the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Aug 2025
Declining runoff sensitivity to precipitation following permafrost degradation: Insights from event-scale runoff response in the Yellow River source region
Abstract. Frozen ground, including permafrost and seasonally frozen ground (SFG), is a critical component of the cryosphere. Rapid atmospheric warming has accelerated the degradation of frozen ground, profoundly altering hydrological processes in cold regions and affecting downstream water resources. Here we investigate the impacts of frozen ground degradation on event-scale runoff responses to daily precipitation in the source region of the Yellow River (SRYR) on the northeastern Tibetan Plateau using ensemble rainfall-runoff analysis (ERRA). ERRA is a data-driven, nonparametric, and model-independent method that quantifies dynamic, nonlinear, and spatially heterogeneous linkages between streamflow and precipitation. Applying ERRA, we evaluate changes in daily precipitation-streamflow coupling within the permafrost region, where frozen soil depth has decreased by ~0.1 m per decade, and within the SFG region, where frozen soil depth has remained relatively stable, declining by only 0.03 m per decade. Between 1979–1998 and 1999–2018, the permafrost zone experienced a 47 % reduction in peak runoff response per unit precipitation and a 32 % decrease in the 25-day runoff coefficient. By contrast, no substantial changes in runoff response were observed in the SFG region. Rising temperatures and increased active layer thickness in the permafrost zone have substantially reduced streamflow sensitivity to precipitation, particularly under higher precipitation intensities. Specifically, for daily precipitation intensities exceeding 10 mm d-1, peak runoff response in the permafrost zone declined by 73 % and the 25-day runoff coefficient declined by 72 % between the two periods. These changes likely result from increased hydraulic connectivity and water storage capacity within the thawing active layer, facilitating increased infiltration and subsurface storage. Our findings underscore the effectiveness of data-driven methods in capturing hydrological regime shifts and offer critical insights for drought mitigation and flood risk assessment in permafrost-affected regions amid ongoing climate warming.
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Status: closed
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RC1: 'Comment on egusphere-2025-3018', Anonymous Referee #1, 21 Aug 2025
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AC1: 'Reply on RC1', Yuting Yang, 26 Aug 2025
Response to Anonymous Referee #1’s comments:
Anonymous Referee #1 expresses the view that "this study does not find anything that was previously not known or not understood." However, what is "known" and "understood" depends on which side one takes in the ongoing debate over the hydrological impacts of permafrost degradation. On the one hand, several studies suggest that permafrost degradation enhances runoff, as the melting of ground ice releases additional water into the hydrological system (Kuang et al., 2024; Li et al., 2016; Ma et al., 2019; Walvoord and Kurylyk, 2016; Sun et al., 2019; see Manuscript Lines 52–58). On the other hand, other studies argue that permafrost degradation may reduce runoff, primarily due to the thickening of the active layer, which increases soil water storage capacity, enhances evaporation from the active layer, and weakens the barrier function of permafrost, thereby promoting infiltration (Cheng and Jin, 2013; Cheng and Wu, 2007; Guo et al., 2025; Qiu, 2012; Wang et al., 2018; Yang et al., 2023; see Manuscript Lines 58–63). Because this topic remains under debate, with diametrically opposing views in the recent literature, almost any result (either ours, for example, or the exact opposite) could be rhetorically dismissed as nothing "that was not previously known" – at least by somebody, on some side of the current debate.
But of course, it is precisely because of this debate that new analyses and new lines of evidence, like those we present, are particularly important. In particular, the specific focus of our analysis (how permafrost thawing affects streamflow peaks, rather than average streamflow, assessed from real-world data rather than simulation models) has remained, to our knowledge, unexplored in the literature to date.
The referee says that our study "simply quantifies the effect of permafrost loss using recently developed methods." We note that actually quantifying the effect of permafrost loss on whole-basin stormflow response to precipitation – directly from data, not from simulation models with their associated assumptions – is something that has not been attempted before. We further note that doing this is far from "simple", as our analysis shows. In particular, our paper demonstrates how it is possible to separate the effects of precipitation falling in the permafrost region versus in the seasonally frozen ground region, even though these effects are overprinted on one another in Tangnaihai river discharge. The necessary methodology for this was only proposed last year (Kirchner, 2024) and our study represents the first large-scale application of this approach.
Our analysis of hydrological responses to permafrost degradation is based on real-world observational data (i.e., runoff, precipitation, temperature, etc.) rather than hydrological modeling. Ensemble rainfall-runoff analysis (ERRA) is a data-driven approach that operates independently of the predefined assumptions inherent in hydrological models (Gao et al., 2018; Zheng et al., 2018; Yi et al., 2014), thereby enhancing the robustness of our findings. Moreover, compared with conventional statistical methods (e.g., Hu et al., 2011; Ma et al., 2019; Wang et al., 2018; Wu et al., 2020; Chang et al., 2024), ERRA enables analyses at shorter temporal scales (e.g., event scale), across heterogeneous spatial domains, and under different rainfall intensities. This flexibility allows us to design a variety of controlled experiments to quantitatively assess how thawing permafrost alters runoff generation, relying solely on observed data (see Manuscript Lines 63-93).
Our study provides the first event-scale observational evidence that runoff sensitivity to rainfall (as distinct from the sensitivity of total runoff to rainfall) is substantially reduced in degrading permafrost regions. Compared with conventional statistical methods based on observations, ERRA enables analyses at shorter temporal scales, over heterogeneous spatial domains, and across wide ranges of rainfall intensities.
The reviewer points out that our study "does contribute positively to the debate on what happens to river flow with the rise in global temperatures in the presence of permafrost/seasonally frozen ground." The reviewer also "did not find anything that can be improved significantly in this study."
For all of the reasons outlined above, we believe that the reviewer's call for rejection is not supported by a balanced view of our work and its scientific context.
