the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Exploring the Potential Processes Controls for Changes of Precipitation-Runoff Relationships in Non-stationary Environments
Abstract. The influence of climate change and anthropogenic activities on precipitation-runoff relationships (PRR) has been widely discussed. Traditional models assuming stationary conditions can lead to inaccurate streamflow predictions. To address this issue, we propose a Driving index for changes in Precipitation-Runoff Relationships (DPRR), identified as key PRR influencers, involving climate forcing, groundwater, vegetation dynamics, and anthropogenic influences. According to the quantitative results of inputting the candidate driving factors to a holistic conceptual model, the possible process explanations for changes in the PRR were deduced. This framework is validated across five sub-basins in the Wei River Basin. Moreover, non-stationary hydrological processes were initially detected, and the nonlinear correlations among the factors were assessed. The results show that baseflow emerges as the primary factor positively influencing PRR (enhancing PRR), but with high uncertainty. Potential evapotranspiration plays a dominant role in driving negative PRR changes in the sub-basin which are characterized by a semi-arid climate and minor human interference. Vegetation dynamics negatively influence PRR, with driving levels correlating with the scale of soil and water conservation engineering, displaying lower uncertainty. Anthropogenic influences, represented by Impervious Surface Ratio (ISR), Night-Time Light (NTL), and population density (POP), exhibit varying driving levels, with ISR having the strongest and direct impact, closely linked to urbanization processes and scale. The temporal dynamics of driving factors computed by dynamic DPRR generally correspond with hydrological regime shifts in non-stationary environments. The study's findings offer a comprehensive understanding of hydrological processes, enabling informed decision-making for the development of sustainable hydrological models.
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Status: final response (author comments only)
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RC1: 'Comment on hess-2024-118', Anonymous Referee #1, 25 Jun 2024
The topic “Exploring the Potential Processes Controls for Changes of Precipitation-Runoff Relationships in Non-stationary Environments” is valuable for hydrology. But this paper reads like a case study. The impacts of the study for the general hydrology and its novelty are not clear. The three main objectives of this study are developing an integrated framework, proposing a novel driving index for changes in DPRR, and establishing a holistic conceptual model. But developed the framework, driving index and conceptual model are also not clear and seem not innovative enough.
Detail comments:
1) To the best of my knowledge, the response of runoff to rainfall is non-linear, especially in the semi-arid regions, where infiltration excess runoff is dominant and the amount of runoff is sensitive to rainfall intensity. Rainfall as a major factor influencing the runoff coefficient should be considered, besides potential evapotranspiration.
2) In terms of anthropogenic activities, the constructions of check dams and reservoirs may be the more dominant factor influencing the runoff generation and the precipitation-runoff relationships in the region compared to ISR, NTL and POP.
3) Vegetation dynamics are affected by both climate and afforestation, and how to distinguish them or consider their relationship with other factors?
4) Lines 96-97. What does the driving level and direction refer to?
5) Figure 1-2. These sub-figures for each basin in Fig 1 and Fig 2(b) can be removed.
6) Figure 3. It is inappropriate to put tables and graphs together in a figure.
7) 302-315. The heat map in Fig 4b is hard to understand and more detail is needed to explain. What’s the relationship among these sub-figures. It seems inappropriate to put these in a figure.
Citation: https://doi.org/10.5194/hess-2024-118-RC1 -
AC1: 'Reply on RC1', Tongfang Li, 11 Jul 2024
Dear Anonymous Referee #1,
We appreciate your positive evaluation of our study and your affirmation of its value to the field of hydrology. Your comments and suggested improvements to the manuscript and figures presentation have been valuable in enhancing the quality of our manuscript.We have carefully studied, considered, and responded to all comments point-by-point.
Yours sincerely,
Tongfang Li
E-mail: tongfangli@chd.edu.cn
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AC1: 'Reply on RC1', Tongfang Li, 11 Jul 2024
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RC2: 'Comment on hess-2024-118', Anonymous Referee #2, 01 Aug 2024
- Lines 75-82 the author wrote that hydrological models regionalize the PRR over a specific period, assuming minimal anthropogenic disturbance to simulate hydrologic processes. However, several hydrological models already consider anthropogenic effects on hydrological processes, such as WEP-L, watergap, and PCR-GLOBWB, which effectively incorporate anthropogenic impacts on hydrological processes into their simulations. So the statement "Hence, they may not be suitable for non-stationary hydrological processes" is inappropriate. Meanwhile, the list of PRR identification methods is not comprehensive. The author should highlight the similarities and differences between this study and these previous methods (hydrological model, machine learning, etc.), i.e., the research gaps, and emphasize the real advantages of the method in this study over the hydrological model, which has a physical mechanism, otherwise, it will be hard to be convincing.
- The author described the catchment response conceptual model with a very detailed relational network in Fig.2, Fig.6, and Fig.7. use a slightly more concise presentation? It might be more reader-friendly.
- How to validate the effectiveness of the constructed methods in the study for the identification of non-stationary hydrological processes and their drivers? It seems unconvincing to describe its advantages over hydrological modeling only through text. There have been many studies analyzing the non-stationary hydrological processes in the Weihe River, and there is a need to compare with them to enhance the reliability of the results, as well as to quantify the uncertainties.
Citation: https://doi.org/10.5194/hess-2024-118-RC2 -
AC2: 'Reply on RC2', Tongfang Li, 05 Aug 2024
Dear Anonymous Referee #2,
Thank you for your insightful comments. The suggestions are helpful in improving this manuscript. We have carefully studied, considered, and responded to all comments point-by-point. For clarity, the comments are given in black, and responses are given in blue text.
Yours sincerely,
Tongfang Li
E-mail: tongfangli@chd.eud.cn
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