Brenden Jongman

Assessing flood risk at the global scale: model setup, results, and sensitivity

Globally, economic losses from flooding exceeded

Declining vulnerability to river floods and the global benefits of adaptation

19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP (

Strong influence of El Niño Southern Oscillation on flood risk around the world

1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures.

Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data

Significance Understanding the vulnerability of societies around the world is crucial for understanding historical trends in flood risk and for producing accurate projections of fatalities and losses. We reproduced historical river flood occurrence using daily climate data for the period 1980–2010 and quantified the natural and socioeconomic contributions to flood risk trends. We show that the fatalities and losses as a share of the exposed population and gross domestic product are decreasing with rising income. We also show that there is a tendency of convergence in vulnerability levels between low- and high-income countries. Projections based on a wide range of climate change and socioeconomic development scenarios demonstrate that amplified adaptation efforts have the potential to largely contain losses from future floods. The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low- and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations, and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies.

Flood risk assessments at different spatial scales

Significance El Niño Southern Oscillation (ENSO) affects hydrological processes around the globe. However, little is known about its influence on the socioeconomic impacts of flooding (i.e., flood risk). We present, to our knowledge, the first global assessment of ENSO’s influence on flood risk in terms of economic damage and exposed population and gross domestic product. We show that reliable flood risk anomalies exist during ENSO years in basins spanning almost half of Earth’s surface. These results are significant for flood-risk management. Because ENSO can be predicted with lead times of several seasons with some skill, the findings pave the way for developing probabilistic flood-risk projections. These could be used for improved disaster planning, such as temporarily increasing food and medicine stocks by relief agencies. El Niño Southern Oscillation (ENSO) is the most dominant interannual signal of climate variability and has a strong influence on climate over large parts of the world. In turn, it strongly influences many natural hazards (such as hurricanes and droughts) and their resulting socioeconomic impacts, including economic damage and loss of life. However, although ENSO is known to influence hydrology in many regions of the world, little is known about its influence on the socioeconomic impacts of floods (i.e., flood risk). To address this, we developed a modeling framework to assess ENSO’s influence on flood risk at the global scale, expressed in terms of affected population and gross domestic product and economic damages. We show that ENSO exerts strong and widespread influences on both flood hazard and risk. Reliable anomalies of flood risk exist during El Niño or La Niña years, or both, in basins spanning almost half (44%) of Earth’s land surface. Our results show that climate variability, especially from ENSO, should be incorporated into disaster-risk analyses and policies. Because ENSO has some predictive skill with lead times of several seasons, the findings suggest the possibility to develop probabilistic flood-risk projections, which could be used for improved disaster planning. The findings are also relevant in the context of climate change. If the frequency and/or magnitude of ENSO events were to change in the future, this finding could imply changes in flood-risk variations across almost half of the world’s terrestrial regions.

The failed-levee effect: Do societies learn from flood disasters?

An accurate understanding of flood risk and its drivers is crucial for effective risk management. Detailed risk projections, including uncertainties, are however rarely available, particularly in developing countries. This paper presents a method that integrates recent advances in global-scale modeling of flood hazard and land change, which enables the probabilistic analysis of future trends in national-scale flood risk. We demonstrate its application to Indonesia. We develop 1000 spatially-explicit projections of urban expansion from 2000 to 2030 that account for uncertainty associated with population and economic growth projections, as well as uncertainty in where urban land change may occur. The projections show that the urban extent increases by 215%-357% (5th and 95th percentiles). Urban expansion is particularly rapid on Java, which accounts for 79% of the national increase. From 2000 to 2030, increases in exposure will elevate flood risk by, on average, 76% and 120% for river and coastal floods. While sea level rise will further increase the exposure-induced trend by 19%-37%, the response of river floods to climate change is highly uncertain. However, as urban expansion is the main driver of future risk, the implementation of adaptation measures is increasingly urgent, regardless of the wide uncertainty in climate projections. Using probabilistic urban projections, we show that spatial planning can be a very effective adaptation strategy. Our study emphasizes that global data can be used successfully for probabilistic risk assessment in data-scarce countries.

