the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Jul 2021
Maximum Entropy Distribution of Rainfall Intensity and Duration – MEDRID: a method for precipitation temporal downscaling for sediment delivery assessment
Abstract. Scarcity of precipitation data is yet a problem in erosion modelling, especially when working in remote and data scarce areas. While much effort was made to use remote sensing and reanalysis data, they are still considered to be not completely reliable, notably for sub-daily measures such as duration and intensity. A way forward are statistical analyses, which can help modellers to obtain sub-daily precipitation characteristics by using daily totals. In this paper, we propose a novel method (Maximum Entropy Distribution of Rainfall Intensity and Duration – MEDRID) to assess the duration and intensity of sub-daily rainfalls relevant for modelling of sediment delivery ratios. We use the generated data to improve the sediment yield assessment in seven catchments with area varying from 10−3 to 10+2 km2 and broad timespan of monitoring (1 to 81 years). The best probability density function derived from MEDRID to reproduce sub-daily duration is the generalised gamma distribution (NSE = 0.98), whereas for the rain intensity it is the uniform (NSE = 0.87). The MEDRID method coupled with the SYPoME model (Sediment Yield using the Principle of Maximum Entropy) represents a significant improvement over empirically-based SDR models, given its average absolute error of 21 % and a Nash-Sutcliffe Efficiency of 0.96 (rather than 105 % and −4.49, respectively
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RC1: 'Comment on hess-2021-278', Anonymous Referee #1, 17 Aug 2021
I have reviewed the manuscript titled with “Maximum Entropy Distribution of Rainfall Intensity and Duration – MEDRID: a method for precipitation temporal downscaling for sediment delivery assessment” by Pedro Henrique Lima Alencar et al..
In this manuscript, the authors presents a method (MEDRID) for precipitation temporal downscaling, then coupled with the SYPoME model to indirectly assess the MEDRID performance. Even though the results presented in the several catchments indicated that the MEDRID method have a good performance, but the authors should make it clear what the novelty of this study is. In addition, the description of how to couple with the SYPoME model is not clear, which makes a direct application difficult of this method.
I would then suggest rejection of the article with invitation to resubmit. My major comments are described below.
(1) The novelty of the MEDRID method is not clear in this version. The Maximum Entropy Principle (MEP) has been widely used in many fields for the selection of an optimal distribution function. The authors seems just use the MEP to select an optimal distribution function for rainfall intensity and duration, if so, the article obviously lacks innovation. Thus, the authors should classify the novelty of the MEDRID method.
(2) The description of how to calculate the series of the ratio D/H and I30/H is confused. Is D/H and I30/H relative to a rainfall event (may last for several days) or just relative to a daily rainfall (only one day)? Should all non-zero rainfall days be considered?
(3) The application of the D/H distribution, coupled with the SYPoME model, were described in Sect.2.3. But I did not see relative description of how to use the I30/H distribution for SYPoME model. The reliability should be improved.
(4) The authors indirectly assess the performance of the MEDRID method by comparing the M1 and M2 model. However, it can be found from the Figure 5 that the M2 error is systematically large, why? Does this affect the reliability of the comparison result?
Citation: https://doi.org/10.5194/hess-2021-278-RC1 - AC1: 'Reply on RC1', Pedro Henrique Lima Alencar, 23 Aug 2021
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RC2: 'Comment on hess-2021-278', Anonymous Referee #2, 26 Aug 2021
This manuscript by Alencar et al. addresses a very important topic to estimate the sediment yield in data scarce region. Although research topic and Introduction motivated me to look forward to further sections on Methodology and Results in the manuscript, I must say that it was very confusing from Section 2 onwards to follow because Authors kept referring to previous work by one of the co-authors de Araujo 2007 and 2017. I looked into supplementary material which was not really helpful. I suggest Authors to present the methodology clearly and as far as possible, independent from previous work. Otherwise, novelty of the approach becomes questionable.
As a hydrologist, I was hoping to see the results of temporal downscaling in terms of a time series showing daily and subdaily information at the selected sites. There are many literature on the topic of downscaling daily to subdaily data, especially rainfall, but Authors actually went quickly into MEDRID-SYPoME description, overlooking the fact that the downscaled results need to be evaluated carefully as it is one of the major inputs for producing sediment yield.
I wonder the appraoch prsented in this manuscript is area specific. The claim that the presented method is more accurate than the conventional method can't be justfied unless the approach is applied to different topographical and climatic regions. To set up a hydorlogical model to derive sediment yield at the outlet, one has to calibrate so many parameters using the observation data, I am not clear how all those complicated steps can be bypassed by using a set of equations.
The main results for sediment yield is presented in Figure 5. it would be better if the results are presented in terms of time series, not just one red dot showing total yearly sediment yield. Also 5% and 95% confidence limit on the modeled result can be shown in a time series plot.
Overall, Authors should very carefully highlight what is there in this work which is different from their previously published work. Present the methodology clearly so that readers don't need to refer to several other papers to understand it. Also, the results section should be made clearer with more plots.
