Hierarchical decision making for flood risk reduction

Custer, Rocco; Nishijima, K.

doi:10.1201/b16387-704

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Sci. protection (Custer and Nishijima, 2013) and are particularly robust with respect to changes in flood frequency, an aspect that is very desirable in protection planning (Baker et al, 2005;Merz et al, 2014). Additionally, heightening of dikes and walls is reaching a static and aesthetic limit in Rosenheim and thus if a polder can provide at least some of the necessary protection, it should be made use of.…”

Section: Risk Assessment and Planning Recommendationmentioning

confidence: 99%

Risk-based flood protection planning under climate change and modelling uncertainty: a pre-alpine case study

Dittes¹,

Kaiser²,

Špačková³

et al. 2017

Preprint

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Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g. for delaying planning or including a safety margin? Is it 10 sufficient to follow a protection criterion (e.g. to protect from the 100-year flood) or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes), costs and damages? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, 15 cost and climate, the recommendation is robustly for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over a planning of flood protection to a prescribed return period. IntroductionTechnical flood protection measures have long life times of, on average, 80 years (Bund / Länder-Arbeitsgemeinschaft Wasser, 20 2005). The uncertainty over such a long planning horizon is large, both in terms of climatic and socio-economic development.It is thus not trivial for planning authorities to take decisions on flood protection planning that are economical while not leading to excessive losses or high adjustment costs. I, it is important to consider costs -in construction, adjustment and flood damages -over the entire measure life time.Ideally, the planning of flood protection infrastructure is performed through a risk-based approach. Thereby, potential 25 damages are considered in the decision-making process. Considering that the annual maximum discharge is the main driver for flood damages, the annual flood risk in year , t , is defined as (e.g. Merz et al., 2010a) Nat. Hazards Earth Syst. Sci. Discuss., https://doi

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Section: Risk Assessment and Planning Recommendationmentioning

confidence: 99%

Risk-based flood protection planning under climate change and modelling uncertainty: a pre-alpine case study

Dittes¹,

Kaiser²,

Špačková³

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…by implementing a protection system that consists of several different, possibly spatially distributed, measures. That leads to more robust protection in which floods in excess of the design 10 flood do not quickly lead to very high damages or even failure (Blöschl et al, 2013b;Custer and Nishijima, 2013).…”

Section: Introductionmentioning

confidence: 99%

Climate uncertainty in flood protection planning

Dittes

Špačková

Schoppa

et al. 2017

Preprint

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Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure life time, which is typically many decades long. Flood protection requirements should account for multiple future 10 uncertain factors: socio-economic, e.g. whether the population and with it the damage potential grows or falls; technological, e.g. possible advancements in flood protection; and climatic, e.g. whether extreme discharge will become more frequent or not. We focus here on the planning implications of the uncertainty in extreme discharge. We account for the sequential nature of the decision process, in which the adequacy of the protection is regularly revised in the future based on the discharges that have been observed by that point and that reduce uncertainty. For planning purposes, we categorize uncertainties as either 15 'visible', if they can be quantified from available catchment data, or 'hidden', if they cannot be quantified from catchment data and must be estimated, e.g. from literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g. through projections, historic record) is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-20 alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection.

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Managing uncertainty in flood protection planning with climate projections

Dittes

Špačková

Schoppa

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure lifetime, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socioeconomic, e.g., whether the population and with it the damage potential grows or falls; technological, e.g., possible advancements in flood protection; and climatic, e.g., whether extreme discharge will become more frequent or not. This paper focuses on climatic uncertainty. Specifically, we devise methodology to account for uncertainty associated with the use of discharge projections, ultimately leading to planning implications. For planning purposes, we categorize uncertainties as either “visible”, if they can be quantified from available catchment data, or “hidden”, if they cannot be quantified from catchment data and must be estimated, e.g., from the literature. It is vital to consider the “hidden uncertainty”, since in practical applications only a limited amount of information (e.g., a finite projection ensemble) is available. We use a Bayesian approach to quantify the “visible uncertainties” and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection. The results show that hidden uncertainty ought to be considered in planning, but the larger the uncertainty already present, the smaller the impact of adding more. The recommended planning is robust to moderate changes in uncertainty as well as in trend. In contrast, planning without consideration of bias and dependencies in and between uncertainty components leads to strongly suboptimal planning recommendations.

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Hierarchical decision making for flood risk reduction

Cited by 4 publications

References 8 publications

Risk-based flood protection planning under climate change and modelling uncertainty: a pre-alpine case study

Risk-based flood protection planning under climate change and modelling uncertainty: a pre-alpine case study

Climate uncertainty in flood protection planning

Managing uncertainty in flood protection planning with climate projections

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