Harmful algal blooms of Heterosigma akashiwo and environmental features regulate Mesodinium cf. rubrum abundance in eutrophic conditions

Baseflow estimation based on a self-adaptive non-linear reservoir algorithm in a rainy watershed of eastern China

Accurate baseflow estimation is critical for water resources evaluation and management, and non-point source pollution quantification. Nonlinear reservoir algorithm (NRA) has been increasingly applied to baseflow separation because of its good approximation to the real groundwater discharge (commonly dominated by the unconfined aquifer) in most watersheds. However, in the rainy regions, large uncertainties may remain in the traditional NRA-separated baseflow sequences due to its empirical transition function for the rising limb of discharge process, and the evident variations of baseflow recession in the initial period of the falling limb caused by the disturbance from surface flow or rainfall events. To improve the reliability of baseflow separation, a self-adaptive non-linear reservoir algorithm (SA-NRA) was developed in this study based on the NRA, a self-adaptive groundwater discharge modified parameter, and the Particle Swarm Optimization algorithm (PSO). The validation of SA-NRA in a rainy watershed of eastern China showed that SA-NRA could be the approach to provide a goodness-of-fit for baseflow recession behaviors in the rainy regions. The traditional NRA and Eckhardt's two-parameter recursive digital filter (ERDF), calibrated (or validated) only with the pure baseflow recession data, can hardly provide reliable baseflow predictions for the non-pure baseflow recession periods (including the rising limb and the falling limb with surface flow or rainfall disturbance) due to the apparent variations of baseflow recession behavior. Therefore, more attentions should be paid to the uncertainties of baseflow separation for the non-pure baseflow recession periods in the rainy regions.

Growth and Nutrient Uptake Characteristics of Heterosigma akashiwo (Raphidophyceae) under Nitrogen and Phosphorus Concentrations in the East China Sea

Heterosigma akashiwo is classified as a harmful algal bloom (HAB) species that frequently occurs in eutrophic coastal waters and results in the contamination and mortality of fish and shellfish. The growth of H. akashiwo in four phosphate and nitrate concentration scenarios, representing the observed nutrient concentration ranges in the East China Sea (ECS), was evaluated to further understand the effect of nutrient concentrations on H. akashiwo blooms. The specific growth rate in the exponential growth phase (µ′) and the maximum cell density were lower (17–21% and 41%, respectively) under low phosphorus concentration scenarios, compared to the rates observed under high phosphorus concentration scenarios. The cellular nitrogen-to-phosphorus ratios of H. akashiwo were influenced by the initially supplied N:P ratio and the allocation strategy employed. Phosphorus concentration had a greater influence on the total growth of H. akashiwo than nitrate did, within the natural nutrient conditions of the ECS. These results could serve as a reference for coastal water management and marine ecological management and may be useful for further studies on the simulation and prediction of H. akashiwo blooms, particularly in the ECS.