Articles | Volume 27, issue 14
https://doi.org/10.5194/hess-27-2681-2023
© Author(s) 2023. 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-27-2681-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Jul 2023
Research article |
| 21 Jul 2023
| 21 Jul 2023
Application of an improved distributed hydrological model based on the soil–gravel structure in the Niyang River basin, Qinghai–Tibet Plateau
Pengxiang Wang
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Institute of Science and Technology, China Three Gorges Corporation, Beijing 100038, China
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Zuhao Zhou
CORRESPONDING AUTHOR
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Jiajia Liu
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Chongyu Xu
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Department of Geosciences, University of Oslo, Oslo, Norway
Kang Wang
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Yangli Liu
China Power Construction Group Guiyang Engineering Corporation Limited, Guiyang 550081, China
Jia Li
Bureau of South to North Water Transfer of Planning, Designing and Management, Ministry of Water Resources, Beijing 100038, China
Yuqing Li
Department of Water Resources and Civil Engineering, Tibet Agriculture and Animal Husbandry College, Nyingchi 860000, China
Yangwen Jia
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Hao Wang
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Related authors
No articles found.
Zitong Jia, Shouzhi Chen, Yongshuo H. Fu, David Martín Belda, David Wårlind, Stefan Olin, Chongyu Xu, and Jing Tang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4064, https://doi.org/10.5194/egusphere-2025-4064, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Groundwater sustains vegetation and regulates land-atmosphere exchanges, but most Earth system models oversimplify its movement. Our study develops an integrated framework coupling LPJ-GUESS with the 3D hydrological model ParFlow to explicitly represent groundwater-vegetation interactions. Our results add to the evidence that three-dimensional groundwater flow strongly regulates water exchanges, and provides a powerful tool to improve simulations of water cycles in Earth system models.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
Short summary
Short summary
We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Qiumei Ma, Chengyu Xie, Zheng Duan, Yanke Zhang, Lihua Xiong, and Chong-Yu Xu
EGUsphere, https://doi.org/10.5194/egusphere-2025-679, https://doi.org/10.5194/egusphere-2025-679, 2025
Short summary
Short summary
We propose a method to estimate the reservoir WLS curve based on the capacity loss induced by sediment accumulation and further assess the potential negative impact caused by outdated design WLS curve on flood regulation risks. The findings highlight that when storage capacity is considerably reduced, continued use of the existing design WLS curve may significantly underestimate, thus posing potential safety hazards to the reservoir itself and downstream flood protection objects.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
Short summary
Short summary
This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
Short summary
Short summary
Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Tian Lan, Xiao Wang, Hongbo Zhang, Xinghui Gong, Xue Xie, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-384, https://doi.org/10.5194/hess-2024-384, 2025
Preprint under review for HESS
Short summary
Short summary
Hydrological models are vital for water management but often fail to predict water flow in dynamic catchments due to model simplification. This study tackles it by developing an optimized calibration framework that considers dynamic catchment characteristics. To overcome potential difficulties, multiple schemes were tested on over 200 U.S. catchments. The results enhanced our understanding of simulation in dynamic catchments and provided a practical solution for improving future forecasting.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Jinghua Xiong, Shenglian Guo, Abhishek, Jiabo Yin, Chongyu Xu, Jun Wang, and Jing Guo
Hydrol. Earth Syst. Sci., 28, 1873–1895, https://doi.org/10.5194/hess-28-1873-2024, https://doi.org/10.5194/hess-28-1873-2024, 2024
Short summary
Short summary
Temporal variability and spatial heterogeneity of climate systems challenge accurate estimation of probable maximum precipitation (PMP) in China. We use high-resolution precipitation data and climate models to explore the variability, trends, and shifts of PMP under climate change. Validated with multi-source estimations, our observations and simulations show significant spatiotemporal divergence of PMP over the country, which is projected to amplify in future due to land–atmosphere coupling.
