the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Catchment water storage dynamics and its role in modulating streamflow generation in spectral perspective: a case study in the headwater of Baiyang Lake, China
Zhuping Sheng
Yanmin Yang
Shumin Han
Qingzhou Zhang
Huilong Li
Yonghui Yang
Abstract. Although it is important in hydrological cycles, catchment water storage dynamics is still not fully understood because it is affected by multiple drivers simultaneously and is difficult to be estimated using field hydrometric observations and hydrological models. Taking the headwater of Baiyang Lake, China as an example, this study employed a spectral approach to illustrate how catchment water storage was influenced by rainfall and vegetation, and how water storage modulated streamflow for the period of 1982–2015. The competence of the spectral approach in characterizing causality was verified and a more holistic understanding of hydrological cycles was gained. Results showed that under different climatic phases (wet/dry), catchment water storage dynamics were controlled by different factors and dominant streamflow generation mechanisms were not invariant. In the wet phase, catchment water storage dynamics was determined by rainfall. And groundwater flow was the most important part of streamflow, followed by subsurface flow and surface flow. Nevertheless, in the dry phase, catchment water storage dynamics was modulated by evapotranspiration. And the surface flow was the most important part of streamflow, followed by subsurface flow and groundwater flow. The land use change induced by human activities could alter the streamflow sensitivity to rainfall, but could not cause fundamental changes to hydrological cycles. We concluded that the spectral approach can be an effective supplement to the experimental methods and their integration can provide systematic insights into hydrological cycles in the study area and other watershed systems.
Xinyao Zhou et al.
Status: open (until 16 Mar 2023)
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RC1: 'Comment on hess-2022-357', Anonymous Referee #1, 31 Dec 2022
reply
Taking several catchments from North China, this paper used a spectral analysis approach, trying to illustrate how catchment water storage was influenced by rainfall and vegetation, and how water storage modulated streamflow for the period of 1982 - 2015. The topic is important and interesting. However, there are several major concerns to be further clarified before it can be considered for publication. The comments and suggestions are listed as following, hopefully they will be helpful to improve the manuscript.
Major comments:
- The focus and novelty of this paper is not clear. Are you trying to show that the spectral analysis is an effective method in demonstrating water storage dynamics? Or some new findings about catchment storage dynamics and runoff generation mechanisms?
- The manuscript is overall not well organized, and a clearer logic is needed. For example, the land use change or vegetation succession within four different catchments should be in the part of “Methods, Study Area, and Data”. Meanwhile, before further discussion, it is important to show what components are included in the catchment water storage in the study area, such as lakes, groundwater, soil water and weathered bedrock water. What is the most important one among them for catchment water storage dynamics? And why it is reasonable to attribute the water storage dynamics differences to vegetation root water uptake patterns between wet and dry phases?
- Data quality determines the reliability of final results. I don’t think it is appropriate to use precipitation data from only one station to represent the average level for the whole catchment, especially with large altitude gradient as shown in Figure 1.
- The language needs to be improved. For example, in line 24-25, what does “fundamental changes to hydrological cycles” mean?
Specific Comments
Line 103-105: It is not clear how spectral analysis method can be used to detect causality. Please explain more.
In section 2.3, it should be more clearly demonstrated how you processed different spatiotemporal resolution data. For example, why data from 1960-2015 were used for rainfall periodicity detection while others were based on data from 1982-2015? Does it have impact on final results? Similarly, different spatial-resolution ET products were used among the time series, the impact should be evaluated to make the results more convincing.
Line 196: How could ET lags behind water storage by 4 years? Can you interpretate this result with some physical phenomenon or evidence? This is also the base of using such spectral analysis methods to illustrate hydrological processes.
Line 212: Why there is a trough in April in the wet phase?
Line 236-237: why it is not “water storage determines ET”?
Line 242: Do you mean a higher contribution of subsurface flow to stream flow in the wet phase when compared with that in a dry phase?
Line 255-256 References are needed.
Line 267: How will the catchment characteristics impact storage dynamics and streamflow responses among 4 catchments?
Line 318: Is there any irrigation or groundwater/stream water pumping activity in the study area, which may also influence water storage dynamics.
Line 330: see major comment (2).
Line 322-327: the impact of land use change can be long-term lasting, so I doubt this argument.
Line 338: What do you mean “these plants decide that rainfall will increase…”?
Section 6: Conclusions need to be re-organized. One sentence for one paragraph is not a good way at least in my opinion.
Citation: https://doi.org/10.5194/hess-2022-357-RC1
Xinyao Zhou et al.
Xinyao Zhou et al.
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