Articles | Volume 28, issue 16
https://doi.org/10.5194/hess-28-3897-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-28-3897-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Aug 2024
Research article |
| 26 Aug 2024
| 26 Aug 2024
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
Zehua Chang
Key Laboratory of Geographic Information Science (Ministry of Education of China), School of Geographical Sciences, East China Normal University, Shanghai, China
Key Laboratory of Geographic Information Science (Ministry of Education of China), School of Geographical Sciences, East China Normal University, Shanghai, China
Leilei Yong
Key Laboratory of Geographic Information Science (Ministry of Education of China), School of Geographical Sciences, East China Normal University, Shanghai, China
Kang Wang
Key Laboratory of Geographic Information Science (Ministry of Education of China), School of Geographical Sciences, East China Normal University, Shanghai, China
Rensheng Chen
Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
Chuntan Han
Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
Otgonbayar Demberel
Department of Geography and Geology, Khovd branch of National University of Mongolia, Khovd, 84140, Mongolia
Batsuren Dorjsuren
Department of Environment and Forest Engineering, National University of Mongolia, Ulaanbaatar, 210646, Mongolia
Shugui Hou
School of Oceanography (SOO), Shanghai Jiao Tong University (SJTU), No. 1954 Huashan Road, Xuhui District, Shanghai, China
Zheng Duan
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62 Lund, Sweden
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Leilei Yong, Yahui Wang, Batsuren Dorjsuren, Zheng Duan, and Hongkai Gao
Hydrol. Earth Syst. Sci., 30, 1585–1606, https://doi.org/10.5194/hess-30-1585-2026, https://doi.org/10.5194/hess-30-1585-2026, 2026
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Topography and vegetation critically influence hydrology but are often underrepresented in models. Using a stepwise flexible modelling framework, we assessed their roles in two river basins on the Mongolian Plateau. Distributed (FLEXD) and landscape-based (FLEXT) models outperformed lumped models. High elevations showed delayed melt that sustained streamflow, whereas low elevations responded rapidly to rainfall. The study confirms topography and vegetation as key hydrological controls.
Qiuyu Li, Huanting Hu, Guitao Shi, Danhe Wang, Zhe Li, and Shugui Hou
EGUsphere, https://doi.org/10.5194/egusphere-2025-5800, https://doi.org/10.5194/egusphere-2025-5800, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Ancient air trapped in ice bubbles is a valuable archive for studying past climates. However, trapped air can be altered by gas loss through pumping in laboratory. We quantified the characteristics of this loss for the first time based on controlled ice pumping experiments. We discovered that O2 and Ar escape simultaneously through ice microcracks. Crucially, we found that gas loss corrections considering both O2 and Ar significantly reduced data scatter, recovering clearer climate signals.
Chunlei An, Su Jiang, Guitao Shi, Hongmei Ma, Chuanjin Li, Zhe Li, Xiaolong Li, Ye Hu, Yan Liu, Xiao Yan, Ningning Sun, Bo Zhang, Shugui Hou, and Yuansheng Li
EGUsphere, https://doi.org/10.5194/egusphere-2026-769, https://doi.org/10.5194/egusphere-2026-769, 2026
This preprint is open for discussion and under review for Climate of the Past (CP).
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Volcanic eruptions can significantly affect the Earth's climate. Reconstructing past volcanic history can provide valuable information for climate modeling. Our study provides a new volcanic record from Dome A, the highest ice dome in Antarctica. Using this record and three other volcanic records from Antarctica, the prominent volcanic events, the change in volcanic frequency and flux, and the variation of snow accumulation rates at Dome A over the past 4000 years are investigated.
Yishen Wang, Yanqing An, Yulong Tan, Kemei Li, Jianzhong Xu, and Shugui Hou
Atmos. Chem. Phys., 26, 1163–1178, https://doi.org/10.5194/acp-26-1163-2026, https://doi.org/10.5194/acp-26-1163-2026, 2026
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We studied air pollution transported from South Asia to the Himalayas during the pre-monsoon season. Using real-time instruments, we measured airborne particles and trace gases on the northern slope of the mountains. We found that burning biomass was a major source of these particles, which changed chemically as they travelled long distances. These changes were affected by photochemical and cloud processes, with important consequences for the regional climate and melting of glaciers.
Zehong Huang, Shouzhi Chen, Yufeng Gong, Zheng Wang, Zheng Duan, and Yongshuo H. Fu
EGUsphere, https://doi.org/10.5194/egusphere-2025-5503, https://doi.org/10.5194/egusphere-2025-5503, 2025
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Understanding how carbon moves through rivers is vital for managing water quality and climate change. This study developed a new diagnostic framework that combines computer modeling and data analysis to explore why current river carbon simulations are often inaccurate. The results show that parts of the model describing plant growth and carbon cycling cause most errors, and improving these areas can make future environmental predictions more reliable.
Qiumei Ma, Chengyu Xie, Zheng Duan, Yanke Zhang, Lihua Xiong, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 6631–6646, https://doi.org/10.5194/hess-29-6631-2025, https://doi.org/10.5194/hess-29-6631-2025, 2025
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We propose a method to estimate the reservoir water level–storage volume (WLSV) curve based on the capacity loss induced by sediment accumulation and assess the potential negative impact caused by outdated design WLSV curve on flood regulation risks. The findings highlight that when storage capacity is considerably reduced, continued use of design WLSV curves may significantly underestimate, thus posing potential safety hazards to the reservoir itself and downstream flood protection objects.
Hailey Webb, Ethan Pierce, Benjamin W. Abbott, William B. Bowden, Yaping Chen, Yating Chen, Thomas A. Douglas, Joel F. Eklof, Eugénie S. Euskirchen, Moritz Langer, Isla H. Myers-Smith, Irina Overeem, Jens Strauss, Katey Walter Anthony, Kang Wang, Matthew A. Whitley, and Merritt R. Turetsky
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-557, https://doi.org/10.5194/essd-2025-557, 2025
Preprint under review for ESSD
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We created a database of 19,540 thawing permafrost sites across Alaska, including both abrupt and non-abrupt thaw features and explored relationships with elevation, slope, and incoming solar radiation. We use the database to show that existing ground ice maps are too coarse to predict abrupt thaw risk. This database can enhance predictions of future thaw, improve greenhouse gas budget calculations, and guide planning and climate adaptation strategies.