Reference
Chang, Y., Ding, Y., Zhang, S., Zhao, Q., Jin, Z., Qin, J., and Shangguan, D.: Quantifying the response of runoff to glacier shrinkage and permafrost degradation in a typical cryospheric basin on the Tibetan Plateau, Catena, 242, 108124, https://doi.org/10.1016/j.catena.2024.108124, 2024.
Cheng, G. and Jin, H.: Permafrost and groundwater on the Qinghai–Tibet Plateau and in northeast China, Hydrogeol. J., 21, 5, https://doi.org/10.1007/s10040-012-0927-2, 2013.
Cheng, G. and Wu, T.: Responses of permafrost to climate change and their environmental significance, Qinghai–Tibet Plateau, J. Geophys. Res.-Earth, 112, https://doi.org/10.1029/2006JF000631, 2007.
Gao, B., Yang, D., Qin, Y., Wang, Y., Li, H., Zhang, Y., and Zhang, T.: Change in frozen soils and its effect on regional hydrology, upper Heihe basin, northeastern Qinghai–Tibetan Plateau, The Cryosphere, 12, 657–673, https://doi.org/10.5194/tc-12-657-2018, 2018.
Guo, L., Wang, G., Song, C., Sun, S., Li, J., Li, K., et al.: Hydrological changes caused by integrated warming, wetting, and greening in permafrost regions of the Qinghai-Tibetan Plateau, Water Resour. Res., 61, e2024WR038465, https://doi.org/10.1029/2024WR038465, 2025.
Hu, Y., Maskey, S., Uhlenbrook, S., and Zhao, H.: Streamflow trends and climate linkages in the source region of the Yellow River, China, Hydrol. Process., 25, 3399–3411, https://doi.org/10.1002/hyp.8069, 2011.
Kirchner, J. W.: Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using ensemble rainfall–runoff analysis (ERRA): proof of concept, Hydrol. Earth Syst. Sci., 28, 4427–4454, https://doi.org/10.5194/hess-28-4427-2024, 2024.
Kuang, X., Liu, J., Scanlon, B. R., Jiao, J. J., Jasechko, S., Lancia, M., and Zheng, C.: The changing nature of groundwater in the global water cycle, Science, 383, eadf0630, https://doi.org/10.1126/science.adf0630, 2024.
Li, Z., Feng, Q., Wang, Q. J., Yong, S., Li, J., Li, Y., and Wang, Y.: Quantitative evaluation on the influence from cryosphere meltwater on runoff in an inland river basin of China, Glob. Planet. Change, 143, 189–195, https://doi.org/10.1016/j.gloplacha.2016.06.005, 2016.
Ma, Q., Jin, H., Bense, V. F., Luo, D., Marchenko, S. S., Harris, S. A., and Lan, Y.: Impacts of degrading permafrost on streamflow in the source area of Yellow River on the Qinghai-Tibet Plateau, China, Adv. Clim. Change Res., 10, 225–239, https://doi.org/10.1016/j.accre.2020.02.001, 2019.
Qiu, J.: Thawing permafrost reduces river runoff, Nature, 6, https://doi.org/10.1038/nature.2012.9749, 2012.
Sun, A., Yu, Z., Zhou, J., Acharya, K., Ju, Q., Xing, R., ... & Wen, L.: Quantified hydrological responses to permafrost degradation in the headwaters of the Yellow River (HWYR) in High Asia. Sci. Total Environ., 712, 135632. https://doi.org/10.1016/j.scitotenv.2019.135632, 2020
Walvoord, M. A., and Kurylyk, B. L.: Hydrologic impacts of thawing permafrost—A review, Vadose Zone J., 15, vzj2016-01, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Wang, T., Yang, H., Yang, D., Qin, Y., and Wang, Y.: Quantifying the streamflow response to frozen ground degradation in the source region of the Yellow River within the Budyko framework, J. Hydrol., 558, 301–313, https://doi.org/10.1016/j.jhydrol.2018.01.050, 2018.
Wu, P., Liang, S., Wang, X. S., McKenzie, J. M., and Feng, Y.: Climate change impacts on cold season runoff in the headwaters of the Yellow River considering frozen ground degradation, Water, 12, 602, https://doi.org/10.3390/w12020602, 2020.
Yang, J., Wang, T., Yang, D., and Yang, Y.: Insights into runoff changes in the source region of Yellow River under frozen ground degradation, J. Hydrol., 617, 128892, https://doi.org/10.1016/j.jhydrol.2022.128892, 2023.
Yi, S., Wang, X., Qin, Y., Xiang, B., and Ding, Y.: Responses of alpine grassland on Qinghai–Tibetan Plateau to climate warming and permafrost degradation: a modeling perspective, Environ. Res. Lett., 9, 074014, https://doi.org/10.1088/1748-9326/9/7/074014, 2014.
Zheng, D., van der Velde, R., Su, Z., Wen, J., Wang, X., and Yang, K.: Impact of soil freeze-thaw mechanism on the runoff dynamics of two Tibetan rivers, J. Hydrol., 563, 382–394, https://doi.org/10.1016/j.jhydrol.2018.06.024, 2018.
Citation: https://doi.org/10.5194/egusphere-2025-3018-AC1
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AC1: 'Reply on RC1', Yuting Yang, 26 Aug 2025
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RC2: 'Comment on egusphere-2025-3018', Anonymous Referee #2, 02 Oct 2025
Greetings. I revised the paper entitled ‘Declining runoff sensitivity to precipitation following permafrost degradation: Insights from event-scale runoff response in the Yellow River source region’. The work deals with eventual changes in hydrological phenomena due to a decreasing frozen soil cover in the Yellow River Region.
The main novel aspects that the work aims to underline are, as far as I understood, two, mainly due to altered components of the hydrological cycle: (i) a negligible variation in runoff and (ii) an increased storage capacity of the soil. I appreciated the research questions, the overall data employed, and the conceptualization of the changes, especially in groundwater regimes due to alteration in the frozen soil cover, hence in the terms coming into the hydrological cycle.
