[1] Abawi, G. Y., S. C. Dutta, T. Aris, et al., 2000: The use of seasonal climate forecasts in water resources management. Proc. 3rd International Hydrology and Water Resources Symposium of the Institute of Engineers, Australian Institute of Engineers, Canberra, 20–23.
[2] Abtew, W., and P. Trimble, 2010: El Niño–Southern Oscillation link to South Florida hydrology and water management applications. Water Resour. Manage., 24, 4255–4271. doi: 10.1007/s11269-010-9656-2
[3] Ban, X., B. Y. Zhu, P. Shu, et al., 2018: Trend and driving force of climate and hydrological process in Hanjiang basin. Resour. Environ. Yangtze Basin, 27, 2817–2829. (in Chinese) doi: 10.11870/cjlyzyyhj201812018
[4] Biemans, H., I. Haddeland, P. Kabat, et al., 2011: Impact of reservoirs on river discharge and irrigation water supply during the 20th century. Water Resour. Res., 47, W03509. doi: 10.1029/2009WR008929
[5] Cannon, A. J., S. R. Sobie, and T. Q. Murdock, 2015: Bias correction of GCM precipitation by quantile mapping: How well do methods preserve changes in quantiles and extremes? J. Climate, 28, 6938–6959. doi: 10.1175/JCLI-D-14-00754.1
[6] Chen, T., J. Xia, and L. Zou, 2019: The response of the upstream hydrological cycle process to climate change in the upper Hanjiang River basin. China Rural Water and Hydropower, 9, 1–7. (in Chinese) doi: 10.3969/j.issn.1007-2284.2019.09.001
[7] Ding, Y. H., G. Y. Ren, G. Y. Shi, et al., 2007: China’s national assessment report on climate change (I): Climate change in China and the future trend. Adv. Climate Change Res., 3, 1–5. (in Chinese) doi: 10.3969/j.issn.1673-1719.2007.z1.001
[8] Ehsani, N., C. J. Vörösmarty, B. M. Fekete, et al., 2017: Reservoir operations under climate change: Storage capacity options to mitigate risk. J. Hydrol., 555, 435–446. doi: 10.1016/j.jhydrol.2017.09.008
[9] Fang, S. D., M. Liu, and Y. J. Ren, 2018: Drought and waterlogging characteristics and risk prediction in different river basin areas of middle route of South-to-North Water Transfer Project. Bull. Soil Water Conserv., 38, 263–267, 276. (in Chinese) doi: 10.13961/j.cnki.stbctb.2018.06.040
[10] Feldman, D. L., and H. M. Ingram, 2009: Making science useful to decision makers: Climate forecasts, water management, and knowledge networks. Wea. Climate Soc., 1, 9–21. doi: 10.1175/2009WCAS1007.1
[11] Feng, M. Y., P. Liu, S. L. Guo, et al., 2017: Identifying changing patterns of reservoir operating rules under various inflow alteration scenarios. Adv. Water Res., 104, 23–36. doi: 10.1016/j.advwatres.2017.03.003
[12] Gao, X. J., J. Wu, Y. Shi, et al., 2018: Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations. Atmos. Ocean. Sci. Lett., 11, 291–299. doi: 10.1080/16742834.2018.1471578
[13] Giorgi, F., C. Jones, and G. R. Asrar, 2009: Addressing climate information needs at the regional level: The CORDEX framework. WMO Bull., 58, 175–183.