Hongkai Gao, Markus Hrachowitz, Lan Wang-Erlandsson, Fabrizio Fenicia, Qiaojuan Xi, Jianyang Xia, Wei Shao, Ge Sun, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 4477–4499, https://doi.org/10.5194/hess-28-4477-2024, https://doi.org/10.5194/hess-28-4477-2024, 2024
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The concept of the root zone is widely used but lacks a precise definition. Its importance in Earth system science is not well elaborated upon. Here, we clarified its definition with several similar terms to bridge the multi-disciplinary gap. We underscore the key role of the root zone in the Earth system, which links the biosphere, hydrosphere, lithosphere, atmosphere, and anthroposphere. To better represent the root zone, we advocate for a paradigm shift towards ecosystem-centred modelling.
Jiaxing Liang, Hongkai Gao, Fabrizio Fenicia, Qiaojuan Xi, Yahui Wang, and Hubert H. G. Savenije
EGUsphere, https://doi.org/10.5194/egusphere-2024-550, https://doi.org/10.5194/egusphere-2024-550, 2024
Preprint archived
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The root zone storage capacity (Sumax) is a key element in hydrology and land-atmospheric interaction. In this study, we utilized a hydrological model and a dynamic parameter identification method, to quantify the temporal trends of Sumax for 497 catchments in the USA. We found that 423 catchments (85 %) showed increasing Sumax, which averagely increased from 178 to 235 mm between 1980 and 2014. The increasing trend was also validated by multi-sources data and independent methods.
Hongkai Gao, Fabrizio Fenicia, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2607–2620, https://doi.org/10.5194/hess-27-2607-2023, https://doi.org/10.5194/hess-27-2607-2023, 2023
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It is a deeply rooted perception that soil is key in hydrology. In this paper, we argue that it is the ecosystem, not the soil, that is in control of hydrology. Firstly, in nature, the dominant flow mechanism is preferential, which is not particularly related to soil properties. Secondly, the ecosystem, not the soil, determines the land–surface water balance and hydrological processes. Moving from a soil- to ecosystem-centred perspective allows more realistic and simpler hydrological models.
Chuntan Han, Chao Kang, Chengxian Zhao, Jianhua Luo, and Rensheng Chen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-241, https://doi.org/10.5194/tc-2022-241, 2023
Manuscript not accepted for further review
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This paper presents analysis results of temperatures collected at three monitoring stations on a reservoir along Irtysh River. Temperatures close to ice surface were analyzed and correlated with air temperature. Ice thickness was correlated with temperatures, variations of temperature and AFDD. Regression models were proposed and compared using the dataset in this study which was then validated using data from stations in Russia and Finland.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Jiajia Wang, Hongxi Pang, Shuangye Wu, Spruce W. Schoenemann, Ryu Uemura, Alexey Ekaykin, Martin Werner, Alexandre Cauquoin, Sentia Goursaud Oger, Summer Rupper, and Shugui Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-384, https://doi.org/10.5194/essd-2022-384, 2022
Revised manuscript not accepted
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Stable water isotopic observations in surface snow over Antarctica provide a basis for validating isotopic models and interpreting Antarctic ice core records. This study presents a new compilation of Antarctic surface snow isotopic dataset based on published and unpublished sources. The database has a wide range of potential applications in studying spatial distribution of water isotopes, model validation, and reconstruction and interpretation of Antarctic ice core records.
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
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The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci., 26, 4187–4208, https://doi.org/10.5194/hess-26-4187-2022, https://doi.org/10.5194/hess-26-4187-2022, 2022
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Frozen soil hydrology is one of the 23 unsolved problems in hydrology (UPH). In this study, we developed a novel conceptual frozen soil hydrological model, FLEX-Topo-FS. The model successfully reproduced the soil freeze–thaw process, and its impacts on hydrologic connectivity, runoff generation, and groundwater. We believe this study is a breakthrough for the 23 UPH, giving us new insights on frozen soil hydrology, with broad implications for predicting cold region hydrology in future.
Wangbin Zhang, Shugui Hou, Shuang-Ye Wu, Hongxi Pang, Sharon B. Sneed, Elena V. Korotkikh, Paul A. Mayewski, Theo M. Jenk, and Margit Schwikowski
The Cryosphere, 16, 1997–2008, https://doi.org/10.5194/tc-16-1997-2022, https://doi.org/10.5194/tc-16-1997-2022, 2022
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This study proposes a quantitative method to reconstruct annual precipitation records at the millennial timescale from the Tibetan ice cores through combining annual layer identification based on LA-ICP-MS measurement with an ice flow model. The reliability of this method is assessed by comparing our results with other reconstructed and modeled precipitation series for the Tibetan Plateau. The assessment shows that the method has a promising performance.
Yong Yang, Rensheng Chen, Guohua Liu, Zhangwen Liu, and Xiqiang Wang
Hydrol. Earth Syst. Sci., 26, 305–329, https://doi.org/10.5194/hess-26-305-2022, https://doi.org/10.5194/hess-26-305-2022, 2022
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A comprehensive assessment of snowmelt is missing for China. Trends and variability in snowmelt in China under climate change are investigated using historical precipitation and temperature data (1951–2017) and projection scenarios (2006–2099). The snowmelt and snowmelt runoff ratio show significant spatial and temporal variability in China. The spatial variability in snowmelt changes may lead to regional differences in the impact of snowmelt on the water supply.
