Articles | Volume 26, issue 24
https://doi.org/10.5194/hess-26-6399-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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https://doi.org/10.5194/hess-26-6399-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2022
Research article |
| 20 Dec 2022
| 20 Dec 2022
Significant regime shifts in historical water yield in the Upper Brahmaputra River basin
Center for Agricultural Water Research in China, China Agricultural University, Beijing, China
Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium
Baoying Shan
Research Unit Knowledge-based Systems, Ghent University, Ghent, Belgium
Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium
Center for Agricultural Water Research in China, China Agricultural University, Beijing, China
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Akash Koppa
Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium
Feng Zhong
College of Hydrology and Water Resources, Hohai University, Nanjing, China
Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium
Dongfeng Li
Department of Geography, National University of Singapore, Singapore, Singapore
Xuanxuan Wang
Center for Agricultural Water Research in China, China Agricultural University, Beijing, China
Wenfeng Liu
Center for Agricultural Water Research in China, China Agricultural University, Beijing, China
Xiuping Li
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Zongxue Xu
College of Water Sciences, Beijing Normal University, Beijing, China
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Manuscript not accepted for further review
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Cited articles
Biemans, H., Siderius, C., Lutz, A. F., Nepal, S., Ahmad, B., Hassan, T., von Bloh, W., Wijngaard, R. R., Wester, P., Shrestha, A. B., and Immerzeel, W. W.: Importance of snow and glacier meltwater for agriculture on the Indo-Gangetic Plain, Nat. Sustain., 2, 594–601, https://doi.org/10.1038/s41893-019-0305-3, 2019. a, b, c, d, e
Bonan, G. B.: Forests and climate change: forcings, feedbacks, and the climate benefits of forests, Science, 320, 1444–1449, https://doi.org/10.1126/science.1155121, 2008. a
Bonferroni, C. E.: Il calcolo delle assicurazioni su gruppi di teste, in: Studi in onore del professore salvatore ortu carboni, Rome, Italy, 13–60, 1935. a
Brahney, J., Menounos, B., Wei, X., and Curtis, P. J.: Determining annual
cryosphere storage contributions to streamflow using historical hydrometric
records, Hydrol. Process., 31, 1590–1601, https://doi.org/10.1002/hyp.11128, 2017. a
Chinese Academy of Sciences Resource and Environmental Science Data Center: Landuse dataset in China (1980–2015), http://www.resdc.cn/ (last access: 19 December 2022), 2019. a
Cuo, L., Li, N., Liu, Z., Ding, J., Liang, L., Zhang, Y., and Gong, T.: Warming and human activities induced changes in the Yarlung Tsangpo basin of the Tibetan plateau and their influences on streamflow, J. Hydrol.: Reg. Stud., 25, 100625, https://doi.org/10.1016/j.ejrh.2019.100625, 2019. a
Dierauer, J. R., Whitfield, P. H., and Allen, D. M.: Climate controls on runoff and low flows in mountain catchments of Western North America, Water
Resour. Res., 54, 7495–7510, https://doi.org/10.1029/2018WR023087, 2018. a
Fan, H. and He, D.: Temperature and precipitation variability and its effects
on streamflow in the upstream regions of the Lancang–Mekong and Nu–Salween
Rivers, J. Hydrometeorol., 16, 2248–2263, https://doi.org/10.1175/JHM-D-14-0238.1, 2015. a
Fang, H., Baret, F., Plummer, S., and Schaepman-Strub, G.: An overview of
