Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin.

Efficient and accurate flood risk assessment is essential for cultural heritage conservation in the context of increasingly frequent extreme weather events. Conventional flood risk assessment methods primarily aim to approximate inundation patterns across the entire study area, and their analytical units are not necessarily aligned with object-oriented decision-making. To address this limitation, this study develops a site-oriented surrogate modeling approach. The approach integrates site-specific characteristics with multi-scale neighborhood features to characterize local environmental constraints and investigates how neighborhood scale influences predictive performance. To this end, five models are constructed and compared, i.e., M1_Site, M2_50m, M3_200m, M4_500m, and M5_Multi-Scale. Experiments were conducted on 714 cultural heritage sites in Shanghai. Overall, the M2_50m, M3_200m, and M5_Multi-Scale models demonstrate strong predictive performance, with Test F1, GroupKFold F1, and Test Accuracy all above 0.85. According to the results, the site-oriented surrogate modeling approach is feasible, and neighborhood features are important. Model performances also exhibited clear scale sensitivity. This approach provides a practical framework for rapid, site-specific flood risk assessment and offers new insights for decision-making in cultural heritage conservation. Future research could focus on validating this approach in other contexts and applying it to multi-scenario risk analyses to further support heritage conservation planning.