Flood Risk, Uncertainty, and Scientific Information for Decision Making: Lessons from an Interdisciplinary Project

Morss, Rebecca E.; Wilhelmi, Olga; Downton, Mary W.; Gruntfest, Eve

doi:10.1175/bams-86-11-1593

Cited by 285 publications

(210 citation statements)

References 26 publications

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“…Nowadays, for example, weather forecasts out to 10 days and beyond provide the basis for decisionmaking (e.g. Morss et al, 2005). Moreover, analysis or reanalysis data (Kalnay et al, 1996;Uppala et al, 2005), which to varying degrees (depending on the parameters and the region being considered) are based on a first guess (i.e.…”

Section: Introductionmentioning

confidence: 99%

Performance of the ECMWF forecasting system in the Arctic during winter

Jung

Leutbecher

2007

Quart J Royal Meteoro Soc

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ABSTRACT:The performance of the ECMWF forecasting system in the Arctic during boreal winter is investigated. A comparison between different analysis products suggests that synoptic-scale features in the Arctic are relatively well represented by state-of-the-art analysis systems. Furthermore, it is shown that the improvement in deterministic forecast error in the Arctic since the early 1980s closely follows that reported in previous studies for the Northern Hemisphere as a whole. One of the biggest 'jumps' in deterministic forecast skill, both in the troposphere and in the stratosphere, occurred in autumn 2000 when the high-resolution deterministic system (T L 511, about 40 km) was introduced at ECMWF. Our results suggest that 10-day forecasts of the stratospheric circulation have been very skilful, particularly since the introduction of the high-resolution system. Adjoint computations reveal pronounced flow-dependence of the sensitivity of short-range forecast error to initial perturbations at high northern latitudes (north of 70°N); this highlights the importance of using ensemble prediction systems (EPSs) for weather forecasting in the Arctic. Verification of the ECMWF EPS in the Arctic reveals substantial improvements in probabilistic predictive skill since the mid-1990s. The most pronounced increase in probabilistic forecast skill, particularly on synoptic scales, occurred in autumn 2000 when the high-resolution EPS (T L 255, about 80 km) was introduced. Finally, it is shown that the observed stratosphere-troposphere link ('downward propagation' of stratospheric anomalies), which constitutes a potential source of extended-range predictability in high latitudes, is realistically represented in seasonal integrations with the ECMWF model -even at the relatively low horizontal resolution of T L 95 (about 180 km).

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Section: Introductionmentioning

confidence: 99%

Performance of the ECMWF forecasting system in the Arctic during winter

Jung

Leutbecher

2007

Quart J Royal Meteoro Soc

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“…Scientific information about hydrological risk is only one of many components which contribute to decisions concerning flood protection. If the scientific uncertainties are emphasized too much it complicates the already difficult process of decision making (Morss, 2005). Better and more complete information does not necessarily lead to better policies; very complex information can affect the decision making process negatively.…”

Section: Integration Of Fuzzy Numbers In Multiple Criteria Decision Mmentioning

confidence: 99%

Planning of technical flood retention measures in large river basins under consideration of imprecise probabilities of multivariate hydrological loads

Nijssen

Schumann

Pahlow

et al. 2009

Nat. Hazards Earth Syst. Sci.

