The Experts below are selected from a list of 11259 Experts worldwide ranked by ideXlab platform
David Wainwright - One of the best experts on this subject based on the ideXlab platform.
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moving from deterministic towards probabilistic Coastal Hazard and risk assessment development of a modelling framework and application to narrabeen beach new south wales australia
Coastal Engineering, 2015Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Kerrylee Rogers, Amy J. Dougherty, Ruben Jongejan, Peter J. CowellAbstract:Traditional methods for assessing Coastal Hazards have not typically incorporated a rigorous treatment of uncertainty. Such treatment is necessary to enable risk assessments which are now required by emerging risk based Coastal zone management/planning frameworks. While unresolved issues remain, relating to the availability of sufficient data for comprehensive uncertainty assessments, this will hopefully improve in coming decades. Here, we present a modelling framework which integrates geological, engineering and economic approaches for assessing the climate change driven economic risk to Coastal developments. The framework incorporates means for combining results from models that focus on the decadal to century time scales at which coasts evolve, and those that focus on the short term and seasonal time scales (storm bite and recovery). This paper demonstrates the functionality of the framework in deriving probabilistic Coastal Hazard lines and their subsequent use to establish an economically optimal setback line for development at a case study site; the Narrabeen–Collaroy embayment in Sydney, New South Wales.
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An argument for probabilistic Coastal Hazard assessment: Retrospective examination of practice in New South Wales, Australia
Ocean & Coastal Management, 2014Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Peter J. Cowell, Kerrylee RogersAbstract:Determination of Coastal Hazard lines is a key task for Coastal engineers worldwide. While current practice differs from country to country and even within countries, in many Coastal Hazard assessments three main components of coastline recession are taken into account: episodic recession due to storm erosion, long term recession due to an imbalance in sediment transport, and recession due to sea-level rise. In Australia, the state of New South Wales has a well-established procedure for the definition of Coastal Hazards that has evolved since the 1970's. Accepted practice in NSW is intentionally conservative, due to uncertainties and a limited understanding of physical processes. This article (i) provides an historical perspective on the development of the established methodology; (ii) discusses the various components of Coastal Hazard considered, and (iii) examines the way in which these components can be combined. Suggestions are subsequently provided for a way forward that better suits emerging risk-based Coastal management/planning frameworks. The article also considers the advantages and practicalities associated with assigning numerical probabilities to Hazard lines as part of risk-based Coastal management.
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Probabilistic Coastal Hazard lines for risk based Coastal assessment
2013Co-Authors: David Wainwright, David P. Callaghan, Peter J. Cowell, Amy J. Dougherty, Colin D. WoodroffeAbstract:As part of a recent NCCARF funded project "Approaches to Risk Assessment on Australian Coasts", a modelling framework was developed which integrated geological, engineering and economic approaches for assessing the risk of climate change along the Australian Coast. This paper aims to demonstrate the working of the framework in deriving probabilistic Coastal Hazard lines. Within the framework, means for combining results from models that focus on the decadal to century time scale (geomorphic), and those that focus on the short term and seasonal time scales (storm bite and recovery) have been developed. This combination is necessary for the derivation of probabilistic Hazard lines. The Narrabeen - Collaroy embayment on the northern beaches of Sydney was chosen as an appropriate study site due to its data rich nature, with directional wave records extending back 20 years, and ongoing repeated beach survey available since the mid 1970's. The site has been subject to extensive study over recent decades. To demonstrate operation of the framework two models with stochastic capabilities were adapted for use in the study. These are the Shoreface Translation Model (STM), for century scale geomorphic evolution, and the Joint Probability Method - Probabilistic Coastline Recession (JPM-PCR) for shorter term beach erosion and recovery. Both models are introduced and discussed. When projecting forward to future scenarios involving sea level rise, the framework also enables sea level rise over time to be input as a probabilistic variable. Recent research has also provided some guidance as to how this can be achieved using outputs from the most recent IPCC estimates. Overall, the research efforts have aimed to point a way forward that enables the quantitative assessment of Coastal Hazard likelihood for use in robust Coastal risk assessment. This contrasts with present practice which typically adopts a more qualitative approach to risk assessment.
