Information Theoretic Portfolio Decision Model for Designing Optimal Flood Control Strategies

The increasing impact of flooding at the global scale urges the need for developing more effective flood management strategies to guarantee a sustainable urban development and planning. Lessons learned from past and recent catastrophes underline the importance of avoiding local point-scale planning exclusively, but characterizing large scale basic-wide approaches for systemic flood risk management. The increased complexity of river basin management due to the multiplicity of actors, and social, environmental, and economical factors are challenging floodplain managers to provide new solutions. Flood management cannot be treated in deterministic terms and decision factors cannot be treated separately without a quantitative based approach that allows transparent and rigorous decisions.

Here we present a coupled portfolio decision analytical and information theoretic risk model for the maximization of the ecosystem value at the basin scale. Different flood management strategies, represented by spatial combination of flood control structures (FCS) are explored. The portfolio decision analytical model calculates the ecosystem value determined by all feasible combinations of FCS where the value is determined by the payoff that each combination carries to the ecosystem in terms of social, environmental, and economical returns. A multi-criteria decision analytical model evaluates the benefits of all FCS portfolios on assets at the basin scale weighted by stakeholder preferences for assets and criteria. The criteria are evaluated by means of the complementary of the expected flooded area. The risk mapping model is based on a maximum entropy model (MaxEnt) that predicts the risk of floods and the most important drivers for all FCS plans. A stochastic optimization algorithm maximizes the ecosystem value constrained to the budget available calculated as number of FCS. Pareto frontiers provide the optimal FCS plan for any budget level. The proposed model is tested on the 17,000 km^2 Tevere river basin that is the third largest and possibly one the most complex basins in Italy because of the number and magnitude of interactions among the socio-ecological actors.

The coupled portfolio-flood prediction model allows stakeholders the optimal identification of optimal FCS strategies in river basins for a comprehensive evaluation of flood effects and future landscape panning. Sustainable management of river basins considering social, environmental, and economical factors is currently lacking due to the predominance of reductionist and local economical risk approaches despite based on physical based models. The presented model embraces a systemic computational sustainability paradigm that allows decision makers the design of ecosystem management solutions also considering stakeholder preferences.

Authors: 
Matteo Convertino and Fernando Nardi
Room: 
6
Date: 
Tuesday, September 25, 2018 - 17:00 to 17:15

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