Danielle M. Barna, Kolbjørn Engeland, Thomas Kneib, Thordis L. Thorarinsdottir, and Chong-Yu Xu
EGUsphere, https://doi.org/10.5194/egusphere-2023-2335, https://doi.org/10.5194/egusphere-2023-2335, 2023
Preprint archived
Short summary
Short summary
Estimating flood quantiles at data-scarce sites often involves single-duration regression models. However, floodplain management and reservoir design, for example, need estimates at several durations, posing challenges. Our flexible generalized additive model (GAM) enhances accuracy and explanation, revealing that single-duration models may underperform elsewhere, emphasizing the need for adaptable approaches.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Pengxiang Wang, Zuhao Zhou, Jiajia Liu, Chongyu Xu, Kang Wang, Yangli Liu, Jia Li, Yuqing Li, Yangwen Jia, and Hao Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-538, https://doi.org/10.5194/hess-2021-538, 2021
Manuscript not accepted for further review
Short summary
Short summary
Combining the geological characteristics of the thin soil layer on the thick gravel layer and the climate characteristics of the long-term snow cover of the Qinghai-Tibet Plateau, the WEP-QTP hydrological model was constructed by dividing a single soil structure into soil and gravel. In contrast to the general cold area, the special environment of the Qinghai–Tibet Plateau affects the hydrothermal transport process, which can not be ignored in hydrological forecast and water resource assessment.
Qifen Yuan, Thordis L. Thorarinsdottir, Stein Beldring, Wai Kwok Wong, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 25, 5259–5275, https://doi.org/10.5194/hess-25-5259-2021, https://doi.org/10.5194/hess-25-5259-2021, 2021
Short summary
Short summary
Localized impacts of changing precipitation patterns on surface hydrology are often assessed at a high spatial resolution. Here we introduce a stochastic method that efficiently generates gridded daily precipitation in a future climate. The method works out a stochastic model that can describe a high-resolution data product in a reference period and form a realistic precipitation generator under a projected future climate. A case study of nine catchments in Norway shows that it works well.
Tian Lan, Kairong Lin, Chong-Yu Xu, Zhiyong Liu, and Huayang Cai
Hydrol. Earth Syst. Sci., 24, 5859–5874, https://doi.org/10.5194/hess-24-5859-2020, https://doi.org/10.5194/hess-24-5859-2020, 2020
Cited articles
Ala-Aho, P., Autio, A., Bhattacharjee, J., Isokangas, E., Kujala, K., Marttila, H., and Klove, B.:
What conditions favor the influence of seasonally frozen ground on hydrological partitioning? A systematic review, Environ. Res. Lett., 16, 043008, https://doi.org/10.1088/1748-9326/abe82c, 2021.
Beibei, Z., Ming'an, S., and Hongbo, S.:
Effects of rock fragments on water movement and solute transport in a Loess Plateau soil, C. R. Geosci., 341, 462–472, https://doi.org/10.1016/j.crte.2009.03.009, 2009.
Bergström, S. and Lindström, G.: Interpretation of runoff processes in hydrological modelling—experience from the HBV approach, Hydrol. Process., 29, 3535–3545, https://doi.org/10.1002/hyp.10510, 2015.
Chen, B., Luo, S., Lü, S., Zhang, Y., and Ma, D.:
Effects of the soil freeze–thaw process on the regional climate of the Qinghai–Tibet Plateau, Clim. Res., 59, 243–257, https://doi.org/10.3354/cr01217, 2014.
Chen, H., Nan, Z., Zhao, L., Ding, Y., Chen, J., and Pang, Q.:
Noah modelling of the permafrost distribution and characteristics in the West Kunlun area, Qinghai–Tibet Plateau, China, Permafrost Periglac., 26, 160–174, https://doi.org/10.1002/ppp.1841, 2015.
