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An important component of the risks from climate change arises from outcomes that are very unlikely, but whose impacts if they were to occur would be extremely severe. Examples include levels of surface warming, or changes in the water cycle, that are at the extreme of plausible ranges, or crossing of a climate system "tipping point" such as ice sheet or ocean circulation instability. If such changes were to occur their impacts on infrastructure or ecosystems may exceed existing plans for adaptation. The traditional approach of ensemble climate change projections is not well suited to managing these High Impact‐Low Likelihood (HILL) risks, where the objective is to "prepare for the worst" rather than to "plan for what's likely." In this paper we draw together a number of ideas from recent literature, to classify four types of HILL climate outcome and to propose the development of a practical "toolkit" of physical climate information that can be used in future to inform HILL risk management. The toolkit consists of several elements that would need to be developed for each plausible HILL climate outcome, then deployed individually to develop targeted HILL risk management approaches for individual sectors. We argue that development of the HILL toolkit should be an important focus for physical climate research over the coming decade, and that the time is right for a focused assessment of HILL risks by the Intergovernmental Panel on Climate Change in its 7th Assessment Cycle. Plain Language Summary: To prepare for the risks that arise from climate change (and avoid them where possible), it is important to understand how climate is likely to change in future, and what the impacts are likely to be. Over many years, climate science has developed sophisticated climate projections to estimate these likely impacts, and these are widely used to plan how people and societies will need to adapt to climate change. However it is also important to understand possibilities that are unlikely, but would have even more severe impacts if they did occur—for example, global warming levels at the high end of plausible estimates, or crossing a "tipping point" for major changes in ice sheets or ocean currents. A different type of information is needed to plan for these risks. In this paper we propose a new set of climate information "tools" to respond to these high‐impact risks. The tools include plausible scenarios of extreme outcomes, and early warning systems to detect if they are on the horizon. Combining these new tools with existing climate projections will allow society to understand more fully the risks of climate change, and to plan for the likely effects while preparing for the worst. Key Points: Climate outcomes or events that have a high impact are a key component of climate risk, even if their likelihood is lowTraditional climate projections are of limited use to inform management of high impact‐low likelihood risksPhysical climate science needs an increased focus on storylines, early warning and monitoring to inform management of high impact risks [ABSTRACT FROM AUTHOR]

International assessments of evidence on climate change (e.g. Intergovernmental Panel on Climate Change, IPCC) or national climate change risk assessments (e.g. UK Climate Change Risk Assessment, CCRA) do not offer a sufficiently granular perspective on climate impacts to adequately inform governance of resilience to climate risks at the local level. Using an analysis of UK decision-makers managing and responding to heatwaves and flood risks, this paper argues how more robust local evidence is needed to inform decision-making regarding adaptation options for enhancing local resilience. We identify evidence gaps and issues relating to local climate change impacts, including sources and quality of evidence used, adequacy and accessibility of evidence available, ill-communicated evidence and conflicting or misused evidence. A lack of appreciation regarding how scientific evidence and personal judgement can mutually enhance the quality of decision-making underpins all of these gaps. Additionally, we find that the majority of evidence currently used is reductively based upon socio-economic and physical characteristics of climate risks. We argue that a step change is needed in local climate resilience that moves beyond current physical and socio-economic risk characterisation to a more inclusive co-constitution of social and politically defined climate risks at the local scale that are better aligned with the local impacts felt and needs of stakeholders. [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

