Effects of land-based pollution control on coastal hypoxia ... · Effects of land-based pollution...

Procedia Environmental Sciences 13 (2012) 232 – 241

1878-0296 © 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of School of Environment, Beijing Normal University.doi:10.1016/j.proenv.2012.01.022

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Procedia Environmental

Sciences Procedia Environmental Sciences 8 (2011) 232–241

www.elsevier.com/locate/procedia

The 18th Biennial Conference of International Society for Ecological Modelling

Effects of land-based pollution control on coastal hypoxia: a numerical case study of integrated coastal area and river basin

management in Ise Bay, Japan

H. Higashia*, H. Koshikawaa, S. Murakamib, K. Kohataa, M. Mizuochia, T. Tsujimotoc

aNational Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan bCabinet office, Government of Japan, 3-1-1 Kasumigaseki Chiyoda-ku, Tokyo, 100-8970, Japan

cDepartment of Civil Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

Abstract

Integrated Coastal Area and River basin Management (ICARM) is important to maintain/improve the sustainability of the coastal ecosystem services. We describe the effects of the land-based pollution reduction on the water quality in Ise Bay, Japan, based on the numerical simulations. The numerical model for water and material flow-flux in the bay consists of the hydrodynamic and the pelagic-benthic ecosystem models. The hydrodynamic model could predict the 3D current, pressure, salinity, and temperature. The pelagic-benthic ecosystem model simulated the available evaluation for the C-N-P-O biogeochemical cycle. The numerical simulations were carried out in order to investigate the response of coastal hypoxia in Ise Bay to the pollutant loading reductions predicted by the river basin model under the various social scenarios. These simulated results indicated that hypoxia volume could be reduced to 67% of the present loading condition if the most effective control of the point and nonpoint sources was adopted. © 2011 Published by Elsevier Ltd. Keywords: Hypoxia; Pollutant loading control; Numerical simulation; ICARM; Ise Bay

* Corresponding author. Tel.: +81-29-850-2026; fax: +81-29-850-2569. E-mail address: [email protected].

© 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of School of Environment, Beijing Normal University. Open access under CC BY-NC-ND license.

Open access under CC BY-NC-ND license.

http://creativecommons.org/licenses/by-nc-nd/3.0/http://creativecommons.org/licenses/by-nc-nd/3.0/

233H. Higashi et al. / Procedia Environmental Sciences 13 (2012) 232 – 241 H. Higashi et al./ Procedia Environmental Sciences 8 (2011) 232–241 233

1. Introduction

Coastal regions have many important ecosystem services for human society; fishery resources, water quality improvement, habitat provision, amenity landscape, etc. However, many semi-enclosed bay areas have had eutrophication problems during the past half century. The main cause is human activities in the land such as urbanization in the basins, industrialization in the bayside areas, excessive fertilizer in the farmlands, and so on. Therefore, excessive pollutant material has discharged from watershed to coastal region and has impacted on coastal and estuarine ecosystem. Political implementations such as wastewater reduction and sewage treatment have been carried out but their effects on the prevention of the water pollution, the algal blooms, and the anoxic/hypoxic water have not significantly been confirmed in many coastal regions.

Ise Bay, located on the Pacific coast of Central Japan (Fig 1), is one of the famous nutrient enrichment bay areas in Japan. The bay has had severe hypoxia problem for the last few decades although political managements have been carried out since 1970s. So, the bay has many fishery problems. For instance, annual catch yields of short-necked clam (Ruditapes philippinarum) amounted to >10,000 metric tons from 1981 to 1995, but present yields have decreased to almost one-third of this amount in Ise Bay [1]. Despite extensive knowledge of hydrodynamic and water pollution processes in Ise Bay [2-3], the reason of the non-improvement in the marine water quality is not obtained well.

The eutrophication is one of the major marine environmental problems of the world in the present [4]. Recently, the integrated coastal area and river basin management (ICARM) is becoming important for sustainable coastal and marine environment and ecosystem. We developed a numerical assessment model for ICARM in the Ise Bay Eco-compatible River basin Research Project (ERRP). This model, which consists of the river basin and the marine models, is available to predict water and material flow-flux in Ise Bay (including Mikawa Bay) Basin, and to evaluate various ecosystem services at each landscape. The assessment model can evaluate the effects of the material loading changes under the various social scenarios on the marine environment and ecosystem.

This paper describes the effects of the land-based pollution reduction on the water quality in Ise Bay based on the ERRP simulated results. We introduced a hydrodynamic and pelagic-benthic ecosystem coupling model which is the marine part of the assessment model. The numerical simulations were carried out under the pollutant loading conditions produced by the river basin model with the primary objective to clarify the effective land-based pollution control for the prevention of hypoxia in Ise Bay.

