Dynamic computing resource allocation in online flood monitoring and prediction

Kuchař, Štěpán; Podhoranyi, Michal; Vavrik, Radim; Portero, Antoni

doi:10.1088/1755-1315/39/1/012061

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Therefore, realtime hazard maps are delivered to decision makers in 70 min. A faster runtime can be ensured by using a simple model structure (Leandro et al, 2014) and/or high-performance computing (Kuchar et al, 2015). In the absence of such infrastructures or with a very large catchment size, HD models can be replaced with alternatives, such as terrain-based models (Zheng et al, 2018) and satellite images (Voigt et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

Building hazard maps with differentiated risk perception for flood impact assessment

Bhola

Leandro

Disse

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. In operational flood risk management, a single best model is used to assess the impact of flooding, which might misrepresent uncertainties in the modelling process. We have used quantified uncertainties in flood forecasting to generate flood hazard maps that were combined based on different exceedance probability scenarios. The purpose is to differentiate the impacts of flooding depending on the building use, enabling, therefore, more flexibility for stakeholders' variable risk perception profiles. The aim of the study is thus to develop a novel methodology that uses a multi-model combination of flood forecasting models to generate flood hazard maps with differentiated exceedance probability. These maps take into account uncertainties stemming from the rainfall–runoff generation process and could be used by decision makers for a variety of purposes in which the building use plays a significant role, e.g. flood impact assessment, spatial planning, early warning and emergency planning.

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Section: Discussionmentioning

confidence: 99%

Building hazard maps with differentiated risk perception for flood impact assessment

Bhola

Leandro

Disse

2020

Nat. Hazards Earth Syst. Sci.

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“…computing (Kuchar et al, 2015). In the absence of such infrastructures or a very large catchment size, HD models can be replaced with alternatives, such as terrain-based models (Zheng et al, 2018) and satellite images (Voigt et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

Hazard maps with differentiated exceedance probability for flood impact assessment

Bhola

Leandro

Disse

2019

Preprint

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Abstract. In operational flood risk management, a single best-model is used to assess the impact of flooding, which might misrepresent uncertainties in the modelling process. We have used quantified uncertainties in flood forecasting to generate flood hazards maps that were combined based on exceedance probability scenarios. The purpose is to differentiate the impact of flooding depending on the building use. The aim of the study is thus to develop a novel methodology that uses a multi-model combination of flood forecasting models to generate flood hazard maps with differentiated exceedance probability. These maps take into account uncertainties steaming from the rainfall-runoff generation process and could be used by decision-makers for a variety of purposes in which the building use plays a significant role, e.g. flood impact assessment, spatial planning, early warning and emergency planning.

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“…The first application under study is part of the FLOREON+ framework, developed by IT4I [21]. The application is used to simplify the process of disaster management and increase its operability and effectiveness.…”

Section: A Disaster and Flood Management Simulationmentioning

confidence: 99%

HARPA: Tackling physically induced performance variability

Zompakis¹,

Noltsis²,

Ndreu

et al. 2017

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2017

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Continuously increasing application demands on both High Performance Computing (HPC) and Embedded Systems (ES) are driving the IC manufacturing industry on an everlasting scaling of devices in silicon. Nevertheless, integration and miniaturization of transistors comes with an important and nonnegligible trade-off: time-zero and time-dependent performance variability. Increasing guard-bands to battle variability is not scalable, since worst-case design margins are prohibitive for downscaled technology nodes. This paper discusses the FP7-612069-HARPA project of the European Commission which aims to enable next-generation embedded and high-performance heterogeneous many-cores to cost-effectively confront variations by providing Dependable-Performance: correct functionality and timing guarantees throughout the expected lifetime of a platform under thermal, power, and energy constraints. The HARPA novelty is in seeking synergies in techniques that have been considered virtually exclusively in the ES or HPC domains (worstcase guaranteed partly proactive techniques in embedded, and dynamic best-effort reactive techniques in high-performance).

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Dynamic computing resource allocation in online flood monitoring and prediction

Cited by 4 publications

References 12 publications

Building hazard maps with differentiated risk perception for flood impact assessment

Building hazard maps with differentiated risk perception for flood impact assessment

Hazard maps with differentiated exceedance probability for flood impact assessment

HARPA: Tackling physically induced performance variability

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