Reducing inconsistencies in point observations of maximum flood inundation level

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

The monetary benefit of early flood warnings in Europe

Effective disaster risk management relies on science-based solutions to close the gap between prevention and preparedness measures. The consultation on the United Nations post-2015 framework for disaster risk reduction highlights the need for cross-border early warning systems to strengthen the preparedness phases of disaster risk management, in order to save lives and property and reduce the overall impact of severe events. Continental and global scale flood forecasting systems provide vital early flood warning information to national and international civil protection authorities, who can use this information to make decisions on how to prepare for upcoming floods. Here the potential monetary benefits of early flood warnings are estimated based on the forecasts of the continental-scale European Flood Awareness System (EFAS) using existing flood damage cost information and calculations of potential avoided flood damages. The benefits are of the order of 400 Euro for every 1 Euro invested. A sensitivity analysis is performed in order to test the uncertainty in the method and develop an envelope of potential monetary benefits of EFAS warnings. The results provide clear evidence that there is likely a substantial monetary benefit in this cross-border continental-scale flood early warning system. This supports the wider drive to implement early warning systems at the continental or global scale to improve our resilience to natural hazards.

Science for Humanitarian Emergencies and Resilience (SHEAR) scoping study: Annex 3 - Early warning system and risk assessment case studies

This report provides case studies of Early Warning Systems (EWSs) and risk assessments encompassing three main hazard types: drought; flood and cyclone. The case studies are taken from ten countries across three continents (focusing on Africa, South Asia and the Caribbean). The case studies have been developed to assist the UK Department for International Development (DFID) to prioritise areas for Early Warning System (EWS) related research under their ‘Science for Humanitarian Emergencies and Resilience’ (SHEAR) programme. The aim of these case studies is to ensure that DFID SHEAR research is informed by the views of Non-Governmental Organisations (NGOs) and communities engaged with Early Warning Systems and risk assessments (including community-based Early Warning Systems). The case studies highlight a number of challenges facing Early Warning Systems (EWSs). These challenges relate to financing; integration; responsibilities; community interpretation; politics; dissemination; accuracy; capacity and focus. The case studies summarise a number of priority areas for EWS related research: • Priority 1: Contextualising and localising early warning information • Priority 2: Climate proofing current EWSs • Priority 3: How best to sustain effective EWSs between hazard events? • Priority 4: Optimising the dissemination of risk and warning information • Priority 5: Governance and financing of EWSs • Priority 6: How to support EWSs under challenging circumstances • Priority 7: Improving EWSs through monitoring and evaluating the impact and effectiveness of those systems

Continental and global scale flood forecasting systems

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.

Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

A Web GIS Decision Support System For Coastal Risk Assessment and Mitigation Planning

Coastal flooding poses serious threats to coastal areas around the world, billions of dollars in damage to property and infrastructure, and threatens the lives of millions of people. Therefore, disaster management and risk assessment aims at detecting vulnerability and capacities in order to reduce coastal flood disaster risk. In particular, non-specialized researchers, emergency management personnel, and land use planners require an accurate, inexpensive method to determine and map risk associated with storm surge events and long-term sea level rise associated with climate change. This study contributes to the spatially evaluation and mapping of social-economic-environmental vulnerability and risk at sub-national scale through the development of appropriate tools and methods successfully embedded in a Web-GIS Decision Support System. A new set of raster-based models were studied and developed in order to be easily implemented in the Web-GIS framework with the purpose to quickly assess and map flood hazards characteristics, damage and vulnerability in a Multi-criteria approach. The Web-GIS DSS is developed recurring to open source software and programming language and its main peculiarity is to be available and usable by coastal managers and land use planners without requiring high scientific background in hydraulic engineering. The effectiveness of the system in the coastal risk assessment is evaluated trough its application to a real case study.

Relative Energy Balance, CKD, and Risk of Cardiovascular and All-Cause Mortality.

