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Articles

Assessing flood risk in Baiyangdian Lake area in a changing climate using an integrated hydrological-hydrodynamic modelling

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Pages 2006-2014 | Received 22 Mar 2018, Accepted 26 Apr 2019, Published online: 28 Oct 2019

References

  • Asadzadeh, M. and Tolson, B., 2013. Pareto archived dynamically dimensioned search with hypervolume-based selection for multi-objective optimization. Engineering Optimization, 45 (12), 1489–1509. doi:10.1080/0305215X.2012.748046
  • Bergström, S., 1995. The HBV model. In: V.P. Singh, ed. Computer models of watershed hydrology. Highlands Ranch, CO: Water Resources Publications, 443–476.
  • Bouwer, L.M., 2013. Projections of future extreme weather losses under changes in climate and exposure. Risk Analysis, 33 (5), 915–930. doi:10.1111/j.1539-6924.2012.01880.x
  • Chen, J., et al., 2017. Assessing changes of river discharge under global warming of 1.5º and 2º in the upper reaches of the Yangtze River Basin: approach by using multiple-GCMs and hydrological models. Quaternary International, 453, 63–73. doi:10.1016/j.quaint.2017.01.017
  • Chen, Y., et al., 2011. Liuxihe model and its modelling to river basin flood. Journal of Hydrologic Engineering, 16, 33–50. doi:10.1061/(ASCE)HE.1943-5584.0000286
  • Chen, Y., Li, J., and Xu, H., 2016. Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization. Hydrology and Earth System Sciences, 20, 375–392. doi:10.5194/hess-20-375-2016
  • Crooks, S.M., et al., 2000. EUROTAS (European river flood occurrence and total risk assessment system) final report [online]. Task T3: Thames Catchment Study, EU Contract ENV4-CT97-0535, 84. Available from: https://scholar.google.com/scholar?q=EUROTAS%20,%20Final%20Report%20Task%20T3:%20Thames%20Catchment%20Study%20%20EU%20Contract%20ENV4-CT97-0535
  • De Roo, A.P.J., Wesseling, C.G., and Van Deurzen, W.P.A., 2000. Physically-based river basin modelling within a GIS: the LISFLOOD model. Hydrological Processes, 14, 1981–1992. doi:10.1002/1099-1085(20000815/30)14:11/12<1981::AID-HYP49>3.0.CO;2-F
  • Dominguez, F., et al., 2012. Changes in winter precipitation extremes for the western United States under a warmer climate as simulated by regional climate models. Geophysical Research Letters, 39 (5), 0874. doi:10.1029/2011GL050762
  • Duan, Q., Sorooshian, S., and Gupta, V.K., 1994. Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology, 158 (3–4), 265–284. doi:10.1016/0022-1694(94)90057-4
  • Felder, G., Zischg, A., and Weingartner, R., 2017. The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation. Journal of Hydrology, 550, 157–165. doi:10.1016/j.jhydrol.2017.04.052
  • Field, C.B., et al., 2012. Managing the risks of extreme events and disasters to advance climate change adaptation. Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK: Cambridge University Press.
  • Fu, G., Kapelan, Z., and Reed, P., 2012. Reducing the complexity of multi-objective water distribution system optimization through global sensitivity analysis. Journal of Water Resources Planning and Management, 138 (3), 196–207. doi:10.1061/(ASCE)WR.1943-5452.0000171
  • Galland, J.C., Goutal, N., and Hervouet, J.M., 1991. TELEMAC: a new numerical model for solving shallow water equations. Advances in Water Resources, 14 (3), 138–148. doi:10.1016/0309-1708(91)90006-A
  • Graham, D.N. and Butts, M.B., 2006. Flexible, integrated watershed modelling with MIKE SHE. In: V.P. Singh and D.K. Frevert, eds. Watershed models. Highlands Ranch, CO: Water Resources Publications, 245–272.
  • Han, J.T., 1981. A brief introduction of “63.8” large flood event over Hai River basin (in Chinese). Hydrology, (5), 56–59.
