Addressing global sustainability challenges as outlined by the United Nations (UN) Sustainable Development Goals (SDGs) often requires navigating many potentially conflicting societal objectives simultaneously. For instance, increasing hydropower production enhances renewable energy supply but may adversely impact people and nature. Understanding these trade-offs is crucial, and the Pareto frontier - the set of solutions that cannot be improved with respect to one objective without negatively affecting another - is a valuable framework. Strategic hydropower planning concerns finding energy portfolios that achieve decarbonization targets, while balancing energy production with socioeconomic and environmental impacts. Previous work has considered exact and approximate algorithms for Pareto optimization for tree-structured networks, such as rivers, for hydropower planning. However, such approaches do not account for bounding constraints, such as realistic energy production targets, critical in real-world applications. Herein, we propose a novel approach for constraint-aware Pareto optimization for tree-structured networks, incorporating objective bounds to ensure more realistic and robust solution outcomes. We apply our constraint-aware Pareto approach to the strategic planning of hydropower expansion, considering energy bounds to adhere to the UN's net zero by 2050 decarbonization targets, in the Magdalena River basin, home to more than 80% of Colombia’s population. Our analysis demonstrates how lower and upper bounds can significantly modify the unconstrained Pareto frontier, revealing that feasible Pareto solutions can be dominated by infeasible solutions, and thus may be ignored by constraint-agnostic solvers. Our results highlight the importance of considering real-world constraints in multi-objective problems such as optimizing hydropower expansion to meet both energy and sustainability goals.

Climate change and biodiversity loss are among humanity’s most pressing challenges. In 2022, under the auspices of the United Nations, over 190 countries reached a historic agreement to address the alarming loss of biodiversity and restore natural ecosystems. Target 3, often referred to as ``30x30'', seeks to effectively protect and manage 30% of the world’s terrestrial, inland water, coastal, and marine areas by 2030. In this work, we address the UN 30x30 target in the context of global freshwater fish conservation. Freshwater ecosystems are disproportionately unprotected, and their biota are declining at an alarming rate. Our goal is to select new protected areas that protect freshwater fish species as much as possible without exceeding total coverage of 30% of land area. To support this goal, we introduce the Expansion of Connected Components from Alternative Terminals Problem, a graph-based optimization problem that captures ecological priorities and connectivity constraints. We analyze its computational complexity, propose novel integer programming formulations, and develop scalable solution methods. We further evaluate its typical-case complexity under diverse settings and demonstrate that our approach scales to a global real-world scope, encompassing approximately 200,000 freshwater basins and 13,000 species, paving the way for implementing the 30x30 target on a worldwide scale.