However, the work only quantifies runoff changes at one location, namely the stream gauge located in the city of Tangnaihai. Moreover, the conceived changes in the groundwater regimes are just inferred, hence indirectly achieved from considering other variables, such as precipitation, in the hydrological cycle.
From the surface water viewpoint, my feeling is that analyzing just one stream gauge does not depict the whole portrait about how much runoff fluxes could vary in the analyzed catchment. Hence, I would suggest employing at least a 1-D mathematical model, maybe based upon the network theory, to appraise the spatially-distributed patterns of such variations. Indeed, whereas the gross outlet discharge does change, no specifications about local variations, their topographical or geological dependences, or stream-wise ones are given. We may have different contributions from streams of different Horton ranks, and this info would be much more interesting and valuable.
From the groundwater viewpoint, the paper seems even weaker. Such inferred climate-related regime variations should be subject to a numerical model, even a surrogate one, before making conclusions. Moreover, no spatially distributed patterns related to the variation of the spatial frozen soil cover, i.e., the spatial distribution of porosities or hydraulic conductivity, are given. It is not enough to say that, overall, the hydraulic conductivity of the soil would vary, easing groundwater storage via infiltration. Conclusions like these must be supported by (i) numerical simulations, (ii) a heterogeneous appraisal of soil properties, and (iii) the knowledge of preferential groundwater pathways. Without these three key knowledge sources, I think every effort for quantifying or even analyzing in detail groundwater patterns would not be enough.
The work seems somewhat at a draft stage. Therefore, for the reasons above, I suggest rejecting the manuscript in its current form. More research and spatially distributed outcomes are required for research to be outstanding, as the HESS journal deserves.
I wish the Authors the best of luck in improving it. I suggest some further readings for both the surface and the groundwater parts of the analysis. Best regards.
Surface part:
Zuecco, G., Rinderer, M., Penna, D., Borga, M., van Meerveld, H.J., 2019. Quantification of subsurface hydrologic connectivity in four headwater catchments using graph theory. Sci. Total Environ. 646, 1265–1280. https://doi.org/10.1016/j.scitotenv.2018.07.269.
Groundwater part:
Schiavo, M., Riva, M., Guadagnini, L., Zehe, E., Guadagnini, A., 2021. Probabilistic identification of preferential groundwater networks. J. Hydrol. 610 (July 2022) https://doi.org/10.1016/j.jhydrol.2022.127906.
Zehe, E., Loritz, R., Edery, Y., and Berkowitz, B.: Preferential pathways for fluid and solutes in heterogeneous groundwater systems: self-organization, entropy, work, Hydrol. Earth Syst. Sci., 25, 5337–5353, https://doi.org/10.5194/hess-25-5337-2021, 2021.
Citation: https://doi.org/10.5194/egusphere-2025-3018-RC2 -
AC2: 'Reply on RC2', Yuting Yang, 09 Oct 2025
We understand Anonymous Referee #2’s concern that “analyzing just one stream gauge does not depict the whole portrait about how much runoff fluxes could vary in the analyzed catchment,” because this is precisely the challenge our study addresses. Streamflow gauge networks are sparse, and often one wants to understand the hydrological behavior of sub-basins that are not themselves individually gauged. Simulation models offer one approach, but decades of studies have shown that successful calibration of a hydrological model is no guarantee that it correctly represents the phenomena at work in the surrounding catchment. And traditional statistical methods predominantly focus on long-term average streamflow variations, and generally lack the capacity to resolve spatial heterogeneity in runoff responses, unless different land surface types coincide with distinct gauged basins — exactly as the referee has pointed out.
To overcome these limitations in the current state of the art, we applied a newly developed mathematical framework, the Ensemble Rainfall–Runoff Analysis (ERRA) proposed by Kirchner (2024) last year. ERRA enables the quantification of nonlinear, nonstationary, and spatially heterogeneous hydrologic responses directly from observational data. Crucially, it allows the differentiation and quantification of runoff responses from multiple land surface types even when they are not individually gauged. This is made possible by the spatio-temporal heterogeneity of precipitation patterns. By correlating the runoff dynamics at the catchment outlet with precipitation patterns in a specified region upstream (e.g., an individual land surface type), as well as in the rest of the catchment, ERRA can quantify the runoff response of parts of the catchment that are not individually gauged (Kirchner, 2024).
Our Figure 4 demonstrates ERRA’s capability in distinguishing runoff responses from different locations within the catchment. Specifically, ERRA can simultaneously deconvolve the streamflow observed at the Tangnaihai station into runoff responses to precipitation in the upper and lower sub-basins (Figure 4b). This capability is further validated by comparing the observed discharge from the Maqu station with what ERRA predicts for the runoff response at Tangnaihai from precipitation falling above Maqu (Figure 4c). These results confirm that ERRA effectively captures the “local variations” that the referee was concerned about, inferred directly from data. Hence, although our analysis uses observations from a limited number of gauges (as will be inherently true of any study based on real-world data), ERRA enables us to infer the spatial organization of runoff generation processes across the basin in a physically consistent and observation-based manner.
This validation provides the foundation for our subsequent analysis of runoff responses in the permafrost and seasonally frozen ground regions. These regions do not align with basin boundaries, and thus gauging stations cannot measure runoff contributions from each region independently. Instead, runoff signals from both regions are integrated within the streamflow observed at Tangnaihai. The key challenge, therefore, lies in separating these mixed signals. This can be achieved using ERRA’s deconvolution and demixing capabilities, which jointly analyze the effects of precipitation in the permafrost and seasonally frozen ground regions.
