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6 - Coastal and Freshwater Flood Models: A Review in the Context of NBS

Published online by Cambridge University Press:  13 March 2020

By
Neil Sang
Edited by
Neil Sang
Neil Sang
Affiliation:
Swedish University of Agricultural Sciences
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Summary

With much of the world’s population already concentrated into cities, many of which are in low-lying coastal areas or near to rivers, and urbanisation continuing apace, adaptation to climate change is of significant concern to urban planning and managing flooding from both sea inundation and rain storms is a particularly salient and pressing problem. This review aims to discuss some of the key models available today with regards to these two issues.

Type
Chapter
Information
Modelling Nature-based Solutions
Integrating Computational and Participatory Scenario Modelling for Environmental Management and Planning
 , pp. 210 - 246
Publisher: Cambridge University Press
Print publication year: 2020

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References

Abebe, Y. A., Ghorbani, A., Nikolic, I., Vojinovic, Z. & Sanchez, A. 2019. A coupled flood–agent–institution modelling (CLAIM) framework for urban flood risk management. Environmental Modelling & Software, 111, 483–492.CrossRefGoogle Scholar
Abhas, J., Bloch., R. & Lamond, J. 2011. Cities and Flooding: A Guide to Integrated Urban Flood Risk Management for the 21st Century. Washington, DC: World Bank.Google Scholar
Andersen, R. 2003. Mike info Coast – a GIS-based tool for coastal zone management. In: Green, D. R. & King, S. D. (eds.) Coastal and Marine Geo-Information Systems, pp. 467–472. Dordrecht: Springer.CrossRefGoogle Scholar
Bardet, L., Duluc, C.-M., Rebour, V. & L’Her, J. 2011. Regional frequency analysis of extreme storm surges along the French coast. Natural Hazards and Earth System Sciences, 11, 1627–1639.Google Scholar
Broughton, W. 1989. A review of the USDA SCS curve number method. Australian Journal of Soil Research, 27(3), 511–523.CrossRefGoogle Scholar
Brown, S., Nicholls, R. J., Lowe, J. A. & Hinkel, J. 2016. Spatial variations of sea-level rise and impacts: an application of DIVA. Climatic Change, 134, 403–416.Google Scholar
CLIMSYSTEMS. 2017 SimCLIM 4.0 for Desktop Essentials [Online]. http://documents.climsystems.com/SimCLIM%204.0/SimCLIM%204.0%20Essentials.pdfGoogle Scholar
Dietz, M. E. 2007. Low impact development practices: a review of current research and recommendations for future directions. Water, Air, and Soil Pollution, 186, 351–363.Google Scholar
Elliott, A. H. & Trowsdale, S. A. 2007. A review of models for low impact urban stormwater drainage. Environmental Modelling & Software, 22, 394–405.CrossRefGoogle Scholar
Fallahshorshani, M., André, M., Bonhomme, C. & Seigneur, C. 2012. Coupling traffic, pollutant emission, air and water quality models: technical review and perspectives. Procedia – Social and Behavioral Sciences, 48, 1794–1804.Google Scholar
Garen, D. & Moore, D. 2007. Curve number hydrology in water quality modeling. Journal of the American Water Resources Association (JAWRA), 41(2), 377–388.Google Scholar
Haase, D. 2017. Urban wetlands and riparian forests as a nature-based solution for climate change adaptation in cities and their surroundings. In: Kabisch, N., Korn, H., Stadler, J. & Bonn, A. (eds.) Nature-based Solutions to Climate Change Adaptation in Urban Areas: Linkages between Science, Policy and Practice. Cham: Springer International Publishing.Google Scholar
Hinkel, J. & Klein, R. J. T. 2009. Integrating knowledge to assess coastal vulnerability to sea-level rise: the development of the DIVA tool. Global Environmental Change, 19, 384–395.Google Scholar
Hinkel, J., Nicholls, R. J., Tol, R. S. J., Wang, Z. B., Hamilton, J. M., Boot, G., et al. 2013. A global analysis of erosion of sandy beaches and sea-level rise: an application of DIVA. Global and Planetary Change, 111, 150–158.Google Scholar
Hinkel, J., Nicholls, R. J., Vafeidis, A. T., Tol, R. S. & Avagianou, T. 2010. Assessing risk of and adaptation to sea-level rise in the European Union: an application of DIVA. Mitigation and Adaptation Strategies for Global Change, 15, 703–719.CrossRefGoogle Scholar
Hunter, N. M., Horritt, M. S., Bates, P. D., Wilson, M. D. & Werner, M. G. F. 2005. An adaptive time step solution for raster-based storage cell modelling of floodplain inundation. Advances in Water Resources, 28, 975–991.Google Scholar
Huxley, C. 2016, GPU – the next generation modelling for catchment flood plain management. Presentated at the ASFPM Conference, Grand Rapids, USA, June 2016. www.tuflow.com/Download/Presentations/2016/GPU%20-%20Next%20Generation%20Modeling%20for%20Catchment%20Floodplain.pdfGoogle Scholar
Kalantari, Z., Lyon, S.W., Jansson, P. E., Stolte, J., French, H. K., Folkeson, L., et al. 2015. Modeller subjectivity and calibration impacts on hydrological model applications: an event-based comparison for a road-adjacent catchment in south-east Norway. Science of the Total Environment, 502, 315–329.CrossRefGoogle ScholarPubMed
