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Summary

\n

Probabilistic models like the Hydra models contain modules for the calculation of the required strength for water defences. These models are primarily designed to calculate the Hydraulic Boundary Conditions (HBC) for the failure mechanisms ‘overflow’ and ‘wave overtopping’. At a later stage, also failure mechanisms for revetment were incorporated. The HBC calculated by the Hydra’s differ per failure mechanism, since every mechanism has its own “failure set”, formed by all combinations of load variables for which failure of the water defence occurs.

\n

In the recent past it has been demonstrated that the probabilistic concepts of the Hydra models cannot deal appropriately with so-called irregular failure sets (see below). Pragmatic approaches are currently used to avoid these problems, but these are not in line with the VTV (in dutch: Voorschrift Toetsen op Veiligheid), which provides the official rules for the assessment of the safety of dikes. This inevitably introduces errors in the resulting HBC. The aim of this study is to provide an outlook for the further development of the Hydra models, such that these can cope with irregular failure sets and that the HBC can be calculated for all kinds of failure mechanisms.

\n

The various Hydra-models have in common that they consider ‘Threatening Events’ (TE’s), i.e. events that may potentially lead to failure of a flood defence system. The failure set consists of all TE’s that lead to failure of the flood defence. The plot on the left of the figure below shows a typical example of a regular failure domain denoted by F. The concept behind this is that an increase in the variables that represent the TE will lead to an increase in the hydraulic load of the flood defence. The plot on the right of shows a typical example of an irregular failure set. In this case it is possible that an increase in h and u causes the a transition from failure to non-failure. For example, following the arrow in this plot the values of u and h increase. At a certain stage the arrow leaves the failure domain, showing that this is an irregular failure domain.

\n

The report presents a number of examples of irregular failure sets that have been observed or can be expected in practical applications. There are two types of causes for their existence:

\n
    \n
  1. An increase in a random variable like wind speed or sea water level can lead to a decrease in water levels or wave parameters in front of the flood defence. This can e.g. be due to the fact that the wind is directed offshore, due to the closure of flood barriers or due to the fact that an increase in wind speed sometimes causes a decrease in wave period.
    2. \n
  2. The failure mechanism is such that an increase in the local water level can decrease the hydraulic load. This is the case for a substantial number of failure mechanisms in the VTV. For example, an increase in water level may cause parts of the dike revetment to be far enough below the water level that the hydraulic load for these parts is (close to) zero.
    3. \n
\n

 

\n

Note that type one makes that even for failure mechanisms ‘overflow’ and ‘wave overtopping’ irregular failure domains can occur! The report describes a number of striking examples.

\n

The report describes a wide variety of problems that are caused by or related to irregular failure domains, such as:

\n\n

 

\n

The most likely method to deal with the current problems with Hydra-K is to use another probabilistic computation method (instead of method De Haan). Furthermore, as already mentioned in the previous section, a possible solution to deal with irregular failure sets is to make them regular by manipulating the hydraulic load function and/or the description of the failure mechanism. Although a bit unsatisfactory (functions and model outputs need to be manipulated), it is very practical and the errors introduced by the manipulation may be acceptable, although the latter is not easy to establish.

\n

If the failure set is no longer regularised, alternative probabilistic methods are required for the Hydra’s. The report gives an overview of some of the most common methods used to approximate failure probabilities. For each of these calculation methods possible problems regarding irregular failure sets are described. One of the proposed solution methods is the concept of the environmental surface (ES). This method takes the previous mentioned solution a step further. In this case the failure set is not used in the calculation of design points. Design points are calculated using only the probability density functions of the load variables. This solution obviously takes away the problem of irregular failure sets, but again the question is how large the approximation error is. The ES concept may be able to resolve the inconsistencies between design conditions from the current Hydra models and subsequent reliability testing discussed in this report.

\n

The solutions mentioned above are not all developed and tested yet, they are only possible solutions. There are still a number of issues to be resolved, especially the ones concerning the time-scales of events. This needs to be dealt with in the coming years to establish a major improvement to the Hydra’s and their resulting boundary conditions.

