Infrastructure systems were largely designed for a world of environmental stationarity, and the Anthropocene—characterized by accelerating change that often produces more dynamic and extreme stressors—challenges infrastructure robustness. Urban water supply systems (UWSs) epitomize the pressures of socio-environmental change on infrastructure as they increasingly operate outside their physical design conditions, putting new pressure on their institutional designs to weather emerging challenges. Water management institutions must therefore be designed for ‘dynamic fitness,’ defined by anticipatory capacity and responsiveness. However, we do not yet understand the specific institutional design features enabling dynamic fitness and their relation to infrastructure and environmental (i.e. biophysical) characteristics. We advance research on dynamic fitness in UWSs by synthesizing theory and analyzing 35-year data sets of stressors and responses for 16 U.S. urban water utilities using archetype analysis. We find that institutional archetypes capable of coping with higher biophysical complexity invest in information processing capacity and response diversity. While these features of dynamic fitness come at a cost, balancing these promotes efficiency, which can be expanded through polycentric regional governance structures. Institutional designs for dynamic fitness must weigh tradeoffs in flexibility across governance levels and between quick responses and slow transformative changes.
There is increasing interest in adaptable building design as spatial needs, market conditions, and performance expectations evolve over time. Uncertainty in future demand requires designers to assess not only the financial implications of expansion strategies, but also their associated carbon impacts from an early stage. This study applies real options analysis (ROA) to evaluate the value of incorporating adaptability into building design and to support decision-making under uncertainty and fluctuations in future demands. A case study of a commercial building in Singapore is used to compare three alternatives: Fixed (a base case retaining the existing building without expansion), demolish-and-rebuild (D&R), and Flex (embedding adaptability to permit future expansion at five-year decision intervals). Historical vacancy rate data from 2011 to 2023 were used to estimate demand trends and forecast future occupancy through year 2065. The alternatives were assessed using three metrics: cost of construction, net present value (NPV), and embodied carbon (EC). Results show positive mean NPV for all alternatives, with Flex achieving the highest mean NPV at approximately Singapore Dollars (SGD) 654 million. D&R resulted in the highest mean construction cost (SGD 78.6 million), the highest EC (8180 metric tons CO _2 e), and the lowest mean NPV (SGD 233 million). While Fixed offered the lowest immediate cost and carbon impact, it underperformed in capturing future growth. Overall, the findings highlight a clear trade-off between short-term certainty and long-term adaptability, emphasizing that embedding adaptability can improve financial performance while reducing the likelihood of future demolition and rebuilding. The study demonstrates the value of ROA methodology as a decision-support tool to navigate this trade-off between immediate cost certainty, long-term value creation, and environmental responsibility in building design.
Floating photovoltaic (FPV) solar energy is a rapidly expanding renewable energy technology in which photovoltaic panels are deployed on floating structures atop waterbodies. While FPVs may alleviate pressure on terrestrial biodiversity, relatively little is known about aquatic biodiversity within FPV host waterbodies. Most FPV studies have focused on abiotic environmental changes, with comparatively few examining wildlife responses. Furthermore, current biodiversity studies have largely compared FPV and non-FPV waterbodies rather than evaluating spatial variation among microsites within FPV host waterbodies. Here, we quantified aquatic arthropod biodiversity across four FPV host waterbodies in California and Florida using standardized dip-net sampling. We compared arthropod communities among shore, open-water, and FPV-associated microsites across all host waterbodies. Shore samples supported the greatest arthropod abundance, richness, and diversity. Samples collected in association with FPV infrastructure supported similar or slightly higher biodiversity relative to open-water samples, including significantly greater arthropod class richness. We also report an ostracod species ( Bradleytriebella trispinosa ) that likely represents a recent introduction to the United States. To our knowledge, this study provides the first empirical assessment of aquatic arthropod biodiversity within FPV host waterbodies and demonstrates that arthropod communities vary among shore, open-water, and FPV-associated microsites, with FPV-associated microsites supporting biodiversity comparable to, or slightly greater than, nearby open water.
Resource systems like energy and water enable human development and economic growth. The strong linkages between river basins and electricity grids motivate adopting an integrated multi-objective approach to their planning and management to increase service levels, seek economic efficiency, and promote wider societal goals. Connecting multi-sector infrastructure system computer simulators to multi-objective search algorithms offers a practical tool for identifying synergies in these interdependent systems. However, this approach is constrained by the computational resources required to run joint energy-water simulation models many times to explore the multi-objective search space. In this study, we proposed a framework that links a fast power system model emulator to a river system simulator, then connects that integrated model to a multi-objective design process. The emulator in our case is an artificial neural network and the search algorithm is a multi-objective evolutionary optimizer. We compare optimized designs that use emulation with those from a conventional process-based simulator to check the emulators’ ability to guide a computer-aided multi-objective design process. The framework is applied to the Sudanese power system and the Eastern Nile River Basin; the design problem is to search for operational strategies of the Grand Ethiopian Renaissance Dam (GERD) optimizing Ethiopia’s GERD power generation, Sudan’s and Egypt’s water supply and hydropower generation, and Sudan’s thermal generation and energy demand curtailment. Using the fast power system emulator in the design process leads to results similar to ones generated using conventional simulation. The proposed emulation method provides a promising new approach to explore sensitivities, synergies, and trade-offs in multi-sector resource systems.