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how to weigh Coastal Hazard against economic consequence
33rd International Conference on Coastal Engineering 2012 ICCE 2012, 2012Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Ruben Jongejan, Peter J. CowellAbstract:It is well recognised that sea level change over the coming century will have an extraordinary economic impact on Coastal communities. To overcome the uncertainty that still surrounds the mechanics of shoreline recession and stochastic forcing, landuse planning and management decisions will require a robust and quantitative risk-based approach. A new approach is presented, which has been evaluated using field measurements and assessed in economic terms. The paper discusses a framework for Coastal risk analysis which combines four main components 1) the effects of non-stationary climate, including decade scale variability and anthropogenic change; 2) a full probabilistic assessment of incident wave and surge conditions; 3) determination of storm erosion extents; and 4) the economic impact of combined Coastal erosion and recession. The framework is illustrated in Figure 1. The operation of this framework has been demonstrated, building upon previous work (Callaghan et al., 2008; Jongejan et al., 2011; Ranasinghe et al., 2011). The first three components relate to physical Hazards. Using stochastic simulation, we quantify the ‘likelihood’ side of risk. That likelihood is typically represented by lines indicating a projected extreme landward shoreline condition and an associated quantitative probability. For the first time, the effects of non-stationary climate (e.g. sea level rise) have been included. This can be extended to include decadal scale climate variation effects such as beach rotation. The fourth component requires the determination of values associated with land threatened by Coastal erosion during the time frame being considered. We assign a spatially varying value density relationship. The exceedance probability of erosion is combined with the value density to calculate the expected value of damage at a given point in time. In a non-stationary climate scenario, the exceedance probabilities change with time, and this is also considered. Given a known rate of return on investment, the differentials in the rates of return (between Coastal and inland property investments) are subsequently used to determine the efficient position of the setback line. The results are presented within a GIS framework to effectively feed into the Coastal land use planning process. We demonstrate the framework by applying it to using real data (both physical and economic) for our subject site, Narrabeen Beach in Sydney.
Peter J. Cowell - One of the best experts on this subject based on the ideXlab platform.
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moving from deterministic towards probabilistic Coastal Hazard and risk assessment development of a modelling framework and application to narrabeen beach new south wales australia
Coastal Engineering, 2015Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Kerrylee Rogers, Amy J. Dougherty, Ruben Jongejan, Peter J. CowellAbstract:Traditional methods for assessing Coastal Hazards have not typically incorporated a rigorous treatment of uncertainty. Such treatment is necessary to enable risk assessments which are now required by emerging risk based Coastal zone management/planning frameworks. While unresolved issues remain, relating to the availability of sufficient data for comprehensive uncertainty assessments, this will hopefully improve in coming decades. Here, we present a modelling framework which integrates geological, engineering and economic approaches for assessing the climate change driven economic risk to Coastal developments. The framework incorporates means for combining results from models that focus on the decadal to century time scales at which coasts evolve, and those that focus on the short term and seasonal time scales (storm bite and recovery). This paper demonstrates the functionality of the framework in deriving probabilistic Coastal Hazard lines and their subsequent use to establish an economically optimal setback line for development at a case study site; the Narrabeen–Collaroy embayment in Sydney, New South Wales.
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An argument for probabilistic Coastal Hazard assessment: Retrospective examination of practice in New South Wales, Australia
Ocean & Coastal Management, 2014Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Peter J. Cowell, Kerrylee RogersAbstract:Determination of Coastal Hazard lines is a key task for Coastal engineers worldwide. While current practice differs from country to country and even within countries, in many Coastal Hazard assessments three main components of coastline recession are taken into account: episodic recession due to storm erosion, long term recession due to an imbalance in sediment transport, and recession due to sea-level rise. In Australia, the state of New South Wales has a well-established procedure for the definition of Coastal Hazards that has evolved since the 1970's. Accepted practice in NSW is intentionally conservative, due to uncertainties and a limited understanding of physical processes. This article (i) provides an historical perspective on the development of the established methodology; (ii) discusses the various components of Coastal Hazard considered, and (iii) examines the way in which these components can be combined. Suggestions are subsequently provided for a way forward that better suits emerging risk-based Coastal management/planning frameworks. The article also considers the advantages and practicalities associated with assigning numerical probabilities to Hazard lines as part of risk-based Coastal management.