2. Numerical simulation method

2.1. Study site

Ise Bay (water area: 1783km2, mean depth: 20m) is the semi-enclosed structure with a narrow entrance to the Pacific Ocean, a cavity in the central portion which inhibits exchange of seawater with the open sea, and to the relatively shallow Mikawa Bay (water area: 604km2, mean depth: 9m) to the southeast (Fig 1). The catchment area of Ise Bay and Mikawa Bay is 18 153km2, with a population of about 10.7 million. Eight major rivers flow into Ise and Mikawa Bays, and the total amount of annual discharge is 18 billion m3/year. Kiso, Nagara, and Ibi Rivers, which contribute over 80% of the total eight river discharge, show the seasonal variation that is large in summer (~1000m3/s) while small in winter (~200m3/s) [3]. Around Ise Bay, the northwesterly monsoon wind from the Eurasian Continent dominates in the cool season, and the southerly sea breeze does in the warm season [5].

Ise Bay is close to the Chubu industrial area of Japan and receives its point-source pollution. Due to an increasing load of nutrients from rapid industrial development since the 1950s, as well as from livestock

234 H. Higashi et al. / Procedia Environmental Sciences 13 (2012) 232 – 241234 H. Higashi et al./ Procedia Environmental Sciences 8 (2011) 232–241

farms and municipalities on land, the bay has been seriously eutrophicated since then. Although the water pollution inflow has been reduced steadily by the political regulation since 1978, the problems of red tides and low oxygen water have still occurred every year.

Fig. 1. Outline of Ise Bay Fig. 2. Structure of the biogeochemical cycle model


2.2. Numerical model

The numerical model for water and material flow-flux in the bay consists of hydrodynamic and pelagic-benthic biogeochemical cycle models. The hydrodynamic model simulates the quasi-3D physical field; current, pressure, salinity, and temperature. The model is governed by hydrostatic-Boussinesq primitive equations; continuity, momentum, heat, and salinity transports. The vertical mixing process is parameterized with the Level 2.5 turbulence-closure model [6]. Sea surface fluxes as the boundary conditions for the momentum and heat transport equations are evaluated using the air-sea bulk transfer coefficients [7]. These equations are solved by the finite difference method in Cartesian coordinate space under the conditions of coastal topography, bathymetry, river inflow, exchange with external ocean, tides, Coriolis and meteorological forcing. The semi-Lagrangian schemes, R-CIP [8] and R-CIP-CSL2 [9] are used to solve the advection terms. The VOF method [10] is applied to track free water surface movements.

The biogeochemical cycle model in the pelagic system uses the available evaluation for the C-N-P-O coupled cycle (Fig 2). The model variables are phytoplankton, detritus, dissolved organic matter, and dissolved inorganic nutrients. The detritus and the dissolved organic matter are respectively divided into two fractions: fast labile and slow labile. Each material transport in the bay is governed by the quasi-3D advection-diffusion equation, which is solved by coupling with the hydrodynamic model. Mineralization consists of oxic, nitrate reduction, and anoxic processes. The oxic and the nitrate-reduction mineralization are respectively limited by dissolved oxygen (DO) and nitrate. Under the shortages in DO and nitrate condition, the anoxic mineralization occurs with producing oxygen demand units (ODU), representing Mn2+, Fe2+, and S2- [11]. The DO consuming/producing in the model are photosynthesis/respiration of phytoplankton, oxic mineralization, nitrification, and oxidation of ODU.

The biogeochemical cycle model in the benthic system predicts the bottom boundary condition for the biogeochemical cycle model in the pelagic system. The mineralization process and the DO consumption in the benthic system are similar to the ones in the pelagic system. Physical transport is governed by the vertical-1D molecular diffusion equation [12], without horizontal solute movement in the benthic system. The benthic model considers the adsorption/desorption of the phosphate depending on the oxic/anoxic mineralization.


Fig. 3. Annual average discharge of freshwater, CODMn, TN, and TP from the river basin to Ise Bay, evaluated by the river runoff model [13]


2.3. Pollutant loading condition and social scenarios

We carried out the hydrodynamic and the biogeochemical cycle simulations under the following seven conditions of the pollutant loading, which were evaluated by the river basin model of ERRP [13-14]. To investigate the model validity, a control simulation was performed under the basin condition in 2000 (Present). Next, the coastal environments in 1960 (Past) and in 2030 (Future) were predicted. In the Present and the Past runoff simulations, the freshwater and the pollutant material discharge were evaluated with the landuse conditions and the statistical dataset of the point and the nonpoint sources. The Future simulation considered the basin-condition changes of the population, the landuse (urbanization), the sewage infra structure (including the current plan), the industrial and the agricultural products. Finally, the effects of the pollutant control based on the four social scenarios (, , , Vision) were estimated. The scenario was designed mainly according to the improvement in the infra structure by the public management. The scenario was built on the personal/community managements such as lifecycle changes, ecological agriculture, etc. The scenario was based on the ecosystem service restoration in the forest, the stream, the paddy, etc. The Vision scenario was hybrid scenario with , , considered cost effectiveness, possibility, sustainability, etc. The other basin-conditions of the , , , and Vision scenarios were same as that of the Future simulation. Fig 3 shows the annual average discharge of freshwater, CODMn, TN, and TP simulated by the river basin model under the precipitation condition in 1999.

