Global flood depth-damage functions: Methodology and the database with guidelines

Assessing potential damage of flood events is an important component in flood risk management. Determining direct flood damage is commonly done using depth-damage curves, which denote the flood damage that would occur at specific water depths per asset or per land-use class. Many countries have developed flood damage models using depth-damage curves based on analysis of past flood events and on expert judgement. However, the fact that such damage curves are not available for all regions hampers damage assessments in some areas. Moreover, due to different methodologies employed for various damage models in different countries, damage assessments cannot be directly compared with each other, obstructing also supra-national flood damage assessments. To address these problems a globally consistent database of depth-damage curves has been developed. This dataset contains damage curves depicting fractional damage function of water depth as well as maximum damage values for a variety of assets and land use classes. Based on an extensive literature survey concave damage curves have been developed for each continent, while differentiation in flood damage between countries is established by determining maximum damage values at the country scale. These maximum damage values are based on construction cost surveys from multinational construction companies, which provide a coherent set of detailed building cost data across dozens of countries. A consistent set of maximum flood damage values for all countries was computed using statistical regressions with socio-economic World Development Indicators. Further, based on insights from the literature survey, guidance is also given on how the damage curves and maximum damage values can be adjusted for specific local circumstances, such as urban vs. rural locations or use of specific building material. This dataset can be used for consistent supra-national scale flood damage assessments, and guide assessment in countries where no damage model is currently available.JRC.C.6-Economics of Climate Change, Energy and Transpor

The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes

Traditionally, building‐level disaster risk reduction (DRR) measures are aimed at a single natural hazard. However, in many countries the society faces the threat of multiple hazards. Building‐level DRR measures that aim to decrease earthquake vulnerability can have opposing or conflicting effects on flood vulnerability, and vice versa. In a case study of Afghanistan, we calculate the risk of floods and earthquakes, in terms of average annual losses (AAL), in the current situation. Next, we develop two DRR scenarios, where building‐level measures to reduce flood and earthquake risk are implemented. We use this to identify districts for which DRR measures of one hazard increase the risk of another hazard. We then also calculate the optimal situation between the two scenarios by, for each district, selecting the DRR scenario for which the AAL as a ratio of the total exposure is lowest. Finally, we assess the sensitivity of the total risk to each scenario. The optimal measure differs spatially throughout Afghanistan, but in most districts it is more beneficial to take flood DRR measures. However, in the districts where it is more beneficial to take earthquake measures, the reduction in risk is considerable (up to 40%, while flood DRR measures lead to a reduction in risk by 16% in individual districts). The introduction of asynergies between DRR measures in risk analyses allows policy‐makers to spatially differentiate building codes and other building‐level DRR measures to address the most prevalent risk while not compromising the risk resulting from other hazards

Urban transformation with TURAS open innovations; opportunities for transitioning through transdisciplinarity

Transitioning is a unidirectional process of mainstreaming sustainability within normative societal behaviour, which communities hope will build resilience, reduce our dependence on distant resources and lead to the transformation towards more sustainable living as an end product. Throughout Europe there are numerous examples and pilot or demonstration projects that illustrate tools, practices, mechanisms, pathways and policies for how transitioning can be guided and a transformation can be achieved. This paper draws on the experience of the TURAS project by illustrating some of the diverse open innovation opportunities that have been derived using novel transdisciplinary approaches. The paper concludes with identifying possible ways forward by utilising the TURAS innovations to enable the transformation of urban communities

How Close Do We Live to Water? A Global Analysis of Population Distance to Freshwater Bodies

Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water

Modeling urban development and its exposure to river flood risk in Southeast Asia

Countries in Southeast Asia have been developing quickly from a predominantly rural to predominantly urban society, leading to a rapid increase in urban land. This increase in urban land has mainly occurred in river deltas and floodplains, exposing humans and human assets to flood hazard. Here we present an assessment of current and future flood risk in five countries of mainland Southeast Asia, using a new modeling approach that accounts for differences in urban land systems. To that effect we mapped urban land on a rural-urban gradient and projected urban development until the year 2040 in two contrasting scenarios. The urban expansion scenario mainly projects the development of new urban areas, while the intensification emphasizes an increase in the number of inhabitants in already existing urban areas. Subsequently, we assessed the expected annual damage due to flood risk, using country specific exposure values for different land-system classes along the rural-urban gradient, based on typical construction materials. Results indicate that expected annual flood damage will increase in all countries and in both scenarios, ranging from +8% in Thailand to +211% in Laos. We showed that preferable development pathways are context dependent. In Cambodia and Laos, the increase in flood risk was largest for the intensification scenario, while for Myanmar, Thailand and Vietnam, the increase in flood risk was largest in the urban expansion scenario

Data and model of urban development and its exposure to river flood risk in Southeast Asia

This dataset contains the data and models used to simulate urban development to 2040 in Cambodia, Laos, Myanmanr, Thailand and Vietnam under two contrasting scenarios