Modeling for Managing Food-Energy-Water-Social-Environmental—NEXUS Security: Novel Systems’ Analysis Approaches

Zagorodny, A., Bogdanov, V., Ermolieva, T., & Komendantova, N. ORCID: https://orcid.org/0000-0003-2568-6179 (2024). Modeling for Managing Food-Energy-Water-Social-Environmental—NEXUS Security: Novel Systems’ Analysis Approaches. In: Nexus of Sustainability. Eds. Zagrorodny, A., Bogdanov, V., & Zaporozhets, A., pp. 1-32 Springer. ISBN 978-3-031-66764-0 10.1007/978-3-031-66764-0_1.

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Abstract

The aim of the chapter is to introduce and discuss novel systems’ analysis models and methodologies being developed within a joint project between National Academy of Science, Ukraine, and International Institute for Applied Systems Analysis—“Integrated modeling for robust management of food-energy-water-social-environmental (FEWSE) nexus security and sustainable development”. These approaches enable science-based support of policies providing coherent strategic coordination and regulations among food, energy, water, social sectors, accounting for complex linkages and differences in spatial and temporal scales between agriculture, energy and water security, potential systemic risks, and new feasible policies at various levels. Systemic risks challenge traditional risk assessment and management approaches. These risks are shaped by systemic interactions, risk exposures and decisions of various agents. The paper discusses the need for the two-stage stochastic optimization models enabling to design robust portfolios of precautionary ex-ante strategic and adaptive ex-post operational decisions making the interdependent systems flexible and robust with respect to risks of all kinds. Thus often, detailed sectoral and regional models have been used to independently plan the developments of respective sectors and regions. However, solutions that are optimal for a sub-system (a sector, a region, selected sectors/regions) may turn out to be infeasible for the entire system. The paper presents new approaches based on the linkage of detailed distributed models of subsystems (e.g., sectoral and regional models) under joint resource constraints thus allowing for truly integrative decision support through optimal and robust solutions across sectors and regions. The linkage solution procedures are based on the parallel solving of equivalent nonsmooth optimization models following a simple iterative stochastic quasigradients (subgradient) algorithm. The procedures can be considered as robust machine learning algorithms, namely, as a general endogenous reinforced learning problem of how software agents (models) make decisions in order to maximize the cumulative reward (total welfare). Based on novel ideas of systems’ linkage under asymmetric information and other uncertainties, we discuss nested strategic-operational and local–global welfare models which are used in combination with, in general, non-Bayesian probabilistic downscaling procedures for analyzing and managing systemic interdependencies and risks. Quantile-based indicators are used to cope with new types of endogenous risks and extreme events generated by the decisions of various stakeholders. For the long-term sustainable functioning of FEWSE systems, robust policies comprise both interdependent strategic long-term (anticipative, ex-ante) decisions and short-term (adaptive, ex-post) decisions (adjustments). The methodologies and models are illustrated with relevant case studies.

Item Type:	Book Section
Research Programs:	Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Cooperation and Transformative Governance (CAT) Biodiversity and Natural Resources (BNR) Biodiversity and Natural Resources (BNR) > Integrated Biosphere Futures (IBF)
Depositing User:	Luke Kirwan
Date Deposited:	28 Aug 2024 10:47
Last Modified:	28 Aug 2024 10:47
URI:	https://pure.iiasa.ac.at/19961

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