Abstract. In Europe, water management is moving from flood defence to a risk management approach, which takes both the probability and the potential consequences of flooding into account. It is expected that climate change and socio-economic development will lead to an increase in flood risk in the Rhine basin. To optimize spatial planning and flood management measures, studies are needed that quantify future flood risks and estimate their uncertainties. In this paper, we estimated the current and future fluvial flood risk in 2030 for the entire Rhine basin in a scenario study. The change in value at risk is based on two land-use projections derived from a land-use model representing two different socio-economic scenarios. Potential damage was calculated by a damage model, and changes in flood probabilities were derived from two climate scenarios and hydrological modeling. We aggregated the results into seven sections along the Rhine. It was found that the annual expected damage in the Rhine basin may increase by between 54% and 230%, of which the major part (∼ three-quarters) can be accounted for by climate change. The highest current potential damage can be found in the Netherlands (110 billion C), compared with the second (80 billion C) and third (62 billion C) highest values in two areas in Germany. Results further show that the area with the highest fluvial flood risk is located in the Lower Rhine in NordrheinWestfalen in Germany, and not in the Netherlands, as is often perceived. This is mainly due to the higher flood protection standards in the Netherlands as compared to Germany.

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These findings suggest that it is not population density in the neighbourhood, but rather the quality of socioeconomic, physical and social neighbourhood characteristics that is associated with the presence and severity of affective disorders.

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PurposeIn the Netherlands, a great variety of objectively measured geo-data is available, but these data are scattered and measured at varying spatial and temporal scales. The centralisation of these geo-data and the linkage of these data to individual-level data from longitudinal cohort studies enable large-scale epidemiological research on the impact of the environment on public health in the Netherlands. In the Geoscience and Health Cohort Consortium (GECCO), six large-scale and ongoing cohort studies have been enriched with a variety of existing geo-data. Here, we introduce GECCO by describing: (1) the phenotypes of the involved cohort studies, (2) the collected geo-data and their sources, (3) the methodology that was used to link the collected geo-data to individual cohort studies, (4) the similarity of commonly used geo-data between our consortium and the nationwide situation in the Netherlands and (5) the distribution of geo-data within our consortium.ParticipantsGECCO includes participants from six prospective cohort studies (eg, 44 657 respondents (18–100 years) in 2006) and it covers all municipalities in the Netherlands. Using postal code information of the participants, geo-data on the address-level, postal code-level as well as neighbourhood-level could be linked to individual-level cohort data.Findings to dateThe geo-data could be successfully linked to almost all respondents of all cohort studies, with successful data-linkage rates ranging from 97.1% to 100.0% between cohort studies. The results show variability in geo-data within and across cohorts. GECCO increases power of analyses, provides opportunities for cross-checking and replication, ensures sufficient geographical variation in environmental determinants and allows for nuanced analyses on specific subgroups.Future plansGECCO offers unique opportunities for (longitudinal) studies on the complex relationships between the environment and health outcomes. For example, GECCO will be used for further research on environmental determinants of physical/psychosocial functioning and lifestyle behaviours.