[14] Golding, N., C. Hewitt, and P. Q. Zhang, 2017: Effective engagement for climate services: Methods in practice in China. Climate Serv., 8, 72–76. doi: 10.1016/j.cliser.2017.11.002
[15] Golding, N., C. Hewitt, P. Q. Zhang, et al., 2019: Co-development of a seasonal rainfall forecast service: Supporting flood risk management for the Yangtze River basin. Climate Risk Manage., 23, 43–49. doi: 10.1016/j.crm.2019.01.002
[16] Guo, S. L., Y. Wang, Y. L. Zhou, et al., 2015: Optimal control of flood water resources for the Danjiangkou reservoir. J. Water Resour. Res., 4, 1–8. (in Chinese) doi: 10.12677/JWRR.2015.41001
[17] Haddeland, I., J. Heinke, H. Biemans, et al., 2014: Global water resources affected by human interventions and climate change. Proc. Natl. Acad. Sci. USA, 111, 3251–3256. doi: 10.1073/pnas.1222475110
[18] Han, Z. Y., B. T. Zhou, Y. Xu, et al., 2017: Projected changes in haze pollution potential in China: An ensemble of regional climate model simulations. Atmos. Chem. Phys., 17, 10,109–10,123. doi: 10.5194/acp-17-10109-2017
[19] Han, Z. Y., Y. Tong, X. J. Gao, et al., 2018: Correction based on quantile mapping for temperature simulated by the RegCM4. Climate Change Res., 14, 331–340. (in Chinese) doi: 10.12006/j.issn.1673-1719.2017.156
[20] Han, Z. Y., X. J. Gao, and Y. Xu, 2020: Mean and extreme precipitation projection over land area of East Asia based on multiple regional climate models. Chinese J. Geophys., doi: 10.6038/cjg2021O0103. (in press)
[21] Harding, R., M. Best, E. Blyth, et al., 2011: WATCH: Current knowledge of the terrestrial global water cycle. J. Hydrometeor., 12, 1149–1156. doi: 10.1175/JHM-D-11-024.1
[22] Hausfather, Z., and G. P. Peters, 2020: Emissions–the ‘business as usual’ story is misleading. Nature, 577, 618–620. doi: 10.1038/d41586-020-00177-3
[23] Hewitt, C., S. Mason, and D. Walland, 2012: The global framework for climate services. Nat. Climate Change, 2, 831–832. doi: 10.1038/nclimate1745
[24] Ho, E., D. V. Budescu, V. Bosetti, et al., 2019: Not all carbon dioxide emission scenarios are equally likely: A subjective expert assessment. Climatic Change, 155, 545–561. doi: 10.1007/s10584-019-02500-y
[25] Huntington, T. G., 2006: Evidence for intensification of the global water cycle: Review and synthesis. J. Hydrol., 319, 83–95. doi: 10.1016/j.jhydrol.2005.07.003
[26] IPCC, 2014: Freshwater resources. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, C. B. Field, V. R. Barros, D. J. Dokken, et al., Eds., Cambridge University Press, Cambridge, 229–269.
[27] Kirchhoff, C. J., 2013: Understanding and enhancing climate information use in water management. Climatic Change, 119, 495–509. doi: 10.1007/s10584-013-0703-x
[28] Koutroulis, A. G., M. G. Grillakis, I. K. Tsanis, et al., 2015: Exploring the ability of current climate information to facilitate local climate services for the water sector. Earth Perspect., 2, 6. doi: 10.1186/s40322-015-0032-5
[29] Lemos, M. C., and R. B. Rood, 2010: Climate projections and their impact on policy and practice. WIREs Climate Change, 1, 670–682. doi: 10.1002/wcc.71
[30] Li, J. F., Y. D. Chen, L. Zhang, et al., 2016: Future changes in floods and water availability across China: Linkage with changing climate and uncertainties. J. Hydrometeor., 17, 1295–1314. doi: 10.1175/JHM-D-15-0074.1
[31] Li, Q. Q., Y. H. Ding, and P. Q. Zhang, 2004: Primary verification and assessment on the extra-seasonally predictive capability of a global atmospheric–oceanic coupled model in raining season. Acta Meteor. Sinica, 62, 740–751. (in Chinese) doi: 10.11676/qxxb2004.070
[32] Liu, H., J. Yin, and L. Feng, 2018: The dynamic changes in the storage of the Danjiangkou reservoir and the influence of the South–North Water Transfer Project. Sci. Rep., 8, 8710. doi: 10.1038/s41598-018-26788-5
[33] Lu, C., G. H. Huang, and X. Q. Wang, 2019: Projected changes in temperature, precipitation, and their extremes over China through the RegCM. Climate Dyn., 53, 5859–5880. doi: 10.1007/s00382-019-04899-7
