With the rapid development of information technology, the shipping industry is also experiencing an important period of change in the development of transition to intelligence and wisdom. Intelligent shipping is a service system that promotes inter-departmental cooperation, cross-regional information resource integration, transportation efficiency improvement and transportation cost reduction by using cloud computing, big data, Internet of Things, sensors and other technologies as a comprehensive application with the construction of big data center as a pioneer. Intelligent shipping is the innovative application of relevant advanced concepts and high technology in the shipping industry arising from the construction of intelligent society, however, the development of intelligent shipping is still in the primary stage, and relevant literature on the field of intelligent shipping is still lacking. In order to understand and develop intelligent shipping, this paper reviewed and summarized intelligent shipping based on the existing literature. This paper mainly introduced the background, connotation and development status of intelligent shipping at home and abroad, summarized the framework system of intelligent shipping from five aspects: intelligent ship, intelligent port, intelligent shipping insurance, intelligent supervision and intelligent service, summarized several key technologies in intelligent shipping, and gave examples of successful applications of intelligent shipping at home and abroad. Combined with the current research status of intelligent shipping, this paper put forward the shortcomings and challenges of intelligent shipping, and looks forward to the future development and research direction of intelligent shipping.

The synergistic management of water resources, the water environment, and the water ecology system (“Three-waters” system) is fundamental to ensuring regional water security and advancing sustainable development. However, existing evaluation indicator systems rely on expert experience and lack quantitative screening criteria, leading to indicator overlap and insufficient representativeness, which restricts the scientificity of management decisions. The study proposes a method integrating meta-analysis with case verification to construct an indicator system. A systematic review of 60 publications (1970–2024) from the Web of Science was conducted and a random effects model was used to merge effect sizes and quantify correlations and heterogeneity between indicators and the “Three-waters” system. The results indicate that the industrial water use proportion (R = −0.77) is the main stress factor in the water resources system, the negative effect of total hardness (R = −0.91) is the most significant in the water environment system, the contribution of the benthic diversity index (R = 0.90) is the most prominent in the water ecology system and vegetation coverage (R = 0.74) exhibits a strong positive effect in the social economic system. The case verification confirms the indicator system established under this method is consistent with the actual situation. This study provides methodological support for system diagnosis, coordinated regulation, and policy formulation, promoting the transformation from single-element to systemic water management.

Seasonal hydrological fluctuations can substantially reshape river–lake networks, but changes in water extent, network morphology, and structural connectivity may not occur synchronously. This study investigated wet–dry seasonal variations in the Poyang Lake Basin using Landsat imagery from eight representative years between 1990 and 2025. Surface water was extracted using a consistent NDWI threshold, and 30 m DEM-derived channel information was used to correct interrupted, duplicated, and spurious river centerlines before Horton–Strahler ordering and graph-theoretic analysis. Mean water area increased from 3407.14 km² in the dry season to 6872.87 km² in the wet season, while mean river-network density increased from 0.0348 to 0.0461 km/km². The maximum Strahler order increased from III in the dry season to IV in the wet season. River-network complexity increased from a dry-season mean of 12.85 to 58.38 in the wet season, and the river-network development coefficient increased from 3.28 to 13.59, indicating a substantially more developed tributary and hierarchical structure under wet-season conditions. In contrast, the mean α, β, and γ indices increased by only 9.8%, 4.6%, and 4.3%, respectively, and dry-season values exceeded wet-season values in some years. From 1990 to 2025, wet-season water area increased by 11.11%, whereas river-network length decreased by 2.77%. These results demonstrate that seasonal changes in water extent, river-network morphology, and structural connectivity are asynchronous, highlighting the need to distinguish these complementary dimensions when evaluating large river-connected lake systems.