global leaf area index (LAI): Methods, products, validation, and applications, Rev. Geophys., 57, 739–799, https://doi.org/10.1029/2018RG000608, 2019. a
Forzieri, G., Miralles, D. G., Ciais, P., Alkama, R., Ryu, Y., Duveiller, G., Zhang, K., Robertson, E., Kautz, M., Martens, B., Jiang, C., Arneth, A., Georgievski, G., Li, W., Ceccherini, G., Anthoni, P., Lawrence, P., Wiltshire, A., Pongratz, J., Piao, S., Sitch, S., Goll, D. S., Arora, V. K., Lienert, S., Lombardozzi, D., Kato, E., Nabel, J. E. M. S., Tian, H., Friedlingstein, P., and Cescatti, A.: Increased control of vegetation on global terrestrial energy fluxes, Nat. Clim. Change, 10, 356–362, https://doi.org/10.1038/s41558-020-0717-0, 2020. a, b, c
Gao, P., Mu, X.-M., Wang, F., and Li, R.: Changes in streamflow and sediment discharge and the response to human activities in the middle reaches of the Yellow River, Hydrol. Earth Syst. Sci., 15, 1–10, https://doi.org/10.5194/hess-15-1-2011, 2011. a
Gao, Y., Chen, F., Lettenmaier, D. P., Xu, J., Xiao, L., and Li, X.: Does
elevation-dependent warming hold true above 5000 m elevation? Lessons from
the Tibetan Plateau, npj Clim. Atmos. Sci., 1, 1–7, https://doi.org/10.1038/s41612-018-0030-z, 2018. a
Gleick, P. H. and Palaniappan, M.: Peak water limits to freshwater withdrawal
and use, P. Natl. Acad. Sci. USA, 107, 11155–11162, https://doi.org/10.1073/pnas.1004812107, 2010. a
Gonsamo, A., Ciais, P., Miralles, D. G., Sitch, S., Dorigo, W., Lombardozzi, D., Friedlingstein, P., Nabel, J. E. M. S., Goll, D. S., O'Sullivan, M., Arneth, A., Anthoni, P., Jain, A. K., Wiltshire, A., Peylin, P., and Cescatti, A.: Greening drylands despite warming consistent with carbon dioxide fertilization effect, Global Change Biol., 27, 3336–3349, https://doi.org/10.1111/gcb.15658, 2021.. a, b
Goulden, M. L. and Bales, R. C.: Mountain runoff vulnerability to increased
evapotranspiration with vegetation expansion, P. Natl. Acad. Sci. USA, 111, 14071–14075, https://doi.org/10.1073/pnas.1319316111, 2014. a
Hallema, D. W., Sun, G., Caldwell, P. V., Norman, S. P., Cohen, E. C., Liu, Y., Bladon, K. D., and McNulty, S. G.: Burned forests impact water supplies,
Nat. Commun., 9, 1307, https://doi.org/10.1038/s41467-018-03735-6, 2018. a
He, J., Yang, K., Tang, W., Lu, H., Qin, J., Chen, Y., and Li, X.: The first
high-resolution meteorological forcing dataset for land process studies over
China, Scient. Data, 7, 1–11, https://doi.org/10.11888/AtmosphericPhysics.tpe.249369.file, 2020. a, b
Hu, Z., Piao, S., Knapp, A. K., Wang, X., Peng, S., Yuan, W., Running, S., Mao, J., Shi, X., Ciais, P., Huntzinger, D. N., Yang, J., and Yu, G.: Decoupling of greenness and gross primary productivity as aridity decreases, Remote Sens. Environ., 279, 113120, https://doi.org/10.1016/j.rse.2022.113120, 2022. a
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. a, b, c
Immerzeel, W. W., Van Beek, L. P., and Bierkens, M. F.: Climate change will
affect the Asian water towers, Science, 328, 1382–1385, https://doi.org/10.1126/science.1183188, 2010. a
Immerzeel, W. W., Pellicciotti, F., and Bierkens, M. F. P.: Rising river flows throughout the twenty-first century in two Himalayan glacierized watersheds, Nature Geosci., 6, 742–745, https://doi.org/10.1038/ngeo1896, 2013. a
Kang, S., Xu, Y., You, Q., Flügel, W.-A., Pepin, N., and Yao, T.: Review of climate and cryospheric change in the Tibetan Plateau, Environ. Res. Lett., 5, 015101, https://doi.org/10.1088/1748-9326/5/1/015101, 2010. a