Anonymous Referee #2 also suggested “employing numerical models for the surface water and groundwater analyses”. It is important to clarify that our study intentionally avoids using simulation models, as these models face substantial challenges in accurately representing the complex water–thermal interactions inherent in frozen soils. Such challenges include quantifying phase-change latent heat fluxes and the associated soil pore structure modifications, as well as parameterizing soil moisture and heat fluxes while accounting for their substantial spatial variability (Gao et al., 2021; Walvoord and Kurylyk, 2016; Andreson et al., 2020; Harp et al., 2016; Lawrence and Slater, 2008). We also note that the reviewer asks for things like "the spatial distribution of porosities or hydraulic conductivity" and "the knowledge of preferential groundwater pathways", for which no reliable real-world data are available anywhere in the world, except for small experimental catchments many orders of magnitude smaller than our study region.
Therefore, our goal is to infer runoff response to frozen ground degradation directly from observational data, without relying on any physical model assumptions or parameterizations. This is made possible through ERRA, as introduced above, which is a data-driven approach that operates independently of the predefined assumptions inherent in traditional hydrological models (Gao et al., 2018; Zheng et al., 2018; Yi et al., 2014), thereby enhancing the robustness and transparency of our findings. Moreover, compared with conventional statistical methods (e.g., Hu et al., 2011; Ma et al., 2019; Wang et al., 2018; Wu et al., 2020; Chang et al., 2024), ERRA allows for analysis at shorter temporal scales (e.g., event scale), across heterogeneous spatial domains, and under varying rainfall intensities. This flexibility enables us to use natural variations in weather drivers to conduct natural experiments that quantitatively assess how thawing frozen ground alters runoff generation—relying solely on observational data.
For all the reasons outlined above, we kindly ask the editor to recognize that the central aim of our study is to analyze runoff responses to frozen ground degradation without invoking the myriad unverifiable assumptions inherent in physical models, and instead relying solely on real-world observations through the novel ERRA framework. This approach directly addresses the referee’s concerns regarding spatial variability and provides an independent, data-driven perspective on frozen-ground hydrology. We therefore believe that the reviewer’s call for rejection does not reflect the scientific intent and methodological innovation of our work.
References
Andresen, C. G., Lawrence, D. M., Wilson, C. J., McGuire, A. D., Koven, C., Schaefer, K., et al.: Soil moisture and hydrology projections of the permafrost region-a model intercomparison, The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, 2020.
Chang, Y., Ding, Y., Zhang, S., Zhao, Q., Jin, Z., Qin, J., and Shangguan, D.: Quantifying the response of runoff to glacier shrinkage and permafrost degradation in a typical cryospheric basin on the Tibetan Plateau, Catena, 242, 108124, https://doi.org/10.1016/j.catena.2024.108124, 2024.
Gao, B., Yang, D., Qin, Y., Wang, Y., Li, H., Zhang, Y., and Zhang, T.: Change in frozen soils and its effect on regional hydrology, upper Heihe basin, northeastern Qinghai–Tibetan Plateau, The Cryosphere, 12, 657–673, https://doi.org/10.5194/tc-12-657-2018, 2018.
Gao, B., Yang, D., Qin, Y., Wang, Y., Li, H., Zhang, Y., and Zhang, T.: Change in frozen soils and its effect on regional hydrology, upper Heihe basin, northeastern Qinghai–Tibetan Plateau, The Cryosphere, 12, 657–673, https://doi.org/10.5194/tc-12-657-2018, 2018.
Harp, D. R., Atchley, A. L., Painter, S. L., Coon, E. T., Wilson, C. J., Romanovsky, V. E., and Rowland, J. C.: Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis, The Cryosphere, 10, 341–358, https://doi.org/10.5194/tc-10-341-2016, 2016.
Hu, Y., Maskey, S., Uhlenbrook, S., and Zhao, H.: Streamflow trends and climate linkages in the source region of the Yellow River, China, Hydrol. Process., 25, 3399–3411, https://doi.org/10.1002/hyp.8069, 2011.
Kirchner, J. W.: Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using ensemble rainfall–runoff analysis (ERRA): proof of concept, Hydrol. Earth Syst. Sci., 28, 4427–4454, https://doi.org/10.5194/hess-28-4427-2024, 2024.
Lawrence, D. M. and Slater, A. G.: Incorporating organic soil into a global climate model, Clim. Dyn., 30, 145–160, https://doi.org/10.1007/s00382-007-0278-1, 2008.
Ma, Q., Jin, H., Bense, V. F., Luo, D., Marchenko, S. S., Harris, S. A., and Lan, Y.: Impacts of degrading permafrost on streamflow in the source area of Yellow River on the Qinghai-Tibet Plateau, China, Adv. Clim. Change Res., 10, 225–239, https://doi.org/10.1016/j.accre.2020.02.001, 2019.
Walvoord, M. A., and Kurylyk, B. L.: Hydrologic impacts of thawing permafrost—A review, Vadose Zone J., 15, vzj2016-01, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Wang, T., Yang, H., Yang, D., Qin, Y., and Wang, Y.: Quantifying the streamflow response to frozen ground degradation in the source region of the Yellow River within the Budyko framework, J. Hydrol., 558, 301–313, https://doi.org/10.1016/j.jhydrol.2018.01.050, 2018.
Wu, P., Liang, S., Wang, X. S., McKenzie, J. M., and Feng, Y.: Climate change impacts on cold season runoff in the headwaters of the Yellow River considering frozen ground degradation, Water, 12, 602, https://doi.org/10.3390/w12020602, 2020.
Yi, S., Wang, X., Qin, Y., Xiang, B., and Ding, Y.: Responses of alpine grassland on Qinghai–Tibetan Plateau to climate warming and permafrost degradation: a modeling perspective, Environ. Res. Lett., 9, 074014, https://doi.org/10.1088/1748-9326/9/7/074014, 2014.
Zheng, D., van der Velde, R., Su, Z., Wen, J., Wang, X., and Yang, K.: Impact of soil freeze-thaw mechanism on the runoff dynamics of two Tibetan rivers, J. Hydrol., 563, 382–394, https://doi.org/10.1016/j.jhydrol.2018.06.024, 2018.