Chen, R., Wang, G., Yang, Y., Liu, J., Han, C., Song, Y., and Kang, E.:
Effects of cryospheric change on alpine hydrology: combining a model with observations in the upper reaches of the Hei River, China, J. Geophys. Res.-Atmos., 123, 3414–3442, https://doi.org/10.1002/2017JD027876, 2018.
Chen, R.-S., Lu, S.-H., Kang, E.-S., Ji, X.-B., 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.
Cheng, G. and Jin, H.: Permafrost and groundwater on the Qinghai-Tibet Plateau and in northeast China, Hydrogeol. J., 21, 5–23, https://doi.org/10.1007/s10040-012-0927-2, 2013.
Cousin, I., Nicoullaud, B., and Coutadeur, C.:
Influence of rock fragments on the water retention and water percolation in a calcareous soil, Catena, 53, 97–114, https://doi.org/10.1016/s0341-8162(03)00037-7, 2003.
Cuo, L., Zhang, Y., Bohn, T. J., Zhao, L., Li, J., Liu, Q., and Zhou, B.:
Frozen soil degradation and its effects on surface hydrology in the northern Tibetan Plateau, J. Geophys. Res.-Atmos., 120, 8276–8298, https://doi.org/10.1002/2015JD023193, 2015.
Dai, L., Guo, X., Zhang, F., Du, Y., Ke, X., Li, Y., Cao, G., Li, Q., Lin, L., and Shu, K.:
Seasonal dynamics and controls of deep soil water infiltration in the seasonally-frozen region of the Qinghai–Tibet plateau, J. Hydrol., 571, 740–748, https://doi.org/10.1016/j.jhydrol.2019.02.021, 2019.
Deng, D., Wang, C., and Peng, P.:
Basic Characteristics and Evolution of Geological Structures in the Eastern Margin of the Qinghai–Tibet Plateau, Earth Sci. Res. J., 23, 283–291, https://doi.org/10.15446/esrj.v23n4.84000, 2019.
Ding, Y., Zhang, S., Wu, J., Zhao, Q., Li, X., and Qin, J.:
Recent progress on studies on cryospheric hydrological processes changes in China, Advances in Water Science, 31, 690–702, https://doi.org/10.14042/j.cnki.32.1309.2020.05.006, 2020.
Douville, H., Royer, J.-F., and Mahfouf, J.-F.:
A new snow parameterization for the Meteo-France climate model, Clim. Dynam., 12, 21–35, https://doi.org/10.1007/BF00208760, 1995.
Foley, J. A., Prentice, I. C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., and Haxeltine, A.:
An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics, Global Biogeochem. Cy., 10, 603–628, https://doi.org/10.1029/96GB02692, 1996.
Franzluebbers, A. J.:
Water infiltration and soil structure related to organic matter and its stratification with depth, Soil Till. Res., 66, 197–205, https://doi.org/10.1016/s0167-1987(02)00027-2, 2002.
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, H., Dong, J., Chen, X., Cai, H., Liu, Z., Jin, Z., and Duan, Z.:
Stepwise modeling and the importance of internal variables validation to test model realism in a data scarce glacier basin, J. Hydrol., 591, 125457, https://doi.org/10.1016/j.jhydrol.2020.125457, 2020.
Gao, H., Wang, J., Yang, Y., Pan, X., Ding, Y., and Duan, Z.:
Permafrost hydrology of the Qinghai–Tibet Plateau: A review of processes and modeling, Front. Earth Sci., 8, 576838, https://doi.org/10.3389/feart.2020.576838, 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.
Goodrich, L. E.:
The influence of snow cover on the ground thermal regime, Can. Geotech. J., 19, 421–432, https://doi.org/10.1139/t82-047, 1982.
Grinsted, A.:
An estimate of global glacier volume, The Cryosphere, 7, 141–151, https://doi.org/10.5194/tc-7-141-2013, 2013.
Hedstrom, N. and Pomeroy, J.: Measurements and modelling of snow interception in the boreal forest, Hydrol. Process., 12, 1611–1625, 1998.