Kendall, M. G.: A new measure of rank correlation, Biometrika, 30, 81–93, https://doi.org/10.1093/biomet/30.1-2.81, 1938. a
Krich, C., Mahecha, M. D., Migliavacca, M., De Kauwe, M. G., Griebel, A., Runge, J., and Miralles, D. G.: Decoupling between ecosystem photosynthesis and transpiration: a last resort against overheating, Environ. Res. Lett., 17, 044013, https://doi.org/10.1088/1748-9326/ac583e, 2022. a
Li, D., Li, Z., Zhou, Y., and Lu, X.: Substantial Increases in the Water and Sediment Fluxes in the Headwater Region of the Tibetan Plateau in Response to Global Warming, Geophys. Res. Lett., 47, e2020G–e87745G, https://doi.org/10.1029/2020GL087745, 2020. a
Li, H.: HaoLi2030/HESS-2022-Water-Yield: version 1.0, Zenodo [code], https://doi.org/10.5281/zenodo.7315564, 2022. a
Li, H., Liu, L., Liu, X., Li, X., and Xu, Z.: Greening Implication Inferred from Vegetation Dynamics Interacted with Climate Change and Human Activities over the Southeast QinghaiTibet Plateau, Remote Sens., 11, 2421, https://doi.org/10.3390/rs11202421, 2019a. a, b
Li, H., Liu, L., Shan, B., Xu, Z., Niu, Q., Cheng, L., Liu, X., and Xu, Z.:
Spatiotemporal variation of drought and associated multi-scale response to
climate change over the Yarlung Zangbo River Basin of Qinghai–Tibet Plateau,
China, Remote Sens., 11, 1596, https://doi.org/10.3390/rs11131596, 2019b. a, b, c
Li, H., Liu, L., Koppa, A., Shan, B., Liu, X., Li, X., Niu, Q., Cheng, L., and Miralles, D.: Vegetation greening concurs with increases in dry season water yield over the Upper Brahmaputra River basin, J. Hydrol., 603, 126–981, https://doi.org/10.1016/j.jhydrol.2021.126981, 2021. a, b, c, d, e, f, g
Li, J., Liu, D., Wang, T., Li, Y., Wang, S., Yang, Y., Wang, X., Guo, H., Peng, S., Ding, J., Shen, M., and Wang, L.: Grassland restoration reduces water yield in the headstream region of Yangtze River, Sci. Rep., 7, 2162, https://doi.org/10.1038/s41598-017-02413-9, 2017. a
Li, X., Long, D., Han, Z., Scanlon, B. R., Sun, Z., Han, P., and Hou, A.:
Evapotranspiration estimation for Tibetan Plateau headwaters using conjoint
terrestrial and atmospheric water balances and multisource remote sensing,
Water Resour. Res., 55, 8608–8630, https://doi.org/10.1029/2019WR025196, 2019. a
Lin, L., Gao, M., Liu, J., Wang, J., Wang, S., Chen, X., and Liu, H.: Understanding the effects of climate warming on streamflow and active groundwater storage in an alpine catchment: the upper Lhasa River, Hydrol. Earth Syst. Sci., 24, 1145–1157, https://doi.org/10.5194/hess-24-1145-2020, 2020. a
Lutz, A., Immerzeel, W., Shrestha, A., and Bierkens, M.: Consistent increase in High Asia's runoff due to increasing glacier melt and precipitation, Nat. Clim. Change, 4, 587–592, https://doi.org/10.1038/nclimate2237, 2014. a, b, c
Mann, H. B.: Nonparametric Tests Against Trend, Econometrica, 13, 245, https://doi.org/10.2307/1907187, 1945. a
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017. a, b
Pellicciotti, F., Buergi, C., Immerzeel, W. W., Konz, M., and Shrestha, A. B.: Challenges and uncertainties in hydrological modeling of remote Hindu
Kush–Karakoram–Himalayan (HKH) basins: suggestions for calibration strategies, Mount. Res. Dev., 32, 39–50, https://doi.org/10.1659/MRD-JOURNAL-D-11-00092.1, 2012. a
Pettitt, A. N.: A non-parametric approach to the change-point problem, J. Roy. Stat. Soc. Ser. C, 28, 126–135, https://doi.org/10.2307/2346729, 1979. a
Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M. D., Muñoz-Marí, J., van Nes, E. H., Peters, J., Quax, R., Reichstein, M., Scheffer, M., Schölkopf, B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., and Zscheischler, J.: Inferring causation from time series in Earth system sciences, Nat. Commun., 10, 2553, https://doi.org/10.1038/s41467-019-10105-3, 2019. a
