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From November 12th to 13th in 1872, an extreme coastal flood event occurred in the south Baltic Sea. An unusual combination of winds created a storm surge reaching up to 3.5 m above mean sea level, which is more than a meter higher than all other observations over the past 200 years. On the Danish, German, and Swedish coasts, about 300 people lost their lives. The consequences of the storm in Denmark and Germany were more severe than in Sweden, with significantly larger destruction and higher numbers of casualties. In Denmark and Germany, the 1872 storm has been more extensively documented and remembered and still influences local and regional risk awareness. A comparative study indicates that the collective memory of the 1872 storm is related to the background knowledge about floods, the damage extent, and the response to the storm. Flood marks and dikes help to remember the events. In general, coastal flood defence is to the largest degree implemented in the affected areas in Germany, followed by Denmark, and is almost absent in Sweden, corresponding to the extent of the collective memory of the 1872 storm. Within the affected countries, there is local variability of flood risk awareness associated with the collective memory of the storm. Also, the economic dependency on flood-prone areas and conflicting interests with the tourism industry have influence on flood protection decisions. The processes of climate change adaptation and implementation of the EU Floods Directive are slowly removing these differences in flood risk management approaches.

Coastal protection has evolved from focusing on hard solutions such as breakwaters and groynes to include soft or nature‐based solutions (NbS). NbS have been proposed as cost‐effective means to offer long‐term coastal protection and at the same time strengthen coastal resilience and biodiversity. However, projects utilizing NbS for coastal protection have often focused on a single solution and the evidence of improved biodiversity remain equivocal. In this paper, we review solutions traditionally used for disparate purposes – namely beach nourishment and the establishment of vascular plants such as seagrass and dune grass. The main incentives behind large‐scale beach nourishment projects are often the cost‐effectiveness, multifunctionality and dynamic shoreline protection whereas the focus of vegetation restoration has typically been on recreating important habitats and not specifically as a coastal protection measure. Based on previous studies and an on‐going large‐scale coastal adaptation project in southern Sweden, we investigate the feasibility of combining these seemingly dichotomous management strategies to yield a viable physical defense and at the same time strengthen coastal biodiversity and ecosystem multifunctionality. Given the urgency in combatting biodiversity loss and adapting to a changing climate, management interventions for coastal protection should explicitly incorporate ecological values into every coastal protection measure and seek innovative, integrated approaches that consider both geomorphological and ecological values and the possible complementarity between the two.

Primary ship waves generated by conventional marine vessels were investigated in the Furusund fairway located in the Stockholm archipelago, Sweden. Continuous water level measurements at two locations in the fairway were analyzed. In total, 466 such events were extracted during two months of measurements. The collected data were used to evaluate 13 existing predictive equations for drawdown height or squat. However, none of the equations were able to satisfactorily predict the drawdown height. Instead, a new equation for drawdown height and period was derived based on simplified descriptions of the main physical processes together with field measurements, employing multiple regression analysis to derive coefficients in the equation. The proposed equation for drawdown height performed better than the existing equations with an R2 value of 0.65, whereas the equation for the drawdown period was R2 = 0.64. The main conclusion from this study is that an empirical equation can satisfactorily predict primary ship waves for a large data set.