A segment-wise dynamic programming algorithm for BSDEs

We introduce and analyze a family of linear least-squares Monte Carlo schemes for backward SDEs, which interpolate between the one-step dynamic programming scheme of Lemor, Warin, and Gobet (Bernoulli, 2006) and the multi-step dynamic programming scheme of Gobet and Turkedjiev (Mathematics of Computation, 2016). Our algorithm approximates conditional expectations over segments of the time grid. We discuss the optimal choice of the segment length depending on the `smoothness' of the problem and show that, in typical situations, the complexity can be reduced compared to the state-of-the-art multi-step dynamic programming scheme.Comment: 35 page

Are There Differences in the Health-Socioeconomic Status Relationship over the Life Cycle? Evidence from Germany

Most research on the relationship between health and socioeconomic status (SES) controls for changing age or investigates the relationship for a particular age range. This paper, however, examines changes in the relationship across ages, as well as controls for potential endogeneity in the health-SES relationship. Using data from German Socio Economic Panel, we find that the health-SES relationship does vary across the life cycle and that endogeneity is an important influence on the relationship. We also find tentative evidence that universal access to health care reduces the impact of income on self-reported health satisfaction

Why climate change adaptation in cities needs customised and flexible climate services

AbstractCities are key players in climate change adaptation and mitigation due to a spatial concentration of assets, people and economic activities. They are thus contributing to and especially vulnerable to climate change. Identifying, planning, implementing and monitoring respective measures in cities is challenging and resource consuming. The paper outlines challenges for adaptation, discusses most common approaches and argues why implementation of theoretical methods has its shortcomings. Based on case studies, an innovative, practice-oriented approach has been tested to develop a climate service prototype product. It provides a general framework that allows a flexible and customised support for cities to adapt to expected impacts of a changing climate

Disentangling coastal groundwater level dynamics on a global data set

This study aims to identify common hydrogeological patterns and to gain a deeper understanding of the underlying similarities and their link to physiographic, climatic, and anthropogenic controls of coastal groundwater. The most striking aspects of GWL dynamics and their controls were identified through a combination of statistical metrics, calculated from about 8,000 groundwater hydrographs, and pattern recognition, classification, and explanation using machine learning techniques and SHapley Additive exPlanations (SHAP). Overall, four different GWL dynamics patterns emerge, independent of the different seasons, time series lengths, and periods. We show in this study that similar GWL dynamics can be observed around the world with different combinations of site characteristics, but also that the main factors differentiating these patterns can be identified. Three of the identified patterns exhibit high short-term and interannual variability and are most common in regions with low terrain elevation and shallow groundwater depth. Climate and soil characteristics are most important in differentiating these patterns. This study provides new insights into the hydrogeological behavior of groundwater in coastal regions and guides systematic and holistic groundwater monitoring and modelling, motivating to consider various aspects of GWL dynamics when, for example, estimating climate-driven GWL changes &ndash; especially when information on potential controls is limited.</p

Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale

Increasing urbanisation in combination with a rise in the frequency and intensity of heavy rain events increase the risk of urban flooding. Flood Regulating Ecosystem Services (FRES) address the capacity of ecosystems to reduce the flood hazard and lower damage. FRES can be estimated by quantification of supply (provision of a service by an ecosystem) and demand (need for specific ES by society). However, FRES for pluvial floods in cities have rarely been studied and there is a gap in research and methods on FRES supply and demand quantification. In this study, we assessed FRES of an urban district in the City of Rostock (Germany) for a one-hour heavy rainfall event using the hydrological model LEAFlood. The hydrological model delivered the FRES supply indicators of soil water retention and water retained by canopies (interception). An intersection of the potential demand (based on indicators of population density, land reference value, monuments and infrastructure) and the modelled surface water depth revealed the actual demand. Comparing the actual demand and supply indicated the budget of FRES to identify unmet demand and supply surplus. Results show highest mean FRES supply on greened areas of forests, woodlands and green areas, resulting in a supply surplus. Whereas, sealed areas (paved surface where water cannot infiltrate into the soil), such as settlements, urban dense areas, traffic areas and industry, have an unmet demand resulting from low supply and relatively high actual demand. With the hydrological model LEAFlood, single landscape elements on the urban scale can be evaluated regarding their FRES and interception can be considered. Both are important for FRES assessment in urban areas. In contrast to flood risk maps, the study of FRES gives the opportunity to take into account the contribution of nature to flood regulation benefits for the socio-economic system. The visualisation of FRES supply and demand balance helps urban planners to identify hotspots and reduce potential impacts of urban pluvial flooding with ecosystem-based adaptations

The Current Use and Limitations of Water Related Digital Twins – a Practical View on Urban Climate Change Adaptation

