Elsevier

Marine Pollution Bulletin

Volume 114, Issue 1, 15 January 2017, Pages 53-63
Marine Pollution Bulletin

A coastal three-dimensional water quality model of nitrogen in Jiaozhou Bay linking field experiments with modelling

https://doi.org/10.1016/j.marpolbul.2016.08.047Get rights and content

Highlights

  • The field culture experiments were conducted in the Jiaozhou Bay.

  • The dynamic parameters of nitrogen were obtained by analysis equations.

  • The parameters of the field culture experiments were applied to correct the water quality model.

  • The simulated NO3-N, NH4-N, DON and Chl-a concentration matched the observed values well.

Abstract

With anthropogenic changes, the structure and quantity of nitrogen nutrients have changed in coastal ocean, which has dramatically influenced the water quality. Water quality modeling can contribute to the necessary scientific grounding of coastal management. In this paper, some of the dynamic functions and parameters of nitrogen were calibrated based on coastal field experiments covering the dynamic nitrogen processes in Jiaozhou Bay (JZB), including phytoplankton growth, respiration, and mortality; particulate nitrogen degradation; and dissolved organic nitrogen remineralization. The results of the field experiments and box model simulations showed good agreement (RSD = 20% ± 2% and SI = 0.77 ± 0.04). A three-dimensional water quality model of nitrogen (3DWQMN) in JZB was improved and the dynamic parameters were updated according to field experiments. The 3DWQMN was validated based on observed data from 2012 to 2013, with good agreement (RSD = 27 ± 4%, SI = 0.68 ± 0.06, and K = 0.48 ± 0.04), which testifies to the model's credibility.

Introduction

Land-based pollution is the primary cause of environmental issues in Jiaozhou Bay (JZB) (Wang et al., 2006, Zhang, 2007, Liu et al., 2010). With the rapid development of industrial and agricultural activities and urbanization in the JZB Rim Region, anthropogenic wastewater, mainly through rivers and wastewater treatment plants, has been discharged into JZB (Sun et al., 2007, Han et al., 2011). Green tide (Enteromorpha), the depletion of fish biodiversity and ecosystem degradation in JZB (Rabalais, 2002, Dai et al., 2007, Borja et al., 2008), are the result of eutrophication subjected to the high concentration of dissolved inorganic nitrogen (DIN) (Shen, 2001, Liu et al., 2005, Meng et al., 2013). Previous survey data showed that not only the load of land-based total dissolved nitrogen (TDN) into JZB increased year by year, but the components of TDN have also changed, with the contribution of dissolved organic nitrogen (DON) particularly increasing gradually in recent years (Liu et al., 2005, Yang, 2014, Lu et al., 2016). Generally, various biogeochemistry processes of TDN in the coastal area lead to DON being transformed into DIN, which affects the water quality of JZB. However, the transport and transformation processes of different nitrogen forms are complicated and difficult to explain. These processes should be analyzed, and their effects on the corresponding water quality should be assessed. A coastal three-dimensional water quality model can describe the transformation processes of different nitrogen forms, help predict changes in water quality, and contribute strongly to the necessary scientific grounding of coastal management (Srinivasan and Arnold, 1994, Krysanova et al., 1998, Drago et al., 2001, Howarth et al., 2002).