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Probabilistic Coastal Hazard lines for risk based Coastal assessment
2013Co-Authors: David Wainwright, David P. Callaghan, Peter J. Cowell, Amy J. Dougherty, Colin D. WoodroffeAbstract:As part of a recent NCCARF funded project "Approaches to Risk Assessment on Australian Coasts", a modelling framework was developed which integrated geological, engineering and economic approaches for assessing the risk of climate change along the Australian Coast. This paper aims to demonstrate the working of the framework in deriving probabilistic Coastal Hazard lines. Within the framework, means for combining results from models that focus on the decadal to century time scale (geomorphic), and those that focus on the short term and seasonal time scales (storm bite and recovery) have been developed. This combination is necessary for the derivation of probabilistic Hazard lines. The Narrabeen - Collaroy embayment on the northern beaches of Sydney was chosen as an appropriate study site due to its data rich nature, with directional wave records extending back 20 years, and ongoing repeated beach survey available since the mid 1970's. The site has been subject to extensive study over recent decades. To demonstrate operation of the framework two models with stochastic capabilities were adapted for use in the study. These are the Shoreface Translation Model (STM), for century scale geomorphic evolution, and the Joint Probability Method - Probabilistic Coastline Recession (JPM-PCR) for shorter term beach erosion and recovery. Both models are introduced and discussed. When projecting forward to future scenarios involving sea level rise, the framework also enables sea level rise over time to be input as a probabilistic variable. Recent research has also provided some guidance as to how this can be achieved using outputs from the most recent IPCC estimates. Overall, the research efforts have aimed to point a way forward that enables the quantitative assessment of Coastal Hazard likelihood for use in robust Coastal risk assessment. This contrasts with present practice which typically adopts a more qualitative approach to risk assessment.
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how to weigh Coastal Hazard against economic consequence
33rd International Conference on Coastal Engineering 2012 ICCE 2012, 2012Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Ruben Jongejan, Peter J. CowellAbstract:It is well recognised that sea level change over the coming century will have an extraordinary economic impact on Coastal communities. To overcome the uncertainty that still surrounds the mechanics of shoreline recession and stochastic forcing, landuse planning and management decisions will require a robust and quantitative risk-based approach. A new approach is presented, which has been evaluated using field measurements and assessed in economic terms. The paper discusses a framework for Coastal risk analysis which combines four main components 1) the effects of non-stationary climate, including decade scale variability and anthropogenic change; 2) a full probabilistic assessment of incident wave and surge conditions; 3) determination of storm erosion extents; and 4) the economic impact of combined Coastal erosion and recession. The framework is illustrated in Figure 1. The operation of this framework has been demonstrated, building upon previous work (Callaghan et al., 2008; Jongejan et al., 2011; Ranasinghe et al., 2011). The first three components relate to physical Hazards. Using stochastic simulation, we quantify the ‘likelihood’ side of risk. That likelihood is typically represented by lines indicating a projected extreme landward shoreline condition and an associated quantitative probability. For the first time, the effects of non-stationary climate (e.g. sea level rise) have been included. This can be extended to include decadal scale climate variation effects such as beach rotation. The fourth component requires the determination of values associated with land threatened by Coastal erosion during the time frame being considered. We assign a spatially varying value density relationship. The exceedance probability of erosion is combined with the value density to calculate the expected value of damage at a given point in time. In a non-stationary climate scenario, the exceedance probabilities change with time, and this is also considered. Given a known rate of return on investment, the differentials in the rates of return (between Coastal and inland property investments) are subsequently used to determine the efficient position of the setback line. The results are presented within a GIS framework to effectively feed into the Coastal land use planning process. We demonstrate the framework by applying it to using real data (both physical and economic) for our subject site, Narrabeen Beach in Sydney.
Kerrylee Rogers - One of the best experts on this subject based on the ideXlab platform.
