Introducing ProMaIDes: A State-of-the Science Flood Risk Management Tool

Bachmann, Daniel; Schotten, Roman; Ghomash, Shahin Khosh Bin

doi:10.5194/egusphere-egu22-2696

Cited by 5 publications

(6 citation statements)

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“…The binary state of the CI point and polygon elements is one example of inherent limitations. It is either fully functional or disrupted, as explained in Schotten and Bachmann [53]. This intrinsic assumption and also the extrinsic model assumptions mentioned above add a level of uncertainty to the model.…”

Section: Discussionmentioning

confidence: 98%

“…This software enables the flood risk analysis of other flood consequences categories in parallel such as affected and endangered population or economic damage [52]. The PROMAIDES software framework is supported by a GIS system, a PostgreSQL database and plugins for pre-and postprocessing [53]. Documentation supports the model generation and analysis of the CI network modelling approach [54].…”

Section: Elementmentioning

confidence: 99%

“…The total size of all the catchments is roughly 360 km 2 , and the area is predominantly urban. For the hydraulic analysis and the analysis of consequence, the PROMAIDES framework is used [53]. Hydraulic calculations are made with a combined 1D-2D approach.…”

Section: Case Study In Accra and CI Integration Into Flood Risk Manag...mentioning

confidence: 99%

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Integrating Critical Infrastructure Networks into Flood Risk Management

Schotten

Bachmann

2023

Sustainability

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Critical infrastructure (CI) networks are essential for the survival and functionality of society and the economy. Disruptions to CI services and the cascading effects of these disruptions are not currently included in flood risk management (FRM). The work presented in this study integrates CI into every step of FRM, including flood risk analysis, risk mitigation and risk communication. A CI network modelling technique enables the flood consequences for CI to be quantified as part of the flood risk analysis. The CI consequences derived from this analysis include spatial overviews and the temporal succession of CI disruptions. The number of affected CI end-users and the duration of the disruption are arranged in a risk matrix and in a decision-making matrix. Thus, the total flood risk is extended with CI consequences. By integrating CI and CI network characteristics into the flood risk assessment and the mitigation steps, a wider range of measures for action can be considered. Additionally, the continuous participation of CI operators is introduced as beneficial for every step of the FRM. A case study in Accra, Ghana proves the benefits of CI integration for all FRM steps. During participatory CI stakeholder engagements for this study six CI sectors were identified for the assembly of the CI network. The backbone of the analysis is a multisectoral, layered CI network model with 433 point elements, 1216 connector elements and 486 polygon elements.

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Section: Discussionmentioning

confidence: 98%

Section: Elementmentioning

confidence: 99%

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Integrating Critical Infrastructure Networks into Flood Risk Management

Schotten

Bachmann

2023

Sustainability

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“…The catchment covers about 271 km 2 and is located close to the sea (see Figure 5). The CI network model is part of an existing modelling chain that includes a hydraulic model and flood consequence models for economic damage based on Huizinga et al (2017) and affected and endangered persons based on Jonkman (2007), for an integrated flood risk analysis (Bachmann et al, 2021). For the hydraulic model, a DEM with a 30 m resolution was used and the floodplains were represented by 414,000 25 Â 25 m 2 raster cells.…”

Section: Proof Of Concept In Odaw Catchment Accra Ghanamentioning

confidence: 99%

Critical infrastructure network modelling for flood risk analyses: Approach and proof of concept in Accra, Ghana

Schotten

Bachmann

2023

J Flood Risk Management

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In flood risk analysis, it is state‐of‐the‐art to determine the direct consequences of flooding for assets and people. Flooding also disrupts critical infrastructure (CI) networks, which are vital in modern society. Cascading effects in a CI network can exceed the hydrological catchment boundaries. The effects of directly impacted CI cascade to other infrastructures, which are thus indirectly affected by a flood. A robust modelling approach of CI networks is a basis for including these effects in flood risk analysis. One challenge is to balance the simplicity of the modelling approach, the reproduction of a CI network's complexity and the decisions made based on potential model outputs. In this article, a topology‐based modelling approach of CI networks for catchment‐wide flood risk analyses is proposed. The basic model elements are points, connectors and polygons, which are utilised to represent a multisectoral and layered CI network. The newly defined approach is implemented as CI network module to the state‐of‐the‐art flood risk analysis framework ProMaIDes. It analyses the CI's direct and cascading impacts as well as the indirect disruption of CI services triggered by flooding scenarios. It quantifies the consequences by determining the number of disrupted CI users or the disruption time. A proof of concept in Accra, Ghana demonstrates the method's capabilities.

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“…In a previous study, distributions of selected soil mechanical parameters were estimated by transforming the results from classification tests [38]. In combination with comprehensive literature research [13,31,[39][40][41][42][43][44][45][46][47][48][49], as well as on experience from the development of the calculation program used [50,51], this study is based on the distributions given in Table 1. For the analysis of the probability of failure (cf.…”

Section: Probabilistic Input Parametersmentioning

confidence: 99%

Geometric and Material Variability of the Probability of Landward Slope Failure for Homogeneous River Levees

Schwiersch

Stamm

2022

Sustainability

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Holistic flood risk management (FRM) aims at minimizing the flood risk (FR) for an entire river basin. To this end, the probability of flooding and its consequences must also be taken into account in the planning of flood risk management measures. If the FR is to be limited by the flooding probability value (e.g., by changing the structural reliability), knowledge of the variability of the limit state is required. As an example, this study quantifies for the first time the variability of the probability of a landside slope failure on homogeneous river levees, using the Monte Carlo simulation. In the slip circle method developed by Krey that is used for this purpose, four geometric and six material input parameters are included as being uncertain, of which four emerge in the result as being relevant influencing variables of the failure probability. These analyses extend our understanding of landward slope failure by the variability of the limit state; the results allow a targeted adjustment of the local failure probability to limit the flood risk. In the future, the methodology presented is to be supplemented by the integration of parameter dependencies and, once in use, expanded to include structured cross-sections or additional failure mechanisms.

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Introducing ProMaIDes: A State-of-the Science Flood Risk Management Tool

Cited by 5 publications

References 0 publications

Integrating Critical Infrastructure Networks into Flood Risk Management

Integrating Critical Infrastructure Networks into Flood Risk Management

Critical infrastructure network modelling for flood risk analyses: Approach and proof of concept in Accra, Ghana

Geometric and Material Variability of the Probability of Landward Slope Failure for Homogeneous River Levees

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