4.6 Article

Towards multi-objective optimization of large-scale fluvial landscaping measures

Journal

NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
Volume 19, Issue 6, Pages 1167-1187

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/nhess-19-1167-2019

Keywords

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Funding

  1. domain Applied and Engineering Sciences (AES) - Netherlands Organization for Scientific Research (NWO)
  2. Ministry of Economic Affairs under the Perspective Programme

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Adapting densely populated deltas to the combined impacts of climate change and socioeconomic developments presents a major challenge for their sustainable development in the 21st century. Decisions for the adaptations require an overview of cost and benefits and the number of stakeholders involved, which can be used in stakeholder discussions. Therefore, we quantified the trade-offs of common measures to compensate for an increase in discharge and sea level rise on the basis of relevant, but inexhaustive, quantitative variables. We modeled the largest delta distributary of the Rhine River with adaptation scenarios driven by (1) the choice of seven measures, (2) the areas owned by the two largest stakeholders (LS) versus all stakeholders (AS) based on a priori stakeholder preferences, and (3) the ecological or hydraulic design principle. We evaluated measures by their efficiency in flood hazard reduction, potential bio-diversity, number of stakeholders as a proxy for governance complexity, and measure implementation cost. We found that only floodplain lowering over the whole study area can offset the altered hydrodynamic boundary conditions; for all other measures, additional dike raising is required. LS areas comprise low hanging fruits for water level lowering due to the governance simplicity and hydraulic efficiency. Natural management of meadows (AS), after roughness smoothing and floodplain lowering, represents the optimum combination between potential biodiversity and flood hazard lowering, as it combines a high potential biodiversity with a relatively low hydrodynamic roughness. With this concept, we step up to a multidisciplinary, quantitative multi-parametric, and multi-objective optimization and support the negotiations among stakeholders in the decision-making process.

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