The joint project “Integrated modeling for robust management of food-energy-water-land use nexus security and sustainable development” between National Academy of Sciences, Ukraine (NASU), and IIASA for the period from 2022 to 2026 is the continuation and the new stage of the joint NASU-IIASA project “Integrated robust management of food-energy-water-land-social nexus for sustainable development” completed in the period from 2017 to 2021 (IIASA Policy brief, 2017; Zagorodny et al., 2013, 2014, 2018, 2020). In the new research period, we address urgent problems of integrated modeling and policy analysis through models’ linkage and distributed optimization of disintegrated distributed food-water-energy-environmental models, precautionary and adaptive dealing with systemic risks and their implications for Food-Energy-Water-Environmental-Social (FEWES) systems security NEXUS management in Ukraine and globally.
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Dnieper Hydroelectric Station in Zaporizhia Oblast from “Hydroelectricity in Ukraine”
The NASU-IIASA research project is a long-term inter-disciplinary research partnership of IIASA and NASU’s seven leading institutes and two National Universities collaborating also with networks of national and international organizations, advisors, and policy makers. NASU Institutions participants of the project: Glushkov’s Institute of Cybernetics, Institute of General Energy, Institute of Economics and Forecasting, Institute of Theoretical Physics, Institute of Demography and Social Studies, Scientific Centre of Aerospace Research of the Earth, Taras Shevchenko National University of Kiev, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”.
The project aims at science-based support of policies providing coherent strategic coordination and regulations among food, energy, water sectors, accounting for complex linkages and differences in spatial and temporal scales between agriculture, energy, water, and environmental security, potential systemic risks and new feasible policies at a country level, taking into account interregional and international trades, global-local pollution, related risks, direct and indirect exchange of resources, etc. The main methodological goal of the projects is to develop further and implement novel systems analysis approaches focusing on problems of common interest for Ukraine, IIASA and globally, emerging in designing solutions for robust sustainable FEWES security nexus management, which cannot be solved by existing traditional approaches.
In the period from 2022 to 2026, novel systems analysis, Machine Learning and Artificial Intelligence approaches will be developed. They will rely on iterative stochastic quasigradient (SQG) procedures for nonsmooth optimization incorporating nested quantile-based robust systemic risks indicators and risk measures (Ermolieva et al., 2021; Ermoliev a,b,c 2009; Ermoliev and Hordijk, 2003; Ermoliev and von Winterfeldt (2013) and references therein).
The project will further develop and implement integrated modeling approaches for linking and optimization of distributed (decentralized) sectoral and regional models (Ermoliev et al., 2021), for joint planning of FEWES sectors under asymmetric information about the models. The development of appropriate downscaling and distributed models’ linkage methods under asymmetric information and systemic risks will enable sectoral and regional systems’ linkage and distributed systems optimization without revealing information about individual sub-models, i.e. in the presence of asymmetric information.
The propagation of direct and indirect impacts through FEWES systems will be investigated to identify potential thresholds and discontinuities in production-supply-demand chains leading to possible systemic failures, breaks of existing and creation of new chains in interdependent agriculture, energy, water systems. A set of feasible preventive and adaptive policies will be identified and analyzed within the existing regional, national (Ukrainian) integrated models and into global IIASA models (two-stage strategic-adaptive GLOBIOM, MESSAGE, WAT). The feasible policies can include the existing and possible new interregional and international supply-demand relations, energy and water supply technologies, production and processing technological chains, trade, insurance, subsidies, taxes, grain and water storages, Common Agricultural Policies, pollution and GHG emissions targets, renewables targets, direct and indirect (virtual) exchange of resources, e.g. pollution trading, virtual water trade. In contrast to traditional studies using different research principles, isolated (independent) models and data from diverse regions at different time intervals, this research aims at systemic view and multi-disciplinary multi-model approaches.
Key Methodological Challenges
- Novel approaches to robust management of the food-energy-water-land use (FEWL) nexus to account for complex linkages and differences in spatial and temporal scales between agriculture, energy, water systems, potential exogenously and endogenously generated collective systemic risks and new coherent feasible policies enabling FEWL nexus security;
- Iterative algorithms of non-smooth optimization converging to the socially optimal solution linking distributed sectorial models for food-energy-water-land security for an optimal allocation and management of scarce resources under asymmetric information and inherent uncertainties;
- Methods for linking global (GLOBIOM) with national models using iterative algorithms, for data harmonization and for robust non-parametric down-scaling;
- Decision supports systems (DSS) to inform decisions on energy-efficient technology investments under resource constraints and systemic risks;
- Integrated water resource management under risks and climate change;
- Robust solutions for agriculture and energy sector in Ukraine.
NASU is the National Member Organization representing Ukraine in IIASA. Ukraine’s membership in IIASA is centered around this project, whose current phase starts in 2022 succeeding the previous 2016-2021 and 2012-2016 activity on “Robust food, energy, water, and land management”.