Delta cities are increasingly exposed to the risks of climate change, particularly to flooding. As a consequence, a variety of new spatial development visions, strategies, plans and programmes are being developed by city governments in delta regions to address these risks and challenges. Based on a general conceptual framework, this paper examines the nature of visions, strategies, plans and programmes in the delta cities of Hong Kong, Guangzhou and Rotterdam which are highly exposed to flooding and connected through a network of epistemic communities. The paper follows two main lines of inquiry. First, it examines the terms, concepts, and dominant institutional characteristics associated with the development of these visions, strategies, plans and programmes as a way of constructing a conceptual framework for understanding and explaining their connectivity. Second, it explores how and why cities’ spatial plans and governance dynamics are shaping climate adaptation responses. The systematic development of conceptual frameworks and in-depth analyses of varied, representative case studies is needed as their findings have important implications for vulnerability and adaptation to climate change in terms of policy options and cities as the optimal level for adaptation. The paper finds that dominant institutional characteristics critically affect the steering capacity of organisations/agencies (including their coordination capacity) to address climate-related risks. The findings have important implications for vulnerability and adaptation to climate change in cities, in general and delta cities, in particular. [ABSTRACT FROM AUTHOR]

In response to flood risk, design flood estimation is a cornerstone of planning, infrastructure design, setting of insurance premiums, and emergency response planning. Under stationary assumptions, flood guidance and the methods used in design flood estimation are firmly established in practice and mature in their theoretical foundations, but under climate change, guidance is still in its infancy. Human-caused climate change is influencing factors that contribute to flood risk such as rainfall extremes and soil moisture, and there is a need for updated flood guidance. However, a barrier to updating flood guidance is the translation of the science into practical application. For example, most science pertaining to historical changes to flood risk focuses on examining trends in annual maximum flood events or the application of non-stationary flood frequency analysis. Although this science is valuable, in practice, design flood estimation focuses on exceedance probabilities much rarer than annual maximum events, such as the 1 % annual exceedance probability event or even rarer, using rainfall-based procedures, at locations where there are few to no observations of streamflow. Here, we perform a systematic review to summarize the state-of-the-art understanding of the impact of climate change on design flood estimation in the Australian context, while also drawing on international literature. In addition, a meta-analysis, whereby results from multiple studies are combined, is conducted for extreme rainfall to provide quantitative estimates of possible future changes. This information is described in the context of contemporary design flood estimation practice to facilitate the inclusion of climate science into design flood estimation practice. [ABSTRACT FROM AUTHOR]

Changes in rainfall patterns due to climate change are expected to have negative impact on urban drainage systems, causing increase in flow volumes entering the system. In this paper, two emission scenarios for greenhouse concentration have been used, the high (A1FI) and the low (B1). Each scenario was selected for purpose of assessing the impacts on the drainage system. An artificial neural network downscaling technique was used to obtain local-scale future rainfall from three coarse-scale GCMs. An impact assessment was then carried out using the projected local rainfall and a risk assessment methodology to understand and quantify the potential hazard from surface flooding. The case study is a selected urban drainage catchment in northwestern England. The results show that there will be potential increase in the spilling volume from manholes and surcharge in sewers, which would cause a significant number of properties to be affected by flooding. [ABSTRACT FROM AUTHOR]

• Analyse the impact of climate change on road transport systems. • Develop a risk prediction tool to reduce climate impact on roads. • Conduct economic analysis of various measures to reduce climate impact on roads. • Conduct an empirical study to provide useful insights for rational risk based climate adaptation. This paper aims to analyse the impacts of climate change to the current and predicted future situations of road transportation in the UK and evaluate the corresponding adaptation plans to cope with them. A conceptual framework of long-term adaptation planning for climate change in road systems is proposed to ensure the resilience and sustainability of road transport systems under various climate risks such as flooding and increased temperature. To do so, an advanced Fuzzy Bayesian Reasoning (FBR) model is first employed to evaluate the climate risks in the UK road transport networks. This modelling approach can tackle the high uncertainty in risk data and thus facilitate the development of the climate adaptation framework and its application in the UK road sector. To examine the feasibility of this model, a nationwide survey is conducted among the stakeholders to analyse the climate risks, in terms of the timeframe of climate threats, the likelihood of occurrence, the severity of consequences, and infrastructure resilience. From the modelling perspective, this work brings novelty by expanding the risk attribute "the severity of consequence" into three sub-attributes including economic loss, damage to the environment, and injuries and/or loss of life. It advances the-state-of-the-art technique in the current relevant literature from a single to multiple tier climate risk modelling structure. Secondly, an Evidential Reasoning (ER) approach is used to prioritise the best adaptation measure(s) by considering both the risk analysis results from the FBR and the implementation costs simultaneously. The main new contributions of this part lie in the rich raw data collected from the real world to provide useful practical insights for achieving road resilience when facing increasing climate risk challenges. During this process, a qualitative analysis of several national reports regarding the impacts posed by climate change, risk assessment and adaptation measures in the UK road sector is conducted for the relevant decision data (i.e. risk and cost). It is also supplemented by an in-depth interview with a senior planner from Highways England. The findings provide road planners and decision makers with useful insights on identification and prioritisation of climate threats as well as selection of cost-effective climate adaptation measures to rationalise adaptation planning. [ABSTRACT FROM AUTHOR]