  • Handmer, J., et al., 2012. Changes in impacts of climate extremes: human systems and ecosystems. In: C.B. Field, et al., ed. Managing the risks of extreme events and disasters to advance climate change adaptation. Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK: Cambridge University Press, 231–290.
  • Hay, L.E., Wilby, R.L., and Leavesle, G.H., 2000. A comparison of Delta Change and downscaled GCM scenarios for three mountainous basins in the United States. Journal of the American Water Resources Association, 36 (2), 387–397. doi:10.1111/j.1752-1688.2000.tb04276.x
  • Hempel, S., et al., 2013. A trend-preserving bias correction - the ISI-MIP approach. Earth System Dynamics, 4, 219–236. doi:10.5194/esd-4-219-2013
  • Hervouet, J.M. and Van Haren, L., 1996. Recent advances in numerical methods for fluid flows. In: M.G. Anderson, D.E. Walling, and P.D. Bates, eds. Floodplain processes. Chichester, UK: Wiley, 183–214.
  • Hirabayashi, Y., et al., 2013. Global flood risk under climate change. Nature Climate Change, 3, 816–821. doi:10.1038/nclimate1911
  • Horritt, M.S. and Bates, P.D., 2001. Predicting floodplain inundation: raster-based modelling versus the finite-element approach. Hydrological Processes, 15 (5), 825–842. doi:10.1002/(ISSN)1099-1085
  • Jiang, B., et al., 2017. Evaluation of the economic value of final ecosystem services from the Baiyangdian wetland (In Chinese). Acta Ecologica Sinica, 37 (8), 2497–2505. doi:10.5846/stxb201410091984
  • Kollat, J.B. and Reed, P.M., 2006. Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design. Advances in Water Resources, 29 (6), 792–807. doi:10.1016/j.advwatres.2005.07.010
  • Lai, J.S., et al., 2010. A well-balanced upstream flux-splitting finite-volume scheme for shallow-water flow simulations with irregular bed topography. International Journal for Numerical Methods in Fluids, 62 (8), 927–944.
  • Leng, G. and Tang, Q., 2014. Modelling the impacts of future climate change on irrigation over China: Sensitivity to adjusted projections. Journal of Hydrometeorology, 15, 2085–2103. doi:10.1175/JHM-D-13-0182.1
  • Li, C.H., et al., 2017. Effects of urban non-point source pollution from Baoding City on Baiyangdian Lake, China. Water, 9 (4), 249. doi:10.3390/w9040249
  • Liang, Q., et al., 2008. Flood inundation modelling with an adaptive quadtree grid shallow water equation solver. Journal of Hydraulic Engineering, 134 (11), 1603–1610. doi:10.1061/(ASCE)0733-9429(2008)134:11(1603)
  • Liang, Q., 2010. Flood simulation using a well-balanced shallow flow model. Journal of Hydraulic Engineering, 136 (9), 669–675. doi:10.1061/(ASCE)HY.1943-7900.0000219
  • Liang, Q., Smith, L., and Xia, X., 2016. New prospects for computational hydraulics by leveraging high-performance heterogeneous computing techniques. Journal of Hydrodynamics, 28 (6), 977–985. doi:10.1016/S1001-6058(16)60699-6
  • Liang, X., et al., 1994. A simple hydrologically based model of land surface and energy fluxes for general circulation models. Journal of Geophysical Research, 99 (14), 415–428. doi:10.1029/94JD00483
  • Liu, X., et al., 2017. Multimodel uncertainty changes in simulated river flows induced by human impact parameterizations. Environmental Research Letters, 12, 025009. doi:10.1088/1748-9326/aa5a3a
  • Logah, F.Y., et al. 2017. Floodplain hydrodynamic modelling of the Lower Volta River in Ghana. Journal of Hydrology: Regional Studies, 14, 1–9.
