general Noah/Scan comparison for Noah in fig 6?
Specific comments:
Line 44-46: Very confusing line: In general, in-situ SM profile data are only available at a few locations in the US for any given period of time. Why the focus on the US? I am sure globally there will only be a few in situ, but this line somehow seems to suggest there are only US data.
Equation 2: for consistency please define SMmod as well.
Table 1: Soil type for site 2037 and 2038 unknown? Also site 2037 typo in Shrubland.

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ED: Publish subject to revisions (further review by editor and referees) (23 Apr 2018) by Theresa Blume

AR by Vikalp Mishra on behalf of the Authors (04 Jun 2018)

ED: Referee Nomination & Report Request started (21 Jun 2018) by Theresa Blume

RR by Anonymous Referee #4 (29 Jun 2018)

RR by Salvatore Manfreda (22 Jul 2018)

RR by Anonymous Referee #5 (24 Jul 2018)

ED: Publish subject to minor revisions (review by editor) (09 Aug 2018) by Theresa Blume

AR by Vikalp Mishra on behalf of the Authors (17 Aug 2018) Author's response Manuscript

ED: Publish subject to technical corrections (06 Sep 2018) by Theresa Blume

AR by Vikalp Mishra on behalf of the Authors (07 Sep 2018) Author's response Manuscript

Short summary

Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.