Citation: https://doi.org/10.5194/egusphere-2025-3018-AC2
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AC2: 'Reply on RC2', Yuting Yang, 09 Oct 2025
Status: closed
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RC1: 'Comment on egusphere-2025-3018', Anonymous Referee #1, 21 Aug 2025
Dear authors,
Your study deals with the quantification of change in runoff response to rainfall in a river that has partial permafrost and partially seasonally frozen ground using existing techniques.
My impression is that this study does not find anything that was previously not known or not understood. It simply quantifies the effect of permafrost loss using recently developed methods. However, it does contribute positively to the debate on what happens to river flow with the rise in global temperatures in the presence of permafrost/seasonally frozen ground. To be honest, I did not find anything that can be improved significantly in this study, as it is simply an application of existing data and techniques. The authors were meticulous with the application and tested various hypotheses to make sure that their claims are valid. It is very clear that they know what they are doing.
A lot of work went in to this paper, I am not denying that. However, I do not see this study to be at the level that justifies its publication in a prestigious journal like HESS. It is better suited to a journal that deals with regional studies, IMO. I am asking for a rejection.
Citation: https://doi.org/10.5194/egusphere-2025-3018-RC1 -
AC1: 'Reply on RC1', Yuting Yang, 26 Aug 2025
Response to Anonymous Referee #1’s comments:
Anonymous Referee #1 expresses the view that "this study does not find anything that was previously not known or not understood." However, what is "known" and "understood" depends on which side one takes in the ongoing debate over the hydrological impacts of permafrost degradation. On the one hand, several studies suggest that permafrost degradation enhances runoff, as the melting of ground ice releases additional water into the hydrological system (Kuang et al., 2024; Li et al., 2016; Ma et al., 2019; Walvoord and Kurylyk, 2016; Sun et al., 2019; see Manuscript Lines 52–58). On the other hand, other studies argue that permafrost degradation may reduce runoff, primarily due to the thickening of the active layer, which increases soil water storage capacity, enhances evaporation from the active layer, and weakens the barrier function of permafrost, thereby promoting infiltration (Cheng and Jin, 2013; Cheng and Wu, 2007; Guo et al., 2025; Qiu, 2012; Wang et al., 2018; Yang et al., 2023; see Manuscript Lines 58–63). Because this topic remains under debate, with diametrically opposing views in the recent literature, almost any result (either ours, for example, or the exact opposite) could be rhetorically dismissed as nothing "that was not previously known" – at least by somebody, on some side of the current debate.
But of course, it is precisely because of this debate that new analyses and new lines of evidence, like those we present, are particularly important. In particular, the specific focus of our analysis (how permafrost thawing affects streamflow peaks, rather than average streamflow, assessed from real-world data rather than simulation models) has remained, to our knowledge, unexplored in the literature to date.
The referee says that our study "simply quantifies the effect of permafrost loss using recently developed methods." We note that actually quantifying the effect of permafrost loss on whole-basin stormflow response to precipitation – directly from data, not from simulation models with their associated assumptions – is something that has not been attempted before. We further note that doing this is far from "simple", as our analysis shows. In particular, our paper demonstrates how it is possible to separate the effects of precipitation falling in the permafrost region versus in the seasonally frozen ground region, even though these effects are overprinted on one another in Tangnaihai river discharge. The necessary methodology for this was only proposed last year (Kirchner, 2024) and our study represents the first large-scale application of this approach.
Our analysis of hydrological responses to permafrost degradation is based on real-world observational data (i.e., runoff, precipitation, temperature, etc.) rather than hydrological modeling. Ensemble rainfall-runoff analysis (ERRA) is a data-driven approach that operates independently of the predefined assumptions inherent in hydrological models (Gao et al., 2018; Zheng et al., 2018; Yi et al., 2014), thereby enhancing the robustness of our findings. Moreover, compared with conventional statistical methods (e.g., Hu et al., 2011; Ma et al., 2019; Wang et al., 2018; Wu et al., 2020; Chang et al., 2024), ERRA enables analyses at shorter temporal scales (e.g., event scale), across heterogeneous spatial domains, and under different rainfall intensities. This flexibility allows us to design a variety of controlled experiments to quantitatively assess how thawing permafrost alters runoff generation, relying solely on observed data (see Manuscript Lines 63-93).
Our study provides the first event-scale observational evidence that runoff sensitivity to rainfall (as distinct from the sensitivity of total runoff to rainfall) is substantially reduced in degrading permafrost regions. Compared with conventional statistical methods based on observations, ERRA enables analyses at shorter temporal scales, over heterogeneous spatial domains, and across wide ranges of rainfall intensities.
The reviewer points out that our study "does contribute positively to the debate on what happens to river flow with the rise in global temperatures in the presence of permafrost/seasonally frozen ground." The reviewer also "did not find anything that can be improved significantly in this study."
For all of the reasons outlined above, we believe that the reviewer's call for rejection is not supported by a balanced view of our work and its scientific context.
Reference
Chang, Y., Ding, Y., Zhang, S., Zhao, Q., Jin, Z., Qin, J., and Shangguan, D.: Quantifying the response of runoff to glacier shrinkage and permafrost degradation in a typical cryospheric basin on the Tibetan Plateau, Catena, 242, 108124, https://doi.org/10.1016/j.catena.2024.108124, 2024.
Cheng, G. and Jin, H.: Permafrost and groundwater on the Qinghai–Tibet Plateau and in northeast China, Hydrogeol. J., 21, 5, https://doi.org/10.1007/s10040-012-0927-2, 2013.
Cheng, G. and Wu, T.: Responses of permafrost to climate change and their environmental significance, Qinghai–Tibet Plateau, J. Geophys. Res.-Earth, 112, https://doi.org/10.1029/2006JF000631, 2007.
Gao, B., Yang, D., Qin, Y., Wang, Y., Li, H., Zhang, Y., and Zhang, T.: Change in frozen soils and its effect on regional hydrology, upper Heihe basin, northeastern Qinghai–Tibetan Plateau, The Cryosphere, 12, 657–673, https://doi.org/10.5194/tc-12-657-2018, 2018.