Flooding is a major natural hazard in many parts of the world, and its frequency and magnitude are projected to increase with global warming. With increased concern over ongoing climate change, more detailed and precise information about climate-change risks is required for formulating local-scale countermeasures. However, the impacts of biases in climate-model outputs on river-flood simulation have not been fully evaluated, and thus evaluation of future flood risks using hazard maps (high-resolution spatial-distribution maps of inundation depths) has not been achieved. Therefore, this study examined methods for constructing future-flood-hazard maps and discussed their validity. Specifically, we compared the runoff-correction method that corrects for bias in general-circulation-model (GCM) runoff using the monthly climatology of reanalysis runoff with the lookup method, which uses the GCM simulation results without bias correction to calculate changes in the return period and depends on the reanalysis simulation to determine absolute flood depths. The results imply that the runoff-correction method may produce significantly different hazard maps compared to those based on reanalysis of runoff data. We found that, in some cases, bias correction did not perform as expected for extreme values associated with the hazard map, even under the historical climate, as the bias of extreme values differed from that of the mean value. We found that the change direction of a future hazard (increase or decrease) obtained using the runoff-correction method relative to the reference reanalysis-based hazard map may be inconsistent with changes projected by Catchment-based Macro-scale Floodplain Model (CaMa-Flood) simulations based on GCM runoff input in some cases. On the other hand, the lookup method produced future-hazard maps that are consistent with flood-hazard changes projected by CaMa-Flood simulations obtained using GCM runoff input, indicating the possibility of obtaining a reasonable inundated-area distribution. These results suggest that the lookup method is more suitable for future-flood hazard-map construction than the runoff-correction method. The lookup method also has the advantage of facilitating research on efficient construction of future-climate hazard maps, as it allows for improvement of the reanalysis hazard map through upgrading of the model and separate estimation of changes due to climate change. We discuss future changes at the global scale in inundation areas and the affected population within the inundation area. Using the lookup method, the total population living in modeled inundation areas with flood magnitudes exceeding the 100-year return period under a future climate would be approximately 1.86 billion. In the assessment of future-climate risks, we found that an affected population of approximately 0.2 billion may be missed if the historical-hazard map is used as an alternative to constructing future-hazard maps, and only frequency changes are considered. These results suggest that, in global flood-risk studies, future-hazard maps are important for proper estimation of climate-change risks rather than assessing solely changes in the frequency of occurrence of a given flood intensity. [ABSTRACT FROM AUTHOR]

