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Information-theoretic Portfolio Decision Model for Optimal Flood Management

Matteo Convertino, Antonio Annis and Fernando Nardi

No k5aut, EarthArXiv from Center for Open Science

Abstract: The increasing impact of flooding urges more effective flood management strategies to guarantee sustainable ecosystem development. Recent catastrophes underline the importance of avoiding local flood management, but characterizing large scale basin wide approaches for systemic flood risk management. Here we introduce an information-theoretic Portfolio Decision Model (iPDM) for the optimization of a systemic ecosystem value at the basin scale by evaluating all potential flood risk mitigation plans. iPDM calculates the ecosystem value predicted by all feasible combinations of flood control structures (FCS) considering environmental, social and economical asset criteria. A multi-criteria decision analytical model evaluates the benefits of all FCS portfolios at the basin scale weighted by stakeholder preferences for assets' criteria as ecosystem services. The risk model is based on a maximum entropy model (MaxEnt) that predicts the flood susceptibility, the risk of floods based on the exceedance probability distribution, and its most important drivers. Information theoretic global sensitivity and uncertainty analysis is used to select the simplest and most accurate model based on a flood return period. A stochastic optimization algorithm optimizes the ecosystem value constrained to the budget available and provides Pareto frontiers of optimal FCS plans for any budget level. Pareto optimal solutions maximize FCS diversity and minimize the criticality of floods manifested by the scaling exponent of the Pareto distribution of flood size that links management and hydrogeomorphological patterns. The proposed model is tested on the 17,000 $km^2$ Tiber river basin in Italy. iPDM allows stakeholders to identify optimal FCS plans in river basins for a comprehensive evaluation of flood effects under future ecosystem trajectories.

New Economics Papers: this item is included in nep-env and nep-rmg
Date: 2019-06-27
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DOI: 10.31219/

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