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STRENGTH" }, { "tag": "4. COASTAL" }, { "tag": "Wadden Sea" } ], "collections": [ "4H2JWSWH" ], "relations": {}, "dateAdded": "2010-11-09T09:03:10Z", "dateModified": "2010-11-09T09:04:06Z" } }, { "key": "F2ADX85D", "version": 1, "library": { "type": "group", "id": 21620, "name": "Flood Risk Uncertainty", "links": { "alternate": { "href": "https://www.zotero.org/groups/flood_risk_uncertainty", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/21620/items/F2ADX85D", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/flood_risk_uncertainty/items/F2ADX85D", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/21620/items/KPDXRXSW", "type": "application/json" } }, "meta": { "createdByUser": { "id": 291895, "username": "kathryn.roscoe", "name": "Kathryn Roscoe", "links": { "alternate": { "href": "https://www.zotero.org/kathryn.roscoe", "type": "text/html" } } } }, "data": { "key": "F2ADX85D", "version": 1, "parentItem": "KPDXRXSW", "itemType": "attachment", "linkMode": "linked_url", "title": "WL bibliographic - Full View of Record", "accessDate": "2010-11-09T09:03:47Z", "url": "http://aleph.library.tudelft.nl/F/HM4TUNQJSM8F9HF2EUCJJ1ELMYRGE4MLLUA935ANY6HLTHADT5-01783?func=full-set-set&set_number=031162&set_entry=000003&format=999", "note": "", "contentType": "text/html", "charset": "utf-8", "tags": [], "relations": {}, "dateAdded": "2010-11-09T09:03:47Z", "dateModified": "2010-11-09T09:03:47Z" } }, { "key": "PRS7DNKG", "version": 1, "library": { "type": "group", "id": 21620, "name": "Flood Risk Uncertainty", "links": { "alternate": { "href": "https://www.zotero.org/groups/flood_risk_uncertainty", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/21620/items/PRS7DNKG", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/flood_risk_uncertainty/items/PRS7DNKG", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/21620/items/CVNGZABK", "type": "application/json" } }, "meta": { "createdByUser": { "id": 395107, "username": "robinnicolai", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/robinnicolai", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "PRS7DNKG", "version": 1, "parentItem": "CVNGZABK", "itemType": "note", "note": "

The method of Bayesian Model Averaging (BMA) is used to generate a probabilistic
forecast from an ensemble of seven deterministic forecasts.

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In deze studie worden kennisonzekerheden expliciet meegenomen in de berekening van de HR. Met PC-Ring zijn HR berekeningen gemaakt voor representatieve locaties in alle watersystemen.

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Note about this report

\n

This report is not intended to be a report about uncertainty. However, as part of the probabilistic approach, the uncertainty and/or natural variability in the input parameters (such as wave height or grain diameter) was summarized and tabulated. See chapter 3 for a description per parameter, or Table 3.11 for a summary of all parameters.

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Objective - Dune Erosion - Product 3: Probabilistic dune erosion prediction method

\n

The objective of this project is to develop a new safety assessment method for dunes as part of the VTV2006. This new methodology should account for effects of the wave period on dune erosion as well be applicable for a nourished coast. This project is focussed on achieving this by improving the existing method (TAW, 1984), because of the following reasons:

\n

 

\n\n

 

\n

Attention is primarily focussed on quantifying effects of the wave period on dune erosion. Other effects, e.g. the effect of storm duration, are foreseen to be taken into account in the VTV2011, if the HR2011 also includes data on storm duration. Therefore, more knowledge has to be developed on other effects in the period between 2006 and 2011. It should be clear that the result of this project is aimed at an improvement of the existing methodology and not at a method that accounts for all relevant phenomena.

\n

 

\n

The new method that will be developed will be evaluated in order to give support to the users and to identify gaps in knowledge. The new method is expected to be robust enough to assess the safety of the dunes on a short term. However, the range of validity will still be limited. The identified knowledge gaps could be a reason for further research for the VTV2011. A part of the present study is to prepare a plan for the period between 2007 and 2011 to identify the knowledge gaps and the required research to achieve an appropriate safety assessment tool for dunes for the VTV2011.

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this is a paper from marjolein.

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Objectives - SBW Wadden Sea, Water level modelling

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The main objective of the study is to asses the sensitivity of applying spatially varying bed characteristics in numerical modelling. In order to improve the numerical model, this report focuses on the following three sub-objectives:

\n\n\n", "tags": [], "relations": {}, "dateAdded": "2010-07-12T13:21:40Z", "dateModified": "2010-07-12T13:22:41Z" } } ]