2.4. Other simulation conditions (meteorology, open sea, resolution)

The numerical simulations were carried out with a horizontal resolution of 1.5 minutes (E–W: 2.3km, N–S: 2.8km). The vertical coordinate, a z-coordinate system, was divided into 20 layers from sea surface to 40m depth, such that the vertical grid size was 1–5m and decreased proportionately as depth decreased. We used the bathymetry data, JTOPO30, provided by Marine Information Research Center (MIRC). In the biogeochemical cycle model in the benthic system, the vertical coordinate was divided into 7 layers from sediment-water interface to 10cm depth, such that the grid size was 0.1–5.0cm.

The meteorological data was set using the observed hourly data at Nagoya, Irago, Tsu, and Yokkaichi stations (see Fig 1), provided by Japan Meteorological Agency (JMA). At the open sea, the monthly statistical data of the sea temperature and the salinity (provided by the Japan Oceanographic Data Center, JODC), the water quality (observed by Mie Prefecture Fisheries Research Institute), and the hourly tidal-level observed at Toba (N34° 29’, E136°49’) by JMA were set. Note that the forward meteorological and tidal level conditions for all simulations were used the observed data in 1999 in order to clarify the effects of the pollutant loading changes on the water quality in Ise Bay.

3. Results and discussion

3.1. Model validity

Fig 4 shows the comparison between the observed and the Present simulation results at three monitoring stations (see Fig 1) for surface temperature/salinity, surface/bottom DO, surface TOC/Chl.a, surface TN/DIN, bottom TN/DIN, surface TP/DIP, and bottom TP/DIP. The model variables of temperature, salinity, DO, TOC, and Chl.a at each station agree well with the observed results. Their seasonal variations are also reproduced by the model. The calculated results of DIN and DIP are roughly same as the observed ones. However, the calculated results TN and TP tend to be higher than the observed ones. In particular, the bottom TN and TP results are large difference in the observed data. These reasons


are certainly less well known in the present but we infer that there is uncertainty in the boundary conditions: open sea quality and/or pollutant loading. Although the numerical model has the above mentioned problems, the numerical simulation can accurately evaluate the hypoxia.

* Observed data provided by Ministry of the Environment and Mie Prefecture Fisheries Research Institute


Fig. 4. Comparison between the observed and the calculated results of water quality (sea surface temperature/salinity, surface/bottom DO, surface TOC/Chl.a, surface TN/DIN, bottom TN/DIN, surface TP/DIP, and bottom TP/DIP) at three stations (Southwestern coast of Ise Bay, Head of Ise Bay, and Mikawa Bay, see Fig 1)

Fig. 5. Simulated contours of annual minimum bottom DO for each pollutant loading condition

Fig. 6. Simulated time series of hypoxia volume for each pollutant loading condition

3.2. Effects of pollutant loading changes on hypoxia in the bay

Fig 5 indicates the comparison with the simulated results of the annual minimum bottom DO for Past, Present, Future, , , , and Vision scenarios. Fig 6 indicates the simulated results of the hypoxia (DO


the Future is smaller than that of the Present is the pollutant loading decrease (see Fig 3) due to the sewage infra structure improvement.

The scenario simulation results indicated that hypoxia volume could be reduced to 67% of the present loading condition. The anoxic water under the , , , and Vision simulations slightly change/decrease from the Future one, however. In particular, the scenario, which we recommend because it is the eco-compatible river basin management, is a little effect for the prevention of the hypoxia in the bay. This is because the type control of the pollutant loading from the basin to the bay is much smaller than the others such as the infra structure improvement, etc. The results serves to imply the fact that the current plan of the sewage infra structure improvement is quite valid and effective, and that the sustainability of coastal and river basin environment and ecosystem is needed not only ecosystem service restoration () but also the public/community/personal managements of the point and nonpoint sources (, ), such as the Vision type scenario.

4. Conclusion

This study describes the effects of the land-based pollution reduction on the water quality in Ise Bay using the hydrodynamic and the biogeochemical cycle models. The numerical simulations were carried out under the pollutant loading conditions produced by the river basin model in order to clarify the effective land-based pollution control for the prevention of hypoxia in Ise Bay. These simulated results indicated that hypoxia volume could be reduced to 67% of the present loading condition if the most effective control was adopted. The proposed model for the integrated coastal and river basin environment can be use to assess the ecosystem services in the bay basin [14].

Acknowledgements

This study was supported by the “Ise Bay Eco-Compatible River Basin Research Project” by a grant in aid of a special coordination fund for promoting science and technology for sustainable national land management (2006–2010), supported by Ministry of Education, Culture, Science, Sports and Technology, Japan. We would like to thank the members of the project.

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