Citation: https://doi.org/10.5194/hess-2021-278-RC2 -
AC2: 'Reply on RC2', Pedro Henrique Lima Alencar, 05 Sep 2021
Dear Referee,
We are thankful for your comments on our work. We would also like to take this opportunity to show our appreciation for the relevant of peer-review work and all energy and time spent.
Please find the comments in the .pdf file attached.
-
AC2: 'Reply on RC2', Pedro Henrique Lima Alencar, 05 Sep 2021
Status: closed
-
RC1: 'Comment on hess-2021-278', Anonymous Referee #1, 17 Aug 2021
I have reviewed the manuscript titled with “Maximum Entropy Distribution of Rainfall Intensity and Duration – MEDRID: a method for precipitation temporal downscaling for sediment delivery assessment” by Pedro Henrique Lima Alencar et al..
In this manuscript, the authors presents a method (MEDRID) for precipitation temporal downscaling, then coupled with the SYPoME model to indirectly assess the MEDRID performance. Even though the results presented in the several catchments indicated that the MEDRID method have a good performance, but the authors should make it clear what the novelty of this study is. In addition, the description of how to couple with the SYPoME model is not clear, which makes a direct application difficult of this method.
I would then suggest rejection of the article with invitation to resubmit. My major comments are described below.
(1) The novelty of the MEDRID method is not clear in this version. The Maximum Entropy Principle (MEP) has been widely used in many fields for the selection of an optimal distribution function. The authors seems just use the MEP to select an optimal distribution function for rainfall intensity and duration, if so, the article obviously lacks innovation. Thus, the authors should classify the novelty of the MEDRID method.
(2) The description of how to calculate the series of the ratio D/H and I30/H is confused. Is D/H and I30/H relative to a rainfall event (may last for several days) or just relative to a daily rainfall (only one day)? Should all non-zero rainfall days be considered?
(3) The application of the D/H distribution, coupled with the SYPoME model, were described in Sect.2.3. But I did not see relative description of how to use the I30/H distribution for SYPoME model. The reliability should be improved.
(4) The authors indirectly assess the performance of the MEDRID method by comparing the M1 and M2 model. However, it can be found from the Figure 5 that the M2 error is systematically large, why? Does this affect the reliability of the comparison result?
Citation: https://doi.org/10.5194/hess-2021-278-RC1 - AC1: 'Reply on RC1', Pedro Henrique Lima Alencar, 23 Aug 2021
-
RC2: 'Comment on hess-2021-278', Anonymous Referee #2, 26 Aug 2021
This manuscript by Alencar et al. addresses a very important topic to estimate the sediment yield in data scarce region. Although research topic and Introduction motivated me to look forward to further sections on Methodology and Results in the manuscript, I must say that it was very confusing from Section 2 onwards to follow because Authors kept referring to previous work by one of the co-authors de Araujo 2007 and 2017. I looked into supplementary material which was not really helpful. I suggest Authors to present the methodology clearly and as far as possible, independent from previous work. Otherwise, novelty of the approach becomes questionable.
As a hydrologist, I was hoping to see the results of temporal downscaling in terms of a time series showing daily and subdaily information at the selected sites. There are many literature on the topic of downscaling daily to subdaily data, especially rainfall, but Authors actually went quickly into MEDRID-SYPoME description, overlooking the fact that the downscaled results need to be evaluated carefully as it is one of the major inputs for producing sediment yield.
I wonder the appraoch prsented in this manuscript is area specific. The claim that the presented method is more accurate than the conventional method can't be justfied unless the approach is applied to different topographical and climatic regions. To set up a hydorlogical model to derive sediment yield at the outlet, one has to calibrate so many parameters using the observation data, I am not clear how all those complicated steps can be bypassed by using a set of equations.
The main results for sediment yield is presented in Figure 5. it would be better if the results are presented in terms of time series, not just one red dot showing total yearly sediment yield. Also 5% and 95% confidence limit on the modeled result can be shown in a time series plot.
Overall, Authors should very carefully highlight what is there in this work which is different from their previously published work. Present the methodology clearly so that readers don't need to refer to several other papers to understand it. Also, the results section should be made clearer with more plots.
Citation: https://doi.org/10.5194/hess-2021-278-RC2 -
AC2: 'Reply on RC2', Pedro Henrique Lima Alencar, 05 Sep 2021
Dear Referee,
We are thankful for your comments on our work. We would also like to take this opportunity to show our appreciation for the relevant of peer-review work and all energy and time spent.
Please find the comments in the .pdf file attached.
-
AC2: 'Reply on RC2', Pedro Henrique Lima Alencar, 05 Sep 2021
Data sets
MEDRID-SyPOME Pedro Alencar, Eva Paton José Carlos de Araújo https://github.com/pedroalencar1/MEDRID-SyPOME
Model code and software
MEDRID-SyPOME Pedro Alencar, José Carlos de Araújo https://github.com/pedroalencar1/MEDRID-SyPOME
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