Adaptive flood risk management under climate change uncertainty using real options and optimization

This is the peer reviewed version of the following article: oodward, M., Kapelan, Z. and Gouldby, B. (2014), Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization. Risk Analysis, 34: 75–92, which has been published in final form at 10.1111/risa.12088. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving: http://olabout.wiley.com/WileyCDA/Section/id-820227.html#termsIt is well recognized that adaptive and flexible flood risk strategies are required to account for future uncertainties. Development of such strategies is, however, a challenge. Climate change alone is a significant complication, but, in addition, complexities exist trying to identify the most appropriate set of mitigation measures, or interventions. There are a range of economic and environmental performance measures that require consideration, and the spatial and temporal aspects of evaluating the performance of these is complex. All these elements pose severe difficulties to decisionmakers. This article describes a decision support methodology that has the capability to assess the most appropriate set of interventions to make in a flood system and the opportune time to make these interventions, given the future uncertainties. The flood risk strategies have been explicitly designed to allow for flexible adaptive measures by capturing the concepts of real options and multiobjective optimization to evaluate potential flood risk management opportunities. A state-of-the-art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time and a multiobjective genetic algorithm is utilized to search for the optimal adaptive strategies. The modeling system has been applied to a reach on the Thames Estuary (London, England), and initial results show the inclusion of flexibility is advantageous, while the outputs provide decisionmakers with supplementary knowledge that previously has not been considered.Engineering and Physical Sciences Research Council (EPSRC)Department of Environment, Food and Rural Affairs/Environment Agency Joint Research Programme on Flood and Coastal DefenceUnited Kingdom Water Industry ResearchOffice of Public Works DublinNorthern Ireland Rivers Agenc

A highly efficient 2D flood modelling with sub-element topography

The need for large-scale and regional probabilistic simulations means that two-dimensional (2D) inundation models are still limited by computational requirements. In addition to parallelisation and physical process simplification, attempts to reduce runtimes typically involve coarsening the computational mesh, which can smooth important topographic features and hence limit accuracy. This paper presents a new 2D flow model that uses an enhanced diffusion-wave algorithm, and incorporates sub-element topography in a computational mesh that adapts to the terrain features. The model utilises a fine topographic resolution without having to use a fine computation mesh, and so achieves fast computational runtimes. The model has been tested against the UK Environment Agency’s 2D benchmarking tests, and even though the model is designed to operate at larger spatial scales than those in the benchmarking tests, it is shown to provide comparable accuracy relative to a selection of conventional 2D models, at significantly faster computational speeds. The model therefore has the potential to offer a step change in performance of large-scale probabilistic flood mapping and systems flood risk analysis modelling

Time-dependent Reliability Analysis of Flood Defence Assets Using Generic Fragility Curve

Flood defence assets such as earth embankments comprise the vital part of linear flood defences in many countries including the UK and protect inland from flooding. The risks of flooding are likely to increase in the future due to increasing pressure on land use, increasing rainfall events and rising sea level caused by climate change also affect aging flood defence assets. Therefore, it is important that the flood defence assets are maintained at a high level of safety and serviceability. The high costs associated with preserving these deteriorating flood defence assets and the limited funds available for their maintenance require the development of systematic approaches to ensure the sustainable flood-risk management system. The integration of realistic deterioration measurement and reliabilitybased performance assessment techniques has tremendous potential for structural safety and economic feasibility of flood defence assets. Therefore, the need for reliability-based performance assessment is evident. However, investigations on time-dependent reliability analysis of flood defence assets are limited. This paper presents a novel approach for time-dependent reliability analysis of flood defence assets. In the analysis, time-dependent fragility curve is developed by using the state-based stochastic deterioration model. The applicability of the proposed approach is then demonstrated with a case study

Optimizing Maritime Terminal Infrastructure Subject To Uncertainty

This paper describes a hydroinformatic model for generating a Pareto set of LNG terminal layouts that are subject to uncertainty using a multi-objective genetic algorithm. The NSGAII is used to select parameters that propagate through a bespoke LNG terminal design algorithm which includes a Monte Carlo simulator to estimate the uncertainty in each concept. This allows the trade-off between cost and risk to be explored at the earliest stage of design. The results of a case study indicate that nearshore terminals typically have lower capital costs but higher maintenance costs and more uncertainty. The paper concludes that in the example site used, locating the terminal 1000m offshore results in an optimal compromise between cost and risk

Real-time flood inundation forecasting and mapping for key railway infrastructure: a UK case study

Flooding events that impede railway infrastructure can cause severe travel delays for the general public and large fines in delayed minutes for the rail industry. Early warnings of flood inundation can give more time to implement mitigation measures which help reduce cancellations, delays and fines. Initial work is reported on the development of a real-time flood inundation forecasting and mapping system for the Cowley Bridge track area near Exeter, UK. This location is on one of the main access routes to South West England and has suffered major floods in the past resulting in significant transport impacts. Flood forecasting systems in the UK mainly forecast river level/flow rather than extent and depth of flood inundation. Here, the development of a chain of coupled models is discussed that link rainfall to river flow, river level and flood extent for the rail track area relating to Cowley Bridge. Historical events are identified to test model performance in predicting inundation of railway infrastructure. The modelling system will operate alongside a series of in-situ sensors chosen to enhance the flood mapping forecasting system. Sensor data will support offline model calibration/verification and real-time data assimilation as well as monitoring flood conditions to inform track closure decisions

Evaluation Of Decision Making Methods For Integrated Water Resource Management Under Uncertainty