Sang, Y., Singh, V. P., Gong, T., Xu, K., Sun, F., Liu, C., Liu, W., and Chen, R.: Precipitation variability and response to changing climatic condition in the Yarlung Tsangpo River basin, China, J. Geophys. Res.-Atmos., 121, 8820–8831, https://doi.org/10.1002/2016JD025370, 2016. a, b
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. a
Sun, H. and Su, F.: Precipitation correction and reconstruction for streamflow simulation based on 262 rain gauges in the upper Brahmaputra of southern Tibetan Plateau, J. Hydrol., 590, 125484, https://doi.org/10.1016/j.jhydrol.2020.125484, 2020. a, b, c, d
Sun, H., Su, F., Huang, J., Yao, T., Luo, Y., and Chen, D.: Contrasting
precipitation gradient characteristics between westerlies and monsoon
dominated upstream river basins in the Third Pole, Chinese Sci. Bull., 65, 91–104, https://doi.org/10.1360/TB-2019-0491, 2019. a
Tang, Q., Su, F., Zhang, Y., Ding, J., He, L., Tang, Y., Liu, X., Liu, X., Xu, X., Sang, Y., Han, D., Sun, H., Leng, G., Wang, L., Fang, H., Chen, D., Zhang, S., and Lan, C.: Streamflow change on the Qinghai-Tibet Plateau and its impacts, Chin. Sci. Bull., 64, 2807–2821, https://doi.org/10.1360/TB-2019-0141, 2019. a
Viviroli, D., Archer, D. R., Buytaert, W., Fowler, H. J., Greenwood, G. B., Hamlet, A. F., Huang, Y., Koboltschnig, G., Litaor, M. I., López-Moreno, J. I., Lorentz, S., Schädler, B., Schreier, H., Schwaiger, K., Vuille, M., and Woods, R.: Climate change and mountain water resources: overview and recommendations for research, management and policy, Hydrol. Earth Syst. Sci., 15, 471–504, https://doi.org/10.5194/hess-15-471-2011, 2011. a, b
Wang, L., Yao, T., Chai, C., Cuo, L., Su, F., Zhang, F., Yao, Z., Zhang, Y., Li, X., Qi, J., Hu, Z., Liu, J., and Wang, Y.: TP-River: Monitoring and Quantifying Total River Runoff from the Third Pole, B. Am. Meteorol. Soc., 102, E948–E965, https://doi.org/10.1175/BAMS-D-20-0207.1, 2021. a, b, c, d
Wang, L., Cuo, L., Luo, D., Su, F., Ye, Q., Yao, T., Zhou, J., Li, X., Li, N., Sun, H., Liu, L., Wang, Y., Zeng, T., Hu, Z., Liu, R., Chai, C., Wang, G., Zhong, X., Guo, X., Zhao, H., Zhao, H., and Yang, W.: Observing Multisphere Hydrological Changes in the Largest River Basin of the Tibetan Plateau, B. Am. Meteorol. Soc., 103, E1595–E1620, https://doi.org/10.1175/BAMS-D-21-0217.1, 2022. a, b
Wei, X. and Zhang, M.: Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study: Large-Scale Forest Disturbance, Water Resour. Res., 46, W12525, https://doi.org/10.1029/2010WR009250, 2010. a, b
Wei, X., Li, Q., Zhang, M., Giles-Hansen, K., Liu, W., Fan, H., Wang, Y., Zhou, G., Piao, S., and Liu, S.: Vegetation cover – another dominant factor in determining global water resources in forested regions, Global Change Biol., 24, 786–795, https://doi.org/10.1111/gcb.13983, 2018. a
Yang, X., Yong, B., Ren, L., Zhang, Y., and Long, D.: Multi-scale validation of GLEAM evapotranspiration products over China via ChinaFLUX ET measurements, Int. J. Remote Sens., 38, 5688–5709, https://doi.org/10.1080/01431161.2017.1346400, 2017. a, b
Yao, T., Li, Z., Yang, W., Guo, X., Zhu, L., Kang, S., Wu, Y., and Yu, W.:
Glacial distribution and mass balance in the Yarlung Zangbo River and its
influence on lakes, Chinese Sci. Bull., 55, 2072–2078, https://doi.org/10.1007/s11434-010-3213-5, 2010. a, b, c