Guo, L., Wang, G., Song, C., Sun, S., Li, J., Li, K., et al.: Hydrological changes caused by integrated warming, wetting, and greening in permafrost regions of the Qinghai-Tibetan Plateau, Water Resour. Res., 61, e2024WR038465, https://doi.org/10.1029/2024WR038465, 2025.
Hu, Y., Maskey, S., Uhlenbrook, S., and Zhao, H.: Streamflow trends and climate linkages in the source region of the Yellow River, China, Hydrol. Process., 25, 3399–3411, https://doi.org/10.1002/hyp.8069, 2011.
Kirchner, J. W.: Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using ensemble rainfall–runoff analysis (ERRA): proof of concept, Hydrol. Earth Syst. Sci., 28, 4427–4454, https://doi.org/10.5194/hess-28-4427-2024, 2024.
Kuang, X., Liu, J., Scanlon, B. R., Jiao, J. J., Jasechko, S., Lancia, M., and Zheng, C.: The changing nature of groundwater in the global water cycle, Science, 383, eadf0630, https://doi.org/10.1126/science.adf0630, 2024.
Li, Z., Feng, Q., Wang, Q. J., Yong, S., Li, J., Li, Y., and Wang, Y.: Quantitative evaluation on the influence from cryosphere meltwater on runoff in an inland river basin of China, Glob. Planet. Change, 143, 189–195, https://doi.org/10.1016/j.gloplacha.2016.06.005, 2016.
Ma, Q., Jin, H., Bense, V. F., Luo, D., Marchenko, S. S., Harris, S. A., and Lan, Y.: Impacts of degrading permafrost on streamflow in the source area of Yellow River on the Qinghai-Tibet Plateau, China, Adv. Clim. Change Res., 10, 225–239, https://doi.org/10.1016/j.accre.2020.02.001, 2019.
Qiu, J.: Thawing permafrost reduces river runoff, Nature, 6, https://doi.org/10.1038/nature.2012.9749, 2012.
Sun, A., Yu, Z., Zhou, J., Acharya, K., Ju, Q., Xing, R., ... & Wen, L.: Quantified hydrological responses to permafrost degradation in the headwaters of the Yellow River (HWYR) in High Asia. Sci. Total Environ., 712, 135632. https://doi.org/10.1016/j.scitotenv.2019.135632, 2020
Walvoord, M. A., and Kurylyk, B. L.: Hydrologic impacts of thawing permafrost—A review, Vadose Zone J., 15, vzj2016-01, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Wang, T., Yang, H., Yang, D., Qin, Y., and Wang, Y.: Quantifying the streamflow response to frozen ground degradation in the source region of the Yellow River within the Budyko framework, J. Hydrol., 558, 301–313, https://doi.org/10.1016/j.jhydrol.2018.01.050, 2018.
Wu, P., Liang, S., Wang, X. S., McKenzie, J. M., and Feng, Y.: Climate change impacts on cold season runoff in the headwaters of the Yellow River considering frozen ground degradation, Water, 12, 602, https://doi.org/10.3390/w12020602, 2020.
Yang, J., Wang, T., Yang, D., and Yang, Y.: Insights into runoff changes in the source region of Yellow River under frozen ground degradation, J. Hydrol., 617, 128892, https://doi.org/10.1016/j.jhydrol.2022.128892, 2023.
Yi, S., Wang, X., Qin, Y., Xiang, B., and Ding, Y.: Responses of alpine grassland on Qinghai–Tibetan Plateau to climate warming and permafrost degradation: a modeling perspective, Environ. Res. Lett., 9, 074014, https://doi.org/10.1088/1748-9326/9/7/074014, 2014.
Zheng, D., van der Velde, R., Su, Z., Wen, J., Wang, X., and Yang, K.: Impact of soil freeze-thaw mechanism on the runoff dynamics of two Tibetan rivers, J. Hydrol., 563, 382–394, https://doi.org/10.1016/j.jhydrol.2018.06.024, 2018.
Citation: https://doi.org/10.5194/egusphere-2025-3018-AC1
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AC1: 'Reply on RC1', Yuting Yang, 26 Aug 2025
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RC2: 'Comment on egusphere-2025-3018', Anonymous Referee #2, 02 Oct 2025
Greetings. I revised the paper entitled ‘Declining runoff sensitivity to precipitation following permafrost degradation: Insights from event-scale runoff response in the Yellow River source region’. The work deals with eventual changes in hydrological phenomena due to a decreasing frozen soil cover in the Yellow River Region.
The main novel aspects that the work aims to underline are, as far as I understood, two, mainly due to altered components of the hydrological cycle: (i) a negligible variation in runoff and (ii) an increased storage capacity of the soil. I appreciated the research questions, the overall data employed, and the conceptualization of the changes, especially in groundwater regimes due to alteration in the frozen soil cover, hence in the terms coming into the hydrological cycle.
However, the work only quantifies runoff changes at one location, namely the stream gauge located in the city of Tangnaihai. Moreover, the conceived changes in the groundwater regimes are just inferred, hence indirectly achieved from considering other variables, such as precipitation, in the hydrological cycle.
From the surface water viewpoint, my feeling is that analyzing just one stream gauge does not depict the whole portrait about how much runoff fluxes could vary in the analyzed catchment. Hence, I would suggest employing at least a 1-D mathematical model, maybe based upon the network theory, to appraise the spatially-distributed patterns of such variations. Indeed, whereas the gross outlet discharge does change, no specifications about local variations, their topographical or geological dependences, or stream-wise ones are given. We may have different contributions from streams of different Horton ranks, and this info would be much more interesting and valuable.