Water quality modeling is an instrumental methodology for studying different nitrogen forms and dynamics in coastal areas because the model results not only confirm existing knowledge derived from field work but also provide insight into the functioning mechanisms of ecosystems, which are difficult to understand only by observations (Liu et al., 2007). Crise et al. attempted to use a seasonal 3D model to study the nitrogen cycle in part of the Mediterranean Sea. They found that the circulation directly or indirectly determines the distribution of the dissolved inorganic nitrogen (Crise et al., 1998). Han et al. (2011) and Li et al. (2015) studied the environmental capacity of nitrogen pollution in JZB based on a 3D water quality model (Han et al., 2011, Li et al., 2015). Previous studies have shown that the stability and veracity of a 3D water quality model depend not only on the hydrodynamic force but also on the functions and parameters of the dynamic processes of an ecosystem (Fasham et al., 1995, Walters et al., 1997, Mann and Lazier, 2006, Ayata et al., 2013). Therefore, the biogeochemical processes of different nitrogen forms might change with changes in the land-based TDN composition in JZB. Thus, it is necessary to correct the dynamic equations and parameters of the water quality model through field culture experiments (Vavilin et al., 2014). Based on a single season/form/process culture experiment, the biogeochemical processes and parameters of the multiple nitrogen forms were mostly unsystematic and unsuitable for the water quality model (Jørgensen et al., 1981, Jørgensen et al., 1986, Morton and Frith, 1995, Suzuki et al., 2000, Fennel et al., 2001). Therefore, we must comprehensively and systematically understand the transformation processes of the multiple nitrogen forms in JZB, which include phytoplankton uptake, death, and respiration; particulate nitrogen (PN) degradation, and DON remineralization processes, through a field culture experiment in JZB.

Although the method of system field culture research can be completed as a multistep process, with different nitrogen sources and a complete period for the transformation processes of multiple nitrogen forms in JZB, the objective of this research is to build and calibrate the structure and dynamic parameters of the water quality model and improve the simulation accuracy. The results of this study can be further applied to evaluate plans for water quality management and lay a foundation for effectively improving water quality in JZB.

Section snippets

Study area

The JZB is located in the southern coastal area of the Shandong peninsula in China, surrounded by the city of Qingdao (Fig. 1). It is a typical semi-enclosed bay with a channel 2.5 km in width connected with the Yellow Sea. The bay has a surface area of 360 km2 and an average depth of 7–8 m (Liu et al., 2005). The bay is increasingly affected by anthropogenic activities. A large amount of land-based pollutants enter JZB mainly through the six rivers of the Dagu, Licun, Yanghe, Loushan, Lianwan,

Analytic equation fitting

Based on the correlation analysis of the field experiment data, the maximum phytoplankton uptake rate and half-saturation constant were obtained using Eq. (1) (Fig. 3). The mortality rate, the degradation rate of PN, the remineralization rate of DON and nitrification rate of NH4-N were obtained using Eq. (2) (Fig. 4 A, C, D, E). The phytoplankton respiration rate was obtained using Eq. (3) (Fig. 4 B). The results showed that these equations were reliable, with R2 > 0.9.

In the field culture

A case study in Jiaozhou Bay

The hydrodynamic processes and the flow field for the 3DWQMN were calculated by ECOMSED in the JZB (Wan et al., 2003, Li et al., 2015). The range of the model is set between 35.75 °N-36.22 °N and 120.00 °E-120.52 °E, with an open boundary in 120.55 °E. We adopt an orthogonal system that is spatially curvilinear, with grids number that measure 128 × 92 (I × J) and a resolution ranging from a minimum of 284 m in JZB to a maximum of 686 m near the boundary of the open ocean (Fig. 2). The model is

Conclusion

The results of this study suggest that integrated conceptual models may generate relatively good estimates of the dynamics of the transformation of different nitrogen forms in field experiments. However, an architectural perspective is needed to understand the linear and nonlinear relationships among variables in the construction of the dynamics of transformation of a multi-nitrogen model.

Many factors can influence the accuracy of the dynamic model for nitrogen, such as the availability of

Acknowledgements

We thank the editor and anonymous reviewers for their constructive comments on an earlier version of this manuscript. We also thank the Institute of Oceanographic Instrumentation at Shandong Academy of Sciences, who shared their terminal workstation at the Zhongyuan dock with us for field experiments. We would also like to acknowledge the chemical engineering undergraduates training on the ship (Dongfanghong II) on which we carried out field experiments. Algae species were identified by

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