This paper considers the possible benefits of mitigation of climate change for coastal areas with a strong emphasis on sea-level rise, as this is one of the most certain consequences of human-induced global warming. There is a long-term ‘commitment to sea-level rise’ due to the long thermal lags of the ocean system and hence the response of sea-level rise to mitigation is slower than for other climate factors. Therefore, while climate stabilisation reduces coastal impacts during the 21st century, compared to unmitigated emissions, the largest benefits may occur in the 22nd century (and beyond). The results of the analysis suggest that a mixture of adaptation and mitigation policies need to be considered for coastal areas, as this will provide a more robust response to human-induced climate change than either policy in isolation. This requires the joint evaluation of mitigation and adaptation in coastal areas, ideally using a probabilistic risk-based methodology, which would be a departure from existing analyses. Because of the long time constants involved such assessments need to continue beyond 2100 to provide the full implications of the different policy choices. [Copyright &y& Elsevier]

A reliable flood event inventory that reflects the occurrence and evolution of past floods is important for studies of flood hazards and risks, hydroclimatic extremes, and future flood projections. However, currently available flood inventories are based on single-sourced data and often neglect underreported or less impactful flood events. Furthermore, traditional archives store flood events only at sparse geographic points, which significantly limits their further applicability. Also, few publicly available archives contain all-inclusive records of potential natural flooded area over time. To tackle these challenges, we construct two types of multisourced flood event inventories (MFI) for all river basins across the contiguous United States covering the period 1998–2013 on daily and subcatchment scales, which is publicly available at http://flood.umd.edu/download/CONUS/. These archives integrate flood information from in situ observations, remote sensing observations, hydrological model simulations, and five high-quality precipitation products. The first inventory (MFI-Actual) includes all actual floods that occurred in the presence of flood protection infrastructures, while the second, "natural (undefended)" inventory (MFI-Natural) reconstructs the possible "historical" floods without flood protection, which could be more directly influenced by climate variation. In the proposed two inventories, 2,755 and 4,661 flood events were estimated, respectively. MFI-Natural reconstructed 1,597 floods in ungauged basins, and recovered 608 extreme streamflow events in gauged subcatchments where floods would have happened if there were no flood protection. There is an average of four upstream dams located in these flood-recovered subcatchments, which indicates that modern flood defenses efficiently prevent significant flooding from extreme precipitation in many catchments over the country. [ABSTRACT FROM AUTHOR]

Research into potential implications of climate change on flood hazard has made significant progress over the past decade, yet efforts to translate this research into practical guidance for flood estimation remain in their infancy. In this commentary, we address the question: how best can practical flood guidance be modified to incorporate the additional uncertainty due to climate change? We begin by summarizing the physical causes of changes in flooding and then discuss common methods of design flood estimation in the context of uncertainty. We find that although climate science operates across aleatory, epistemic and deep uncertainty, engineering practitioners generally only address aleatory uncertainty associated with natural variability through standards-based approaches. A review of existing literature and flood guidance reveals that although research efforts in hydrology do not always reflect the methods used in flood estimation, significant progress has been made with many jurisdictions around the world now incorporating climate change in their flood guidance. We conclude that the deep uncertainty that climate change brings signals a need to shift towards more flexible design and planning approaches, and future research effort should focus on providing information that supports the range of flood estimation methods used in practice. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'. [ABSTRACT FROM AUTHOR]

This study presents the results of the ERTDF S-12 project for searching an optimum reduction scenario of the short-lived climate pollutants (SLCPs) to simultaneously mitigate the global warming and environmental problems. The study utilized REAS emission inventory, Asia-Pacific Integrated Model-Enduse (AIM/Enduse), MIROC6 climate model, NICAM non-hydrostatic atmospheric model, and models for estimating environmental damages to health, agriculture, and flood risks. Results of various scenario search indicate that it is difficult to attain simultaneous reduction of global warming and environmental damages, unless a significant reduction of CO2 is combined with carefully designed SLCP reductions for CH4, SO2, black carbon (BC), NOx, CO, and VOCs. In this scenario design, it is important to take into account the impact of small BC reduction to the surface air temperature and complex atmospheric chemical interactions such as negative feedback between CH4 and NOx reduction. We identified two scenarios, i.e., B2a and B1c scenarios which combine the 2D-scenario with SLCP mitigation measures using End-of-Pipe (EoP) and new mitigation technologies, as promising to simultaneously mitigate the temperature rise by about 0.33 °C by 2050 and air pollution in most of the globe for reducing damages in health, agriculture, and flood risk. In Asia and other heavy air pollution areas, health-care measures have to be enhanced in order to suppress the mortality increase due to high temperature in hot spot areas caused by a significant cut of particulate matter. For this situation, the B1b scenario is better to reduce hot spot areas and high-temperature damage to the public health. [ABSTRACT FROM AUTHOR]