From the groundwater viewpoint, the paper seems even weaker. Such inferred climate-related regime variations should be subject to a numerical model, even a surrogate one, before making conclusions. Moreover, no spatially distributed patterns related to the variation of the spatial frozen soil cover, i.e., the spatial distribution of porosities or hydraulic conductivity, are given. It is not enough to say that, overall, the hydraulic conductivity of the soil would vary, easing groundwater storage via infiltration. Conclusions like these must be supported by (i) numerical simulations, (ii) a heterogeneous appraisal of soil properties, and (iii) the knowledge of preferential groundwater pathways. Without these three key knowledge sources, I think every effort for quantifying or even analyzing in detail groundwater patterns would not be enough.
The work seems somewhat at a draft stage. Therefore, for the reasons above, I suggest rejecting the manuscript in its current form. More research and spatially distributed outcomes are required for research to be outstanding, as the HESS journal deserves.
I wish the Authors the best of luck in improving it. I suggest some further readings for both the surface and the groundwater parts of the analysis. Best regards.
Surface part:
Zuecco, G., Rinderer, M., Penna, D., Borga, M., van Meerveld, H.J., 2019. Quantification of subsurface hydrologic connectivity in four headwater catchments using graph theory. Sci. Total Environ. 646, 1265–1280. https://doi.org/10.1016/j.scitotenv.2018.07.269.
Groundwater part:
Schiavo, M., Riva, M., Guadagnini, L., Zehe, E., Guadagnini, A., 2021. Probabilistic identification of preferential groundwater networks. J. Hydrol. 610 (July 2022) https://doi.org/10.1016/j.jhydrol.2022.127906.
Zehe, E., Loritz, R., Edery, Y., and Berkowitz, B.: Preferential pathways for fluid and solutes in heterogeneous groundwater systems: self-organization, entropy, work, Hydrol. Earth Syst. Sci., 25, 5337–5353, https://doi.org/10.5194/hess-25-5337-2021, 2021.
Citation: https://doi.org/10.5194/egusphere-2025-3018-RC2 -
AC2: 'Reply on RC2', Yuting Yang, 09 Oct 2025
We understand Anonymous Referee #2’s concern that “analyzing just one stream gauge does not depict the whole portrait about how much runoff fluxes could vary in the analyzed catchment,” because this is precisely the challenge our study addresses. Streamflow gauge networks are sparse, and often one wants to understand the hydrological behavior of sub-basins that are not themselves individually gauged. Simulation models offer one approach, but decades of studies have shown that successful calibration of a hydrological model is no guarantee that it correctly represents the phenomena at work in the surrounding catchment. And traditional statistical methods predominantly focus on long-term average streamflow variations, and generally lack the capacity to resolve spatial heterogeneity in runoff responses, unless different land surface types coincide with distinct gauged basins — exactly as the referee has pointed out.
To overcome these limitations in the current state of the art, we applied a newly developed mathematical framework, the Ensemble Rainfall–Runoff Analysis (ERRA) proposed by Kirchner (2024) last year. ERRA enables the quantification of nonlinear, nonstationary, and spatially heterogeneous hydrologic responses directly from observational data. Crucially, it allows the differentiation and quantification of runoff responses from multiple land surface types even when they are not individually gauged. This is made possible by the spatio-temporal heterogeneity of precipitation patterns. By correlating the runoff dynamics at the catchment outlet with precipitation patterns in a specified region upstream (e.g., an individual land surface type), as well as in the rest of the catchment, ERRA can quantify the runoff response of parts of the catchment that are not individually gauged (Kirchner, 2024).
Our Figure 4 demonstrates ERRA’s capability in distinguishing runoff responses from different locations within the catchment. Specifically, ERRA can simultaneously deconvolve the streamflow observed at the Tangnaihai station into runoff responses to precipitation in the upper and lower sub-basins (Figure 4b). This capability is further validated by comparing the observed discharge from the Maqu station with what ERRA predicts for the runoff response at Tangnaihai from precipitation falling above Maqu (Figure 4c). These results confirm that ERRA effectively captures the “local variations” that the referee was concerned about, inferred directly from data. Hence, although our analysis uses observations from a limited number of gauges (as will be inherently true of any study based on real-world data), ERRA enables us to infer the spatial organization of runoff generation processes across the basin in a physically consistent and observation-based manner.
This validation provides the foundation for our subsequent analysis of runoff responses in the permafrost and seasonally frozen ground regions. These regions do not align with basin boundaries, and thus gauging stations cannot measure runoff contributions from each region independently. Instead, runoff signals from both regions are integrated within the streamflow observed at Tangnaihai. The key challenge, therefore, lies in separating these mixed signals. This can be achieved using ERRA’s deconvolution and demixing capabilities, which jointly analyze the effects of precipitation in the permafrost and seasonally frozen ground regions.
Anonymous Referee #2 also suggested “employing numerical models for the surface water and groundwater analyses”. It is important to clarify that our study intentionally avoids using simulation models, as these models face substantial challenges in accurately representing the complex water–thermal interactions inherent in frozen soils. Such challenges include quantifying phase-change latent heat fluxes and the associated soil pore structure modifications, as well as parameterizing soil moisture and heat fluxes while accounting for their substantial spatial variability (Gao et al., 2021; Walvoord and Kurylyk, 2016; Andreson et al., 2020; Harp et al., 2016; Lawrence and Slater, 2008). We also note that the reviewer asks for things like "the spatial distribution of porosities or hydraulic conductivity" and "the knowledge of preferential groundwater pathways", for which no reliable real-world data are available anywhere in the world, except for small experimental catchments many orders of magnitude smaller than our study region.
Therefore, our goal is to infer runoff response to frozen ground degradation directly from observational data, without relying on any physical model assumptions or parameterizations. This is made possible through ERRA, as introduced above, which is a data-driven approach that operates independently of the predefined assumptions inherent in traditional hydrological models (Gao et al., 2018; Zheng et al., 2018; Yi et al., 2014), thereby enhancing the robustness and transparency of our findings. Moreover, compared with conventional statistical methods (e.g., Hu et al., 2011; Ma et al., 2019; Wang et al., 2018; Wu et al., 2020; Chang et al., 2024), ERRA allows for analysis at shorter temporal scales (e.g., event scale), across heterogeneous spatial domains, and under varying rainfall intensities. This flexibility enables us to use natural variations in weather drivers to conduct natural experiments that quantitatively assess how thawing frozen ground alters runoff generation—relying solely on observational data.