BACKGROUND Mortality risk for people with chronic kidney disease is substantially greater than that for the general population, increasing to a 7-fold greater risk for those on dialysis therapy. Higher body mass index, generally due to higher energy intake, appears protective for people on dialysis therapy, but the relationship between energy intake and survival in those with reduced kidney function is unknown. STUDY DESIGN Prospective cohort study with a median follow-up of 14.5 (IQR, 11.2-15.2) years. SETTING & PARTICIPANTS Blue Mountains Area, west of Sydney, Australia. Participants in the general community enrolled in the Blue Mountains Eye Study (n=2,664) who underwent a detailed interview, food frequency questionnaire, and physical examination including body weight, height, blood pressure, and laboratory tests. PREDICTORS Relative energy intake, food components (carbohydrates, total sugars, fat, protein, and water), and estimated glomerular filtration rate (eGFR). Relative energy intake was dichotomized at 100%, and eGFR, at 60mL/min/1.73m(2). OUTCOMES All-cause and cardiovascular mortality. MEASUREMENTS All-cause and cardiovascular mortality using unadjusted and adjusted Cox proportional regression models. RESULTS 949 people died during follow-up, 318 of cardiovascular events. In people with eGFR<60mL/min/1.73m(2) (n=852), there was an increased risk of all-cause mortality (HR, 1.48; P=0.03), but no increased risk of cardiovascular mortality (HR, 1.59; P=0.1) among those with higher relative energy intake compared with those with lower relative energy intake. Increasing intake of carbohydrates (HR per 100g/d, 1.50; P=0.04) and total sugars (HR per 100g/d, 1.62; P=0.03) was associated significantly with increased risk of cardiovascular mortality. LIMITATIONS Under-reporting of energy intake, baseline laboratory and food intake values only, white population. CONCLUSIONS Increasing relative energy intake was associated with increased all-cause mortality in patients with eGFR<60mL/min/1.73m(2). This effect may be mediated by increasing total sugars intake on subsequent cardiovascular events.

Lake sediments as archives of recurrence rates and intensities of past flood events

Palaeoflood hydrology is an expanding field as the damage potential of flood and flood-related processes are increasing with the population density and the value of the infrastructure. Assessing the risk of these hazards in mountainous terrain requires knowledge about the frequency and severness of such events in the past. A wide range of methods is employed using diverse biologic, geomorphic or geologic evidences to track past flood events. Impact of floods are studied and dated on alluvial fans and cones using for example the growth disturbance of trees (Stoffel and Bollschweiler 2008; Schneuwly-Bollschweiler and Stoffel 2012: this volume) or stratigraphic layers deposited by debris flows, allowing to reconstruct past flood frequencies (Bardou et~al. 2003). Further downstream, the classical approach of palaeoflood hydrology (Kochel and Baker 1982) utilizes geomorphic indicators such as overbank sediments, silt lines and erosion features of floods along a river (e.g. Benito and Thorndycraft 2005). Fine-grained sediment settles out of the river suspension in eddies or backwater areas, where the flow velocity of the river is reduced. Records of these deposits at different elevations across a river’s profile can be used to assess the discharge of the past floods. This approach of palaeoflood hydrology studies was successfully applied in several river catchments (e.g. Ely et al. 1993; Macklin and Lewin 2003; O’Connor et al. 1994; Sheffer et al. 2003; Thorndycraft et al. 2005; Thorndycraft and Benito 2006). All these different reconstruction methods have their own advantages and disadvantages, but often these studies have a limited time coverage and the records are potentially incomplete due to lateral limits of depositional areas and due to the erosional power of fluvial processes that remove previously deposited flood witnesses. Here, we present a method that follows the sediment particle transported by a flood event to its final sink: the lacustrine basin.

Firm-level impacts of natural disasters on production networks : evidence from a flood in Thailand

In this paper, we explore the firm-level impacts of flooding in Thailand in 2011, specifically those on the procurement patterns at Japanese affiliates in Thailand. Our findings are as follow. First, the damaged small firms are more likely to lower their local procurement share, particularly the share of procurement from other Japanese-owned firms in Thailand. Second, damaged young firms and damaged old firms are more likely to raise the shares of imports from Japan and China, respectively. Third, there are no impacts on imports from ASEAN and other countries. These findings are useful for uncovering how multinational firms adjust their production networks before and after natural disasters.