Tao Xu, Hongxi Pang, Zhaojun Zhan, Wangbin Zhang, Huiwen Guo, Shuangye Wu, and Shugui Hou
Hydrol. Earth Syst. Sci., 26, 117–127, https://doi.org/10.5194/hess-26-117-2022, https://doi.org/10.5194/hess-26-117-2022, 2022
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In this study, we presented stable isotopes in atmospheric water vapor and precipitation for five extreme winter precipitation events in Nanjing, southeastern China, from December 2018 to February 2019. Our results imply that multiple moisture sources and the rapid shift among them are important conditions for sustaining extreme precipitation events, especially in the relatively cold and dry winter.
Xikun Wei, Guojie Wang, Donghan Feng, Zheng Duan, Daniel Fiifi Tawia Hagan, Liangliang Tao, Lijuan Miao, Buda Su, and Tong Jiang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-418, https://doi.org/10.5194/essd-2021-418, 2021
Preprint withdrawn
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In this study, we use the deep learning (DL) method to generate the temperature data for the global land (except Antartica) at higher spatial resolution (0.5 degree) based on 31 different CMIP6 Earth system model(ESM). Our methods can perform bias correction, spatial downscaling and data merging simultaneously. The merged data have a remarkably better quality compared with the individual ESMs in terms of both spatial dimension and time dimension.
Yetang Wang, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Shugui Hou, and Cunde Xiao
Earth Syst. Sci. Data, 13, 3057–3074, https://doi.org/10.5194/essd-13-3057-2021, https://doi.org/10.5194/essd-13-3057-2021, 2021
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Accurate observation of surface mass balance (SMB) under climate change is essential for the reliable present and future assessment of Antarctic contribution to global sea level. This study presents a new quality-controlled dataset of Antarctic SMB observations at different temporal resolutions and is the first ice-sheet-scale compilation of multiple types of measurements. The dataset can be widely applied to climate model validation, remote sensing retrievals, and data assimilation.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-264, https://doi.org/10.5194/hess-2021-264, 2021
Manuscript not accepted for further review
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Permafrost hydrology is one of the 23 major unsolved problems in hydrology. In this study, we used a stepwise modeling and dynamic parameter method to examine the impact of permafrost on streamflow in the Hulu catchment in western China. We found that: topography and landscape are dominant controls on catchment response; baseflow recession is slower than other regions; precipitation-runoff relationship is non-stationary; permafrost impacts on streamflow mostly at the beginning of melting season.
Shugui Hou, Wangbin Zhang, Ling Fang, Theo M. Jenk, Shuangye Wu, Hongxi Pang, and Margit Schwikowski
The Cryosphere, 15, 2109–2114, https://doi.org/10.5194/tc-15-2109-2021, https://doi.org/10.5194/tc-15-2109-2021, 2021
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We present ages for two new ice cores reaching bedrock, from the Zangser Kangri (ZK) glacier in the northwestern Tibetan Plateau and the Shulenanshan (SLNS) glacier in the western Qilian Mountains. We estimated bottom ages of 8.90±0.57/0.56 ka and 7.46±1.46/1.79 ka for the ZK and SLNS ice core respectively, constraining the time range accessible by Tibetan ice cores to the Holocene.
Cited articles
Abdelhamed, M. S., Elshamy, M. E., Wheater, H. S., and Razavi, S.: Hydrologic-land surface modelling of the Canadian sporadic-discontinuous permafrost: Initialization and uncertainty propagation, Hydrol. Process., 36, E14509, https://doi.org/10.1002/hyp.14509, 2022.
Adler, C., Huggel, C., Orlove, B., and Nolin, A.: Climate change in the mountain cryosphere: impacts and responses, Reg. Environ. Change, 19, 1225–1228, https://doi.org/10.1007/s10113-019-01507-6, 2019.
Andrianaki, M., Shrestha, J., Kobierska, F., Nikolaidis, N. P., and Bernasconi, S. M.: Assessment of SWAT spatial and temporal transferability for a high-altitude glacierized catchment, Hydrol. Earth Syst. Sci., 23, 3219–3232, https://doi.org/10.5194/hess-23-3219-2019, 2019.
Arendt, A., Krakauer, N., Kumar, S. V., Rounce, D. R., and Rupper, S.: Editorial: Collaborative Research to Address Changes in the Climate, Hydrology and Cryosphere of High Mountain Asia, Front. Earth Sci., 8, 605336, https://doi.org/10.3389/feart.2020.605336, 2020.
Arnold, N. S., Rees, W. G., Hodson, A. J., and Kohler, J.: Topographic controls on the surface energy balance of a high Arctic valley glacier, J. Geophys. Res., 111, 2005JF000426, https://doi.org/10.1029/2005JF000426, 2006.
Aubry-Wake, C. and Pomeroy, J. W.: Predicting Hydrological Change in an Alpine Glacierized Basin and Its Sensitivity to Landscape Evolution and Meteorological Forcings, Water Resour. Res., 59, e2022WR033363, https://doi.org/10.1029/2022WR033363, 2023.
Baraer, M., Mark, B. G., McKenzie, J. M., Condom, T., Bury, J., Huh, K.-I., Portocarrero, C., Gómez, J., and Rathay, S.: Glacier recession and water resources in Peru's Cordillera Blanca, J. Glaciol., 58, 134–150, https://doi.org/10.3189/2012JoG11J186, 2012.
Beven, K. J.: Rainfall-Runoff Models: The Primer, WileyBlackwell, New Jersey, USA, online ISBN 9781119951001, https://doi.org/10.1002/9781119951001, 2012.
Blöschl, G., Bierkens, M. F. P., Chambel, A., et al.: Twenty-three unsolved problems in hydrology (UPH) – a community perspective, Hydrolog. Sci. J., 64, 1141–1158, https://doi.org/10.1080/02626667.2019.1620507, 2019.
Bolibar, J., Rabatel, A., Gouttevin, I., Zekollari, H., and Galiez, C.: Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning, Nat. Commun., 13, 409, https://doi.org/10.1038/s41467-022-28033-0, 2022.
