Dynamic Water Systems: The URCA Model’s Blueprint for Resilient Coastal Cities

The paper "Adaptive Evaluation of Urban Water Resource Carrying Capacity: Development and Empirical Study of the URCA Model", authored by Congbao Xu, Yuhang Han, Liyan Qi, Jing Wang, and Wanxiang Yao from the Qingdao University of Technology, China Institute of Water Resources and Hydropower Research, and the Shandong Provincial Key Laboratory of Water Resources and Environmental Engineering, presents an innovative model for assessing how cities manage their water resources under climate and urbanization pressures. It introduces the Urban Water Resource Carrying Capacity Adaptive Assessment (URCA) Model, which redefines how water sustainability is measured by emphasizing adaptability, resilience, and system feedback. Traditional models, which rely on static thresholds, fail to capture the nonlinear and unpredictable nature of urban water systems. Xu and colleagues argue that urban water management must evolve toward dynamic models that simulate how cities self-organize and recover from environmental and social stressors.

The URCA Model: Blending Theory and Practice

At the core of the URCA model are two theoretical pillars, Complex Adaptive Systems (CAS) and Adaptive Cycle (AC) theory. CAS theory treats cities as interconnected systems that evolve through feedback and adaptation, while AC theory divides system behavior into four stages: growth, retention, release, and reorganization. The authors merge these into a six-dimensional evaluation framework called BPSRDU, Background, Pressure, State, Response, Degradation, and Upgrade, providing a comprehensive view of urban water health. Methodologically, the model employs a grey relational entropy method for weighting indicators, allowing it to handle limited or uncertain data. It also introduces a four-quadrant coupling coordination matrix, mapping the balance between internal self-organization (U₁) and external socio-ecological pressures (U₂). To enhance predictive capability, the team integrates an elastic exponential weighted moving average (EWMA) algorithm that automatically adjusts its smoothing factor based on real-time fluctuations, achieving an impressive prediction accuracy with a mean absolute percentage error of 9.96%.

Case Study: China's Five Coastal Cities

The URCA model is empirically tested across five major Chinese coastal cities, Dalian, Qingdao, Ningbo, Xiamen, and Shenzhen, from 2012 to 2023. The results highlight distinct regional patterns. Shenzhen and Xiamen emerge as "high-capacity, low-volatility" systems, operating in the protection phase with stable resource use and effective governance. Qingdao, however, is in a turbulent transformation phase with high volatility and low capacity, reflecting industrial stress and policy transition. Ningbo and Dalian remain in early growth phases, heavily dependent on external drivers. Statistical analysis shows Xiamen's carrying index averaging 0.85 with minimal fluctuation, while Qingdao's coefficient of variation exceeds 70%, revealing deep instability. Graphical evidence underscores a clear north–south divide: southern cities show high socio-ecological coordination indices (0.9–1.0), while northern ones hover around 0.6–0.7.

Resilience, Risk, and Regional Governance

Scenario simulations further illustrate how environmental, economic, and policy shocks influence system resilience. Under accelerated growth, Qingdao must improve industrial water-use efficiency by 4.2% annually to sustain equilibrium. Droughts in Dalian can cut carrying capacity by up to 20%, whereas Shenzhen's desalination and smart water management systems cushion such impacts effectively. Governance interventions, such as reclaimed water programs in Ningbo, raise its index from 1.60 to 1.69, highlighting adaptive policy success. Sensitivity tests reveal that resilient systems like Xiamen remain stable despite parameter shifts, while transitional cities like Qingdao exhibit more than 25% variability with model adjustments. Policy styles also differ: southern cities favor market-based instruments, water rights trading, and ecological compensation, whereas northern cities rely on administrative controls such as quota enforcement and groundwater regulation. Shenzhen's model of "desalination plus intelligent distribution," reducing costs to ¥3.5/m³, stands out as a benchmark for urban innovation.

Toward a Networked Water Resilience Future

The authors advocate for a "Water Resilience Alliance" that links coastal cities such as Jiaozhou Bay and Hangzhou Bay through shared data systems, joint emergency management, and integrated water dispatch mechanisms. They argue that resilience must transcend municipal boundaries, forming interlinked networks capable of adaptive governance under climate uncertainty. For inland or arid regions, the model can be modified by replacing marine indicators with groundwater metrics and adjusting algorithmic parameters to reflect higher variability. Future research, the paper notes, should integrate remote sensing and real-time hydrological data to enhance predictive precision.

Water Systems as Living Organisms

The study reimagines urban water governance as an evolutionary process rather than a static engineering problem. The URCA model provides policymakers with a scientific yet flexible tool for early-warning diagnostics, adaptive management, and cross-regional coordination. Xu and his co-researchers emphasize that cities, much like living organisms, must evolve through feedback, learning, and self-organization to thrive amid ecological and social challenges. By bridging theory and practice, the URCA model represents a breakthrough in sustainability science, one that transforms water management from a question of control into a philosophy of resilient coexistence between human progress and natural systems.