In cold-region environments, ice-jam floods (IJFs) can result in high water levels in rivers to overtop levees, leading to devastating floods. Since climatic conditions play an important role in ice-jam flooding, there is a growing concern among property developers, insurance companies, government agencies, and communities on future IJF probabilities, especially in the context of changing climate. This study presents a stochastic framework for future IJF risk assessment and hazard mapping. Future hydrological conditions derived from a physically based hydrological model (forced with meteorological inputs from the Canadian regional climate model driven by two atmospheric-ocean general circulation climate models) were coupled to a fully dynamic hydraulic river-ice model to evaluate ice-jam scenarios and subsequent backwater-level profiles for the 2041–2070 period along the Athabasca River at Fort McMurray in Alberta, Canada. The modeling results show that future IJF risk will be lower and flood inundations less severe due to projected changes in climate, hydrology, and ice phenology in the 2041–2070 period compared to the baseline period of 1971–2000. However, extreme IJF events are still probable and can flood a considerable area of the town. [ABSTRACT FROM AUTHOR]

Resilience is an intangible concept. One way to describe it is done by indicators that can represent the same unit (index). The purpose of the study is to develop a method of measuring the climate resilience index (RI) based on the concepts and theory of vulnerability, risk, and resilience. The design of study and methods are: 1) framework for analysis of the concepts of vulnerability, risk, and resilience; and 2) develop RI based on a risk management approach and set up resilience forming factors. The method of measuring RI includes the choice of indicators, weighting and scaling indicators, categories of resilience, and applying methods to measure RI at the provincial level in Indonesia. The results showed that RI=(ACI*TCI)/(EI*SI); where RI: climate resilience index, ACI: adaptive capacity index, TCI: transformative capacity index, EI: exposure index, and SI: sensitivity index. In the case of Indonesia, the average of RI is 0.70. The highest was Jakarta SCR (1.61) and the lowest was East Nusa Tenggara (0.29). In other words, East Nusa Tenggara has to be the first priority of development in the face of climate change threat. [ABSTRACT FROM AUTHOR]

Modes of climate variability are known to influence rainy season onset, but there is less understanding of how they impact flood timing. We use streamflow reanalysis and gauged observation data sets to examine the influence of the Indian Ocean Dipole and El Niño–Southern Oscillation across sub‐Saharan Africa. We find significant changes in flood timing between positive and negative phases of both Indian Ocean Dipole and El Niño–Southern Oscillation; in some cases the difference in the timing of annual flood events is more than three months. Sensitivity to one or other mode of variability differs regionally. Changes in flood timing are larger than variability in rainy season onset reported in the literature, highlighting the need to understand how the hydrological system alters climate variability signals seen in rainy season onset, length, and rainfall totals. Our insights into flood timing could support communities who rely on flood‐based farming systems to adapt to climate variability. Plain Language Summary: Patterns of climate variability such as the El Niño–Southern Oscillation or the Indian Ocean Dipole affect the timing of the start of the rainy season, but little is known about how this translates into changes in the timing of the annual flood in rivers. We use computer model reconstructions and observed records of river flows in Africa to understand how these patterns of climate variability are changing the timing of river floods. In eastern and southern Africa, in particular, the differences in flood timing can be more than three months. This information could help farmers in African floodplains to adapt their water management, planting, and cropping practices to these patterns of climate variability. Key Points: Modes of climate variability in the Pacific and Indian Oceans drive significant changes in flood timing across sub‐Saharan AfricaThe hydrological system enhances and alters climate variability signals seen in rainy season onset, duration, and total rainfallUnderstanding of how climate variability changes the timing of floods can support flood‐based farming systems [ABSTRACT FROM AUTHOR]

