Estimating Flood Frequency and Average Annual Damage

Beard, Leo R.

doi:10.1061/(asce)0733-9496(1997)123:2(84)

Cited by 19 publications

(8 citation statements)

References 5 publications

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“…Special estimators have been developed to compute design events that on average are exceeded with the specified probability, and have the anticipated risk of being exceeded (Beard 1960(Beard , 1997Rosbjerg 1989, 1991a, b;Stedinger 1997;Rosbjerg and Madsen 1998).…”

Section: ð6:62þmentioning

confidence: 99%

An Introduction to Probability, Statistics, and Uncertainty

Loucks

Beek

2017

Water Resource Systems Planning and Management

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Section: ð6:62þmentioning

confidence: 99%

An Introduction to Probability, Statistics, and Uncertainty

Loucks

Beek

2017

Water Resource Systems Planning and Management

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“…The simplicity of Eq. (3) belies the potential complexity of the underlying calculations in practice, which have been extensively explored elsewhere (Beard, 1997;Dawson and Hall, 2006;Stedinger, 1997). In order to estimate flood risks it is necessary to be able to:…”

Section: Formal Decision Problem Applied To Flood Risk Managementmentioning

confidence: 99%

“…Other situations are more problematic though it is usually possible to estimate conservative bounds on joint probability distributions (Ferson et al, 2004). (5) Propagate uncertainties through to outputs of interest Uncertainty propagation involves calculating the uncertainty distribution of one or more outputs of a model, given the quantified uncertainties on the inputs. In this analysis the key output variables of interest are flood risk indicators, costs, and specified environmental impacts.…”

Section: (4) Construct Appropriate Functions Quantifying Uncertaintiesmentioning

confidence: 99%

A framework for uncertainty analysis in flood risk management decisions

Hall¹,

Solomatine

2008

International Journal of River Basin Management

179

124

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Modern flood risk management involves responding sustainably to flood risk with portfolios of structural and non-structural measures. Under these circumstances of multi-attribute choice between portfolios of options, the motivation for uncertainty analysis becomes more compelling than ever. Uncertainty analysis is required in order to understand the implications for decision makers of limited data, model uncertainties, changes in the flooding system over the long term, incommensurate scales of appraisal and potentially conflicting decision objectives. In recognition of the importance of uncertainty analysis as an integral aspect of sustainable flood risk management, a new framework for uncertainty analysis within flood risk management decisions has been established. The proliferation of methods for uncertainty analysis can be placed within the coherent framework. As well as estimating the amount of uncertainty associated with key decision variables, the framework supports the decision making process by identifying the most influential sources of uncertainty, and the implications of uncertainty for the preference ordering between options. The challenges posed by severe uncertainty about the potential for long term changes in the flooding system are discussed and robustness analysis is advocated in response to these uncertainties.

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“…Using structural and nonstructural options as common ways for flood damage reduction have been reported by many investigators including Wood et al (1985) and Lund (2002). The effectiveness of structural options on floodplain management (Wood et al 1985;Lind 1967;Correia et al 1999a, b) and the assignment of probabilities in an economic evaluation of flood damages (Arnell 1989;Beard 1997;Goldman 1997;Stedinger 1997) have long been recognized. But only a few cases are reported which include probability assignments to integrate flood control options (Imani 2006), including land use changes.…”

Section: Introductionmentioning

confidence: 99%

Development of Optimization Schemes for Floodplain Management; A Case Study

Karamouz

Abesi

Moridi

et al. 2008

Water Resour Manage

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In this paper, two optimization models are presented. The first model is developed to determine economical combination of permanent and emergency flood control options and the second one is used to determine the optimal crop pattern along a river based on the assigned flood control options by the first optimization model. The optimal combination of flood protection options is determined to minimize flood damages and construction cost of flood control options along the river using the genetic algorithm (GA) optimization model. In order to consider the effects of flood control options on hydraulic characteristics of flow, two hydrological routing models for the reservoir and the river are coupled with the optimization model. Discharge-elevation and elevation-damage curves obtained based on separate hydraulic simulations of the river are used for flood damage calculations in the optimization model. The parameters of a hydrologic river routing model are also calibrated using the developed hydraulic model results. The proposed model is applied to the Kajoo river in the south-eastern part of Iran. The results demonstrate an economical integration of permanent and emergency flood control options along the river which include minimum expected value of damages related to floods with different return periods and construction cost of flood control options. Finally the resulting protection scheme is used for land use planning through identifying the optimal crop mix along the river. In this approach, the objective function of M. Karamouz et al. the optimization model is an economic function with a probabilistic framework to maximize the net benefit of agricultural activities. The study exhibits the importance of floodplain management and land use planning to achieve the development goals in the river basins.

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Estimating Flood Frequency and Average Annual Damage

Cited by 19 publications

References 5 publications

An Introduction to Probability, Statistics, and Uncertainty

An Introduction to Probability, Statistics, and Uncertainty

A framework for uncertainty analysis in flood risk management decisions

Development of Optimization Schemes for Floodplain Management; A Case Study

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