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moving from deterministic towards probabilistic Coastal Hazard and risk assessment development of a modelling framework and application to narrabeen beach new south wales australia
Coastal Engineering, 2015Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Kerrylee Rogers, Amy J. Dougherty, Ruben Jongejan, Peter J. CowellAbstract:Traditional methods for assessing Coastal Hazards have not typically incorporated a rigorous treatment of uncertainty. Such treatment is necessary to enable risk assessments which are now required by emerging risk based Coastal zone management/planning frameworks. While unresolved issues remain, relating to the availability of sufficient data for comprehensive uncertainty assessments, this will hopefully improve in coming decades. Here, we present a modelling framework which integrates geological, engineering and economic approaches for assessing the climate change driven economic risk to Coastal developments. The framework incorporates means for combining results from models that focus on the decadal to century time scales at which coasts evolve, and those that focus on the short term and seasonal time scales (storm bite and recovery). This paper demonstrates the functionality of the framework in deriving probabilistic Coastal Hazard lines and their subsequent use to establish an economically optimal setback line for development at a case study site; the Narrabeen–Collaroy embayment in Sydney, New South Wales.
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An argument for probabilistic Coastal Hazard assessment: Retrospective examination of practice in New South Wales, Australia
Ocean & Coastal Management, 2014Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Peter J. Cowell, Kerrylee RogersAbstract:Determination of Coastal Hazard lines is a key task for Coastal engineers worldwide. While current practice differs from country to country and even within countries, in many Coastal Hazard assessments three main components of coastline recession are taken into account: episodic recession due to storm erosion, long term recession due to an imbalance in sediment transport, and recession due to sea-level rise. In Australia, the state of New South Wales has a well-established procedure for the definition of Coastal Hazards that has evolved since the 1970's. Accepted practice in NSW is intentionally conservative, due to uncertainties and a limited understanding of physical processes. This article (i) provides an historical perspective on the development of the established methodology; (ii) discusses the various components of Coastal Hazard considered, and (iii) examines the way in which these components can be combined. Suggestions are subsequently provided for a way forward that better suits emerging risk-based Coastal management/planning frameworks. The article also considers the advantages and practicalities associated with assigning numerical probabilities to Hazard lines as part of risk-based Coastal management.
David P. Callaghan - One of the best experts on this subject based on the ideXlab platform.
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moving from deterministic towards probabilistic Coastal Hazard and risk assessment development of a modelling framework and application to narrabeen beach new south wales australia
Coastal Engineering, 2015Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Kerrylee Rogers, Amy J. Dougherty, Ruben Jongejan, Peter J. CowellAbstract:Traditional methods for assessing Coastal Hazards have not typically incorporated a rigorous treatment of uncertainty. Such treatment is necessary to enable risk assessments which are now required by emerging risk based Coastal zone management/planning frameworks. While unresolved issues remain, relating to the availability of sufficient data for comprehensive uncertainty assessments, this will hopefully improve in coming decades. Here, we present a modelling framework which integrates geological, engineering and economic approaches for assessing the climate change driven economic risk to Coastal developments. The framework incorporates means for combining results from models that focus on the decadal to century time scales at which coasts evolve, and those that focus on the short term and seasonal time scales (storm bite and recovery). This paper demonstrates the functionality of the framework in deriving probabilistic Coastal Hazard lines and their subsequent use to establish an economically optimal setback line for development at a case study site; the Narrabeen–Collaroy embayment in Sydney, New South Wales.
-
An argument for probabilistic Coastal Hazard assessment: Retrospective examination of practice in New South Wales, Australia
Ocean & Coastal Management, 2014Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Peter J. Cowell, Kerrylee RogersAbstract:Determination of Coastal Hazard lines is a key task for Coastal engineers worldwide. While current practice differs from country to country and even within countries, in many Coastal Hazard assessments three main components of coastline recession are taken into account: episodic recession due to storm erosion, long term recession due to an imbalance in sediment transport, and recession due to sea-level rise. In Australia, the state of New South Wales has a well-established procedure for the definition of Coastal Hazards that has evolved since the 1970's. Accepted practice in NSW is intentionally conservative, due to uncertainties and a limited understanding of physical processes. This article (i) provides an historical perspective on the development of the established methodology; (ii) discusses the various components of Coastal Hazard considered, and (iii) examines the way in which these components can be combined. Suggestions are subsequently provided for a way forward that better suits emerging risk-based Coastal management/planning frameworks. The article also considers the advantages and practicalities associated with assigning numerical probabilities to Hazard lines as part of risk-based Coastal management.