  • Mehrotra, R., et al., 2013. Assessing future rainfall projections using multiple GCMs and a multi-site stochastic downscaling model. Journal of Hydrology, 488, 84–100. doi:10.1016/j.jhydrol.2013.02.046
  • Mehrotra, R. and Sharma, A., 2010. Development and application of a multisite rainfall stochastic downscaling framework for climate change impact assessment. Water Resources Research, 46 (7), 759–768. doi:10.1029/2009WR008423
  • Meinshausen, M., et al., 2011. The RCP greenhouse gas concentrations and their extension from 1765 to 2300. Climate Change, 109, 213–241. doi:10.1007/s10584-011-0156-z
  • Mignot, E., Paquier, A., and Haider, S., 2006. Modelling floods in a dense urban area using 2D shallow water equations. Journal of Hydrology, 327 (1–2), 186–199. doi:10.1016/j.jhydrol.2005.11.026
  • Moore, R.J., 2007. The PDM rainfall-runoff model. Hydrology and Earth System Sciences, 11, 483–499.
  • Nakićenović, N., et al., 2000. IPCC special report on emissions scenarios. Cambridge, UK and New York, NY: Cambridge University Press, 599.
  • Nakićenović, N., et al., 2003. IPCC SRES revisited: a response. Energy and Environment, 14 (2), 187–214. doi:10.1260/095830503765184592
  • Orlowsky, B., et al., 2008. A resampling scheme for regional climate simulations and its performance compared to a dynamical RCM. Theoretical and Applied Climatology, 92, 209–223. doi:10.1007/s00704-007-0352-y
  • Perrin, C., Michel, C., and Andréassian, V., 2003. Improvement of a parsimonious model for streamflow simulation. Journal of Hydrology, 279 (1–4), 275–289. doi:10.1016/S0022-1694(03)00225-7
  • Reshmidevi, T.V., et al., 2018. Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs. Journal of Hydrology, 556, 1192–1204. doi:10.1016/j.jhydrol.2017.02.016
  • Reynard, N.S., et al., 2001. The flood characteristics of large UK rivers: potential effects of changing climate and land use. Climate Change, 48, 343–359. doi:10.1023/A:1010735726818
  • Seneviratne, S.I., et al., 2012. Changes in climate extremes and their impacts on the natural physical environment. In: C.B. Field, et al., ed. Managing the risks of extreme events and disasters to advance climate change adaptation. Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge, UK: Cambridge University Press, 109–230.
  • Smith, L.S. and Liang, Q., 2013. Towards a generalised GPU/CPU shallow-flow modelling tool. Computers & Fluids, 88, 334–343. doi:10.1016/j.compfluid.2013.09.018
  • Smith, L.S. and Liang, Q., 2015. A high-performance integrated hydrodynamic modelling system for urban flood simulations. Journal of Hydroinformatics, 17 (4), 518–533. doi:10.2166/hydro.2015.029
  • Tan, M.L., et al., 2017. Climate change impacts under CMIP5 RCP scenarios on water resources of the Kelantan River Basin, Malaysia. Atmospheric Research, 189, 1–10. doi:10.1016/j.atmosres.2017.01.008
  • Tang, Q., et al., 2016. Hydrological monitoring and seasonal forecasting: progress and perspectives. Journal of Geographical Sciences, 26 (7), 904–920. doi:10.1007/s11442-016-1306-z
  • Tang, Q. and Ge, Q., eds., 2018. Atlas of environmental risks facing China under climate change. IHDP/Future Earth-Integrated Risk Governance Project Series. Singapore: Springer.
  • Tang, Q. and Oki, T., eds., 2016. Terrestrial water cycle and climate change: natural and human-induced impacts. American Geophysical Union (AGU) Geophysical Monograph Series. Vol. 221. New York, NY: John Wiley & Sons.
  • Todini, E., 1996. The ARNO rainfall–runoff model. Journal of Hydrology, 175, 339–382. doi:10.1016/S0022-1694(96)80016-3
  • Tolson, B.A., et al., 2009. Hybrid discrete dynamically dimensioned search (HD-DDS) algorithm for water distribution system design optimization. Water Resources Research, 45 (12), 1–15. doi:10.1029/2008WR007673
  • Vehviläinen, B., 1994. The watershed simulation and forecasting system in the national board of waters and environment. Publications of the Water and Environment Research Institute, 17, 3–16.