[34] Oki, T., and S. Kanae, 2006: Global hydrological cycles and world water resources. Science, 313, 1068–1072. doi: 10.1126/science.1128845
[35] Peng, Z. L., W. P. Hu, G. Liu, et al., 2019: Estimating daily inflows of large lakes using a water-balance-based runoff coefficient scaling approach. Hydrol. Processes, 33, 2535–2550. doi: 10.1002/hyp.13486
[36] Piao, S. L., P. Ciais, Y. Huang, et al., 2010: The impacts of climate change on water resources and agriculture in China. Nature, 467, 43–51. doi: 10.1038/nature09364
[37] Qin, P. C., H. M. Xu, M. Liu, et al., 2020: Climate change impacts on Three Gorges Reservoir impoundment and hydropower generation. J. Hydrol., 580, 123922. doi: 10.1016/j.jhydrol.2019.123922
[38] Rayner, S., D. Lach, and H. Ingram, 2005: Weather forecasts are for wimps: Why water resource managers do not use climate forecasts. Climatic Change, 69, 197–227. doi: 10.1007/s10584-005-3148-z
[39] Ren, H.-L., Y. J. Wu, Q. Bao, et al., 2019: The China Multi-Mo-del Ensemble Prediction System and its application to flood-season prediction in 2018. J. Meteor. Res., 33, 540–552. doi: 10.1007/s13351-019-8154-6
[40] Ren, Z. H., Y. Yu, F. L. Zhou, et al., 2012: Quality detection of surface historical basic meteorological data. J. Appl. Meteor. Sci., 23, 739–747. (in Chinese) doi: 10.3969/j.issn.1001-7313.2012.06.011
[41] Reshmidevi, T. V., D. N. Kumar, R. Mehrotra, et al., 2018: Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs. J. Hydrol., 556, 1192–1204. doi: 10.1016/j.jhydrol.2017.02.016
[42] Rice, J. L., C. A. Woodhouse, and J. J. Lukas, 2009: Science and decision making: Water management and tree-ring data in the western United States. J. Amer. Water Res. Assoc., 45, 1248–1259. doi: 10.1111/j.1752-1688.2009.00358.x
[43] Ritchie, J. W., C. Zammit, and D. Beal, 2004: Can seasonal climate forecasting assist in catchment water management decision-making?: A case study of the Border Rivers catchment in Australia. Agric. Ecosyst. Environ., 104, 553–565. doi: 10.1016/j.agee.2004.01.029
[44] Shi, Y., G. L. Wang, and X. J. Gao, 2018a: Role of resolution in regional climate change projections over China. Climate Dyn., 51, 2375–2396. doi: 10.1007/s00382-017-4018-x
[45] Shi, Y., D. F. Zhang, Y. Xu, et al., 2018b: Changes of heating and cooling degree days over China in response to global warming of 1.5°C, 2°C, 3°C and 4°C. Adv. Climate Change Res., 9, 192–200. doi: 10.1016/j.accre.2018.06.003
[46] Tong, Y., X. J. Gao, Z. Y. Han, et al., 2017: Bias correction of daily precipitation simulated by RegCM4 model over China. Chinese J. Atmos. Sci., 41, 1156–1166. (in Chinese) doi: 10.3878/j.issn.1006-9895.1704.16275
[47] Tong, Y., X. J. Gao, Z. Y. Han, et al., 2020: Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods. Climate Dyn., . doi: 10.1007/s00382-020-05447-4
[48] van Vliet, M. T. H., C. Donnelly, L. Strömbäck, et al., 2015: European scale climate information services for water use sectors. J. Hydrol., 528, 503–513. doi: 10.1016/j.jhydrol.2015.06.060
[49] Wang, G. Q., X. L. Yan, J. Y. Zhang, et al., 2013: Detecting evolution trends in the recorded runoffs from the major rivers in China during 1950–2010. J. Water Climate Change, 4, 252–264. doi: 10.2166/wcc.2013.021
[50] Wang, Y., S. L. Guo, and T. Y. Li, 2014: Study of scheme of impounding in advance for Danjiangkou reservoir. Eng. J. Wuhan Univ., 47, 433–439. (in Chinese)
[51] Wang, Y. J., L. C. Song, C. Hewitt, et al., 2020: Improving China’s resilience to climate-related risks: The China framework for climate services. Wea. Climate Soc., 12, 729–744. doi: 10.1175/WCAS-D-19-0121.1
[52] WMO, 2014: Implementation Plan of the Global Framework for Climate Services. Available online at https://gfcs.wmo.int//sites/default/files/implementation-plan/GFCS-IMPLEMENTATION-PLAN-FINAL-14211_en.pdf. Accessed on 8 January 2021.