Brovkin, V., Brook, E., Williams, J. W., Bathiany, S., Lenton, T. M., Barton, M., DeConto, R. M., Donges, J. F., Ganopolski, A., McManus, J., Praetorius, S., De Vernal, A., Abe-Ouchi, A., Cheng, H., Claussen, M., Crucifix, M., Gallopín, G., Iglesias, V., Kaufman, D. S., Kleinen, T., Lambert, F., Van Der Leeuw, S., Liddy, H., Loutre, M.-F., McGee, D., Rehfeld, K., Rhodes, R., Seddon, A. W. R., Trauth, M. H., Vanderveken, L., and Yu, Z.: Past abrupt changes, tipping points and cascading impacts in the Earth system, Nat. Geosci., 14, 550–558, https://doi.org/10.1038/s41561-021-00790-5, 2021.
Chadburn, S. E., Burke, E. J., Cox, P. M., Friedlingstein, P., Hugelius, G., and Westermann, S.: An observation-based constraint on permafrost loss as a function of global warming, Nat. Clim. Change, 7, 340–344, https://doi.org/10.1038/nclimate3262, 2017.
Chai, C., Wang, L., Chen, D., Zhou, J., Liu, H., Zhang, J., Wang, Y., Chen, T., and Liu, R.: Future snow changes and their impact on the upstream runoff in Salween, Hydrol. Earth Syst. Sci., 26, 4657–4683, https://doi.org/10.5194/hess-26-4657-2022, 2022.
Chang, Z., Qi, P., Zhang, G., Sun, Y., Tang, X., Jiang, M., Sun, J., and Li, Z.: Latitudinal characteristics of frozen soil degradation and their response to climate change in a high-latitude water tower, Catena, 214, 106272, https://doi.org/10.1016/j.CATENA.2022.106272, 2022.
Chen, R., Duan, K., Shang, W., Shi, P., Meng, Y., and Zhang, Z.: Increase in seasonal precipitation over the Tibetan Plateau in the 21st century projected using CMIP6 models, Atmos. Res., 277, 106306, https://doi.org/10.1016/j.atmosres.2022.106306, 2022.
Chen, R. S., Lu, S.-H., Kang, E. S., Ji, X., Zhang, Z., Yang, Y., and Qing, W.: A distributed water-heat coupled model for mountainous watershed of an inland river basin of Northwest China (I) model structure and equations, Environ. Geol., 53, 1299–1309, https://doi.org/10.1007/s00254-007-0738-2, 2008.
Chen, X., Wang, S., Gao, H., Huang, J., Shen, C., Li, Q., Qi, H., Zheng, L., and Liu, M.: Comparison of deep learning models and a typical process-based model in glacio-hydrology simulation, J. Hydrol., 615, 128562, https://doi.org/10.1016/j.jhydrol.2022.128562, 2022.
Connon, R. F., Chasmer, L., Haughton, E., Helbig, M., Hopkinson, C., Sonnentag, O., and Quinton, W. L.: The implications of permafrost thaw and land cover change on snow water equivalent accumulation, melt and runoff in discontinuous permafrost peatlands, Hydrol. Process., 35, e14363, https://doi.org/10.1002/hyp.14363, 2021.
Cooper, M. G., Zhou, T., Bennett, K. E., Bolton, W. R., Coon, E. T., Fleming, S. W., Rowland, J. C., and Schwenk, J.: Detecting Permafrost Active Layer Thickness Change From Nonlinear Baseflow Recession, Water Resour. Res., 59, e2022WR033154, https://doi.org/10.1029/2022WR033154, 2023.
Ding, Y., Zhang, S., Zhao, L., Li, Z., and Kang, S.: Global warming weakening the inherent stability of glaciers and permafrost, Sci. Bull., 64, 245–253, https://doi.org/10.1016/j.scib.2018.12.028, 2019.
Ding, Y., Zhang, S., and Chen, R.: Cryospheric Hydrology: Decode the Largest Freshwater Reservoir on Earth, Bulletin of the Chinese Academy of Sciences, 35, 414–424, 2020.
Elshamy, M. E., Princz, D., Sapriza-Azuri, G., Abdelhamed, M. S., Pietroniro, A., Wheater, H. S., and Razavi, S.: On the configuration and initialization of a large-scale hydrological land surface model to represent permafrost, Hydrol. Earth Syst. Sci., 24, 349–379, https://doi.org/10.5194/hess-24-349-2020, 2020.
Farinotti, D.: A consensus estimate for the ice thickness distribution of all glaciers on Earth – dataset, ETH Zurich [data set], https://doi.org/10.3929/ethz-b-000315707, 2019.
Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H., Maussion, F., and Pandit, A.: A consensus estimate for the ice thickness distribution of all glaciers on Earth, Nat. Geosci., 12, 168–173, https://doi.org/10.1038/s41561-019-0300-3, 2019.
Feng, S., Cook, J. M., Naegeli, K., Anesio, A. M., Benning, L. G., and Tranter, M.: The Impact of Bare Ice Duration and Geo-Topographical Factors on the Darkening of the Greenland Ice Sheet, Geophys. Res. Lett., 51, e2023GL104894, https://doi.org/10.1029/2023GL104894, 2024.
Fenicia, F. and McDonnell, J. J.: Modeling streamflow variability at the regional scale: (1) perceptual model development through signature analysis, J. Hydrol., 605, 127287, https://doi.org/10.1016/j.jhydrol.2021.127287, 2022.
Gao, H., Feng, Z., Zhang, T., Wang, Y., He, X., Li, H., Pan, X., Ren, Z., Chen, X., Zhang, W., and Duan, Z.: Assessing glacier retreat and its impact on water resources in a headwater of Yangtze River based on CMIP6 projections, Sci. Total Environ., 765, 142774, https://doi.org/10.1016/j.scitotenv.2020.142774, 2021.
