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River flood events have the potential to affect society adversely, in terms of fatalities and material damage. A precise estimation of these consequences is an essential task and a prerequisite in order to effectively cope with flooding. PRAMo is a probabilistic flood risk analysis model, which is able to describe and analyse the potential monetary costs of river flooding and therewith directly contribute to effective flood risk management.
Developed by alpS GmbH
Flood risk analysis usually addresses three question: (1) How do possible flood scenarios look like? (2) How likely is their occurrence? (3) What are the consequences? PRAMo is able to answer these questions and delivers information about the expected annual damage within a region. The model considers the spatially heterogeneous nature of flooding, direct damages of buildings and uses a multivariate algorithm for generation of synthetic events and thereby guarantees an estimation of damages.
See more information about this level and the TRL and SRL levels.
PRAMo is a software package that consists of three modules which interact fully automatically. The modules are: (1) a Hazard Module, (2) an Impact Module, and (3) a Risk Assessment Module. The above noted general questions about flood risk can be answered by means of these modules. PRAMo is a generic model which can be applied in any region, in which certain input data are available. These are: (i) terrain information, (ii) observed runoff time series, (iii) inundation maps, and (iv) building assets. The model reproduces a large data set of possible hazard scenarios, combines it with potential consequences and delivers information about the expected annual damages and damages associated a low probability of occurrence (e.g. 0.5% p.a.).
Limitations/conditions under which this innovation does not work or is less effective
The model is suited for risk analysis in meso- to macro scale study areas. In smaller domains, PRAMo cannot deliver an added value compared to commonly applied risk model. The reason therefore is, that the consideration of spatially heterogeneous flood events, which is one of the main features of PRAMo, is not relevant in small study areas.
Added value
Precise information about the possible costs of flooding are inevitable for effective flood management. Thus, the results of PRAMo could have added value for institutions involved in flood management, such as public authorities, insurance and reinsurance companies etc. The outcome of the model could be an essential component for a cost-benefit analysis of flood mitigation measures following the principles of fairness and equity.
River flood events have the potential to affect society adversely, in terms of fatalities and material damage. A precise estimation of these consequences is an essential task and a prerequisite in order to effectively cope with flooding. PRAMo is a probabilistic flood risk analysis model, which is able to describe and analyse the potential monetary costs of river flooding and therewith directly contribute to effective flood risk management.
Developed by alpS GmbH
Flood risk analysis usually addresses three question: (1) How do possible flood scenarios look like? (2) How likely is their occurrence? (3) What are the consequences? PRAMo is able to answer these questions and delivers information about the expected annual damage within a region. The model considers the spatially heterogeneous nature of flooding, direct damages of buildings and uses a multivariate algorithm for generation of synthetic events and thereby guarantees an estimation of damages.
The main components of the system have been tested separately, and an initial integration exercise has been conducted.
PRAMo is a software package that consists of three modules which interact fully automatically. The modules are: (1) a Hazard Module, (2) an Impact Module, and (3) a Risk Assessment Module. The above noted general questions about flood risk can be answered by means of these modules. PRAMo is a generic model which can be applied in any region, in which certain input data are available. These are: (i) terrain information, (ii) observed runoff time series, (iii) inundation maps, and (iv) building assets. The model reproduces a large data set of possible hazard scenarios, combines it with potential consequences and delivers information about the expected annual damages and damages associated a low probability of occurrence (e.g. 0.5% p.a.).
Limitations/conditions under which this innovation does not work or is less effective
The model is suited for risk analysis in meso- to macro scale study areas. In smaller domains, PRAMo cannot deliver an added value compared to commonly applied risk model. The reason therefore is, that the consideration of spatially heterogeneous flood events, which is one of the main features of PRAMo, is not relevant in small study areas.
Added value
Precise information about the possible costs of flooding are inevitable for effective flood management. Thus, the results of PRAMo could have added value for institutions involved in flood management, such as public authorities, insurance and reinsurance companies etc. The outcome of the model could be an essential component for a cost-benefit analysis of flood mitigation measures following the principles of fairness and equity.
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