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Abstract. As a result of the severe floods in Europe at the turn of the millennium, the ongoing shift from safety oriented flood control towards flood risk management was accelerated. With regard to technical flood control measures it became evident that the effectiveness of flood control measures depends on many different factors, which cannot be considered with single events used as design floods for planning. The multivariate characteristics of the hydrological loads have to be considered to evaluate complex flood control measures. The effectiveness of spatially distributed flood control systems differs for varying flood events. Event-based characteristics such as the spatial distribution of precipitation, the shape and volume of the resulting flood waves or the interactions of flood waves with the technical elements, e.g. reservoirs and flood polders, result in varying efficiency of these systems. Considering these aspects a flood control system should be evaluated with a broad range of hydrological loads to get a realistic assessment of its performance under different conditions. The consideration of this variety in flood control planning design was one particular aim of this study. Hydrological loads were described by multiple criteria. A statistical characterization of these criteria is difficult, since the data base is often not sufficient to analyze the variety of possible events. Hydrological simulations were used to solve this problem. Here a deterministic-stochastic flood generator was developed and applied to produce a large quantity of flood events which can be used as scenarios of possible hydrological loads. However, these simulations imply many uncertainties. The results will be biased by the basic assumptions of the modeling tools. In flood control planning probabilities are applied to characterize uncertain-ties. The probabilities of the simulated flood scenarios differ from probabilities which would be derived from long time series. With regard to these known unknowns the bias of the simulations was considered by imprecise probabilities. Probabilities, derived from measured flood data were combined with probabilities which were estimated from long simulated series. To consider imprecise probabilities, fuzzy sets were used to distinguish the results between more or less possible design floods. The need for such a differentiated view on the performance of flood protection systems is demonstrated by a case study.

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“…hydraulic engineers, hydrologists and modelers) and the use of that expert knowledge by practitioners (i.e. policy analysts or political decision-makers) (Morss, Wilhelmi et al 2005;Faulkner, Parker et al 2007;McCarthy, Tunstall et al 2007;Demeritt, Nobert et al 2010). Flood policy decision making can be characterized as a complex and uncertain problem environment due to its complex hydrodynamic processes, the interrelation with socio-economic issues and the involvement of many different stakeholders (Downton, Morss et al 2005;Morss, Wilhelmi et al 2005;Timmerman, Beinat et al 2010).…”

Section: The Case Of Flood Policy Decision-makingmentioning

confidence: 99%

“…policy analysts or political decision-makers) (Morss, Wilhelmi et al 2005;Faulkner, Parker et al 2007;McCarthy, Tunstall et al 2007;Demeritt, Nobert et al 2010). Flood policy decision making can be characterized as a complex and uncertain problem environment due to its complex hydrodynamic processes, the interrelation with socio-economic issues and the involvement of many different stakeholders (Downton, Morss et al 2005;Morss, Wilhelmi et al 2005;Timmerman, Beinat et al 2010). Expert knowledge, including the outputs of flood simulation modelling, can therefore be very helpful in the production of knowledge relied upon in the management of flood risks (Porter and Demeritt 2012;Landström and Whatmore 2014).…”

Section: The Case Of Flood Policy Decision-makingmentioning

confidence: 99%

“…For example, flood depth predictions can be provided at a spatial resolution of 0,25 m 2 and can be visualized in various formats, including realistic 3D-visualizations comparable with those used in flight simulators (Schuurmans, Leskens et al 2010) Despite the advantages that flood simulation modelling may provide, experiences have proven that the information from these models is of limited use in flood disaster management. Morss et al (2005) show that practitioners of flood disaster management, operating under regulatory, institutional, political, resource, and other constraints, prioritize other concerns over more sophisticated model information about flood risk, particularly when they cannot readily see the feasibility or value of incorporating new or more detailed information from models. This lack of consideration of sophisticated model information, under circumstances of high time pressure, large consequences, high complexity and uncertainty, can be understood as a 'simplification strategy'.…”

Section: Introductionmentioning

confidence: 99%

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Interactive use of simulation models for collaborative knowledge construction

Leskens

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Flood Risk, Uncertainty, and Scientific Information for Decision Making: Lessons from an Interdisciplinary Project

Abstract: This essay discusses the complex ways in which scientific information and uncertainty can interact with societal decision making, and proposes a collaborative, integrated approach to societally useful scientific research.

Cited by 285 publications

References 26 publications

Performance of the ECMWF forecasting system in the Arctic during winter

Performance of the ECMWF forecasting system in the Arctic during winter

Planning of technical flood retention measures in large river basins under consideration of imprecise probabilities of multivariate hydrological loads

Interactive use of simulation models for collaborative knowledge construction

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