An integrated river basin-coast-sea modelling scenariofor nitrogen management in coastal waters

G. Schernewski & H. Behrendt & T. Neumann

Received: 3 March 2008 /Revised: 13 November 2008 /Accepted: 18 November 2008# Springer Science + Business Media B.V. 2008

Abstract Linked river basin and coastal water models wereapplied to analyse the effects of an optimal nitrogenmanagement scenario in the Oder/Odra river basin on waterquality in the Oder (Szczecin) Lagoon and the PomeranianBay (Baltic Sea). This scenario would reduce nitrogen loadsinto the coastal waters by about 35%, a level which issimilar to the load of the late 1960’s. During summer theprimary production and algae biomass in the Oder estuaryis limited by nitrogen, which makes a nitrogen managementreasonable. The comparison of the late 1960’s and the mid1990’s shows that an optimal nitrogen management haspositive effects on coastal water quality and algae biomass.However, this realistic nitrogen reduction scenario wouldnot ensure a good coastal water quality according to theEuropean Water Framework Directive. A good waterquality in the river will not be sufficient to ensure a goodwater quality in the lagoon. Nitrogen load reductions bearthe risk of increased potentially toxic, blue-green algaeblooms, especially in the Baltic coastal sea. However, toreach water quality improvements in lagoons and innercoastal waters, nitrogen cuts are necessary. A mere focus onphosphorus is not sufficient.

Keywords Odra estuary . Szczecin lagoon . Baltic sea .

Eutrophication . River load .Water quality . Nitrogenlimitation . Reference conditions .Water framework directive

Introduction

Motivation and background

Estuaries or coastal waters linked to large rivers cannot bemanaged independently. These coastal ecosystems dependon processes, utilisation, structure and management in theriver basin. Water quality in coastal waters, for example,depends on water discharge and nutrient loads by the rivers.The nutrient loads in these rivers are a mirror of activities inthe river basin. The close dependencies between riverbasin-river-coastal waters and the sea are well known and,with respect to water quality, already reflected in theEuropean Water Framework Directive (WFD). As aconsequence, the WFD asks for a large scale managementapproach and plan covering river basins and coastal waterswith the aim to ensure a good water quality in all Europeansurface water during the next decade. In practise, it meansthat we need models and tools to analyse, assess andevaluate the efficiency of river basin management measureson surface and especially coastal water quality. The modelsare available. The challenge is, to link these very differenttypes of models, to develop realistic nutrient managementscenarios and to assess and evaluate their efficiency. Weshow a case, how this can look like and focus on a concreteexample: The Oder river basin, the river and its estuary inthe southern Baltic Sea.

The Oder (Polish: Odra) estuary is located at theGerman/Polish border. It consists of the Oder Lagoon(Szczecin Lagoon) and the Pomeranian Bay (a part of the

J Coast ConservDOI 10.1007/s11852-008-0035-6

G. Schernewski (*) : T. NeumannLeibniz-Institute for Baltic Sea Research,Seestrasse 15,D-18119 Rostock, Germanye-mail: gerald.schernewski@io-warnemuende.de

H. BehrendtDepartment of Shallow Lakes and Lowland Rivers,Leibniz-Institute for Freshwater Ecology and Inland Fisheries,Müggelseedamm 310,D-12587 Berlin, Germanye-mail: behrendt@igb-berlin.de

Baltic Sea) (Fig. 1). The lagoon is large (687 km2) butshallow (average depth of 3.8 m) and can be subdividedinto an eastern bay (Wielki Zalew) on the Polish territoryand the Kleines Haff in the west, on the German side. Threeoutlets link the lagoon with the Pomeranian Bay.

The entire estuary is controlled by the discharge of theOder River into the lagoon. With a length of 854 km, ariver basin of 120,000 km2, an annual discharge between9.5 km2 (1990) and 25 km2 (1980) and an averagedischarge of 17 km2 (530 m2 s−1) (Institute of Meteorologyand Water Management, unpublished report for the years1980–1983 and 1987–1999) the Oder is the third largestriver in the Baltic region. About 89% of the river basin islocated in Poland, 6% in Czech Republic and 5% inGermany. The Odra contributes at least 94% to the lagoon’swater budget and dominates the nutrient budgets, as well.

Why is a good water quality of outstanding importancein the Oder estuary? Tourism is the major source of incomein the Oder estuary. Bathing tourism depends on goodwater quality. Especially during summer, eutrophicationeffects like algae blooms or fish kills can cause seriouseconomic damage. Therefore, water quality, especiallyduring the summer season, is an important economic factor.Further, the entire region is under nature protection andgood water quality is imperative for ecosystem health.