An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policymaking, and harmonization of climate change adaptation strategies. There is, however, limited insight into the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the coastal flood risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea level (ESL), (ii) the underlying uncertainty in the digital elevation model (DEM), (iii) flood defence information, (iv) the assumptions behind the use of depth-damage functions that express vulnerability, and (v) different climate change projections. The impact of these uncertainties on estimated expected annual damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal, and on the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, and their absolute and relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large datasets with sufficient resolution and accuracy, the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality. [ABSTRACT FROM AUTHOR]

Flood risk management (FRM) is moving towards more proactive and collaborative direction to enable adaptation to changing conditions. We present a case study on collaborative planning process, which contributed to the development of adaptive FRM in one of the largest river basins in Finland. The focus was on the possibility and acceptability of using large regulated lakes as storage for flood water in an extreme flood event to decrease flood damage at the downstream riverside towns. We defined an extreme flood event that would cause dramatic flood damage and developed tools for simulating the event with alternative regulation strategies using Watershed Simulation and Forecasting System (WSFS). We organized a stakeholder event to demonstrate the alternative lake regulation strategies, their socio-economic consequences, and to discuss their acceptability. We found that storing flood water in the lakes above the regulation limits and preparing for winter floods in advance by lowering the lakes in the autumn can minimize the total damage in the target area. The majority of stakeholders considered these actions acceptable in an extreme flood event, regardless of deliberately induced flooding of areas where no floods have occurred for over 50 years. However, lowering the lakes in the autumn on annual basis gained less support. We emphasize the importance of deliberations on the FRM procedures and responsibilities in extreme flood events with the stakeholders in advance to increase adaptive capacity and legitimacy of decisions. [ABSTRACT FROM AUTHOR]

Climate change is expected to significantly affect flooding regimes of river systems in the future. For Western Europe, flood risk assessments generally assume an increase in extreme events and flood risk, and as a result major investments are planned to reduce their impacts. However, flood risk assessments for the present day and the near future suffer from uncertainty, coming from short measurements series, limited precision of input data, arbitrary choices for particular statistical and modelling approaches, and climatic non-stationarities. This study demonstrates how historical and sedimentary information can extend data records, adds important information on extremes, and generally improves flood risk assessments. The collection of specific data on the occurrence and magnitude of extremes and the natural variability of the floods is shown to be of paramount importance to reduce uncertainty in our understanding of flooding regime changes in a changing climate. For the Lower Rhine (the Netherlands and Germany) estimated recurrence times and peak discharges associated with the current protection levels correlate poorly with historical and sedimentary information and seem biased towards the recent multi-decadal period of increased flood activity. Multi-decadal and centennial variability in flood activity is recorded in extended series of discharge data, historical information and sedimentary records. Over the last six centuries that variability correlates with components of the Atlantic climate system such as the North Atlantic Oscillation (NAO) and Atlantic Multi-decadal Oscillation (AMO). These climatic non-stationarities importantly influence flood activity and the outcomes of flood risk assessments based on relatively short measurement series. [ABSTRACT FROM AUTHOR]