Currently urban areas have to face many challenges. Overall, urbanization, demographic change, digitalization and climate change are main drivers that may directly or indirectly have an impact on the lifestyle and well-being of city dwellers. All drivers are interconnected and together with other sector-relevant drivers they form a complex network, that is often difficult to understand at first glance, and has many points of friction between different interests. For example, a growing urban population needs more space for housing areas which increases sealed surfaces and reduces natural groundwater recharge. Due to climate change, temperatures are rising (especially over sealed surfaces), also leading to an increasing water demand and rising evaporation rates. Both factors, besides others, influence the natural water cycle. In addition, in many places summer becomes drier, while more precipitation falls in winter times. The number and intensity of heavy rainfall events increases and dry periods are becoming longer. On the supply side, higher demand peaks in summer already pose greater challenges to water suppliers. Heavy rainfall can for example flood facility sites, parts of the critical infrastructure or cause power outages, which can lead to systemic interuptions. In recent years, also a trend towards “smart cities” can be seen to improve the the quality of life for residents. The idea of the progressing digitalization is to transfer parts of the real word into virtual representatives. Some are referred to as digital twins. However, these digital twins differ in their technical structure, complexity, and target for which they were developed. For years, many city administrations partly already use hydrological or urban climatological models as one form of simplified digital twins. Against this background, the paper presents and discusses the practical use, main results and lessons learned from case studies using two different hydrological models as digital twins in two German cities. Overall, the experiences from these case studies show that also the use of simplified digital models of a city – or parts of a city – without the need for big-data and monitoring information can be good planning tools to assess plausible results regarding possible future impacts based on climate change on a small scale. However, hydrological models currently are focussing on one or two challenges, only. But, due to the complexity of natural systems with a high number of connected processes, the whole story with interacting multiple drivers is not included totally. Depending on the modelling approach used, it is therefore possible to obtain different results with different models. Therefore, a better combination of several of such digital twins or the development of more powerful tools will be necessary, for example to transform an urban area towards being climate resilient and sustainable

Urban flood regulating ecosystem services under climate change: how can Nature-based Solutions contribute?

Urban areas are mostly highly sealed spaces, which often leads to large proportions of surface runoff. At the same time, heavy rainfall events are projected to increase in frequency and intensity with anthropogenic climate change. Consequently, higher risks and damages from pluvial flooding are expected. The analysis of Flood Regulating Ecosystem Services (FRES) can help to determine the benefits from nature to people by reducing surface runoff and runoff peaks. However, urban FRES are rarely studied for heavy rainfall events under changing climate conditions. Therefore, we first estimate the functionality of current urban FRES-supply and demand under changing climate conditions. Second, we identify the effects of Nature-based Solutions (NbS) on FRES-supply and demand and their potential future functionality and benefits concerning more intensive rainfall events. A district of the city of Rostock in northeastern Germany serves as the case study area. In addition to the reference conditions based on the current land use, we investigate two potential NbS: (1) increasing the number of trees; and (2) unsealing and soil improvement. Both NbS and a combination of both are applied for three heavy rainfall scenarios. In addition to a reference scenario, two future scenarios were developed to investigate the FRES functionality, based on 21 and 28% more intense rainfall. While the potential FRES-demand was held constant, we assessed the FRES-supply and actual demand for all scenario combinations, using the hydrological model LEAFlood. The comparison between the actual demand and supply indicates the changes in FRES-supply surplus and unmet demand increase. Existing land use structures reached a FRES capacity and cannot buffer more intense rainfall events. Whereas, the NbS serve FRES benefits by increasing the supply and reducing the actual demand. Using FRES indicators, based on hydrological models to estimate future functionality under changing climate conditions and the benefits of NbS, can serve as an analysis and decision-support tool for decision-makers to reduce future urban flood risk

Awareness about the Relevance of Cascading Effects in Urban Critical Infrastructure Networks under Climate Change – a Participatory Impact Matrix Approach

Addressing climate change adaptation in urban areas is increasingly urgent. To achieve sustainable and climate-adapted fields of action requires fundamental transformations of supply chains and infrastructures such as transport and mobility, electricity and water supply, or telecommunication as well as an improved understanding of their interactions. Practical experiences show, that in general there is an increasing awareness about this, but for example emergency plans or crisis communication often falls short regarding the indirect impacts of climate change on potential infrastructural failures. Hence, there is also a growing need for applied research and systemic approaches to overcome the current prevailing isolated sectoral view of climate change impacts to gain a holistic understanding of the critical infrastructure networks. Against this background, the paper highlights the relevance of climate change impacts on critical infrastructures, infrastructure interdependencies and potential systemic cascading effects. The analysis uses a participatory approach that has been applied within a case-study for the metropolitan area of Hamburg, Germany. It is based on transdisciplinary research methods, connecting the realms of scientific knowledge about regional climate change with real-world experiences. A strong focus lies on the use of a specific impact matrix approach carried out with key stakeholders from different sectors to identify climate-related drivers causing the most severe failures and losses in the system – either directly in the same sector or indirectly due to breakdowns in other sectors. In sum, the case-study enables a first categorization of the role single key variables play in the infrastructure system. Furthermore, it introduces the topic of adaptation to climate change as a starting point for a better understanding and management of systemic risks in order to build and maintain resilient critical infrastructures and to make urban areas safe, resilient and sustainable

Urban Climate Under Change [UC]2 – A National Research Programme for Developing a Building-Resolving Atmospheric Model for Entire City Regions

Large cities and urban regions are confronted with rising pressure by environmental pollution, impacts of climate change, as well as natural and health hazards. They are characterised by heterogeneous mosaics of urban structures, causing modifications of atmospheric processes on different temporal and spatial scales. Planning authorities need reliable, locally relevant information on urban atmospheric processes, providing fine spatial resolutions in city quarters or street canyons, as well as projections of future climates, specifically downscaled to individual cities. Therefore, building-resolving urban climate models for entire city regions are required as tool for urban development and planning, air quality control, as well as for design of actions for climate change mitigation and adaptation. To date, building-resolving atmospheric models covering entire large cities are mostly missing. The German research programme “Urban Climate Under Change” ([UC]2) aims at developing a new urban climate model, to acquire three-dimensional observational data for model testing and validation, and to test its practicability and usability in collaboration with relevant stakeholders to provide a scientifically sound and practicable instrument to address the above mentioned challenges. This article provides an outline of the collaborative activities of the [UC]2 research programme