A multivariate design framework for river confluences

Hydrological Sciences Journal

Volumn 61, Issue 3, 2016, Pages 471-482

  Bender, Jens ^a   Wahl, Thomas ^a,b   Müller, Alfred ^a   Jensen, Jürgen ^a  

^a UNIVERSITY OF SIEGEN   (Germany)

^b UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

confluences; copulas; flood risk assessment; non simultaneous extremes

Indexed keywords

DESIGN; MULTIVARIANT ANALYSIS; RISK ASSESSMENT;

CONFLUENCES; COPULAS; FLOOD RISK ASSESSMENTS; MULTIVARIATE DESIGN; NON-SIMULTANEOUS; RIVER CONFLUENCE; STATISTICAL APPROACH; STATISTICAL FRAMEWORK;

FLOODS;

CONFLUENCE; DESIGN; FLOOD; HYDRODYNAMICS; MULTIVARIATE ANALYSIS; NUMERICAL MODEL; RISK ASSESSMENT; RIVER SYSTEM;

RHINE RIVER; SIEG;

EID: 84955063063     PISSN: 02626667     EISSN: 21503435     Source Type: Journal    
DOI: 10.1080/02626667.2015.1052816     Document Type: Article

References (28)

1. J.Bender,, T.Wahl,, and J.Jensen,, 2014. Multivariate design in the presence of non-stationarity. Journal of Hydrology, 514, 123–130. doi:10.1016/j.jhydrol.2014.04.017
2. BfG (Bundesanstalt für Gewässerkunde), 2009. Flusshydrologische Software (River hydrologic software) – User Manual, version 2.1.3, Bundesanstalt für Gewässerkunde (German Federal Institute of Hydrology).
3. L.Chen,, et al., 2012. Flood coincidence risk analysis using multivariate copula functions. Journal of Hydrologic Engineering, 17 (6), 742–755. doi:10.1061/(ASCE)HE.1943-5584.0000504
4. S.Coles,, J.Heffernan,, and J.Tawn,, 1999. Dependence measures for extreme value analyses. Extremes, 2 (4), 339–365. doi:10.1023/A:1009963131610
5. C.De Michele, and G.Salvadori,, 2003. A generalized Pareto intensity-duration model of storm rainfall exploiting 2-copulas. Journal of Geophysical Research, 108 (D2), 4067. doi:10.1029/2002JD002534
6. A.-C.Favre,, et al., 2004. Multivariate hydrological frequency analysis using copulas. Water Resources Research, 40, W01101. doi:10.1029/2003WR002456
7. C.Genest,, B.Rémillard,, and D.Beaudoin,, 2009. Goodness-of-fit tests for copulas: a review and a power study. Insurance: Mathematics and Economics, 44, 199–213.
8. B.Gräler,, et al., 2013. Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation. Hydrologyand Earth System Sciences, 17, 1281–1296. doi:10.5194/hess-17-1281-2013
9. S.Grimaldi, and F.Serinaldi,, 2006. Design hyetograph analysis with 3-copula function. Hydrological Sciences Journal, 51 (2), 223–238. doi:10.1623/hysj.51.2.223
10. I.I.Gringorten,, 1963. A plotting rule for extreme probability paper. Journal of Geophysical Research, 68 (3), 813–814. doi:10.1029/JZ068i003p00813
11. C.Hauer,, G.Mandlburger,, and H.Habersack,, 2009. Hydraulically related hydro-morphological units: description based on a new conceptual mesohabitat evaluation model (MEM) using lidar data as geometric input. River Research and Applications, 25, 29–47. doi:10.1002/rra.1083
12. S.Kao, and R.S.Govindaraju,, 2010. A copula-based joint deficit index for droughts. Journal of Hydrology, 380 (1–2), 121–134. doi:10.1016/j.jhydrol.2009.10.029
13. S.Karmakar, and S.P.Simonovic,, 2008. Bivariate flood frequency analysis: part 1 - Determination of marginals by parametric and nonparametric techniques. Journal of Flood Risk Management, 1, 190–200. doi:10.1111/j.1753-318X.2008.00022.x
14. S.Karmakar, and S.P.Simonovic,, 2009. Bivariate flood frequency analysis. Part 2: a copula-based approach with mixed marginal distributions. Journal of Flood Risk Management, 2 (1), 32–44. doi:10.1111/j.1753-318X.2009.01020.x
15. M.G.Kendall,, 1955. Rank correlation methods. London: Griffin.
16. H.B.Mann,, 1945. Nonparametric tests against trend. Econometrica, 13, 245–259.
17. C.D.Morris, and S.J.Calise,, 1987. Bivariate analysis of concurrent flooding. In: V.P.Singh, ed. Hydrologic frequency modeling: proceedings of the international symposium on flood frequency and risk analysis, 14–17 May 1986 Baton Rouge, Louisiana. Dordrecht: Reidel, 615–632.
18. NCHRP, 2010. Estimating Joint Probabilities of Design Coincident Flows at Stream Confluences. National Cooperative Highway Research Program (NCHRP) Report 15–36. Washington, USA.
19. R.B.Nelsen,, 2006. An introduction to copulas. Lecture notes in statistics. 2nd ed. New York: Springer.
20. M.Nujic,, 1999. Praktischer Einsatz eines hochgenauen Verfahrens für die Berechnung von tiefengemittelten Strömungen. Mitteilungen des Instituts für Wasserwesen der Universität der Bundeswehr München, Nr. 64.
21. P.Pironneau,, 1989. Finite element methods for fluids. Paris: Masson.
22. J.A.Raynal, and J.D.Salas,, 1987. A probabilistic model for flooding downstream of the junction of two rivers. In: V.P.Singh, ed. Hydrologic frequency modeling: proceedings of the international symposium on flood frequency and risk analysis, 14–17 May 1986 Baton Rouge, Louisiana. Dordrecht: Reidel, 595–601.
23. G.Salvadori, and C.De Michele,, 2004. Frequency analysis via copulas: theoretical aspects and applications to hydrological events. Water Resources Research, 40, W12511. doi:10.1029/2004WR003133
24. F.Serinaldi,, 2014. Dismissing return periods! Stochastic Environmental Research and Risk Assessment. doi:10.1007/s00477-014-0916-1
25. C.Svensson,, W.Z.Kundzewicz,, and T.Maurer,, 2005. Trend detection in river flow series: 2. Flood and low-flow index series. Hydrological Sciences Journal, 50 (5), 811–824. doi:10.1623/hysj.2005.50.5.811
26. T.Wahl,, C.Mudersbach,, and J.Jensen,, 2012. Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on Copula functions. Natural Hazards and Earth System Sciences, 12, 495–510. doi:10.5194/nhess-12-495-2012
27. C.Wang,, N.-B.Chang,, and G.-T.Yeh,, 2009. Copula-based flood frequency (COFF) analysis at the confluences of river systems. Hydrological Processes, 23, 1471–1486. doi:10.1002/hyp.7273
28. L.Zhang, and V.P.Singh,, 2006. Bivariate flood frequency analysis using the copula method. Journal ofHydrologicEngineering, 11 (2), 150–164. doi:10.1061/(ASCE)1084-0699(2006)11:2(150)