  • Wang, Y., et al., 2011. A 2D shallow flow model for practical dam-break simulations. Journal of Hydraulic Research, 49 (3), 307–316. doi:10.1080/00221686.2011.566248
  • Wang, Y., et al., 2013. Land use/cover change effects on floods with different return periods: a case study of Beijing, China. Frontiers of Environmental Science & Engineering, 7 (5), 769–776. doi:10.1007/s11783-013-0542-z
  • Warszawski, L., et al., 2014. The inter-sectoral impact model intercomparison project (ISI-MIP): project framework. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 111, 3228–3232. doi:10.1073/pnas.1312330110
  • Weedon, G.P., et al., 2011. Creation of the watch forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. Journal of Hydrometeorology, 12, 823–848. doi:10.1175/2011JHM1369.1
  • Wigmosta, M.S., Nijssen, B., and Storck, P., 2002. The distributed hydrology soil vegetation model. In: V.P. Singh and D.K. Frevert, eds. Mathematical models of small watershed hydrology and applications. Littleton, CO: Water Resource Publications, 7–42.
  • Wigmosta, M.S., Vail, L.W., and Lettenmaier, D.P., 1994. A distributed hydrology soil vegetation model for complex terrain. Water Resources Research, 30 (6), 665–1679. doi:10.1029/94WR00436
  • Wu, B., et al., 2017. Integrated hydrologic and hydrodynamic modelling to assess water exchange in a data-scarce reservoir. Journal of Hydrology, 555, 15–30. doi:10.1016/j.jhydrol.2017.09.057
  • Wu, H., et al., 2014. Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model. Water Resource Research, 50, 2693–2717. doi:10.1002/2013WR014710
  • Wu, H., et al., 2016. Hydrometeorological hazards: monitoring, forecasting, risk assessment, and socioeconomic responses. Advances in Meteorology, 2016, 2367939. doi:10.1155/2016/2367939
  • Yamazaki, D., et al., 2011. A physically based description of floodplain inundation dynamics in a global river routing model. Water Resources Research, 47 (4), W04501. doi:10.1029/2010WR009726
  • Yang, D., Herath, S., and Musiake, K., 1998. Development of a geomorphology-based hydrological model for large catchments. Annual Journal of Hydraulic Engineering, JSCE, 42, 169–174. doi:10.2208/prohe.42.169
  • Yang, X., et al., 2016. Evaluation of the effect of land use/cover change on flood characteristics using an integrated approach coupling land and flood analysis. Hydrology Research, 47 (6), 1161–1171. doi:10.2166/nh.2016.108
  • Yin, Y., et al., 2017. Water scarcity under various socio-economic pathways and its potential effects on food production in the Yellow River Basin. Hydrology and Earth System Sciences, 21, 791–804. doi:10.5194/hess-21-791-2017
  • Yu, J.Y., 2010. Combined regulations of Baiyangdian Lake and upstream reservoirs for flood controlling over Daqinghe River basin (In Chinese). Water Resources Planning and Design, 5, 14–16.
  • Zhang, X., et al., 2014. A long-term land surface hydrologic fluxes and states dataset for China. Journal of Hydrometeorology, 15, 2067–2084. doi:10.1175/JHM-D-13-0170.1
  • Zhang, X., et al., 2017a. Soil moisture drought monitoring and forecasting using satellite and climate model data over southwestern China. Journal of Hydrometeorology, 18 (6), 5–23. doi:10.1175/JHM-D-16-0045.1
  • Zhang, X., et al., 2017b. On the dominant factor controlling seasonal hydrological forecast skill in China. Water, 9 (11), 902. doi:10.3390/w9110902
  • Zhang, X. and Tang, Q., 2015. Combining satellite precipitation and long-term ground observations for hydrologic monitoring in China. Journal of Geophysical Research: Atmospheres, 120 (13), 6426–6443.
  • Zhu, Z., et al., 2016. Integrated urban hydrologic and hydraulic modelling in Chicago, Illinois. Environmental Modelling & Software, 77, 63–70. doi:10.1016/j.envsoft.2015.11.014

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