Rainfall erosivity in catchments contaminated with fallout from the  Fukushima Daiichi nuclear power plant accident

Laceby, J. Patrick; Chartin, Caroline; Evrard, Olivier; Onda, Yuichi; Garcia-Sanchez, Laurent; Cerdan, Olivier

doi:https://doi.org/10.5194/hess-20-2467-2016

Articles | Volume 20, issue 6

https://doi.org/10.5194/hess-20-2467-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-20-2467-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 6

Research article

|

23 Jun 2016

Research article |

| 23 Jun 2016

Rainfall erosivity in catchments contaminated with fallout from the Fukushima Daiichi nuclear power plant accident

J. Patrick Laceby, Caroline Chartin, Olivier Evrard, Yuichi Onda, Laurent Garcia-Sanchez, and Olivier Cerdan

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Final revised paper (published on 23 Jun 2016)
Supplement to the final revised paper
Preprint (discussion started on 30 Jul 2015)
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Interactive discussion

Status: closed

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

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RC C3296: 'Overall evaluation', Christos Karydas, 25 Aug 2015
- AC C3766: 'Response to Reviewer 1's Overall Evaluation', J. Patrick Laceby, 18 Sep 2015
RC C3499: 'Reviewer 2', Anonymous Referee #2, 08 Sep 2015
- AC C3773: 'Response to Reviewer 2', J. Patrick Laceby, 18 Sep 2015
EC C3657: 'Start discussing', Nunzio Romano, 14 Sep 2015
RC C4599: 'Comment on hess-2015-298 (referee)', Anonymous Referee #3, 03 Nov 2015

Peer-review completion

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

ED: Reconsider after major revisions (08 Nov 2015) by Nunzio Romano

AR by J. Patrick Laceby on behalf of the Authors (29 Feb 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (06 Mar 2016) by Nunzio Romano

RR by Anonymous Referee #4 (14 Mar 2016)

RR by Anonymous Referee #3 (24 Mar 2016)

Suggestions for revision or reasons for rejection

The manuscript has been greatly improved but some improvements can still be suggested. The authors use rather advanced methods of statistics but clearly do not understand the basic concepts od statistics (standard deviation, population and sample, autocorrelation; see L 27, 237, 258 below). This leaves at least some doubt whether the statistical analysis has been correctly applied.

Details:
L 27: Sigma is used as symbol for the standard deviation of the population. The authors clearly do not know the population but just have a sample. The symbol then is s in equations while SD is the accepted abbreviation in plain text. Hence either use s or preferably use SD but sigma is wrong (the same applies for µ, which also is used later on). This will also avoid present inconsistencies because later the authors switch from sigma to S.D.

L 39: I wonder why the authors switch between typhoon and cyclone in some places. Although both are the same weather phenomenon, “cyclones” occur in the South Pacific and Indian Ocean but not near Japan.

L 54: Fixated is not the correct technical term. Better use “adsorbed” because Cs can be exchanged by other cations like K. If it would be fixated, plants could not take it up and we would not have to worry about it.

L 66: Event duration is not a criterion of the R factor. The way it is put here, it can be misleading to readers and the authors should be especially precise in this case, because this is the center of their topic.

L 72: the references do not fit to the sentence because they neither prove “around the world” nor do most of them correlate the R factor with measured soil loss. Either change the sentence or find appropriate references.

L 112: Shouldn’t the unit be Bq/m² instead of Bq/kg. The spatial pollution should have space as unit because no mass can be associated with space (or you would have at least to define a depth and a density)

L 115: Is the climate based on the classification or is rather the classification based on the climate?

L 126: Radius is misplaced

L 130: Blank after 115 is missing; comparable to what?

L 131: What are other analyses? No analyses were mentioned yet.

L 132: Sentence not clear. I read: you exclude long-term stations because of their short measuring period??

L 133: Isn’t there any better data? Usually much better data are available at meteorological authorities that those made available to the public (for several reasons)

L 135: not clear. Rain always has breakpoints (like the start of rain). I guess that something different was meant but guessing is not part of the game.

L 150: unit energy is not the correct term. You use the correct description anyhow in L 152. Move it to L 150. This also avoids the mistake of defining a symbol twice and with different definitions.