Kaykhosravi, S., Khan, U. & Jadidi, A. 2018. A comprehensive review of low impact development models for research, conceptual, preliminary and detailed design applications. Water, 10, 1541.CrossRefGoogle Scholar
Liu, Q., Quin, Y. & Guodong, L. 2018. Fast simulation of large scale floods based on GPU parallel computing. Water, 10, 589.Google Scholar
Liu, Y., Okada, N., Shen, D. & Li, S. 2009. Agent-based flood evacuation simulation of life-threatening conditions using vitae system model. Journal of Natural Disaster Science, 31, 33–41.Google Scholar
Madsen, H. 2000. Automatic calibration of a conceptual rainfall–runoff model using multiple objectives. Journal of Hydrology, 235, 276–288.CrossRefGoogle Scholar
May, D. B. & Sivakumar, M. 2009. Prediction of urban stormwater quality using artificial neural networks. Environmental Modelling Software, 24, 296–302.Google Scholar
McKenna, D., Krüger, I. & Hinzmann, M. 2015. Coastal protection and suds – nature-based solutions. Recreate Policy Brief No. 4. Berlin.Google Scholar
Mcleod, E., Poulter, B., Hinkel, J., Reyes, E. & Salm, R. 2010. Sea-level rise impact models and environmental conservation: a review of models and their applications. Ocean & Coastal Management, 53, 507–517.Google Scholar
Murray-Rust, D., Robinson, D. T., Guillem, E., Karali, E. & Rounsevell, M. 2014. An open framework for agent based modelling of agricultural land use change. Environmental Modelling & Software, 61, 19–38.Google Scholar
Néelz, S. & Pender, G. 2009. Desktop Review of 2D Hydraulic Modelling Packages.Bristol: Environment Agency.Google Scholar
Néelz, S. & Pender, G. 2013. Benchmarking the Latest Generation of 2D Hydraulic Modelling Packages. Bristol: Environment Agency.Google Scholar
Nishat, A. & Mukherjee, N. 2013. Climate change impacts, scenario and vulnerability of Bangladesh. In: Climate Change Adaptation Actions in Bangladesh. New York, NY: Springer.Google Scholar
Passeri, D., Hagen, S., Medieros, S., Bilksie, M., Alizad, K. & Wang, D. 2015. The dynamic effects of sea level rise on low‐gradient coastal landscapes: a review. Earth’s Future, 3, 159–181.CrossRefGoogle Scholar
Robbins, J. 2016. How Forest Loss is Leading to a Rise in Human Disease. New Haven, CT: Yale School of Forestry and Environmental Studies.Google Scholar
Schneiders, A., Van Daele, T., Van Landuyt, W. & Van Reeth, W. 2012. Biodiversity and ecosystem services: complementary approaches for ecosystem management? Ecological Indicators, 21, 123–133.CrossRefGoogle Scholar
Sonaje, N. 2013. Modeling of infiltration process – a review. Indian Journal of Applied Research, 3, 226–230.Google Scholar
Stark, J., Plancke, Y., Ides, S., Meire, P. & Temmerman, S. 2016. Coastal flood protection by a combined nature-based and engineering approach: modeling the effects of marsh geometry and surrounding dikes. Estuarine, Coastal and Shelf Science, 175, 34–45.Google Scholar
Teng, J., Jakeman, A. J., Vaze, J., Croke, B. F. W., Dutta, D. & Kim, S. 2017. Flood inundation modelling: a review of methods, recent advances and uncertainty analysis. Environmental Modelling & Software, 90, 201–216.Google Scholar
TUFLOW. 2016. TUFLOW User Manual Build 2016–03-AA. TUFLOW.Google Scholar
UNDP. 2008. Community-based Adaptation to Climate Change through Coastal Afforestation in Bangladesh. www.thegef.org/project/community-based-adaptation-climate-change-through-coastal-afforestationGoogle Scholar
UNDP. 2011. Community-based adaptation to climate change through coastal afforestation in Bangladesh. Bangladesh Project Identification Form (23 November 2011).Google Scholar
Vafeidis, A. T., Nicholls, R. J., McFadden, L., Tol, R. S. J., Hinkel, J., Spencer, T., et al. 2008. A new global coastal database for impact and vulnerability analysis to sea-level rise. Journal of Coastal Research, 244, 917–924.Google Scholar
Vojinovic, Z., Keerakamolchai, W., Weesakul, S., Pudar, R., Medina, N. & Alves, A. 2017. Combining ecosystem services with cost-benefit analysis for selection of green and grey infrastructure for flood protection in a cultural setting. Environments, 4(1), 3.Google Scholar
Wong, P. & Losada, I. 2014. Coastal systems and low-lying areas. In: WGII AR5. Geneva: IPCC.Google Scholar
WMO. 2013. Intercomparison of flood forecasting models for review. Decision-Support Tool for the Selection of Flood Forecasting Model Working Group, Koblenz, Germany. www.wmo.int/pages/prog/hwrp/documents/FFI/Intercomparison_of_flood_forecasting_models_for_review.pdfGoogle Scholar
Vuik, V., Jonkman, S. N., Borsje, B. W. & Suzuki, T. 2016. Nature-based flood protection: the efficiency of vegetated foreshores for reducing wave loads on coastal dikes. Coastal Engineering, 116, 42–56.CrossRefGoogle Scholar
Zhou, Q. 2014. A review of sustainable urban drainage systems considering the climate change and urbanization impacts. Water Air and Soil Pollution, 6, 976–992.Google Scholar

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