Elevating decision-making for maintaining inner-city quay walls

A conceptual decision-making model for implementing intervention measures

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Abstract

It is no secret that (asset)managers are currently dealing with a difficult task to maintain and improve the quality of their assets. The main reason for this urgency is the change of use and the end of lifespan of these assets. This is especially the case regarding the inner-city quay walls. These quay walls are usually owned and managed by local governments. The city of Amsterdam in particular has a tough task ahead of them. Approximately 200 km of quay wall need to be maintained or renewed of which the technical state is unknown. A vast majority of these inner-city quay walls are retaining walls on wooden piles. The absence of this information makes it extremely difficult for the asset owner, to determine the current technical state of their quay walls. The combination of limited information and time have shown in practice that quay walls can fail at any moment. To prevent this from happening a variety of intervention measures can be deployed to ‘extend’ the lifespan of the quay walls (short-term). Thereafter a systematic approach can be applied to rebuild or renovate these quay walls (long-term). However, the implementation of intervention measures is an overall complex task due to the densely built area and the stakeholders with divergent interests. This study provides an objective conceptual decision-making model to determine which intervention method is best suited for a particular location while considering the impact on the city, stakeholders and organizations. The research revealed six important topics which need to be incorporated in to the decision- making model. The topics were determined based on literature review, a case study and interviews. These six topics are: the critical cases (1), failure mechanisms (2), intervention measures (3), characteristics of the physical surrounding and the intervention measures (4), decision- making criteria (5) and lastly mitigation measures (6). Additionally, three decision-making moments are identified.