Gao, H., Han, C., Chen, R., Feng, Z., Wang, K., Fenicia, F., and Savenije, H.: Frozen soil hydrological modeling for a mountainous catchment northeast of the Qinghai–Tibet Plateau, Hydrol. Earth Syst. Sci., 26, 4187–4208, https://doi.org/10.5194/hess-26-4187-2022, 2022.
Gao, T., Kang, S., Chen, R., Zhang, T., Zhang, T., Han, C., Tripathee, L., Sillanpää, M., and Zhang, Y.: Riverine dissolved organic carbon and its optical properties in a permafrost region of the Upper Heihe River basin in the Northern Tibetan Plateau, Sci. Total Environ., 686, 370–381, https://doi.org/10.1016/j.scitotenv.2019.05.478, 2019.
Gilg, O., Kovacs, K. M., Aars, J., Fort, J., Gauthier, G., Grémillet, D., Ims, R. A., Meltofte, H., Moreau, J., Post, E., Schmidt, N. M., Yannic, G., and Bollache, L.: Climate change and the ecology and evolution of Arctic vertebrates, Ann. NY Acad. Sci., 1249, 166–190, https://doi.org/10.1111/j.1749-6632.2011.06412.x, 2012.
Giovando, J. and Niemann, J. D.: Wildfire Impacts on Snowpack Phenology in a Changing Climate Within the Western U. S., Water Resour. Res., 58, e2021WR031569, https://doi.org/10.1029/2021WR031569, 2022.
Gisnås, K., Westermann, S., Schuler, T. V., Melvold, K., and Etzelmüller, B.: Small-scale variation of snow in a regional permafrost model, The Cryosphere, 10, 1201–1215, https://doi.org/10.5194/tc-10-1201-2016, 2016.
Guan, X., Guo, S., Huang, J., Shen, X., Fu, L., and Zhang, G.: Effect of seasonal snow on the start of growing season of typical vegetation in Northern Hemisphere, Geography and Sustainability, 3, 268–276, https://doi.org/10.1016/j.geosus.2022.09.001, 2022.
Hamon, W. R.: Estimating potential evapotranspiration, J. Hydraul. Div.-ASCE, 87, 107–120, 1961.
Han, L. and Menzel, L.: Hydrological variability in southern Siberia and the role of permafrost degradation, J. Hydrol., 604, 127203, https://doi.org/10.1016/j.jhydrol.2021.127203, 2022.
He, Q., Kuang, X., Chen, J., Hao, Y., Feng, Y., Wu, P., and Zheng, C.: Glacier retreat and its impact on groundwater system evolution in the Yarlung Zangbo source region, Tibetan Plateau, J. Hydrol.: Regional Studies, 47, 101368, https://doi.org/10.1016/j.ejrh.2023.101368, 2023.
He, Z., Duethmann, D., and Tian, F.: A meta-analysis based review of quantifying the contributions of runoff components to streamflow in glacierized basins, J. Hydrol., 603, 126890, https://doi.org/10.1016/j.jhydrol.2021.126890, 2021.
Hu, G., Li, X., Yang, X., Shi, F., Sun, H., and Cui, B.: Identifying Spatiotemporal Patterns of Hillslope Subsurface Flow in an Alpine Critical Zone on the Qinghai-Tibetan Plateau Based on Three-Year, High-Resolution Field Observations, Water Resour. Res., 58, e2022WR032098, https://doi.org/10.1029/2022WR032098, 2022.
Huss, M. and Hock, R.: Global-scale hydrological response to future glacier mass loss, Nat. Clim. Change, 8, 135–140, https://doi.org/10.1038/s41558-017-0049-x, 2018.
Huss, M., Jouvet, G., Farinotti, D., and Bauder, A.: Future high-mountain hydrology: a new parameterization of glacier retreat, Hydrol. Earth Syst. Sci., 14, 815–829, https://doi.org/10.5194/hess-14-815-2010, 2010.
IPCC – Intergovernmental Panel On Climate Change: The Ocean and Cryosphere in a Changing Climate: Special Report of the Intergovernmental Panel on Climate Change, 1st edn., Cambridge University Press, https://doi.org/10.1017/9781009157964, 2022.
Jia, Q., Jia, H., Li, Y., and Yin, D.: Applicability of CMIP5 and CMIP6 Models in China: Reproducibility of Historical Simulation and Uncertainty of Future Projection, J. Climate, 36, 5809–5824, https://doi.org/10.1175/JCLI-D-22-0375.1, 2023.
Jiang, R., Li, T., Liu, D., Fu, Q., Hou, R., Li, Q., Cui, S., and Li, M.: Soil infiltration characteristics and pore distribution under freezing–thawing conditions, The Cryosphere, 15, 2133–2146, https://doi.org/10.5194/tc-15-2133-2021, 2021.
Jin, X., Jin, H., Luo, D., Sheng, Y., Wu, Q., Wu, J., Wang, W., Huang, S., Li, X., Liang, S., Wang, Q., He, R., Serban, R. D., Ma, Q., Gao, S., and Li, Y.: Impacts of Permafrost Degradation on Hydrology and Vegetation in the Source Area of the Yellow River on Northeastern Qinghai-Tibet Plateau, Southwest China, Front. Earth Sci., 10, 845824, https://doi.org/10.3389/feart.2022.845824, 2022.
Jones, M. W., Sebestyen, S. D., Dymond, S. F., Ng, G. H. C., and Feng, X.: Soil frost controls streamflow generation processes in headwater catchments, J. Hydrol., 617, 128801, https://doi.org/10.1016/j.jhydrol.2022.128801, 2023.
Kaplan Pastíriková, L., Hrbáček, F., Uxa, T., and Láska, K.: Permafrost table temperature and active layer thickness variability on James Ross Island, Antarctic Peninsula, in 2004–2021, Sci. Total Environ., 869, 161690, https://doi.org/10.1016/j.scitotenv.2023.161690, 2023.
