the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The relative importance of antecedent soil moisture and precipitation in flood generation in the middle and lower Yangtze River basin
- 1Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou 310058, China
- 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
- 1Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou 310058, China
- 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
Abstract. Floods have caused severe environmental and social economic losses worldwide in human history, and are projected to exacerbate due to climate change. Many floods are caused by heavy rainfall with highly saturated soil, however, the relative importance of rainfall and antecedent soil moisture and how it changes from place to place has not been fully understood. Here we examined annual floods from more than 200 hydrological stations in the middle and lower Yangtze River basin. Our results indicate that the dominant factor of flood generation shifts from rainfall to antecedent soil moisture with the increase of watershed area. The ratio of the relative importance of antecedent soil moisture and daily rainfall (SPR) is positively correlated with topographic wetness index and has a negative correlation with the magnitude of annual floods. This linkage between watershed characteristics that are easy to measure and the dominant flood generation mechanism provides a quantitative method for flood control and early warnings in ungauged watersheds in the middle and lower Yangtze River basin.
Sheng Ye et al.
Status: final response (author comments only)
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RC1: 'Comment on hess-2021-531', Anonymous Referee #1, 20 Dec 2021
The authors aimed to reveal the dominant factor controlling flood generation in the middle and lower Yangtze River basin by calculating the ratio of the relative importance of antecedent soil moisture and daily rainfall (SPR). And they further analyzed the relationship of SPR with topographic wetness index to understand the linkage between the dominant flood generation mechanism and watershed characteristics. It is a valuable study and within the scope of this journal. However, there are several aspects that need to be clarified and improved.
Major concern:
- In this manuscript, some conclusions were drawn based on correlation analysis but not casual analysis. For example, on the relationship of soil moisture with flood events in large catchments, due to long concentration time, it is possible that high soil moisture is the result of large rainfall, and at the same time the large rainfall leads to flood under the condition with low antecedent soil moisture. But when using correlation, the used soil moisture is not the soil moisture generating this flood but the one after rainfall. Therefore, I suggest that the authors add area information of the study catchments and calculate the concentration time. Based on the information, some further casual analysis should be taken.
- The analysis was based on the estimation of antecedent soil moisture, whose reliability was dependent on the water balance. However, there isn’t enough description for the method to estimate soil moisture. (1) The authors simulated daily soil water storage using a water balance equation, in which there isn’t the exchange of soil moisture with groundwater. It can lead to a large error in humid regions, such as Yangtze River basin. (2) Equation 6 was used to estimate the change in soil water storage, but it isn’t clear how to determine the initial value. (3) There is lack of necessary assessment on the estimated soil moisture. (4) As an important element of water balance, ET was calculated according to Equation 7, which needs being re-considered. First, the dimension of ET0 and ET is mm/d, while that of S is mm. Second, why the upper limit of ET is 0.75*ET0? (5) It isn’t clear whether the soil moisture has an upper limit.
- The authors assumed that “When SPR is larger than 1, floods at those sites are more dominated by antecedent soil moisture; when SPR is less than 1, rainfall is the primary driver of floods.” Why it is 1, not any other value? More explanations on its rationality are required.
Detailed comment:
- Line 60-61, it states that “Little work has been conducted on the flood generation mechanisms in China (except Yang et al., 2019)”. It isn’t correct. I notice that Yang et al. (2020) has been listed in the reference. In fact, based on casual analysis, Yang et al. (2020) explored the flood generation mechanism and the dominant factors (antecedent soil moisture, rainfall, snow melt and etc.) in the Eastern Monsoon Region of China, including most of the Yangtze River basin.
- Line 76-77, a comment is similar to the above one.
- Line 171, maximum daily discharge?
- Line 179, it isn’t clear how to obtain Smax. Which data was used?
- Line 181, it isn’t clear how to define Pmax, the maximum in one year, or the maximum in all the years.
- AC1: 'Reply on RC1', Jin Wang, 14 Mar 2022
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RC2: 'Comment on hess-2021-531', Anonymous Referee #2, 17 Jan 2022
The authors analyse the relative importance of soil moisture and precipitation for the generation of the average annual flood in the Yangtze river basin. This is achieved by comparing the ratios of precipitation and soil moisture before the flood event with recorded maximum of the respective variable. The relative ratio of both variables shows a positive correlation with topographic wetness index and a negative correlation with magnitude.
