Flood Mitigation Measures under Forecast Uncertainty
Ensemble Streamflow Forecasting becomes a well-established technique in operational (flood) forecasting centers to assess forecast uncertainty. Currently, these forecasts are communicated to decision makers; however, taking decisions is still up to the subjective experience of the specific stakeholder. Due to the large amount of information in ensemble forecasts, this task is a major challenge in particular when time is limited during ongoing flood events.
There is a lack of objective methods to take qualified decisions under consideration of forecast uncertainty. Whereas stochastic optimization techniques based on ensemble forecasts are applied in other water management domains (e.g. for scheduling hydropower assets), they are so far not used in the scope of flood forecasting and early warning systems. One major reason is probably the conceptual difficulty to integrate binary decisions (“Evacuate a region or not”) or logical constraints (“Measure A excludes measure B”) into the decision-making under consideration of forecast uncertainty.
Doel van het project
This research will assess the application of several multi-stage stochastic and robust optimization approaches in combination with a mixed-logical optimization setup to model flood mitigation measures under forecast uncertainty. We will investigate the potential and applicability of these approaches to provide objective decision support to stakeholders in the flood management domain.
Ensemble Streamflow Forecasting becomes a well-established technique in operational (flood) forecasting centers to assess forecast uncertainty. Currently these forecasts are communicated to decision makers however taking decisions is still up to the subjective experience of the specific stakeholder. Due to the large amount of information in ensemble forecasts this task is a major challenge in particular when time is limited during ongoing flood events.There is a lack of objective methods to take qualified decisions under consideration of forecast uncertainty. Whereas stochastic optimization techniques based on ensemble forecasts are applied in other water management domains (e.g. for scheduling hydropower assets) they are so far not used in the scope of flood forecasting and early warning systems. One major reason is probably the conceptual difficulty to integrate binary decisions (“Evacuate a region or not”) or logical constraints (“Measure A excludes measure B”) into the decision-making under consideration of forecast uncertainty.
Year 1:1. Inventory of the need for decision support in the flood management domain in collaboration with several stakeholders and the definition of a number of representative academic test cases2. Inventory of state-of-the-art approaches in the field of stochastic and robust optimization and the representation of mixed-logical systems as well as the design of a new conceptual framework to support water managers.3. Developing the right formulations of the flood mitigation models. Often optimization problems can be reformulated into equivalent problems that have (much) better properties e.g. with respect to convexity differentiability … A proper reformulation can drastically improve the performance of the optimization method.Year 2:4. Implementation of promising stochastic and robust optimization approaches covering the integration of ensemble forecasts (representing forecast uncertainty) with models of the hydrological system as well as flood mitigation measures and the related decision-making.5. Assessment of the feasibility of these approaches by evaluating its performance based on the academic test cases defined in activity 1Year 3:6. Conceptual and technical refinement of a selected approach and its application to more integrated and larger-scale problem setups7. Discussion of the future deployment and dissemination of the novel techniques for practical applications in collaboration with several stakeholders
The quantification of forecast uncertainty by probabilistic ensemble forecasts and further processing is implemented in state-of-the-art (flood) forecasting system and subject of ongoing research. Deltares contributes to the state-of-the-art research and supplies the technical platform for operational forecasting systems (oss.deltares.nl/web/delft-fews) of many national flood forecasting agencies. Till now operating staff uses ensemble forecasts in a subjective manner and no approach exists to derive objective decisions from these forecasts. The stochastic and robust short-term management of water resource systems is an ongoing research subject . Work focuses primarily on hydropower systems and the maximization of their benefits. Deltares contributes to this field in the context of the ongoing HYPROM project for the Bonneville Power Administration (USA) and CEMIG (Brazil) with a total hydropower portfolio of approximately 28 GW. Furthermore it currently executes consultancy projects in the order of 4M€ aiming at the implementation of production systems for short-term decision-making.The proposed project extends the scope of the existing research and development activities towards the following novel components:• Assessment of the applicability of stochastic and robust short-term optimization to the management of extreme events (novel approach for the related stakeholders)• Integration of probabilistic ensemble forecasts stochastic and robust optimization and mixed-logical systems to consider binary decisions and logical conditions into a conceptual framework including a proof-of-conceptThe combination of aspects above makes this research a high-risk and challenging subject.
General dissimilation activities of the consortium:
• Inception workshop for the consortium members and additional stakeholders at the beginning of the project, final workshop probably embedded into one of the conferences mentioned below
• 3 scientific publications in international, peer-reviewed journals and regular participation at scientific conferences (AGU, EGU HEPEX)
• For end users: presentation of results at i) the national and international (Delft-FEWS) users meeting for the flood forecasting community, the RTC-Tools optimization model course during the Delft Software Days, notifications on the webpages of Delft-FEWS and RTC-Tools
• Publications, software prototypes and test cases will be put online for download on oss.deltares.nl
Individual members of the consortium will conduct further dissemination activities in their communities:
• NZV within the regional water authorities in the Netherlands
• RWS within the federal administration and international partners
• N&S via their partners and clients
Alle partijen krijgen alle resultaten van het Project ter beschikking. De resultaten van de samenwerking kunnen breed verspreid worden. Partijen kunnen over deze resultaten vrijelijk publiceren. De resultaten zullen volledig openbaar beschikbaar zijn, met uitzondering van ter beschikking gestelde achtergrondkennis.
De informatie over dit project wordt kenbaar gemaakt via de website van de TKI Deltatechnologie (projectbeschrijving) en de projectwiki van Deltares (projectvoortgang en resultaten).
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