Structured Coupling of Probability Loss Distributions: Assessing Joint Flood Risk in Multiple River Basins

Managing flood risk, i.e. both the hazard and the potential consequences, is an important aspect of adapting to global change and has gained much traction in recent decades. As a result, a priori flood risk assessments have become an important part of flood management practices. Many methodologies have been set up, ranging from global risk assessments for the world as a whole, to local assessments for a particular stretch of a river/coast or small town. Most assessment frameworks generally follow a similar approach, but there are also notable differences between assessments at different spatial scales. This review article examines these differences, for instance those related to the methodology, use of assessments and uncertainties. From this review, future research needs are identified in order to improve flood risk assessments at different scales. At global/continental scale, there is a clear need for harmonised information on flood defences to improve assessments. Furthermore, inclusions of indirect economic effects at the macro-/meso-scale would give a better indication of the total effects of catastrophic flooding. At the meso-/micro-scale, there is an urgent need to improve our understanding of the effects of flooding on critical infrastructures, given their importance to society, the economy, emergency management and reconstruction. An overarching theme at all scales is the validation of flood risk assessments, which is often limited. More detailed post-disaster information would allow for improved calibration, validation and thus performance of flood risk models. Lastly, the link between spatial scales also deserves attention, for instance up- or downscaling methodologies.

Understanding risk: what makes a risk assessment successful?

Human societies have learnt to cope with flood risks in several ways, the most prominent ways being engineering solutions and adaptive measures. However, from a more sustainable point of view, it can be argued that societies should avoid or at least minimize urban developments in floodplain areas. While many scientists have studied the impact of human activities on flood risk, only a few studies have investigated the opposite relationships, i.e. the impacts of past flood events on floodplain development. In this study, we make an initial attempt to understand the impact of the occurrence of flood disasters on the spatial distribution of population dynamics in floodplain areas. Two different methodologies are used to uncover this relationship, a large-scale study for the USA and a case-study analysis of the 1993 Mississippi flood. The large-scale analysis is performed at county level scale for the whole of the USA and indicates a positive relationship between property damage due to flood events and population growth. The case-study analysis examines a reach of the Mississippi river and the territory, which was affected by flooding in 1993. Contrary to the large-scale analysis, no significant relationship is found in this detailed study. However, a trend of dampened population growth right after the flood followed by an accelerated growth a decade later could be identified in the raw data and linked to explanations found in the literature.

Disaster Risk, Climate Change, and Poverty: Assessing the Global Exposure of Poor People to Floods and Droughts

Losses due to natural hazard events can be extraordinarily high and difficult to cope with. Therefore, there is considerable interest to estimate the potential impact of current and future extreme events at all scales in as much detail as possible. As hazards typically spread over wider areas, risk assessment must take into account interrelations between regions. Neglecting such interdependencies can lead to a severe underestimation of potential losses, especially for extreme events. This underestimation of extreme risk can lead to the failure of riskmanagement strategies when they are most needed, namely, in times of unprecedented events. In this article, we suggest a methodology to incorporate such interdependencies in risk via the use of copulas. We demonstrate that by coupling losses, dependencies can be incorporated in risk analysis, avoiding the underestimation of risk. Based on maximum discharge data of river basins and stream networks, we present and discuss different ways to couple loss distributions of basins while explicitly incorporating tail dependencies. We distinguish between coupling methods that require river structure data for the analysis and those that do not. For the later approach we propose a minimax algorithm to choose coupled basin pairs so that the underestimation of risk is avoided and the use of river structure data is not needed. The proposed methodology is especially useful for large-scale analysis and we motivate and apply our method using the case of Romania. The approach can be easily extended to other countries and natural hazards.

What if Dutch investors started worrying about flood risk? Implications for disaster risk reduction

Purpose Understanding risk is more than just modeling risk; it requires an understanding of the development and social processes that underlie and drive the generation of disaster risk. Here, in addition to a review of more technical factors, this paper aims to discuss a variety of institutional, social and political considerations that must be managed for the results of a risk assessment to influence actions that lead to reductions in natural hazard risk. Design/methodology/approach The technical approaches and the institutional, social and political considerations covered in this paper are based on a wide range of experiences gleaned from case studies that touch on a variety of activities related to assessing the risks and impacts of natural hazards, and from the activities of the World Bank’s Global Facility for Disaster Reduction and Recovery. Findings Risk information provides a critical foundation for managing disaster risk across a wide range of sectors. Appropriate communication of robust risk information at the right time can raise awareness and trigger action to reduce risk. Communicating this information in a way that triggers action requires an understanding of the developments and social processes that underlie and drive the generation of risk, as well as of the wider Disaster Risk Management (DRM) decision-making context. Practical implications Prior to the initiation of a quantitative risk assessment one should clearly define why an assessment is needed and wanted, the information gaps that currently prevent effective DRM actions and the end-users of the risk information. This requires developing trust through communication among the scientists and engineers performing the risk assessment and the decision-makers, authorities, communities and other intended users of the information developed through the assessment. Originality/value This paper summarizes the technical components of a risk assessment as well as the institutional, social and political considerations that should be considered to maximize the probability of successfully reducing the risk defined by a risk assessment.