Yao, T., Xue, Y., Chen, D., Chen, F., Thompson, L., Cui, P., Koike, T., Lau, W. K.-M., Lettenmaier, D., Mosbrugger, V., Zhang, R., Xu, B., Dozier, J., Gillespie, T., Gu, Y., Kang, S., Piao, S., Sugimoto, S., Ueno, K., Wang, L., Wang, W., Zhang, F., Sheng, Y., Guo, W., Ailikun, Yang, X., Ma, Y., Shen, S. S. P., Su, Z., Chen, F., Liang, S., Liu, Y., Singh, V. P., Yang, K., Yang, D., Zhao, X., Qian, Y., Zhang, Y., and Li, Q.: Recent Third Pole's Rapid Warming Accompanies Cryospheric Melt and Water Cycle Intensification and Interactions between Monsoon and Environment: Multidisciplinary Approach with Observations, Modeling, and Analysis, B. Am. Meteorol. Soc., 100, 423–444, https://doi.org/10.1175/BAMS-D-17-0057.1, 2019. a, b, c, d
Zhang, G., Yao, T., Piao, S., Bolch, T., Xie, H., Chen, D., Gao, Y., O'Reilly, C. M., Shum, C. K., Yang, K., Yi, S., Lei, Y., Wang, W., He, Y., Shang, K., Yang, X., and Zhang, H.: Extensive and drastically different alpine lake changes on Asia's high plateaus during the past four decades, Geophys. Res. Lett., 44, 252–260, https://doi.org/10.1002/2016GL072033, 2017. a
Zhang, L., Nan, Z., Wang, W., Ren, D., Zhao, Y., and Wu, X.: Separating climate change and human contributions to variations in streamflow and its components using eight time-trend methods, Hydrol. Process., 33, 383–394, https://doi.org/10.1002/hyp.13331, 2019. a
Zhang, M. and Wei, X.: Deforestation, forestation, and water supply, Science,
371, 990–991, https://doi.org/10.1126/science.abe7821, 2021. a
Zhang, M., Ren, Q., Wei, X., Wang, J., Yang, X., and Jiang, Z.: Climate change, glacier melting and streamflow in the Niyang River Basin, Southeast Tibet, China, Ecohydrology, 4, 288–298, https://doi.org/10.1002/eco.206, 2011. a
Zhang, Y., Xu, C.-Y., Hao, Z., Zhang, L., Ju, Q., and Lai, X.: Variation of Melt Water and Rainfall Runoff and Their Impacts on Streamflow Changes during Recent Decades in Two Tibetan Plateau Basins, Water, 12, 3112, https://doi.org/10.3390/w12113112, 2020.
a
Zhou, X., Zhang, Y., Beck, H. E., and Yang, Y.: Divergent negative spring vegetation and summer runoff patterns and their driving mechanisms in natural ecosystems of northern latitudes, J. Hydrol., 592, 125848, https://doi.org/10.1016/j.jhydrol.2020.125848, 2021. a
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao, S., Nemani, R. R., and Myneni, R. B.: Global data sets of vegetation leaf area index (LAI) 3g and fraction of photosynthetically active radiation (FPAR) 3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2011, Remote Sens., 5, 927–948, https://doi.org/10.3390/rs5020927, 2013. a
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais, P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E., Koven, C., Li, Y., Lian, X., Liu, Y., Liu, R., Mao, J., Pan, Y., Peng, S., Peñuelas, J., Poulter, B., Pugh, T. A. M., Stocker, B. D., Viovy, N., Wang, X., Wang, Y., Xiao, Z., Yang, H., Zaehle, S., and Zeng, N.: Greening of the Earth and its drivers, Nat. Clim. Change, 6, 791–795, https://doi.org/10.1038/nclimate3004, 2016. a, b
Short summary
This study examines changes in water yield by determining turning points in the direction of yield changes and highlights that regime shifts in historical water yield occurred in the Upper Brahmaputra River basin, both the climate and cryosphere affect the magnitude of water yield increases, climate determined the declining trends in water yield, and meltwater has the potential to alleviate the water shortage. A repository for all source files is made available.
This study examines changes in water yield by determining turning points in the direction of...
