A marine ecosystem box model was developed to reproduce the seasonal variations nutrient concentrations and phytoplankton biomasses in Jiaozhou Bay (JZB) of China. Then, by removing each of the external sources of nutrients (river input, aquaculture, wastewater discharge, and atmospheric deposition) in the model calculation, we quantitatively estimated its influences on nutrient structure and the phytoplankton community. Removing the river input of nutrients enhanced silicate (SIL) limitation to diatoms (DIA) and decreased the ratio of DIA to flagellates (FLA); removing the aquaculture input of nutrients decreased FLA biomass because it provided less dissolved inorganic nitrogen (DIN) but more dissolved inorganic phosphate (DIP) as compared to the Redfield ratio; removing the wastewater input of nutrients changed the DIN concentration dramatically, but had a relatively weaker impact on the phytoplankton community than removing the aquaculture input; removing atmospheric deposition had a negligible influence on the model results. Based on these results, we suppose that the change in the external nutrients sources in the past several decades can explain the long-term variations in nutrient structure and phytoplankton community. Actually, the simulations for the 1960s, 1980s, and 2000s in JZB demonstrated the shift of limiting nutrients from DIP to SIL. A reasonable scenario for this is the decrease in riverine SIL and increase in DIP from aquaculture that has reduced DIA biomass, promoted the growth of FLA, and led to the miniaturization of the phytoplankton.

The harmonic constants extracted from tidal gauge stations and satellite altimeter observations are usually sparsely distributed in the continental marginal seas, but they are precious data for addressing the main characteristics of different constituents. In this paper, a dynamically constrained interpolation methodology (DCIM) is developed and applied to interpolate the observed harmonic constants of the M₂ constituent from satellite altimeter observations in the Bohai, Yellow, and East China Seas (BYECS) with those from tidal gauge stations for validation. In the DCIM, the tide model provides dynamical constraints to interpolate the observations, and the adjoint assimilation method provides iterative optimization for the interpolated results by adjusting key model parameters. In particular, a substantial quantity of enhanced “observations” generated from the interpolated results of the domain are further interpolated with the sparse observations in the subdomain. The final interpolated results for each subdomain, naturally blending the dynamical constraints from the dynamical model with statistical information from observations, can describe the main characteristics of the M₂ constituent in the BYECS, the continental shelf sea of the East China Sea, and the Zhejiang–Fujian coastal area, respectively. The results indicate that the DCIM is feasible and effective to utilize the observations to obtain high-accuracy cotidal charts for regional ocean.