The Dutch flood defences are subjected to the new Dutch safety assessment program (WBI 2017) that incorporates the latest insights and safety regulations. As a consequence of the updated piping assessment model, studies are expected to identify more piping prone areas in the Netherlands, which makes it worthwhile to investigate alternative piping mitigation solutions that could be less expensive. A new potential solution is the Pipingontspanner, which consists of relief wells in combination with a water catchment area. The Pipingontspanner relieves water pressure fromthe aquifer and uses the water as counter pressure against the Uplift mechanism, thereby reducing the likelihood of piping. The study investigates the technical and economic feasibility of the Pipingontspanner as a piping mitigation measure. A problem analysis was used to identify the components that form challenges in realising the concept and pinpoint the research to the functioning, effectiveness and applicability of the Pipingontspanner concept. A hydraulic model and a design approach demonstrate the functioning of the concept. The hydraulic model describes the flow underneath the dyke, through the well and towards the basin above it. A critical point for the flow calculation appeared to be the time-dependent interaction between the river and the basin water level, which leaves only numerical calculation methods to describe the problem. The numerical program Modflow was chosen to predict the Pipingontspanner groundwater flow by simulating a flood wave scenario for a green dyke with piping problems and implementing relief wells and a basin. A parametric design approach was followed to create a Pipingontspanner model that could obtain the optimal configuration for a measure that can only be calculated with a groundwater flow model. For the verification of design configurations, relevant failure mechanisms have been included in this model. For the selection of the optimal configuration, a cost-benefit analysis has been used as an evaluation criterion. The Pipingontspanner model creates, calculates, verifies and evaluates the different design configurations. The effectiveness of the Pipingontspannerwas illustratedwith a sensitivity and a cost analysis. For a variety of subsoil and hydraulic conditions, the sensitivity analysis showed that the safety factor for Uplift increases substantially for higher permeability of the aquifers and slowly growing hydraulic loads. The influence of the cover layer permeability and storage coefficient is negligible on the performance of the Pipingontspanner. On the other hand, the costs analysis showed that well maintenance, well monitoring and basin dyke construction costs are the main cost drivers of the design. The total cost grows exponentially if the basin width behind the dyke is limited as the number of wells increases for smaller basins. The applicability of the Pipingontspanner was demonstrated through a case study of a green dyke in Tiel with piping problems. In addition, the design and costs of the Pipingontspanner in Tiel were compared against a traditional piping berm measure to illustrate the economic feasibility of the concept. The results showed that the Pipingontspanner is not only able to mitigate the piping problem, but it does so with a smaller footprint and lower total cost than the piping berm. However, the case study also showed that limitations in the current groundwater flow model setup required an adaptation of the case geometry to prevent the drying up of the top layer cells, which would terminate the simulations. The Pipingontspanner concept has proven to be technically feasible and economically competitive compared to the piping bermunder the conditions of: 1. a permeable aquifer with a minimum transmissivity of 25 m^2/d; 2. a minimum hinterland space of 10 m behind the dyke.

Since 2003 there is a cooperation between the Hydraulic Engineering department of Delft University of Technology and Bulgarian universities. The cooperation focusses on exchange of knowledge and the development of the coast in the area of Varna. Dutch and Bulgarian students get the possibility to gain experience in data collecting, processing and interpreting. Repeating this fieldwork every year in the same area will provide an overview of the coastal development in the Varna area. The students will act as consultants for local hotel owners at the Varna coast. Their work consists of measuring hydraulic aspects in the project area and making a rehabilitation plan for the St. Elias Marina. Data collection consist of inventory material near site, beach measurements, wave measurements, profile measurements, quarry analysis and a bathymetric survey. The rehabilitation plan contains the development of sub-areas in the St. Elias Marina like the peninsula, north beach, south beach and the breakwater.

The reliability assessment of hydraulic structures, in primary water defences before 2017, is characterised by exceedance probabilities and implicit uncertainty. In January of 2017, the new water law enforces a change in the assessment of primary water defences. The water law requests a probability of flooding when assessing the safety requirements. The studies of VNK1 and 2 are based on this new safety approach and provide background information and a basis for the new water law. A failure probability and explicit uncertainties provide an increase of reliability in the safety judgement of primary water defences and more specifically hydraulic structures. The aim of a more reliable assessment procedure is to some extent limited by the tools prescribed by the water law. The assessment tool Riskeer does not allow the engineers to have transparency in calculations results, which prevents insight into the model behaviour and contribution to the failure probability. To investigate the mechanics contributing to the overall failure probability for hydraulic structures, analysis of the limit states, failure mechanisms and Riskeer software were performed. The results of the analysis were incorporated into a reference model to validate the suspected mechanics. The input for the reference model was a sensitivity analysis and case study, which cover the assessment tracks of Non-Closure and Strength and Stability for hydraulic structures. The aim of this reference model was not to replace the Riskeer software but describe the mechanics in the correct way. Analysis of the schematisation manual and previous assessment software (Ring toets) provided the incorporated failure mechanisms and the specific model that was used to obtain the limit state. Additionally, a fault tree defined how the different failure mechanisms are related. The knowledge of the fault trees combined with sensitivity analysis provided information about the largest contributors to the overall failure probability, regarding resistance and solicitation variables. The dominant solicitation factor in all failure mechanisms was the water level difference. The resistance factor was dominated by the failure probability of Non-Closure in the gate and the strength of a gate element. In the comparison of the reference model with the Riskeer software, the results were similar but not accurate enough to replace one with another. The reference model was significantly influenced by the approximation in the hydraulic boundary condition, which is formed by assuming a distribution for the water level, wave height and wave period. In the testing of the Riskeer software, the software results showed a difference between two levels of the fault tree. The lower level describes the fault tree including all mechanisms and sub-mechanisms. The top level shows the top probability of the fault tree on which extra simulations of scenarios are executed. The Riskeer software showed the top level as the final result, however, the reference model only describes the lower level. The extra simulations work in a conservative capacity and cannot be assessed by the reference model. The main processes in the fault trees were validated by the reference model, as is shown by their characteristics in the sensitivity analysis. Together with the temporary calculation results, a rough validation of the input parameters was feasible in the lower level. In contrast to the top level, where numerous scenarios were simulated without any transparency to what these values entail. The sensitivity analysis also showed the difference of the two levels over the different variables, which is a (almost constant) significant difference.