-
Probabilistic Coastal Hazard lines for risk based Coastal assessment
2013Co-Authors: David Wainwright, David P. Callaghan, Peter J. Cowell, Amy J. Dougherty, Colin D. WoodroffeAbstract:As part of a recent NCCARF funded project "Approaches to Risk Assessment on Australian Coasts", a modelling framework was developed which integrated geological, engineering and economic approaches for assessing the risk of climate change along the Australian Coast. This paper aims to demonstrate the working of the framework in deriving probabilistic Coastal Hazard lines. Within the framework, means for combining results from models that focus on the decadal to century time scale (geomorphic), and those that focus on the short term and seasonal time scales (storm bite and recovery) have been developed. This combination is necessary for the derivation of probabilistic Hazard lines. The Narrabeen - Collaroy embayment on the northern beaches of Sydney was chosen as an appropriate study site due to its data rich nature, with directional wave records extending back 20 years, and ongoing repeated beach survey available since the mid 1970's. The site has been subject to extensive study over recent decades. To demonstrate operation of the framework two models with stochastic capabilities were adapted for use in the study. These are the Shoreface Translation Model (STM), for century scale geomorphic evolution, and the Joint Probability Method - Probabilistic Coastline Recession (JPM-PCR) for shorter term beach erosion and recovery. Both models are introduced and discussed. When projecting forward to future scenarios involving sea level rise, the framework also enables sea level rise over time to be input as a probabilistic variable. Recent research has also provided some guidance as to how this can be achieved using outputs from the most recent IPCC estimates. Overall, the research efforts have aimed to point a way forward that enables the quantitative assessment of Coastal Hazard likelihood for use in robust Coastal risk assessment. This contrasts with present practice which typically adopts a more qualitative approach to risk assessment.
-
how to weigh Coastal Hazard against economic consequence
33rd International Conference on Coastal Engineering 2012 ICCE 2012, 2012Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Ruben Jongejan, Peter J. CowellAbstract:It is well recognised that sea level change over the coming century will have an extraordinary economic impact on Coastal communities. To overcome the uncertainty that still surrounds the mechanics of shoreline recession and stochastic forcing, landuse planning and management decisions will require a robust and quantitative risk-based approach. A new approach is presented, which has been evaluated using field measurements and assessed in economic terms. The paper discusses a framework for Coastal risk analysis which combines four main components 1) the effects of non-stationary climate, including decade scale variability and anthropogenic change; 2) a full probabilistic assessment of incident wave and surge conditions; 3) determination of storm erosion extents; and 4) the economic impact of combined Coastal erosion and recession. The framework is illustrated in Figure 1. The operation of this framework has been demonstrated, building upon previous work (Callaghan et al., 2008; Jongejan et al., 2011; Ranasinghe et al., 2011). The first three components relate to physical Hazards. Using stochastic simulation, we quantify the ‘likelihood’ side of risk. That likelihood is typically represented by lines indicating a projected extreme landward shoreline condition and an associated quantitative probability. For the first time, the effects of non-stationary climate (e.g. sea level rise) have been included. This can be extended to include decadal scale climate variation effects such as beach rotation. The fourth component requires the determination of values associated with land threatened by Coastal erosion during the time frame being considered. We assign a spatially varying value density relationship. The exceedance probability of erosion is combined with the value density to calculate the expected value of damage at a given point in time. In a non-stationary climate scenario, the exceedance probabilities change with time, and this is also considered. Given a known rate of return on investment, the differentials in the rates of return (between Coastal and inland property investments) are subsequently used to determine the efficient position of the setback line. The results are presented within a GIS framework to effectively feed into the Coastal land use planning process. We demonstrate the framework by applying it to using real data (both physical and economic) for our subject site, Narrabeen Beach in Sydney.
Roshanka Ranasinghe - One of the best experts on this subject based on the ideXlab platform.