Publications
Zagorodny, A.G., Ermoliev, Yu.N., Bogdanov, V.L., & Ermolieva, T., eds. (2020). Integrated modeling and management of Food-Energy-Water NEXUS for sustainable development. Kiev, Ukraine: Committee for Systems Analysis at Presidium of National Academy of Sciences of Ukraine — National Member Organization of Ukraine in International Institute for Applied Systems Analysis (IIASA). ISBN 978-966-02-9344-1
Zagorodny, A.G., Ermoliev, Y., Bogdanov, V.L., Kostyuchenko, Y.V., & Ermolieva, T. (2020). Integrated robust management of food-energy-water-land use nexus for sustainable development. In: Integrated modeling and management of Food-Energy-Water NEXUS for sustainable development. Eds. Zagorodny, A.G., Ermoliev, Yu.N., Bogdanov, V.L., & Ermolieva, T., Kiev, Ukraine: Committee for Systems Analysis at Presidium of National Academy of Sciences of Ukraine — National Member Organization of Ukraine in International Institute for Applied Systems Analysis (IIASA). ISBN 978-966-02-9344-1
Ermoliev, Y., Zagorodny, A.G., Bogdanov, V.L., Ermolieva, T., Havlik, P., Obersteiner, M. , & Rovenskaya, E. (2020). Linking distributed sectorial and regional optimization models under asymmetric information: towards robust food-water-energy-environmental nexus. In: Integrated modeling and management of Food-Energy-Water NEXUS for sustainable development. Eds. Zagorodny, A.G., Ermoliev, Yu.N., Bogdanov, V.L., & Ermolieva, T., Kiev, Ukraine: Committee for Systems Analysis at Presidium of National Academy of Sciences of Ukraine — National Member Organization of Ukraine in International Institute for Applied Systems Analysis (IIASA). ISBN 978-966-02-9344-1
Ermolieva, T., Ermoliev, Y., Obersteiner, M. , & Rovenskaya, E. (2021). Chapter 4 Two-Stage Nonsmooth Stochastic Optimization and Iterative Stochastic Quasigradient Procedure for Robust Estimation, Machine Learning and Decision Making. In: Resilience in the Digital Age. pp. 45-74 Springer. ISBN 978-3-030-70369-1 10.1007/978-3-030-70370-7_4.
Ermoliev, Y., Zagorodny, A.G., Bogdanov, V.L., Knopov, P.S., Borodina, O.M., Ermolieva, T., Rovenskaya, E. , Kostjuchenk, Y.V., Gorbachuk, V.M., & Zaslavskiy, V. (2018). Integrated robust management of NEXUS between agricultural, water, energy economic sectors: consistent algorithms for linking distributed models. In: Proceedings of the 6-th International Conference on Mathematical modeling, optimization and information technologies. pp. 108-112 Kischinev, Moldova: Evrica.
Gorbachuk, V.M., Ermoliev, Y., Ermolieva, T., & Dunajevskij, M.S. (2019). Quantile-based regression for the assessment of economic and ecological risks. In: Proceedings of the 5th International scientific conference on Computational Intelligence, 15-20 April, 2019. pp. 188-190 Uzgorod, Ukraine: Ministry of Education and Science of Ukraine.
Zagorodny, A.G., Ermoliev, Y.M., & Bogdanov, V.L. (2014). Integrated Management, Security and Robustness. NASU & Innovation Center of the NASU. ISBN 978-966-02-7376-4
Zagorodny, A.G. & Ermoliev, Y. (2013). Integrated Modeling of Food, Energy and Water Security Management for Sustainable Social, Economic and Environmental Developments. Kiev: National Academy of Sciences of Ukraine. ISBN 978-966-02-6824-1
Ermoliev, Y. & Hordijk, L. (2006). Global Changes: Facets of Robust Decisions. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-06-001
Ermoliev, Y. & von Winterfeldt, D. (2012). Systemic risk and security management. In: Managing Safety of Heterogeneous Systems. Eds. Ermoliev, Y, Makowski, M , & Marti, K, Heidelberg: Springer. 10.1007/978-3-642-22884-1_2.
Ermoliev, Y. (2009). Stochastic quasigradient methods. In: Encyclopedia of Optimization. Eds. Floudas, C.A. & Pardalos, P.M., New York: Springer-Verlag. ISBN 978-0-387-74758-3 10.1007/978-0-387-74759-0_662.
Ermoliev, Y. (2009). Two-stage stochastic programming: Quasigradient method. In: Encyclopedia of Optimization. Eds. Floudas, C.A. & Pardalos, P.M., New York: Springer-Verlag. ISBN 978-0-387-74758-3 10.1007/978-0-387-74759-0_690.
Ermoliev, Y. (2009). Stochastic quasigradient methods in minimax problems. In: Encyclopedia of Optimization. Eds. Floudas, C.A. & Pardalos, P.M., New York: Springer-Verlag. ISBN 978-0-387-74758-3 10.1007/978-0-387-74759-0_664.