Overall, I think the authors present a very thoughtful analysis which addresses some important drawbacks in our current approach to flood generating processes. Instead of annually averaged results I would have liked some more event-based results. Other recommended improvements are detailed below. I encourage the authors to take them into account for a great and improved article.
Soil moisture estimation
The authors quote two sources upon which the soil moisture routine is based on: Berghuijs et al, (2016) and Deb et al (2019). Deb et al (2019) use a water balance equation, however they did not use it to calculate soil moisture. I do not see any relevance of this reference at this point. I would recommend following the simple bucket model by Berghuijs et al (2016) to calculate soil moisture, the update version in Stein et al (2020) or to consider a modelled soil moisture product, such as ERA5. They are less prone to water balance errors.
Normalizing precipitation/soil moisture
Precipitation has more of an extreme tail than soil moisture. This is due to the fact that soil moisture has an upper limit, e.g. when the soil is completely saturated. Although this is not currently reflected in the equation used for soil storage calculation, this difference should still be taken into account. Another problem with the current normalisation approach is that some catchments in the study period will have experienced more extreme precipitation events than others, simply due to the small time period. If catchment A has experienced a 100-year precipitation event in the observed time period, but catchment B has not, then the values of catchment B will generally be higher than in catchment A. An approach to reduce this uncertainty is to use percentile values as a form of normalisation instead which is more robust (though still not perfect) to this error.
Section 4.3.
Being able to predict average annual flood magnitude for ungauged catchments would be a valuable discovery. This should certainly be explored further in another study. However, since all results are presented at an average and not event scale, I am not convinced that these approaches would work for flood early warning. For that the diversity of flood generating processes (Stein et al, 2020) is too high and the interplay between soil moisture and precipitation too diverse (e.g. Figure 5b, Saffapour et al, 2016). Just because a catchment is dominated by soil moisture, does not mean that an extreme precipitation event will not cause a flood. I would therefore recommend removing the discussion around early warning system and focus on predicting mean annual flood for ungauged catchments.
Minor comments
L61: Yang et al, 2020 presented an analysis on flood generating mechanisms in China.
L132: “with at least 20 years records from 1970 to 1990 and from 2007 to 2016 were selected”. Unclear. Does that mean that some of the stations only have data between 1970 and 1990, while others only have data between 2007 and 2016? These time periods have likely different climatic conditions and the older ones might have since had dams added to their catchment. Please clarify if my understanding is correct. If yes, please discuss the implications for your analysis and add a Figure to the supplement indicating data ranges for the stations.
L190-193: Can be removed since it repeats information from the Introduction.
L200-203, 237-242, 256-266: Please ensure that you are not mixing results and discussion.
L220: There are no red dots on the colour scale in Figure 2. Please clarify.
L308: Can you explain why the fact that smaller watersheds more easily reach saturation supports that they are less soil moisture dominated? They way the results by Sharma et al (2018) are mentioned might confuse some readers otherwise.
L321-322: The correlation between TWI and SPR is much weaker in the regulated watershed. It will most likely not be sufficient for any form of prediction in those catchments.
L333-336: Where are the event scale results presented? It would be most interesting to see event scale results as well. Currently, I do not see any evidence that the results can easily be transferred to event scale.
Figures:
Please try to avoid the use of red and green together when they are the only distinguishing feature. People with colour vision deficiency will not be able to differentiate them. For alternatives, please check Stoelzle & Stein (2021).
Figure 5: The scaling of point size according to drainage area is barely visible. Since drainage area is covered in Figure 6b as well, I would suggest to remove this scaling.
Figure 5: It is unclear what the dashed lines indicate.
Figure 6b and 7: Since the text talks only about topographic gradient and not slope I would recommend using the same terminology in the Figures.
Saffarpour, S., Western, A. W., Adams, R., and McDonnell, J. J.: Multiple runoff processes and multiple thresholds control agricultural runoff generation, Hydrol. Earth Syst. Sci., 20, 4525–4545, https://doi.org/10.5194/hess-20-4525-2016, 2016.
Stein, L., Pianosi, F. and Woods, R., 2020. Event-based classification for global study of river flood generating processes. Hydrological Processes, 34(7), pp.1514-1529.
Stoelzle, M., & Stein, L. (2021). Rainbow color map distorts and misleads research in hydrology–guidance for better visualizations and science communication. Hydrology and Earth System Sciences, 25(8), 4549-4565.
