A proxy-based framework for assessing external stressors on green infrastructure

ABSTRACT Green infrastructure such as bioretentions are critical for urban stormwater management. Yet, their performance can degrade over time due to environmental and anthropogenic stressors. Proactive maintenance planning is essential, but often hampered by limited performance data. Without monitoring data or inspection records, proxy indicators offer a practical way to estimate the intensity of external stressors. However, their usefulness depends on selecting relevant proxies and access to suitable datasets. This study uses a two-step decision tree to identify relevant external stressors and select suitable proxies. It also evaluates datasets needed to calculate these proxies for bioretention systems. Twelve stressor categories were identified based on spatial variability and external origin. For 11 of these, 30 proxy indicators were identified from literature, sensitivity analyses, or empirical studies. Norway serves as a case study to assess dataset accessibility and suitability. Some proxies, particularly those related to traffic infrastructure or points of interest, had high-quality open-access datasets. Others were limited or unavailable, highlighting the need for improved institutional data sharing and, potentially, citizen science initiatives. The identified proxies help estimate stressor intensity and support the prioritization of monitoring, inspection, and maintenance. This approach provides a practical framework for improving GI asset management in data-scarce contexts.