Urban flooding has become a key issue for many cities around the world. The project ‘INnovations for eXtreme Climatic EventS’ (INXCES) developed new innovative technological methods for risk assessment and mitigation of extreme hydroclimatic events and optimization of urban water-dependent ecosystem services at the catchment level. DEMs (digital elevation maps) have been used for more than a decade now as quick scan models to indicate locations that are vulnerable to urban flooding. In the last years the datasets are getting bigger and multidisciplinary stakeholders are becoming more demanding and require faster and more visual results. In this paper, the development and practical use of DEMs is exemplified by the case study of Bergen (Norway), where flood modelling using DEM is carried out in 2017 and in 2009. We can observe that the technology behind tools using DEMs is becoming more common and improved, both with a higher accuracy and a higher resolution. Visualization tools are developed to raise awareness and understanding among different stakeholders in Bergen and around the world. We can conclude that the evolution of DEMS is successful in handling bigger datasets and better (3D) visualization of results with a higher accuracy and a higher resolution. With flood maps the flow patterns of stormwater are analysed and locations are selected to implement (sub-)surface measures as SuDS (Sustainable Urban Drainage systems) that store and infiltrate stormwater. In the casestudy Bergen the following (sub-)surface SuDS have been recently implemented with the insights of DEMS: settlement storage tank, rainwater garden, swales, permeable pavement and I/T-drainage. The research results from the case study Bergen will be shared by tools to stimulate international knowledge exchange. New improved DEMs and connected (visualization) tools will continue to play an important role in (sub-)surface flood management and climate resilient urban planning strategies around the world.
It is by no means uncommon that academic scholars, journalists and even poets use the epi-thet ‘age of’ to signal how a certain feature is particularly characteristic of the times in which we live. In this chapter, we argue that it makes sense to address our current epoch as an ‘age of emotions’. Broadly speaking this entails that emotions, in many shapes and forms, have been widely recognized as decisive factors in social, cultural, economic and political realms in ways that were not the case before. For example, emotions are proven to play a key role in otherwise rational aspects of life such as political orientation and elections, as Arlie R. Hochschild so forcefully has demonstrated in her account of how people’s deep emotions are decisive when constructing their political identity and casting their vote (Hochschild 2016). In a more specific sense, emotions have historically been singled out as particularly informative about the psychic constitution of the times in which we live. W. H. Auden in 1947 famously declared that this epoch was an ‘age of anxiety’ (Auden 1948). Written in the aftermath of World War II, this pessimistic statement is not surprising: Anxiety was a normal human response to extraordinary circumstances. Recently, journalist of The Guardian, Oli-ver Burkeman, has pondered whether we currently live in an ‘age of rage’, in which people are – simply put – angrier than before, and in which social media is supporting and encourag-ing the ventilation of people’s rage and fury in a hitherto unseen manner. In relation to this chapter, the statement made by Allan V. Horwitz and Jerome C. Wakefield, based on an in-creasing prevalence of the phenomenon in question, that contemporary society should be understood as an ‘age of depression’, is noteworthy (Horwitz and Wakefield 2005). This characteristic begs the questions of how depression has become such an influential and prev-alent disorder in our times and how – even if – we should understand the phenomenon as an indicatory emotion of our epoch? Both as a sign of our times and as an emotion, depression is a particularly interesting phenomenon to study. This is not least due to its long and prolific history. As literary scholar Clark Lawlor has stated, it seems as if depression has been around forever and that depres-sion has been ‘fashionable throughout its history’ (Lawlor 2012:2). For centuries, Lawlor explains, depression has been a socio-cultural weighty condition that a significant amount of people has been emotionally affected by. Similarly, however, he also implies that the under-standing of depression – as a fashionable type of suffering – has changed proportionate to various socio-historical transformations. That is, depression is by no means a static descrip-tion of a specific type of human suffering. Depression changes and ‘relates’ to the societal circumstances it is situated in. If we focus on contemporary late modern society, two things hold true. First of all, there seems to be no doubt about the fact that the dominating under-standing of depression, by and large, is equivalent with the medically informed definition of Major Depression Disorder found in the DSM (Diagnostic and Statistical Manual of Mental Disorders). In here, depression is perceived as a biomedical disease that people suffer from. Secondly, we are witnessing a societal proliferation of the diagnosis of depression unseen in history. WHO has expressed that a veritable depression alarm is ringing loudly worldwide, and that more than 264 million people of all ages now suffer from depression (www.who.int). The combination of these facts is interesting. It informs us about a situation in which a biomedical understanding of depression has inserted itself in the societal discourse about what depression is, and that this understanding has internalized itself in the lives of many people. How are we to fathom this? In this chapter, we shall address this by following four main steps. First, we shall explore how depression has come to be understood as a biomedical disorder that is treated as a specific diagnosable disease, and then show how this understand-ing has been criticized. Second, we elucidate how – and against the backdrop of what – con-temporary depression can be understood as an emotion. Third, we will attempt to nuance the understanding of depression as emotion by arguing that when one zooms in on the phenome-non – that is on the experience of depression – one comes to understand depression as ele-mentary disconnection. Fourth, and based on this deepened understanding, we shall show how the alleged ‘depression epidemic’ can be sensibly linked to a certain subject-position in contemporary culture. Lastly, we will discuss some important implications of this nuanced understanding of depression. This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in "Emotions in Culture and Everyday Life Conceptual, Theoretical and Empirical Explorations". on 27.05.2024, available online: https://www.routledge.com/Emotions-in-Culture-and-Everyday-Life-Conceptual-Theoretical-and-Empirical-Explorations/Jacobsen/p/book/9781032077314?srsltid=AfmBOop3BqR29YtXXk7FrP4zXPX2BNdx5XizlZGoNZo4fDYC9HJ9OwQE
Objectives The aim of this study was to examine the reciprocal association between work–family conflict and depressive complaints over time. Methods Cross-lagged structural equation modeling (SEM) was used and three-wave follow-up data from the Maastricht Cohort Study with six years of follow-up [2416 men and 585 women at T1 (2008)]. Work–family conflict was operationalized by distinguishing both work–home interference and home–work interference, as assessed with two subscales of the Survey Work–Home Interference Nijmegen. Depressive complaints were assessed with a subscale of the Hospital Anxiety and Depression scale. Results The results showed a positive cross-lagged relation between home–work interference and depressive complaints. The results of the χ 2 difference test indicated that the model with cross-lagged reciprocal relationships resulted in a significantly better fit to the data compared to the causal (Δχ 2 (2)=9.89, P=0.001), reversed causation model (Δχ 2 (2)=9.25, P=0.01), and the starting model (Δχ 2 (4)=16.34, P=0.002). For work–home interference and depressive complaints, the starting model with no cross-lagged associations over time had the best fit to the empirical data. Conclusions The findings suggest a reciprocal association between home–work interference and depressive complaints since the concepts appear to affect each other mutually across time. This highlights the importance of targeting modifiable risk factors in the etiology of both home–work interference and depressive complaints when designing preventive measures since the two concepts may potentiate each other over time.