- AC2: 'Reply on RC2', Jin Wang, 14 Mar 2022
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RC3: 'Comment on hess-2021-531', Anonymous Referee #3, 18 Jan 2022
I enjoyed reading this manuscript and believe the results presented here are very convincing – showing the dependence between soil moisture, rainfall, catchment area and flood magnitude. Although previous studies have attempted in parts to show this interplay (e.g. looking at trends), I feel this manuscript probably shows the most convincing and comprehensive results to date.
Some general comments:
Line 178-187: I must admit I am having a bit of trouble with the S’/P’ ratio. Maybe the wording could be changed a little bit; in line 181 it isn’t the contribution of rainfall but really just the relative magnitude; in Line 186 it is not that one is more dominant than the other, it is just a relative measure. The demarcation on “1” is arbitrary and not helpful.
I am not convinced by Section 4.3 or Lines 411-423 for the flood warning because any SPR (low or high) could cause a flood because it is just a relative measure and has no measure of magnitude. You could have low rainfall and low soil moisture and get the same SPR as a high rainfall and high soil moisture. I don’t think this can be used for forecasting.
Also, I would concur with the other reviewer on the colour choice
Line by line comments:
Line 42: “frequency and intensity”?
Line 43: And hence understanding the drivers of change becomes more and more important
Villarini, G., Wasko, C., 2021. Humans, climate and streamflow. Nat. Clim. Chang. 11, 725–726. https://doi.org/10.1038/s41558-021-01137-z
Line 61: remove “except Yang et al 2019” because in the next paragraph you demonstrate there are more studies than just this one.
Line 76: I think there is an opportunity here to state what has been performed in terms of understanding the balance between soil moisture and rainfall as flood drivers (e.g. dependence on magnitude, catchment size, region etc). I appreciate these papers are quite recent and may not have come to the authors attention when writing their manuscript. Examples include:
Brunner, M.I., Swain, D.L., Wood, R.R. et al. An extremeness threshold determines the regional response of floods to changes in rainfall extremes. Commun Earth Environ 2, 173 (2021). https://doi.org/10.1038/s43247-021-00248-x
Wasko, C., Nathan, R., Stein, L., O’Shea, D., 2021. Evidence of shorter more extreme rainfalls and increased flood variability under climate change. J. Hydrol. 603, 126994. https://doi.org/10.1016/j.jhydrol.2021.126994
Bennett, B., Leonard, M., Deng, Y., Westra, S., 2018. An empirical investigation into the effect of antecedent precipitation on flood volume. J. Hydrol. 567, 435–445. https://doi.org/10.1016/j.jhydrol.2018.10.025
Bertola, M., Viglione, A., Vorogushyn, S., Lun, D., Merz, B., Blöschl, G., 2021. Do small and large floods have the same drivers of change? A regional attribution analysis in Europe. Hydrol. Earth Syst. Sci. 25, 1347–1364. https://doi.org/10.5194/hess-25-1347-2021
Line 93: “The Yangtze River”
Line 106: The ‘s’ is a typo.
Section 2: I am not sure Figure 1 was referenced anywhere? The caption says: “climate stations and hydrological”, the legend “hydrological and precipitation stations” and the text in Section 2.2 “meteorological and streamflow”. As a result, I am not actually sure what stations have what data.
Figure 3 caption: Rather than saying “the green ones” you could say “the green circles” or “the green dots”
Line 231: “Dominant driver” – again, this is subjective and I would remove this sentence altogether.
Figure 4 y-axis: please label with normalized precipitation like you did in Figure 3.
Figure 5: What are the slope units? The size of the dots needs a scale too. Figure 5 needs more explanation in the text to justify its place in the paper.
Line 275: Remove “the influential factors of”
Figure 6: Units of drainage area?
Line 286: What is the practical implication of the TWI? Is it just dominated by the area? Not sure about the value or physical interpretation of Figure 6c. Okay – this comes in the discussion – but I think more should be mentioned in the results to point to this.
Figure 7: Again, more discussion is needed in the text, the authors may consider a log scale for the y-axis.
Line 375: Remove “for sure”
Line 377: “be used”
- AC3: 'Reply on RC3', Jin Wang, 14 Mar 2022
Sheng Ye et al.
Sheng Ye et al.
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