Li, L., Xu, Z., Zuo, D., and Zhao, J.: A grid-based integrated surface–groundwater model (GISMOD), J. Water Clim. Change, 7, 296–320, https://doi.org/10.2166/wcc.2015.006, 2016.
Li, X., Jin, H., Sun, L., Wang, H., Huang, Y., He, R., Chang, X., Yu, S., and Zang, S.: TTOP-model-based maps of permafrost distribution in Northeast China for 1961–2020, Permafrost Periglac., 33, 425–435, https://doi.org/10.1002/ppp.2157, 2022.
Li, Z., Feng, Q., Liu, W., Wang, T., Cheng, A., Gao, Y., Gao, X.,Peng Y., Jianguo, L., Rui, G., and Bing, J.: Study on the contribution of cryosphere to runoff in the cold alpine basin: A case study of Hulugou River Basin in the Qilian Mountains, Global Planet. Change, 122, 345–361, https://doi.org/10.1016/j.gloplacha.2014.10.001, 2014.
Liu, J. and Chen, R.: Discriminating types of precipitation in Qilian Mountains, Tibetan Plateau, Journal of Hydrology: Regional Studies, 5, 20–32, https://doi.org/10.1016/j.ejrh.2015.11.013, 2016.
Liu, S., Wang, X., Zhang, L., Kong, W., Gao, H., and Xiao, C.: Effect of glaciers on the annual catchment water balance within Budyko framework, Advances in Climate Change Research, 13, 51–62, https://doi.org/10.1016/j.accre.2021.10.004, 2022.
Liu, Z., Cuo, L., and Sun, N.: Tracking snowmelt during hydrological surface processes using a distributed hydrological model in a mesoscale basin on the Tibetan Plateau, J. Hydrol., 616, 128796, https://doi.org/10.1016/j.jhydrol.2022.128796, 2023.
Ma, J., Li, R., Huang, Z., Wu, T., Wu, X., Zhao, L., Liu, H., Hu, G., Xiao, Y., Du, Y., Yang, S., Liu, W., Jiao, Y., and Wang, S.: Evaluation and spatio-temporal analysis of surface energy flux in permafrost regions over the Qinghai-Tibet Plateau and Arctic using CMIP6 models, Int. J. Digit. Earth, 15, 1947–1965, https://doi.org/10.1080/17538947.2022.2142307, 2022.
Martin, L. C. P., Westermann, S., Magni, M., Brun, F., Fiddes, J., Lei, Y., Kraaijenbrink, P., Mathys, T., Langer, M., Allen, S., and Immerzeel, W. W.: Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes, Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, 2023.
McCarthy, M., Meier, F., Fatichi, S., Stocker, B. D., Shaw, T. E., Miles, E., Dussaillant, I., and Pellicciotti, F.: Glacier Contributions to River Discharge During the Current Chilean Megadrought, Earths Future, 10, e2022EF002852, https://doi.org/10.1029/2022EF002852, 2022.
Michel, A., Schaefli, B., Wever, N., Zekollari, H., Lehning, M., and Huwald, H.: Future water temperature of rivers in Switzerland under climate change investigated with physics-based models, Hydrol. Earth Syst. Sci., 26, 1063–1087, https://doi.org/10.5194/hess-26-1063-2022, 2022.
Miner, K., Turetsky, M., Malina, E., Bartsch, A., Tamminen, J., McGuire, A., Fix, A., Sweeney, C., Elder, C., and Miller, C.: Permafrost carbon emissions in a changing Arctic, Nature Reviews Earth & Environmental, 3, 55–67, https://doi.org/10.1038/s43017-021-00230-3, 2022.
Mohammed, A. A., Cey, E. E., Hayashi, M., and Callaghan, M., V.: Simulating preferential flow and snowmelt partitioning in seasonally frozen hillslopes, Hydrol. Process., 35, E14277, https://doi.org/10.1002/hyp.14277, 2021.
Mohammadi, B., Gao, H., Feng, Z., Pilesjö, P., Cheraghalizadeh, M., and Duan, Z.: Simulating glacier mass balance and its contribution to runoff in Northern Sweden, J. Hydrol., 620, 129404, https://doi.org/10.1016/j.jhydrol.2023.129404, 2023.
Moreno, P. I., Fercovic, E. I., Soteres, R. L., Ugalde, P. I., Sagredo, E. A., and Villa-Martínez, R. P.: Glacier and terrestrial ecosystem evolution in the Chilotan archipelago sector of northwestern Patagonia since the Last Glacial Termination, Earth-Sci. Rev., 235, 104240, https://doi.org/10.1016/j.earscirev.2022.104240, 2022.
Mukhopadhyay, B. and Khan, A.: A reevaluation of the snowmelt and glacial melt in river flows within Upper Indus Basin and its significance in a changing climate, J. Hydrol., 527, 119–132, https://doi.org/10.1016/j.jhydrol.2015.04.045, 2015.
Nan, Y. and Tian, F.: Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau, Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, 2024.
Negi, V. S., Tiwari, D. C., Singh, L., Thakur, S., and Bhatt, I. D.: Review and synthesis of climate change studies in the Himalayan region, Environ. Dev. Sustain., 24, 10471–10502, https://doi.org/10.1007/s10668-021-01880-5, 2022.
Ni, J., Wu, T., Zhu, X., Hu, G., Zou, D., Wu, X., Li, R., Xie, C., Qiao, Y., Pang, Q., Hao, J., and Yang, C.: Simulation of the Present and Future Projection of Permafrost on the Qinghai-Tibet Plateau with Statistical and Machine Learning Models, J. Geophys. Res.-Atmos., 126, e2020JD033402, https://doi.org/10.1029/2020JD033402, 2021.
Nury, A. H., Sharma, A., Mehrotra, R., Marshall, L., and Cordery, I.: Projected Changes in the Tibetan Plateau Snowpack Resulting From Rising Global Temperatures, J. Geophys. Res.-Atmos., 127, e2021JD036201, https://doi.org/10.1029/2021JD036201, 2022.