Coastal Urban Flood Resislience versus Climate Change

Processes of founding and expanding cities in coastal areas have undergone great changes over time driven by environmental conditions. Coastal settlements looked for places above flood levels and away from swamps and other wetlands whenever possible. As populations grew, cities were extending trying to avoid low and wet lands. No city has been able to limit its growth. The risk of flooding can never be eliminated, but only reduced to the extent possible. Flooding of coastal areas is today dramatically attributed to eustasic sea level rise caused by global climate change. This can be inaccurate. Current climate change is generating an average sea level upward trend, but other regional and local factors result in this trend being accentuated in some places or attenuated, and even reversed, in others. Then, the intensity and frequency of coastal flooding around the planet, although not so much as a unique result of this general eustasic elevation, but rather of the superposition of marine and crustal dynamic elements, the former also climate-related, which give rise to a temporary raising in average sea level in the short term. Since the Little Ice Age the planet has been suffering a global warming change leading to sea level rise. The idea of being too obeying to anthropogenic factors may be attributed to Arrhenius (1896), though it is of much later highlight after the sixties of the last century. Never before, the human factor had been able of such an influence on climate. However, other types of changes in sea levels became apparent, resulting from vertical movements of the crust, modifications of sea basins due to continents fracturing, drifting and coming together, or to different types of climate patterns. Coastal zones are then doubly susceptible to floods. Precipitation immediately triggers pluvial flooding. If it continues upland or when snow and glaciers melt eventually fluvial flooding can occur. The urban development presence represents modifying factors. Additional interference is caused by river and waste water drainage systems. Climate also influences sea levels in coastal areas, where tides as well as the structure and dynamic of the geoid and its crust come into play. From the sea, waters can flood and break or push back berms and other coastline borders. The sea level, controlling the mouth of the main channel of the basin's drainage system, is ultimately what governs flood levels. A temporary rise in sea level acts as a dam at the mouth. Even in absence of that global change, so, floods are likely going to increase in many urban coastal areas. Some kind of innovative methodologies and practices should be needed to get more flood resilience cities

A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping

Reinstatement of flood affected properties:experiences of SMEs affected by the 2009 Cockermouth flood event

Recent policy changes in the UK encourage at-risk communities to learn to live with and adapt to flooding. Adaptation of individual properties by embracing resilient and resistant measures is an important aspect endorsed therein. Uptake of such protection measures by property owners, including that of Small and Medium-sized Enterprises (SMEs), has traditionally been low. A post-flood situation offers an opportunity to reinstate / reconstruct by integrating flood protection measures, in such a way that reduce damage and enhance the ability to recover in the event of a future flood incidence. In order to investigate the reinstatement / reconstruction experiences of flood affected SMEs, those affected by the 2009 Cockermouth flood event were studied. The results of a questionnaire survey revealed that many SMEs have opted for traditional reinstatement rather than resilient reinstatement. A detailed case study revealed requirements of getting the business back and running as soon as possible, a lack of guidance and advice from professionals and financial concerns as some of the barriers faced by SMEs. It is important that SMEs are provided with necessary guidance during the post-flood reinstatement stage, in order to make sure that the opportunity to build back better, integrating flood-protection measures is grasped by the SME owners. Stakeholders related to the construction industry, who are actively involved with post-flood reinstatement work, have an important role to play in this regard, providing necessary guidance and expertise to flooded SMEs.

Models and methods for damage and quantitative risk assessment of Natech scenarios

Natural events are a widely recognized hazard for industrial sites where relevant quantities of hazardous substances are handled, due to the possible generation of cascading events resulting in severe technological accidents (Natech scenarios). Natural events may damage storage and process equipment containing hazardous substances, that may be released leading to major accident scenarios called Natech events. The need to assess the risk associated with Natech scenarios is growing and methodologies were developed to allow the quantification of Natech risk, considering both point sources and linear sources as pipelines. A key element of these procedures is the use of vulnerability models providing an estimation of the damage probability of equipment or pipeline segment as a result of the impact of the natural event. Therefore, the first aim of the PhD project was to outline the state of the art of vulnerability models for equipment and pipelines subject to natural events such as floods, earthquakes, and wind. Moreover, the present PhD project also aimed at the development of new vulnerability models in order to fill some gaps in literature. In particular, a vulnerability model for vertical equipment subject to wind and to flood were developed. Finally, in order to improve the calculation of Natech risk for linear sources an original methodology was developed for Natech quantitative risk assessment methodology for pipelines subject to earthquakes. Overall, the results obtained are a step forward in the quantitative risk assessment of Natech accidents. The tools developed open the way to the inclusion of new equipment in the analysis of Natech events, and the methodology for the assessment of linear risk sources as pipelines provides an important tool for a more accurate and comprehensive assessment of Natech risk.