Hock, R.:
A distributed temperature-index ice-and snowmelt model including potential direct solar radiation, J. Glaciol., 45, 101–111, https://doi.org/10.3189/S0022143000003087, 1999.
Hu, Z. and Islam, S.:
Prediction of ground surface temperature and soil moisture content by the force-restore method, Water Resour. Res., 31, 2531–2539, https://doi.org/10.1029/95WR01650, 1995.
Huyan, Y., Yao, W., Xie, X., and Wang, L.:
Provenance, source weathering, and tectonics of the Yarlung Zangbo River overbank sediments in Tibetan Plateau, China, using major, trace, and rare earth elements, Geol. J., 57, 37–51, https://doi.org/10.1002/gj.4282, 2022.
Ireson, A., Van Der Kamp, G., Ferguson, G., Nachshon, U., and Wheater, H.:
Hydrogeological processes in seasonally frozen northern latitudes: understanding, gaps and challenges, Hydrogeol. J., 21, 53–66, https://doi.org/10.1007/s10040-012-0916-5, 2013.
Jansson, P. and Karlberg, L.: Coupled heat and mass transfer model for soil-plant-atmosphere systems, Royal Institute of Technology, Dept of Civil and Environmental Engineering, Stockholm, https://www.researchgate.net/publication/304714926 (last access: 25 June 2021), 2004.
Jia, Y. and Tamai, N.:
Integrated analysis of water and heat balances in Tokyo metropolis with a distributed model, Journal of Japan Society of Hydrology and Water Resources, 11, 150–163, https://doi.org/10.3178/jjshwr.11.150, 1998.
Jia, Y., Ni, G., Kawahara, Y., and Suetsugi, T.:
Development of WEP model and its application to an urban watershed, Hydrol. Process., 15, 2175–2194, https://doi.org/10.1002/hyp.275, 2001.
Jia, Y., Wang, H., Zhou, Z., Qiu, Y., Luo, X., Wang, J., Yan, D., and Qin, D.:
Development of the WEP-L distributed hydrological model and dynamic assessment of water resources in the Yellow River basin, J. Hydrol., 331, 606–629, https://doi.org/10.1016/j.jhydrol.2006.06.006, 2006.
Jia, Y., Ding, X., Qin, C., and Wang, H.:
Distributed modeling of landsurface water and energy budgets in the inland Heihe river basin of China, Hydrol. Earth Syst. Sci., 13, 1849–1866, https://doi.org/10.5194/hess-13-1849-2009, 2009.
Kurylyk, B. L., MacQuarrie, K. T., and McKenzie, J. M.:
Climate change impacts on groundwater and soil temperatures in cold and temperate regions: Implications, mathematical theory, and emerging simulation tools, Earth-Sci. Rev., 138, 313–334, https://doi.org/10.1016/j.earscirev.2014.06.006, 2014.
Larsbo, M., Holten, R., Stenrød, M., Eklo, O. M., and Jarvis, N.:
A dual-permeability approach for modeling soil water flow and heat transport during freezing and thawing, Vadose Zone J., 18, https://doi.org/10.2136/vzj2019.01.0012, 2019.
Li, J., Zhou, Z., Wang, H., Liu, J., Jia, Y., Hu, P., and Xu, C.-Y.:
Development of WEP-COR model to simulate land surface water and energy budgets in a cold region, Hydrol. Res., 50, 99–116, https://doi.org/10.2166/nh.2017.032, 2019.
Li, Z., Yu, G., Xu, M., Hu, X., Yang, H., and Hu, S.:
Progress in studies on river morphodynamics in Qinghai–Tibet Plateau, Advances in Water Science, 27, 617–628, https://doi.org/10.14042/j.cnki.32.1309.2016.04.017, 2016.
Ling, F. and Zhang, T.:
Sensitivity of ground thermal regime and surface energy fluxes to tundra snow density in northern Alaska, Cold Reg. Sci. Technol., 44, 121–130, https://doi.org/10.1016/j.coldregions.2005.09.002, 2006.