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moving from deterministic towards probabilistic Coastal Hazard and risk assessment development of a modelling framework and application to narrabeen beach new south wales australia
Coastal Engineering, 2015Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Kerrylee Rogers, Amy J. Dougherty, Ruben Jongejan, Peter J. CowellAbstract:Traditional methods for assessing Coastal Hazards have not typically incorporated a rigorous treatment of uncertainty. Such treatment is necessary to enable risk assessments which are now required by emerging risk based Coastal zone management/planning frameworks. While unresolved issues remain, relating to the availability of sufficient data for comprehensive uncertainty assessments, this will hopefully improve in coming decades. Here, we present a modelling framework which integrates geological, engineering and economic approaches for assessing the climate change driven economic risk to Coastal developments. The framework incorporates means for combining results from models that focus on the decadal to century time scales at which coasts evolve, and those that focus on the short term and seasonal time scales (storm bite and recovery). This paper demonstrates the functionality of the framework in deriving probabilistic Coastal Hazard lines and their subsequent use to establish an economically optimal setback line for development at a case study site; the Narrabeen–Collaroy embayment in Sydney, New South Wales.
-
An argument for probabilistic Coastal Hazard assessment: Retrospective examination of practice in New South Wales, Australia
Ocean & Coastal Management, 2014Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Colin D. Woodroffe, Peter J. Cowell, Kerrylee RogersAbstract:Determination of Coastal Hazard lines is a key task for Coastal engineers worldwide. While current practice differs from country to country and even within countries, in many Coastal Hazard assessments three main components of coastline recession are taken into account: episodic recession due to storm erosion, long term recession due to an imbalance in sediment transport, and recession due to sea-level rise. In Australia, the state of New South Wales has a well-established procedure for the definition of Coastal Hazards that has evolved since the 1970's. Accepted practice in NSW is intentionally conservative, due to uncertainties and a limited understanding of physical processes. This article (i) provides an historical perspective on the development of the established methodology; (ii) discusses the various components of Coastal Hazard considered, and (iii) examines the way in which these components can be combined. Suggestions are subsequently provided for a way forward that better suits emerging risk-based Coastal management/planning frameworks. The article also considers the advantages and practicalities associated with assigning numerical probabilities to Hazard lines as part of risk-based Coastal management.
-
how to weigh Coastal Hazard against economic consequence
33rd International Conference on Coastal Engineering 2012 ICCE 2012, 2012Co-Authors: David Wainwright, Roshanka Ranasinghe, David P. Callaghan, Ruben Jongejan, Peter J. CowellAbstract:It is well recognised that sea level change over the coming century will have an extraordinary economic impact on Coastal communities. To overcome the uncertainty that still surrounds the mechanics of shoreline recession and stochastic forcing, landuse planning and management decisions will require a robust and quantitative risk-based approach. A new approach is presented, which has been evaluated using field measurements and assessed in economic terms. The paper discusses a framework for Coastal risk analysis which combines four main components 1) the effects of non-stationary climate, including decade scale variability and anthropogenic change; 2) a full probabilistic assessment of incident wave and surge conditions; 3) determination of storm erosion extents; and 4) the economic impact of combined Coastal erosion and recession. The framework is illustrated in Figure 1. The operation of this framework has been demonstrated, building upon previous work (Callaghan et al., 2008; Jongejan et al., 2011; Ranasinghe et al., 2011). The first three components relate to physical Hazards. Using stochastic simulation, we quantify the ‘likelihood’ side of risk. That likelihood is typically represented by lines indicating a projected extreme landward shoreline condition and an associated quantitative probability. For the first time, the effects of non-stationary climate (e.g. sea level rise) have been included. This can be extended to include decadal scale climate variation effects such as beach rotation. The fourth component requires the determination of values associated with land threatened by Coastal erosion during the time frame being considered. We assign a spatially varying value density relationship. The exceedance probability of erosion is combined with the value density to calculate the expected value of damage at a given point in time. In a non-stationary climate scenario, the exceedance probabilities change with time, and this is also considered. Given a known rate of return on investment, the differentials in the rates of return (between Coastal and inland property investments) are subsequently used to determine the efficient position of the setback line. The results are presented within a GIS framework to effectively feed into the Coastal land use planning process. We demonstrate the framework by applying it to using real data (both physical and economic) for our subject site, Narrabeen Beach in Sydney.