[53] Wu, C. H., G. R. Huang, H. J. Yu, et al., 2014: Impact of climate change on reservoir flood control in the upstream area of the Beijiang River basin, South China. J. Hydrometeor., 15, 2203–2218. doi: 10.1175/JHM-D-13-0181.1
[54] Wu, J., and X. J. Gao, 2013: A gridded daily observation dataset over China region and comparison with the other datasets. Chinese J. Geophys., 56, 1102–1111. (in Chinese)
[55] Wu, T. W., L. C. Song, X. W. Liu, et al., 2013: Progress in developing the short-range operational climate prediction system of China National Climate Center. J. Appl. Meteor. Sci., 24, 533–543. (in Chinese) doi: 10.3969/j.issn.1001-7313.2013.05.003
[56] Xi, Y., S. S. Peng, P. Ciais, et al., 2018: Contributions of climate change, CO2, land-use change, and human activities to changes in river flow across 10 Chinese basins. J. Hydrometeor., 19, 1899–1914. doi: 10.1175/JHM-D-18-0005.1
[57] Xia, J., X. P. Luo, J. T. Cao, et al., 2015: Impact and assessment of climate change on the water resources vulnerability in the eastern China monsoon region. Progressus Inquisitiones Mutatione Climatis, 11, 8–14. (in Chinese) doi: 10.3969/j.issn.1673-1719.2015.01.002
[58] Xu, Y., X. J. Gao, Y. Shen, et al., 2009: A daily temperature dataset over China and its application in validating a RCM simulation. Adv. Atmos. Sci., 26, 763–772. doi: 10.1007/s00376-009-9029-z
[59] Yu, J. Y., J. Xia, D. X. She, et al., 2018: The analysis of encounter probability of drought between the water source area and the Hai River water receiving area in the middle route of the South-to-North Water Transfer Project in China. South-to-North Water Transf. Water Sci. Technol., 16, 63–68, 194. (in Chinese) doi: 10.13476/j.cnki.nsbdqk.20180010
[60] Zhang, D. F., Z. Y. Han, and Y. Shi, 2017: Comparison of climate projections between driving CSIRO-Mk3.6.0 and downscaling simulation of RegCM4.4 over China. Adv. Climate Change Res., 8, 245–255. doi: 10.1016/j.accre.2017.10.001
[61] Zhang, H., C. H. Wu, W. J. Chen, et al., 2017: Assessing the impact of climate change on the waterlogging risk in coastal cities: A case study of Guangzhou, South China. J. Hydrometeor., 18, 1549–1562. doi: 10.1175/JHM-D-16-0157.1
[62] Zhang, H., B. Wang, D. L. Liu, et al., 2019: Impacts of future climate change on water resource availability of eastern Australia: A case study of the Manning River basin. J. Hydrol., 573, 49–59. doi: 10.1016/j.jhydrol.2019.03.067
[63] Zhang, L. P., L. L. Qin, Z. F. Hu, et al., 2010: Simulated hydrologic responses to climate change of water source area in the Middle Route of South-to-North Water Transfer Project. J. Hyd. Eng., 41, 1261–1271. (in Chinese) doi: 10.13243/j.cnki.slxb.2010.11.001
[64] Zheng, Z. H., H. L. Ren, and J. P. Huang, 2009: Analogue correction of errors based on seasonal climatic predictable components and numerical experiments. Acta Phys. Sinica, 58, 7359–7367. (in Chinese) doi: 10.3321/j.issn:1000-3290.2009.10.114
[65] Zhou, B. T., Z. Y. Wang, Y. Shi, et al., 2018: Historical and future changes of snowfall events in China under a warming background. J. Climate, 31, 5873–5889. doi: 10.1175/JCLI-D-17-0428.1
[66] Zhu, J. X., G. Huang, X. Q. Wang, et al., 2018: High-resolution projections of mean and extreme precipitations over China through PRECIS under RCPs. Climate Dyn., 50, 4037–4060. doi: 10.1007/s00382-017-3860-1