Liu, X., Yang, W., Zhao, H., Wang, Y., and Wang, G.:
Effects of the freeze–thaw cycle on potential evapotranspiration in the permafrost regions of the Qinghai–Tibet Plateau, China, Sci. Total Environ., 687, 257–266, https://doi.org/10.1016/j.scitotenv.2019.06.005, 2019.
Liu, Z., Yao, Z., Wang, R., and Yu, G.:
Estimation of the Qinghai–Tibetan Plateau runoff and its contribution to large Asian rivers, Sci. Total Environ., 749, 141570, https://doi.org/10.1016/j.scitotenv.2020.141570, 2020.
Lundberg, A., Ala-Aho, P., Eklo, O., Klöve, B., Kværner, J., and Stumpp, C.:
Snow and frost: implications for spatiotemporal infiltration patterns–a review, Hydrol. Process., 30, 1230–1250, https://doi.org/10.1002/hyp.10703, 2016.
Monteith, J.:
Principles of Environmental Physics, Edward Arnold, London, 214 p, https://doi.org/10.1016/0002-1571(74)90085-5, 1973.
Mualem, Y.:
Hydraulic conductivity of unsaturated soils: Prediction and formulas, in: Methods of Soil Analysis, Part 1 Physical and Mineralogical Methods, edited by: Klute, A., 5, 799–823, https://doi.org/10.2136/sssabookser5.1.2ed.c31, 1986.
Niu, G. and Yang, Z.:
Effects of frozen soil on snowmelt runoff and soil water storage at a continental scale, J. Hydrometeorol., 7, 937–952, https://doi.org/10.1175/jhm538.1, 2006.
Pan, X., Li, Y., Yu, Q., Shi, X., Yang, D., and Roth, K.:
Effects of stratified active layers on high-altitude permafrost warming: a case study on the Qinghai–Tibet Plateau, The Cryosphere, 10, 1591–1603, https://doi.org/10.5194/tc-10-1591-2016, 2016.
Pan, Y., Lyu, S., Li, S., Gao, Y., Meng, X., Ao, Y., and Wang, S.:
Simulating the role of gravel in freeze–thaw process on the Qinghai–Tibet Plateau, Theor. Appl. Climatol., 127, 1011–1022, https://doi.org/10.1007/s00704-015-1684-7, 2017.
Pitman, A., Yang, Z., and Henderson-Sellers, A.:
Description of bare essentials of surface transfer for the Bureau of Meteorology Research Centre AGCM, Bureau of Meteorology, Melbourne, Australia, 1991.
Radić, V. and Hock, R.:
Regional and global volumes of glaciers derived from statistical upscaling of glacier inventory data, J. Geophys. Res.-Earth, 115, F01010, https://doi.org/10.1029/2009JF001373, 2010.
Savenije, H. H. G.:
HESS Opinions “Topography driven conceptual modelling (FLEX-Topo)”, Hydrol. Earth Syst. Sci., 14, 2681–2692, https://doi.org/10.5194/hess-14-2681-2010, 2010.
Shang, S.-H., Lei, Z., and Yang, S.:
Numerical simulation improvement of coupled moisture and heat transfer during soil freezing, Journal-Tsinghua University, 37, 62–64, 1997.
Song, C., Wang, G., Sun, X., and Hu, Z.:
River runoff components change variably and respond differently to climate change in the Eurasian Arctic and Qinghai–Tibet Plateau permafrost regions, J. Hydrol., 601, 126653, https://doi.org/10.1016/j.jhydrol.2021.126653, 2021.
St. Jacques, J. M. and Sauchyn, D. J.:
Increasing winter baseflow and mean annual streamflow from possible permafrost thawing in the Northwest Territories, Canada, Geophys. Res. Lett., 36, L01401, https://doi.org/10.1029/2008GL035822, 2009.