Water companies and utilities in the UK are required to produce Water Resource Management Plans (WRMPs) every five years that outline their future strategies for maintaining a secure water supply to meet anticipated demand levels. Regulatory frameworks differ around the world but in most countries similar plans are developed under the auspices of Integrated Water Resources Management (IWRM) programmes. The plans justify new demand management and water supply infrastructure needed and validate management decisions. One of the greatest problems now facing decision makers in the water industry are the increasing uncertainties in the variables used in estimating the supply and demand balance due to increased levels of climate change. WRMPs in the future will need to deliver plans that can adapt water systems to face a widening variation of possible future states; with increased consideration to uncertain water availability, resource deterioration and demand levels. This paper reviews several established decision making methods and analyses their performance and suitability within an IWRM problem. The methods include Info-Gap decision theory, Robust Optimisation, Minimax Regret, Laplace theory and Maximin theory. These methods have been designed to aid decision making under severe uncertainty but differences exist in their approach and attitude to risk. For example, the Info-Gap methodology offers solutions that provide robustness of sufficing over a wide range of uncertainty, but is highly dependent on initial parameter settings. Robust Optimisation concentrates on optimising for robustness over a set of objective functions instead of satisfying a set of constraints. Laplace, Maximin and Minimax Regret are all classical decision methods that implicitly reflect a particular attitude to risk when dealing with severe uncertainty. These methods were applied to a case study resembling the Sussex North region in England, assessing their applicability at improving the IWRM problem and highlighting the strengths and weaknesses of each method

Multiobjective optimization for improved management of flood risk

Journal ArticleEffective flood risk management requires consideration of a range of different mitigation measures. Depending on the location, these could include structural or nonstructural measures as well as maintenance regimes for existing levee systems. Risk analysis models are used to quantify the benefits, in terms of risk reduction, when introducing different measures; further investigation is required to identify the most appropriate solution to implement. Effective flood risk management decision making requires consideration of a range of performance criteria. Determining the better performing strategies, according to multiple criteria, can be a challenge. This article describes the development of a decision support system that couples a multiobjective optimization algorithm with a flood risk analysis model and an automated cost model. The system has the ability to generate potential mitigation measures that are implemented at different points in time. It then optimizes the performance of the mitigation measures against multiple criteria. The decision support system is applied to an area of the Thames Estuary and the results obtained demonstrate the benefits multiobjective optimization can bring to flood risk management. © 2014 American Society of Civil Engineers.Engineering and Physical Sciences Research Council (EPSRC)Department of Environment, Food and Rural Affairs/Environment Agency (Defra/EA) Joint Research Programme on Flood and Coastal DefenceUnited Kingdom Water Industry Research (UKWIR)Office of Public Works (OPW) DublinNorthern Ireland Rivers Agency (DARDNI

Spatial and temporal analysis of extreme sea level and storm surge events around the coastline of the UK

In this paper we analyse the spatial footprint and temporal clustering of extreme sea level and skew surge events around the UK coast over the last 100 years (1915-2014). The vast majority of the extreme sea level events are generated by moderate, rather than extreme skew surges, combined with spring astronomical high tides. We distinguish four broad categories of spatial footprints of events and the distinct storm tracks that generated them. There have been rare events when extreme levels have occurred along two unconnected coastal regions during the same storm. The events that occur in closest succession (< 4 days) typically impact different stretches of coastline. The spring/neap tidal cycle prevents successive extreme sea level events from happening within 4-8 days. Finally, the 2013/14 season was highly unusual in the context of the last 100 years from an extreme sea level perspective

Tracking the spatial footprints of extreme storm surges around the coastline of the UK and Ireland

Storm surges are the most important driver of flooding in many coastal areas. Understanding the spatial extent of storm surge events has important financial and practical implications for flood risk management, reinsurance, infrastructure reliability and emergency response. In this paper, we apply a new tracking algorithm to a high-resolution surge hindcast (CODEC, 1980–2017) to characterize the spatial dependence and temporal evolution of extreme surge events along the coastline of the UK and Ireland. We quantify the severity of each spatial event based on its footprint extremity to select and rank the collection of events. Several surge footprint types are obtained based on the most impacted coastal stretch from each particular event, and these are linked to the driving storm tracks. Using the collection of the extreme surge events, we assess the spatial distribution and interannual variability of the duration, size, severity, and type. We find that the northeast coastline is most impacted by the longest and largest storm surge events, while the English Channel experiences the shortest and smallest storm surge events. The interannual variability indicates that the winter seasons of 1989-90 and 2013–14 were the most serious in terms of the number of events and their severity, based on the return period along the affected coastlines. The most extreme surge event and the highest number of events occurred in the winter season 1989–90, while the proportion of events with larger severities was higher during the winter season 2013–14. This new spatial analysis approach of surge extremes allows us to distinguish several categories of spatial footprints of events around the UK/Ireland coast and link these to distinct storm tracks. The spatial dependence structures detected can improve multivariate statistical methods which are crucial inputs to coastal flooding assessments

Evolutionary leap in large-scale flood risk assessment needed

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems and socio-economic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insurance portfolios. We review several examples of process interactions and highlight their importance in shaping spatio-temporal risk patterns. We call for a fundamental redesign of the approaches used for large-scale flood risk assessment. They need to be capable to form a basis for large-scale flood risk management and insurance policies worldwide facing the challenge of increasing risks due to climate and global change. In particular, implementation of the European Flood Directive needs to be adjusted for the next round of flood risk mapping and development of flood risk management plans focussing on methods accounting for more process interactions in flood risk systems