The placement of artificial reefs (ARs) significantly influences local hydrodynamics and nutrient transport, both of which are crucial for enhancing marine ecosystems and improving marine habitats. Large eddy simulations (LESs) are performed to study the flow field around a cuboid artificial reef (CAR) with three inflow angles ($\alpha$ = 0°, 45°, and 90°). The numerical method is successfully validated with experimental data, and a reasonable grid resolution is chosen. The results demonstrate that the case with an inflow angle of 45° exhibits superior flow field performance, including the largest recirculation bubble length and the maximum volumes for both the upwelling and wake regions. Stronger turbulence is also observed around the CAR at this inflow angle, attributed to the intensified shear layer. The instantaneous flow features torn horseshoe vortices and rollers shed from the shear layer, which further develop into hairpin vortices.

Monitoring water quality in narrow tributary bays of large river-type reservoirs is hindered by sparse sampling and cloud-limited imagery. This study develops a Trophic State Index (TSI) inversion for Xiangxi Bay, a major tributary bay of the Three Gorges Reservoir, using Landsat data and a backpropagation (BP) neural network, with hyperparameters tuned via a grid search algorithm (GSA). Environmental drivers such as water temperature, solar radiation, and photosynthetically active radiation were combined with Landsat spectral bands. Eleven sites measured monthly in 2009 yielded 98 samples after preprocessing, and training achieved R² = 0.94. Predictions for 2009 show clear spatiotemporal heterogeneity: those for April and September (TSI = 48–59) exceeded those for July and October (46–56), with mid–lower reaches (52–59) being higher than mid–upper reaches (47–54). Out-of-period predictions for April/June 2019 and August/November 2020 were consistent with seasonal expectations, with higher spring–summer TSIs (2019: 50–57; 2020 August: 45–55) than in November 2020 (37–47). Key limitations include the small sample size, cloud-related data gaps, and sensitivity to evolving reservoir operations. This framework demonstrates a practical route to the satellite-based monitoring and mapping of trophic status in narrow reservoir tributaries.