Floods account for more than half of the global hydrometeorological risks. Severe floods cause significant economic shocks and loss of lives, particularly for developing countries such as Jamaica. There is need for more information on the present and projected flood risks to justify macro-scale planning for climate change adaptation and facilitate the decision-making processes. In this study, a catalogue of 198 flood events occurring between 1678 and 2010 is compiled for Jamaica and used to examine the climatology, occurrence, trends, causes and duration of the island's severe events. The annual flood risk is estimated to be a loss of life rate of 4 persons and estimated annual damage of USD96.3 million per annum in 2010 values and approximately 0.84 % of GDP per annum. Macro-scale models for flood risks (deaths and damages) are also developed using data from the flood catalogue and maximum precipitation at the town and parish level. The models examine the relationship between flood risks (death and damages) and extreme rainfall depths and intensities. Future climate risks of loss of lives and damages are predicted to increase 11 and 9 %, respectively, to 4.4 persons and USD105.2 million per annum. [ABSTRACT FROM AUTHOR]

This study examines a tool developed by the U.S. FEMA for performing earthquake, hurricane, and flood hazard modeling and damage assessment. The focus of this research was to compare the native flood modeling and damage assessment functionalities of this tool with the May 2010 floods that impacted Davidson County (Nashville), Tennessee. Flood scenarios were created at the county and subcounty levels by using 1 and 1=3 arc-second digital elevation models and 100, 500, and 1,000 year flood return periods. The predicted flood surface area and damage levels were compared to observed flooding and damage from the 2010 floods. At the county level, the software was useful in predicting 87% of flood surface area and in identifying areas of damage, but its predictive value was limited at the subcounty level. These findings indicate that this predictive tool can be used primarily for large, county-level estimations as a screening tool to identify high impact areas that may require further analysis using more advanced hydrologic analysis. [ABSTRACT FROM AUTHOR]

Urban planning can play a potentially meaningful role in managing the risks of climate change. It is, however, unclear to what extent planning practice can be transformed in order to address these risks effectively in the global south. Using Johannesburg in South Africa as an illustrative case and the interrelated challenges of flood risks and informal growth as an example, it is demonstrated how the identification of a particular planning practice with historically informed values of justice substantially constrains the realization of adaptive planning options. Correspondingly, its implications for managing flood risks of climate change through planning under conditions of urban divide are outlined. [ABSTRACT FROM AUTHOR]

A warmer climate would increase the risk of floods. So far, only a few studies have projected changes in floods on a global scale. None of these studies relied on multiple climate models. A few global studies have started to estimate the exposure to flooding (population in potential inundation areas) as a proxy of risk, but none of them has estimated it in a warmer future climate. Here we present global flood risk for the end of this century based on the outputs of 11 climate models. A state-of-the-art global river routing model with an inundation scheme was employed to compute river discharge and inundation area. An ensemble of projections under a new high-concentration scenario demonstrates a large increase in flood frequency in Southeast Asia, Peninsular India, eastern Africa and the northern half of the Andes, with small uncertainty in the direction of change. In certain areas of the world, however, flood frequency is projected to decrease. Another larger ensemble of projections under four new concentration scenarios reveals that the global exposure to floods would increase depending on the degree of warming, but interannual variability of the exposure may imply the necessity of adaptation before significant warming. [ABSTRACT FROM AUTHOR]

The article presents a study about the potential impact of climate change on the risk of fluvial flooding in Great Britain. The study offers a comparison between published works and records about the historical trends of rainfall and river flow in the region and the high-resolution regional climate change projections. It also examines the techniques used for climate change detection and attribution and the effects of land-use change. The need to integrate climate and land-management interactions in order to understand flooding risk is discussed.

The aim of this research is to develop the Pluvial Flood Risk Assessment tool (PFRA) for rainwater management and adaptation to climate change in newly urbanised areas. PFRA allows pluvial hazard assessment, as well as pluvial flood risk mapping. The original model was created using ArcGIS software with the ArcHydro extension, and the script was written using the Python programming language. The PFRA model effectively combines information about land cover, soils, microtopography (LiDAR data), and projected hydro-meteorological conditions, which enables the identification of the spatial and temporal distribution of pluvial flood risks in newly developed areas. Further improvements to the PFRA concern the quantification of pluvial flood-related damages, the application of high resolution precipitation data, and the optimisation of coding. [ABSTRACT FROM AUTHOR]