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May 6-8, 2008 1 PROBABILISTIC SENSITIVITY ANALYSIS OF DUNE EROSION CALCULATIONS 4 th International Symposium on Flood Defence, Toronto, Canada Kees den.

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Presentation on theme: "May 6-8, 2008 1 PROBABILISTIC SENSITIVITY ANALYSIS OF DUNE EROSION CALCULATIONS 4 th International Symposium on Flood Defence, Toronto, Canada Kees den."— Presentation transcript:

1 May 6-8, 2008 1 PROBABILISTIC SENSITIVITY ANALYSIS OF DUNE EROSION CALCULATIONS 4 th International Symposium on Flood Defence, Toronto, Canada Kees den Heijer, Jan van de Graaff and Pieter van Gelder Section of Hydraulic Engineering

2 May 7, 20082 Contents Introduction Model description Probabilistic model Dune erosion model Approach Results Conclusions

3 May 7, 20083 Introduction approximately 350 km Dutch coastline 254 km dunes 34 km sea dikes 38 km beach flats 27 km of boulevards, beach walls etc. Design conditions very extreme (10 -5 year -1 ) No prototype data for these extreme situations Policy to maintain coastline of 1990

4 May 7, 20084 Introduction Current method for Dutch dune safety assessment: Empirical model Applied in semi-deterministic way Conditions based on probabilistic investigations (WL | Delft Hydraulics, 2007)

5 May 7, 20085 Objective This study aims at more insight in the sensitivity of the rate of dune erosion for the stochastic characteristics of various variables, currently taken into account. Remarks: 10 -5 year -1 probability of exceedance DUROS-plus dune erosion model Simple cross-shore profile

6 May 7, 20086 Model description Probabilistic model Prob2B (former 'Probox'; Courage & Steenbergen, 2007) FORM method Easy to couple with other software

7 May 7, 20087 Model description Dune erosion model (DUROS-plus)

8 May 7, 20088 DUROS-plus Within McTools (Van Koningsveld, Stive and Mulder, 2005), recently the DUROS-plus code has been re- written: Efficient iteration procedure Modular structure

9 May 7, 20089 Approach Stochastic characteristics of reference situation are mainly based on the probabilistic investigation of WL | Delft Hydraulics (2007) The stochastic characteristics have been changed one by one, keeping the others the same

10 May 7, 200810 Overview Reference situation ParameterMean valueUncertainty/varianceDistribution type Water levelRelated to P exceedance -Conditional Weibull Wave heightRelated to water level0.6 mNormal Wave periodRelated to wave height1 sNormal Grain size 225  m10% of mean (22.5  m) Normal Profile fluctuation060 m 3 /m 1 Normal Surge duration010 % * ANormal Model accuracy015 % * ANormal

11 May 7, 200811 Reference situation

12 May 7, 200812 Design point VariableValueRelative contribution [%] Water level5.48 m89.53 Model accuracy58.4 m 3 /m 1 3.40 Grain size 208  m 3.28 Surge duration26.0 m 3 /m 1 1.51 Wave height7.92 m1.26 Profile fluctuation-23.4 m 3 /m 1 0.84 Wave period12.71 s0.19 Retreat distance78.8 m

13 May 7, 200813 Overview of investigations VariableMean valueUncertainty/variance Water levelReference situation + [-0.5, -0.25, 0, 0.25, 0.5] m- Wave heightReference situation + [-0.5, -0.25, 0, 0.25, 0.5] m[0, 0.3, 0.6, 0.9 and 1.2] m Wave periodReference situation + [0, 1 and 2] s[0, 0.5, 1.0, 1.5 and 2.0] s Grain size [200, 225, 250, 275 and 300]  m[0, 5, 10 and 15] % of 225  m Profile fluctuation[-20, 0 and 20] m 3 /m 1 [0, 30, 60, 90 and 120] m 3 /m 1 Surge duration[0, 5 and 10] % * A[0, 5, 10, 15 and 20] % * A Model accuracy[0, 5 and 10] % * A[0, 5, 10, 15 and 20] % * A

14 May 7, 200814 Results: Sensitivity water level

15 May 7, 200815 Sensitivity mean grain size

16 May 7, 200816 Standard deviation grain size

17 May 7, 200817 Standard deviation peak wave period

18 May 7, 200818 Conclusions Water level and grain size distribution are the most important variables in current safety assessment method for the Dutch dune coast Proper field data of these variables are crucial The other variables do have their contribution, but changing their stochastic char. does not have so much influence

19 May 7, 200819 Water level

20 May 7, 200820 Wave height

21 May 7, 200821 Peak wave period


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