L 166 to 169: This doesn’t sound like reliable sources. I would expect JMA to be reliable but if you additionally need Google news even JMA seems not to be reliable. The whole typhoon story a weak already from the beginning.

L 172: Blank after 250

L 172-175: The sentence does not really provide an argument. I guess that you wanted to say that you do not have enough stations to perform kriging. This is, however not the case, as Goovaerts (2000, J Hydrol) has shown that even with 36 stations, kriging outperforms regression. I do not argue against the use of regression techniques, my point is that a sound justification has to be given (and sample size is not sufficient in your case). If I would have chosen regression, I would have written something like: Regression technique was preferred over geostatistical techniques even though this might be on the expense of a slightly inferior spatial interpolation (Goovaerts 2000) but it allows better identification of driving parameters.

L 196: not clear in which dimension the resolution was applied (lateral or vertical?)

L 237-238: this does not comply with the concept of autocorrelation

L 258-259 and several places in the following: the fact that 26% of the values fall outside one SD around the mean does not imply large heterogeneity but it is an inherent property of any SD. In fact, for a perfect normal distribution 32% of all data should fall outside this range. This is true for very homogenous data (small SD) and very heterogeneous data (large SD). Your conclusions are thus wrong.

L 263: see L 258

L 267: Entire sentence not clear. Rephrase. Why do you subtract the mean from SD? Doing it the other way round could make sense.

L 270: no references in the Results section

L 272: do you really mean “perioidic” (occurring in fixed intervals)

L 275 and many places in the following: what is a maximum average? You need to be more explicit over which domain you average the data and over which domain you determine the maximum. Otherwise the reader has to speculate. This becomes even worse in the following.

L 277: there is no highest maximum because by definition the maximum itself is already highest. What do you mean?

L 278: what is a lowest maximum?

L 279: What is a highest mean annual maximum daily precipitation? Is it annual or daily, is it mean or maximum, what is a highest maximum ...

L 286: Mean? Again it is not clear over which domain you average your data. This is especially unclear for SD. Is this the SD among station years or is it the SD among stations or is it the SD among years? These SDs will differ and carry different information.

L 289: Again, unnecessary information that some data plot outside the SD

L 294: Sentence seems to be incomplete

L 298-301: This is very typical also in areas where no typhoons occur. Hence this does not indicate a special effect of typhoons

L 309: You claim that the SD of the predicted values was smaller than the SD of the observed values during the typhoon season. However, your data show the same effect also outside the typhoon season. Again, this is too weak to indicate any special effect of the typhoons

L 368: I found the whole chapter about typhoons not convincing and your concluding sentence trivial (“typhoons contribute a significant amount of rainfall erosivity”). If you would do a similar analysis for Sundays, you could also conclude “Sundays contribute a significant amount of rainfall erosivity”. Or, you could conclude “Rain days contribute a significant amount of rainfall erosivity”. What would we learn from this?

L 373: “Likely” is not acceptable here, because this is in the center of you topic; there should be enough meteorological knowledge on this.

L 432: Better write “high”; otherwise you need to say what is higher than what.

L 442: I found the whole chapter (2 pages!) unnecessary (for instance, what has paddy rice to do with rain erosivity?), full of speculations, wrong or incomplete statements. Delete or reduce to one paragraph.

L 491: suddenly you change the abbreviation of year.

L 527: formatting of the references is inconsistent

Table 2: The SDs clearly show that no decimals are justified (for the SD and the mean).

Figure 3: What is a SAI? What is annul?

Figure 4: typo (anomaly)

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ED: Reconsider after major revisions (06 Apr 2016) by Nunzio Romano

AR by J. Patrick Laceby on behalf of the Authors (29 Apr 2016) Author's response Manuscript

ED: Publish as is (25 May 2016) by Nunzio Romano

AR by J. Patrick Laceby on behalf of the Authors (02 Jun 2016)

Short summary

Characterizing rainfall erosivity in the Fukushima fallout-impacted region is important for predicting radiocesium behavior. The majority of rainfall (60 %) and rainfall erosivity (86 %) occurs between June and October. Tropical cyclones contribute 22 % of the precipitation though 44 % of the rainfall erosivity. Understanding the rainfall regime and the influence of tropical cyclones is important managing radiocesium transfers in contaminated catchments in the Fukushima prefecture.