Integrated Modelling for Catastrophic and Systemic Risks Management: Robust Coherent Balance Between Ex-Ante and Ex-Post Measures

The impacts of climate changes are expected to increase catalyzed by the growing complexity of systemic interdependencies, introduction of new policies and technologies in risk prone areas, growing population and demands, increasing frequency and severity of floods, hurricanes, windstorms, droughts, landslides, prolonged heatwaves. Catastrophic dependent systemic losses have analytically intractable multidimensional probability distributions dependent on the exogenous shocks, activities of economic sectors, interactions among goals and constraints of the involved actors and systems, environmental standards, critical infrastructure in place, feasible structural and financial measures, investment potentials, etc. We argue for the design of proper integrated Decision Support Systems (DSSs) and integrated catastrophe analysis and management modeling approaches, the development of which is being supported in frames of the EU funded PARATUS project and the IIASA and NASU joint projects. We discuss several important aspects and components of the DSSs. These include introduction of safety and security constraints of the involved agents, the necessity for robust interdependent ex-ante and ex-post strategic and operational structural and financial measures, the need for stochastic catastrophe models (scenario generators), and proper stochastic optimization solution procedures to provide the decision-support regarding proper systemic ex-ante and ex-post risk management options. We argue that in risk-prone areas, because of significant interdependencies among catastrophe losses across different locations, the demand for a particular measure (structural or financial) cannot be separated from the demand for other risk reduction and risk transfer measures. The diversion of capital from ex-post compensations to ex-ante investments into structural loss reduction measures may essentially reduce dependencies among losses and, hence, improve the resilience, stabilize loss compensation programs, and reduce the demand for risk sharing on national and international levels.