For all the reasons outlined above, we kindly ask the editor to recognize that the central aim of our study is to analyze runoff responses to frozen ground degradation without invoking the myriad unverifiable assumptions inherent in physical models, and instead relying solely on real-world observations through the novel ERRA framework. This approach directly addresses the referee’s concerns regarding spatial variability and provides an independent, data-driven perspective on frozen-ground hydrology. We therefore believe that the reviewer’s call for rejection does not reflect the scientific intent and methodological innovation of our work.
References
Andresen, C. G., Lawrence, D. M., Wilson, C. J., McGuire, A. D., Koven, C., Schaefer, K., et al.: Soil moisture and hydrology projections of the permafrost region-a model intercomparison, The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, 2020.
Chang, Y., Ding, Y., Zhang, S., Zhao, Q., Jin, Z., Qin, J., and Shangguan, D.: Quantifying the response of runoff to glacier shrinkage and permafrost degradation in a typical cryospheric basin on the Tibetan Plateau, Catena, 242, 108124, https://doi.org/10.1016/j.catena.2024.108124, 2024.
Gao, B., Yang, D., Qin, Y., Wang, Y., Li, H., Zhang, Y., and Zhang, T.: Change in frozen soils and its effect on regional hydrology, upper Heihe basin, northeastern Qinghai–Tibetan Plateau, The Cryosphere, 12, 657–673, https://doi.org/10.5194/tc-12-657-2018, 2018.
Gao, B., Yang, D., Qin, Y., Wang, Y., Li, H., Zhang, Y., and Zhang, T.: Change in frozen soils and its effect on regional hydrology, upper Heihe basin, northeastern Qinghai–Tibetan Plateau, The Cryosphere, 12, 657–673, https://doi.org/10.5194/tc-12-657-2018, 2018.
Harp, D. R., Atchley, A. L., Painter, S. L., Coon, E. T., Wilson, C. J., Romanovsky, V. E., and Rowland, J. C.: Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis, The Cryosphere, 10, 341–358, https://doi.org/10.5194/tc-10-341-2016, 2016.
Hu, Y., Maskey, S., Uhlenbrook, S., and Zhao, H.: Streamflow trends and climate linkages in the source region of the Yellow River, China, Hydrol. Process., 25, 3399–3411, https://doi.org/10.1002/hyp.8069, 2011.
Kirchner, J. W.: Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using ensemble rainfall–runoff analysis (ERRA): proof of concept, Hydrol. Earth Syst. Sci., 28, 4427–4454, https://doi.org/10.5194/hess-28-4427-2024, 2024.
Lawrence, D. M. and Slater, A. G.: Incorporating organic soil into a global climate model, Clim. Dyn., 30, 145–160, https://doi.org/10.1007/s00382-007-0278-1, 2008.
Ma, Q., Jin, H., Bense, V. F., Luo, D., Marchenko, S. S., Harris, S. A., and Lan, Y.: Impacts of degrading permafrost on streamflow in the source area of Yellow River on the Qinghai-Tibet Plateau, China, Adv. Clim. Change Res., 10, 225–239, https://doi.org/10.1016/j.accre.2020.02.001, 2019.
Walvoord, M. A., and Kurylyk, B. L.: Hydrologic impacts of thawing permafrost—A review, Vadose Zone J., 15, vzj2016-01, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Wang, T., Yang, H., Yang, D., Qin, Y., and Wang, Y.: Quantifying the streamflow response to frozen ground degradation in the source region of the Yellow River within the Budyko framework, J. Hydrol., 558, 301–313, https://doi.org/10.1016/j.jhydrol.2018.01.050, 2018.
Wu, P., Liang, S., Wang, X. S., McKenzie, J. M., and Feng, Y.: Climate change impacts on cold season runoff in the headwaters of the Yellow River considering frozen ground degradation, Water, 12, 602, https://doi.org/10.3390/w12020602, 2020.
Yi, S., Wang, X., Qin, Y., Xiang, B., and Ding, Y.: Responses of alpine grassland on Qinghai–Tibetan Plateau to climate warming and permafrost degradation: a modeling perspective, Environ. Res. Lett., 9, 074014, https://doi.org/10.1088/1748-9326/9/7/074014, 2014.
Zheng, D., van der Velde, R., Su, Z., Wen, J., Wang, X., and Yang, K.: Impact of soil freeze-thaw mechanism on the runoff dynamics of two Tibetan rivers, J. Hydrol., 563, 382–394, https://doi.org/10.1016/j.jhydrol.2018.06.024, 2018.
Citation: https://doi.org/10.5194/egusphere-2025-3018-AC2
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AC2: 'Reply on RC2', Yuting Yang, 09 Oct 2025
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Dear authors,
Your study deals with the quantification of change in runoff response to rainfall in a river that has partial permafrost and partially seasonally frozen ground using existing techniques.
My impression is that this study does not find anything that was previously not known or not understood. It simply quantifies the effect of permafrost loss using recently developed methods. However, it does contribute positively to the debate on what happens to river flow with the rise in global temperatures in the presence of permafrost/seasonally frozen ground. To be honest, I did not find anything that can be improved significantly in this study, as it is simply an application of existing data and techniques. The authors were meticulous with the application and tested various hypotheses to make sure that their claims are valid. It is very clear that they know what they are doing.
A lot of work went in to this paper, I am not denying that. However, I do not see this study to be at the level that justifies its publication in a prestigious journal like HESS. It is better suited to a journal that deals with regional studies, IMO. I am asking for a rejection.