Peng, Z., Tian, F., Wu, J., Huang, J., Hu, H., and Darnault, C. J. G.: A numerical model for water and heat transport in freezing soils with nonequilibrium ice-water interfaces, Water Resour. Res., 52, 7366–7381, https://doi.org/10.1002/2016WR019116, 2016.
Pomeroy, J. W., Brown, T., Fang, X., Shook, K. R., Pradhananga, D., Armstrong, R., Harder, P., Marsh, C., Costa, D., Krogh, S. A., Aubry-Wake, C., Annand, H., Lawford, P., He, Z., Kompanizare, M., and Lopez Moreno, J. I.: The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding, J. Hydrol., 615, 128711, https://doi.org/10.1016/j.jhydrol.2022.128711, 2022.
Pothula, S. K. and Adams, B. J.: Community assembly in the wake of glacial retreat: A meta-analysis, Glob. Change Biol., 28, 6973–6991, https://doi.org/10.1111/gcb.16427, 2022.
Qin, D., Yao, T., Ding, Y., and Ren, J.: Classification and Geographical Distribution of Cryosphere, in: Introduction to Cryospheric Science, Springer Singapore, Singapore, 33–79, https://doi.org/10.1007/978-981-16-6425-0_2, 2021.
Ragettli, S., Immerzeel, W. W., and Pellicciotti, F.: Contrasting climate change impact on river flows from high-altitude catchments in the Himalayan and Andes Mountains, P. Natl. Acad. Sci. USA, 113, 9222–9227, https://doi.org/10.1073/pnas.1606526113, 2016.
Rasul, G., Pasakhala, B., Mishra, A., and Pant, S.: Adaptation to mountain cryosphere change: issues and challenges, Clim. Dev., 12, 297–309, https://doi.org/10.1080/17565529.2019.1617099, 2020.
Rosier, S. H. R., Reese, R., Donges, J. F., De Rydt, J., Gudmundsson, G. H., and Winkelmann, R.: The tipping points and early warning indicators for Pine Island Glacier, West Antarctica, The Cryosphere, 15, 1501–1516, https://doi.org/10.5194/tc-15-1501-2021, 2021.
Schwank, J., Escobar, R., Girón, G. H., and Morán-Tejeda, E.: Modeling of the Mendoza river watershed as a tool to study climate change impacts on water availability, Environ. Sci. Policy, 43, 91–97, https://doi.org/10.1016/j.envsci.2014.01.002, 2014.
Serban, R., Jin, H., Serban, M., and Luo, D.: Shrinking thermokarst lakes and ponds on the northeastern Qinghai-Tibet plateau over the past three decades, Permafrost Periglac., 32, 601–617, https://doi.org/10.1002/ppp.2127, 2021.
Stecher, G., Hohensinner, S., and Herrnegger, M.: Changes in the water retention of mountainous landscapes since the 1820s in the Austrian Alps, Front. Environ. Sci., 11, 1219030, https://doi.org/10.3389/fenvs.2023.1219030, 2023.
Sun, B., Liu, J., Ren, F., Li, H., Zhang, G., Ma, J., Ma, B., and Li, Z.: Effects of seasonal freeze–thaw and wind erosion on runoff and sediment yields of three loamy slopes of Loess Plateau, China, Catena, 215, 106309, https://doi.org/10.1016/j.catena.2022.106309, 2022.
Tang, G., Clark, M. P., Knoben, W. J. M., Liu, H., Gharari, S., Arnal, L., Beck, H. E., Wood, A. W., Newman, A. J., and Papalexiou, S. M.: The Impact of Meteorological Forcing Uncertainty on Hydrological Modeling: A Global Analysis of Cryosphere Basins, Water Resour. Res., 59, e2022WR033767, https://doi.org/10.1029/2022WR033767, 2023.
Teng, J., Liu, J., Zhang, S., and Sheng, D.: Frost heave in coarse-grained soils: experimental evidence and numerical modelling, Geotechnique, 73, 1100–1111, https://doi.org/10.1680/jgeot.21.00182, 2022.
Teutschbein, C. and Seibert, J.: Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods, J. Hydrol., 456–457, 12–29, https://doi.org/10.1016/j.jhydrol.2012.05.052, 2012.
Van Der Geest, K. and Van Den Berg, R.: Slow-onset events: a review of the evidence from the IPCC Special Reports on Land, Oceans and Cryosphere, Curr. Opin. Env. Sust., 50, 109–120, https://doi.org/10.1016/j.cosust.2021.03.008, 2021.
Vincent, C. and Thibert, E.: Brief communication: Non-linear sensitivity of glacier mass balance to climate attested by temperature-index models, The Cryosphere, 17, 1989–1995, https://doi.org/10.5194/tc-17-1989-2023, 2023.
Wang, J., Chen, X., Gao, M., Hu, Q., and Liu, J.: Changes in nonlinearity and stability of streamflow recession characteristics under climate warming in a large glaciated basin of the Tibetan Plateau, Hydrol. Earth Syst. Sci., 26, 3901–3920, https://doi.org/10.5194/hess-26-3901-2022, 2022.
Wang, K., Zhang, T., and Clow, G. D.: Permafrost Thermal Responses to Asymmetrical Climate Changes: An Integrated Perspective, Geophys. Res. Lett., 50, e2022GL100327, https://doi.org/10.1029/2022GL100327, 2023.
Wang, Q., Qi, J., Wu, H., Zeng, Y., Shui, W., Zeng, J., and Zhang, X.: Freeze-Thaw cycle representation alters response of watershed hydrology to future climate change, Catena, 195, 104767, https://doi.org/10.1016/j.catena.2020.104767, 2020.
Wang, S., Yang, Y., and Che, Y.: Global Snow- and Ice-Related Disaster Risk: A Review, Nat. Hazards Rev., 23, 03122002, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000584, 2022.