Sun, A., Yu, Z., Zhou, J., Acharya, K., Ju, Q., Xing, R., and 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.
Sun, H.:
Formation and Evolution of Qinghai–Xizang Plateau, Shanghai Science and Technology Press, Shanghai, China, ISBN 9787532340231, 1996.
Sun, R., Zhang, X., Sun, Y., Zheng, D., and Fraedrich, K.:
SWAT-based streamflow estimation and its responses to climate change in the Kadongjia River watershed, southern Tibet, J. Hydrometeorol., 14, 1571–1586, https://doi.org/10.1175/jhm-d-12-0159.1, 2013.
Van Genuchten, M. T.:
A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Walvoord, M. A. and Kurylyk, B. L.:
Hydrologic impacts of thawing permafrost – A review, Vadose Zone J., 15, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Wang, A., Xie, Z., Feng, X., Tian, X., and Qin, P.:
A soil water and heat transfer model including changes in soil frost and thaw fronts, Sci. China Earth Sci., 57, 1325–1339, https://doi.org/10.1007/s11430-013-4785-0, 2014.
Wang, H., Xiao, B., and Wang, M.:
Modeling the soil water retention curves of soil–gravel mixtures with regression method on the Loess Plateau of China, PLOS ONE, 8, e59475, https://doi.org/10.1371/journal.pone.0059475, 2013.
Wang, L., Koike, T., Yang, K., Jin, R., and Li, H.:
Frozen soil parameterization in a distributed biosphere hydrological model, Hydrol. Earth Syst. Sci., 14, 557–571, https://doi.org/10.5194/hess-14-557-2010, 2010.
Wang, Y., Yang, H., Yang, D., Qin, Y., Gao, B., and Cong, Z.:
Spatial interpolation of daily precipitation in a high mountainous watershed based on gauge observations and a regional climate model simulation, J. Hydrometeorol., 18, 845–862, https://doi.org/10.1175/jhm-d-16-0089.1, 2017.
Watanabe, K. and Kugisaki, Y.:
Effect of macropores on soil freezing and thawing with infiltration, Hydrol. Process., 31, 270–278, https://doi.org/10.1002/hyp.10939, 2017.
Yang, K., Chen, Y.-Y., and Qin, J.:
Some practical notes on the land surface modeling in the Tibetan Plateau, Hydrol. Earth Syst. Sci., 13, 687–701, https://doi.org/10.5194/hess-13-687-2009, 2009.
Yi, S., Chen, J., Wu, Q., and Ding, Y.:
Simulating the role of gravel on the dynamics of permafrost on the Qinghai-Tibetan Plateau, The Cryosphere Discuss., 7, 4703–4740, https://doi.org/10.5194/tcd-7-4703-2013, 2013.
Zaradny, H.:
Groundwater Flow in Saturated and Unsaturated Soil, Balkema Press, Rotterdam, ISBN 90-5410-100-8, 1993.
Zhang, B. and Zhou, W.:
Spatial–temporal characteristics of precipitation and its relationship with land use/cover change on the Qinghai–Tibet Plateau, China, Land, 10, 269, https://doi.org/10.3390/land10030269, 2021.
Zhou, J., Pomeroy, J. W., Zhang, W., Cheng, G., Wang, G., and Chen, C.:
Simulating cold regions hydrological processes using a modular model in the west of China, J. Hydrol., 509, 13–24, https://doi.org/10.1016/j.jhydrol.2013.11.013, 2014.
Short summary
Considering the impact of the special geological and climatic conditions of the Qinghai–Tibet Plateau on the hydrological cycle, this study established the WEP-QTP hydrological model. The snow cover and gravel layers affected the temporal and spatial changes in frozen soil and improved the regulation of groundwater on the flow process. Ignoring he influence of special underlying surface conditions has a great impact on the hydrological forecast and water resource utilization in this area.
Considering the impact of the special geological and climatic conditions of the Qinghai–Tibet...
