Parameter Uncertainties in Flood Hazard Analysis of Heavy Rain Events
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 2
Abstract
Flooding due to intensive precipitation poses a major threat to lives and property. To deal with the resulting risks, information about flood-prone areas regarding water levels and flow velocities is needed. The flood probability of a certain point in the landscape depends on the one hand on the occurrence probability of a surface runoff generating–rainfall event and on the other hand on the flow- and runoff-determining properties of the terrain, e.g., the surface morphology and the hydraulic roughness. Simulation models for the flow of surface water are common tools for assessing the dynamics of flooding caused by intensive precipitation events. Major input parameters for such simulation tools are digital elevation models, surface roughness datasets, as well as data on the precipitation input. In order to make informed decisions that take the uncertainties of modeling results into account and to get an idea of the probability space, it is important to quantify the effects of different alternative model parameter sets regarding data sources as well as the spatial and temporal resolution of the input data. We evaluated the effects of different parameter sets for the hydronumeric computational fluid dynamics model HiPIMS on flow velocities and water levels.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The presented work is based on results from project “RAINMAN - Integrated Heavy Rain Risk Management” founded by the European Union (European Regional Development Fund, Interreg CENTRAL EUROPE 2020) and basic funding from the Leibniz Institute of Ecological and Regional Development (IOER).
References
Barredo, J. I. 2007. “Major flood disasters in Europe: 1950–2005.” Nat. Hazards 42 (1): 125–148. https://doi.org/10.1007/s11069-006-9065-2.
Bhola, P. K., J. Leandro, and M. Disse. 2020. “Building hazard maps with differentiated risk perception for flood impact assessment.” Nat. Hazards Earth Syst. Sci. 20 (10): 2647–2663. https://doi.org/10.5194/nhess-20-2647-2020.
Candela, A., and G. T. Aronica. 2017. “Probabilistic flood hazard mapping using bivariate analysis based on copulas.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 3 (1): A4016002. https://doi.org/10.1061/ajrua6.0000883.
Conrad, O., B. Bechtel, M. Bock, H. Dietrich, E. Fischer, L. Gerlitz, J. Wehberg, V. Wichmann, and J. Böhner. 2015. “System for automated geoscientific analyses (SAGA) v. 2.1.4.” Geosci. Model Dev. 8 (7): 1991–2007. https://doi.org/10.5194/gmd-8-1991-2015.
De Paola, F., R. De Risi, G. Di Crescenzo, M. Giugni, A. Santo, and G. Speranza. 2017. “Probabilistic assessment of debris flow peak discharge by Monte Carlo simulation.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 3 (1): A4015002. https://doi.org/10.1061/ajrua6.0000855.
DWA (Deutschen Vereinigung für Wasserwirtschaft, Abwasser und Abfall). 2006. Hydraulische bemessung und nachweis von entwässerungssystemen [Hydraulic design of urban drainage systems]. Hennef, Germany: DWA.
DWD (German Weather Service). 2010. “Coordinated heavy precipitation regionalization and evaluation of the DWD.” Accessed August 5, 2020. https://www.dwd.de/DE/leistungen/kostra_dwd_rasterwerte/kostra_dwd_rasterwerte.html.
Gaume, E., et al. 2009. “A compilation of data on European flash floods.” J. Hydrol. 367 (1–2): 70–78. https://doi.org/10.1016/j.jhydrol.2008.12.028.
Grigg, N. S. 2020. “Uncertainty and legal foreseeability in flood risk management.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 6 (3): 06020001. https://doi.org/10.1061/AJRUA6.0001082.
Henonin, J., B. Russo, O. Mark, and P. Gourbesville. 2013. “Real-time urban flood forecasting and modeling: A state of the art.” J. Hydroinf. 15 (3): 717–736. https://doi.org/10.2166/hydro.2013.132.
Kron, W. 2009. “Flood insurance: From clients to global financial markets.” J. Flood Risk Manage. 2 (1): 68–75. https://doi.org/10.1111/j.1753-318X.2008.01015.x.
Lam, J. C., J. Hackl, B. T. Adey, M. Heitzler, and L. Hurni. 2020. “Impact assessment of extreme hydrometeorological hazard events on road networks.” J. Infrastruct. Syst. 26 (2): 04020005. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000530.
Liang, Q., and L. S. Smith. 2014. “A high-performance integrated hydrodynamic modelling system for urban flood inundation.” J. Hydroinf. 17 (4): 518–533. https://doi.org/10.2166/hydro.2015.029.
Liang, Q., X. Xia, and J. Hou. 2016. “Catchment-scale high-resolution flash flood simulation using the GPU-based technology.” Procedia Eng. 154: 975–981. https://doi.org/10.1016/j.proeng.2016.07.585.
Nofal, O. M., and J. W. van de Lindt. 2020. “Probabilistic flood loss assessment at the community scale: Case study of 2016 flooding in Lumberton, North Carolina.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 6 (2): 05020001. https://doi.org/10.1061/AJRUA6.0001060.
Nogal, M., A. O’Connor, B. Martinez-Pastor, and B. Caulfield. 2017. “Novel probabilistic resilience assessment framework of transportation networks against extreme weather events.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 3 (3): 04017004. https://doi.org/10.1061/AJRUA6.0000908.
Sahoo, S. N., and P. Sreeja. 2017. “Development of flood inundation maps and quantification of flood risk in an urban catchment of Brahmaputra River.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 3 (1): A4015001. https://doi.org/10.1061/ajrua6.0000822.
Sauer, A., A. Olfert, L. Körte, and R. Ortlepp. 2018. “An uncertain business: Mapping flood hazards caused by heavy rain.” In Vol. 113 of Proc., Extended Abstracts of the 16th International Probabilistic Workshop 2018 in Vienna, 95–100. Berlin: Ernst & Sohn Verlag. https://doi.org/10.1002/best.201800059.
Smith, L. S., and Q. Liang. 2013. “Towards a generalised GPU/CPU shallow-flow modelling tool.” Comput. Fluids 88 (Dec): 334–343. https://doi.org/10.1016/j.compfluid.2013.09.018.
Smith, L. S., Q. Liang, and P. F. Quinn. 2015. “Towards a hydrodynamic modelling framework appropriate for applications in urban flood assessment and mitigation using heterogeneous computing.” Urban Water J. 12 (1): 67–78. https://doi.org/10.1080/1573062X.2014.938763.
Winterrath, T., W. Rosenow, and E. Weigl. 2012. “On the DWD quantitative precipitation analysis and nowcasting system for real-time application in German flood risk management.” In Vol. 351 of Weather radar and hydrology, edited by R. J. Moore, S. J. Cole, and A. J. Illingworth, 323–329. Wallingford, UK: IAHS Press.
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© 2021 American Society of Civil Engineers.
History
Received: Aug 5, 2020
Accepted: Dec 3, 2020
Published online: Mar 9, 2021
Published in print: Jun 1, 2021
Discussion open until: Aug 9, 2021
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