Wang, X., Chen, R., Liu, G., Yang, Y., Song, Y., Liu, J., Liu, Z., Han, C., Liu, X., Guo, S., Wang, L., and Zheng, Q.: Spatial distributions and temporal variations of the near-surface soil freeze state across China under climate change, Global Planet. Change, 172, 150–158, https://doi.org/10.1016/j.gloplacha.2018.09.016, 2019.
Wang, Y., Yang, H., Gao, B., Wang, T., Qin, Y., and Yang, D.: Frozen ground degradation may reduce future runoff in the headwaters of an inland river on the northeastern Tibetan Plateau, J. Hydrol., 564, 1153–1164, https://doi.org/10.1016/j.jhydrol.2018.07.078, 2018.
Wei, L., Zhao, W., Feng, X., Han, C., Li, T., Qi, J., and Li, Y.: Freeze-thaw desertification of alpine meadow in Qilian Mountains and the implications for alpine ecosystem management, Catena, 232, 107471, https://doi.org/10.1016/j.catena.2023.107471, 2023.
Wen, Y., Liu, B., Jiang, H., Li, T.-Y., Zhang, B., and Wu, W.: Initial soil moisture prewinter affects the freeze–thaw profile dynamics of a Mollisol in Northeast China, Catena, 234, 107648, https://doi.org/10.1016/j.catena.2023.107648, 2024.
Wiersma, P., Aerts, J., Zekollari, H., Hrachowitz, M., Drost, N., Huss, M., Sutanudjaja, E. H., and Hut, R.: Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff, Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, 2022.
Xing, Z. P., Zhao, L., Fan, L., Hu, G. J., Zou, D. F., Wang, C., Liu, S. C., Du, E. J., Xiao, Y., Li, R., Liu, G. Y., Qiao, Y. P., and Shi, J. Z.: Changes in the ground surface temperature in permafrost regions along the Qinghai–Tibet engineering corridor from 1900 to 2014: A modified assessment of CMIP6, Advances in Climate Change Research, 14, 85–96, https://doi.org/10.1016/j.accre.2023.01.007, 2023.
Xu, P., Yan, D., Weng, B., Bian, J., Wu, C., and Wang, H.: Evolution trends and driving factors of groundwater storage, recharge, and discharge in the Qinghai-Tibet Plateau: Study progress and challenges, J. Hydrol., 631, 130815, https://doi.org/10.1016/j.jhydrol.2024.130815, 2024.
Yang, M., Li, Z., Anjum, M. N., Kayastha, R., Kayastha, R. B., Rai, M., Zhang, X., and Xu, C.: Projection of Streamflow Changes Under CMIP6 Scenarios in the Urumqi River Head Watershed, Tianshan Mountain, China, Front. Earth Sci., 10, 857854, https://doi.org/10.3389/feart.2022.857854, 2022.
Yao, T., Bolch, T., Chen, D., Gao, J., Immerzeel, W., Piao, S., Su, F., Thompson, L., Wada, Y., Wang, L., Wang, T., Wu, G., Xu, B., Yang, W., Zhang, G., and Zhao, P.: The imbalance of the Asian water tower, Nature Reviews Earth & Environment, 3, 618–632, https://doi.org/10.1038/s43017-022-00299-4, 2022.
Yao, Y., Zheng, C., Andrews, C. B., Scanlon, B. R., Kuang, X., Zeng, Z., Jeong, S.-J., Lancia, M., Wu, Y., and Li, G.: Role of Groundwater in Sustaining Northern Himalayan Rivers, Geophys. Res. Lett., 48, e2020GL092354, https://doi.org/10.1029/2020GL092354, 2021.
Yin, G.-A., Niu, F.-J., Lin, Z.-J., Luo, J., and Liu, M.-H.: Data-driven spatiotemporal projections of shallow permafrost based on CMIP6 across the Qinghai-Tibet Plateau at 1 km2 scale, Advances in Climate Change Research, 12, 814–827, https://doi.org/10.1016/j.accre.2021.08.009, 2021.
Zekollari, H., Huss, M., Farinotti, D., and Lhermitte, S.: Ice-Dynamical Glacier Evolution Modeling – A Review, Rev. Geophys., 60, e2021RG000754, https://doi.org/10.1029/2021RG000754, 2022.
Zhang, S., Gao, X., Zhang, X., and Hagemann, S.: Projection of glacier runoff in Yarkant River basin and Beida River basin, Western China, Hydrol. Process., 26, 2773–2781, https://doi.org/10.1002/hyp.8373, 2012.
Zhang, T.: Influence of the seasonal snow cover on the ground thermal regime: An overview, Rev. Geophys., 43, 2004RG000157, https://doi.org/10.1029/2004RG000157, 2005.
Zhang, T., Li, D., and Lu, X.: Response of runoff components to climate change in the source-region of the Yellow River on the Tibetan plateau, Hydrol. Process., 36, E14633, https://doi.org/10.1002/hyp.14633, 2022.
Zhang, Y. and Ma, N.: Spatiotemporal variability of snow cover and snow water equivalent in the last three decades over Eurasia, J. Hydrol., 559, 238–251, https://doi.org/10.1016/j.jhydrol.2018.02.031, 2018.
Zhang, Z., Wang, Y., Ma, Z., and Lv, M.: Response mechanism of soil structural heterogeneity in permafrost active layer to freeze-thaw action and vegetation degradation, Catena, 230, 107250, https://doi.org/10.1016/j.catena.2023.107250, 2023.
Zhao, Q., Ding, Y., Wang, J., Gao, H., Zhang, S., Zhao, C., Xu, J., Han, H., and Shangguan, D.: Projecting climate change impacts on hydrological processes on the Tibetan Plateau with model calibration against the glacier inventory data and observed streamflow, J. Hydrol., 573, 60–81, https://doi.org/10.1016/j.jhydrol.2019.03.043, 2019.
Zhu, Y. Y. and Yang, S.: Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5, Advances in Climate Change Research, 11, 239–251, https://doi.org/10.1016/j.accre.2020.08.001, 2020.
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers,...
