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<p>Addressing the escalating challenges of population growth and urbanization, which intensify water, energy, and food demands in both Euro-Mediterranean and Sub-Saharan regions, this study employs artificial intelligence (AI) and system dynamics modelling (SDM) to address the water–energy–food (WEF) nexus in urban planning, focusing on Goma in the Democratic Republic of Congo (DRC). Utilizing qualitative measures such the Joint Monitoring Programme (JMP), Energy Sector Management Assistance Program (ESMAP), and Food Insecurity Experiences Scale (FIES), combined with the Household Dietary Diversity Score (HDDS) and remote sensing for urban land cover mapping, the research provides a comprehensive understanding of resource management challenges. A survey of 90 households, augmented by AI and machine learning (ML) algorithms, informs a system dynamics modelling (SDM) under the Global Scenario Group (GSG) scenarios. In addition, secondary data were used to compare WEF urban stainability in the Euro-Mediterranean regions. The findings indicate that the Great Transition scenario, despite the challenges posed by Goma's socio-economic context, presents a sustainable path for socio-economic development and resource management, with lower projected resource demands by 2050. Using secondary data, the study also draws comparisons of WEF consumption with cities in the Euro-Mediterranean region. This comparison highlights shared challenges related to urban growth and resource constraints and offers insights that could benefit both regions. Key recommendations include infrastructure improvements, diversification of energy sources, sustainable agricultural practices, and expanding water supply infrastructure, potentially supported by external financing or tariff changes. The integration of advanced technologies illustrates their role in crafting transdisciplinary solutions for urban planning, offering valuable insights for policymakers and planners. This work lays the foundation for similar holistic resource management assessments in the DRC and Central Africa, emphasizing the need for integrated approaches to foster regional sustainable development, a concept equally relevant to the Euro-Mediterranean context.</p>

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Urban–artificial intelligence and system dynamics modelling of the water–energy–food nexus in Goma (DR Congo) and Euro-Mediterranean regions

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  • 发表日期：

    2025年7月1日

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  • Derrick Mirindi

摘要

Addressing the escalating challenges of population growth and urbanization, which intensify water, energy, and food demands in both Euro-Mediterranean and Sub-Saharan regions, this study employs artificial intelligence (AI) and system dynamics modelling (SDM) to address the water–energy–food (WEF) nexus in urban planning, focusing on Goma in the Democratic Republic of Congo (DRC). Utilizing qualitative measures such the Joint Monitoring Programme (JMP), Energy Sector Management Assistance Program (ESMAP), and Food Insecurity Experiences Scale (FIES), combined with the Household Dietary Diversity Score (HDDS) and remote sensing for urban land cover mapping, the research provides a comprehensive understanding of resource management challenges. A survey of 90 households, augmented by AI and machine learning (ML) algorithms, informs a system dynamics modelling (SDM) under the Global Scenario Group (GSG) scenarios. In addition, secondary data were used to compare WEF urban stainability in the Euro-Mediterranean regions. The findings indicate that the Great Transition scenario, despite the challenges posed by Goma's socio-economic context, presents a sustainable path for socio-economic development and resource management, with lower projected resource demands by 2050. Using secondary data, the study also draws comparisons of WEF consumption with cities in the Euro-Mediterranean region. This comparison highlights shared challenges related to urban growth and resource constraints and offers insights that could benefit both regions. Key recommendations include infrastructure improvements, diversification of energy sources, sustainable agricultural practices, and expanding water supply infrastructure, potentially supported by external financing or tariff changes. The integration of advanced technologies illustrates their role in crafting transdisciplinary solutions for urban planning, offering valuable insights for policymakers and planners. This work lays the foundation for similar holistic resource management assessments in the DRC and Central Africa, emphasizing the need for integrated approaches to foster regional sustainable development, a concept equally relevant to the Euro-Mediterranean context.