Beside phosphorus and silicate, nitrogen is a majornutrient with respect to water eutrophication and pollution.This is not only true for coastal and marine waters, butholds for groundwater, lakes and rivers, as well. Duringsummer, primary production in the Oder Lagoon, as well asin the Baltic Sea is most often limited by the availability ofnitrogen and/or light. Both resources determine the amount

of algae and the state of eutrophication in the coastalwaters. In a narrow coast strip of the Baltic Sea phosphoruscan temporarily become a scarce resource, as well. However,water quality during summer depends largely on theavailability of nitrogen. Its availability in the Oder estuarydepends on nitrogen load in the Oder River. Light conditionsin the lagoon are mainly determined by wind-inducedresuspension of sediment and can hardly be managed. Thenitrogen load in the river can be managed. In this study, weentirely focus on nitrogen and the summer season, beingaware that in other seasons, other nutrients play a major role.

Aims of the study

A set of realistic and efficient measures to minimise theloss of nitrogen from the river basin are defined. Thesemeasures would minimise the nitrogen load in the OderRiver and form our optimal nitrogen management scenario.Based on this optimal scenario, we apply the models toanswer the following questions: To what extent can thenitrogen load in the Oder River be reduced? What will bethe spatial effects of reduced nitrogen availability in theestuarine system? What will be the effect on coastal waterquality? Can we reach a good status according to the WaterFramework Directive? Is it reasonable to focus our loadreduction and management efforts on nitrogen alone? Whatare the possibilities and limitation of our approach as wellas the practical consequences for water management?Further, we would like to add a regional coastal perspectiveto the ongoing controversial discussion in Sweden, whethernitrogen cuts are beneficial for the Baltic Sea (Boesch et al2006; Elmgren and Larsson 2001).

Fig. 1 The Oder estuary and the river basin. The entire river basin is spatially covered by the model MONERIS. In general, the model ERGOMcovers the entire Baltic Sea. The Oder Lagoon and the Pomeranian Bay have been simulated in a high spatial resolution

G. Schernewski et al.

The modelling approach

Background and innovation

To be able to analyse, assess and evaluate the effects ofnitrogen management in the Oder river basin on coastalwater quality we apply a new, spatially linked, large-scalemodel approach, which covers the entire river basin-river-coastal water—sea system. For this purpose the river basinmodel MONERIS has been linked to the three-dimensionalecosystem model of the Baltic Sea (ERGOM). One majorproblem during the last years was the non-optimal spatialresolution as well as the restriction of ERGOM to the BalticSea. In this approach, ERGOM is extended into the lagoonwhich allows a direct use of MONERIS results (riverdischarge and loads) as an input for ERGOM. Before, wehad to use a separate box-model for lagoon (Schernewskiand Wielgat 2001) which did not allow a coupling withERGOM.

However, the river basin model MONERIS and thecoastal and marine ecosystem model ERGOM are verydifferent with respect to structure, temporal and spatialresolution and data requirements. MONERIS needs largeamounts of spatial data for many parameters. Requirementswith respect to the temporal resolution of data are not high,but monthly hydro-meteorological data are beneficial. Themodel outputs are average annual loads of nitrogen, phos-phorus and heavy metals for many sub-basins and riversegments. Calculations and simulations with MONERIS arecomparatively fast and not very costly. The model ERGOM isvery different. The number of input parameters is very limited,but the data is required in high spatial and temporal resolution.For example, to run the three-dimensional flow model, dailywind data for the entire Baltic Sea is required and at leastmonthly data for river loads have to be provided. To beable to simulate the spatial dynamics, the Baltic Sea has tobe covered with a dense horizontal grid and the water bodyhas to be subdivided into vertical layers. In this study, theflow and ecosystem model had to be calculated foraltogether about 700,000 grid points. The temporal resolu-tion is 1 min. A simulation over 10 years, the minimum toget stable conditions, requires about 5 million time steps. Inthis case, altogether 3.5 billion single calculations for everyvariable have to be carried out. Therefore high computationpower is required to run ERGOM. Simulations are costlyand time-consuming.

The direct linking of the river basin to the coastal seamodel offers new opportunities for large scale management.It not only allows to carry out scenario analysis and toevaluate the effects of future and past policy and land-usechanges in the river basin on coastal waters and the BalticSea. It allows the opposite approach, as well. We now canpre-define water quality objectives in coastal and marine

waters and are able to analyse, which nutrient and nutrientsource in which sub-basin has to be tackled to reach thenecessary total nutrient load in the river to meet these waterquality objectives. Earlier analyses (e.g. Bangel et al. 2004;Neumann and Schernewski 2005) were based on river loadsprovided by authorities. This data was partly inconsistent(changing sampling intervals and changing laboratorymethods) and no long-term data was available due to a latestart of monitoring activities in the 1970’s. Further,downstream the station Schwedt loads were lacking.Because of the MONERIS model simulations, we wereable to use validated and complete long-term data sets forthis study and to increase the quality and reliability of theanalyses.

ERGOM—the 3D ecosystem model for coastalwaters and the Baltic Sea

The ecosystem model ERGOM is an integrated biogeo-chemical model linked to a 3D circulation model coveringthe entire Baltic Sea. The basic structure is shown in Fig. 2.The circulation model is an application of the ModularOcean Model (MOM 3) code (Pacanowski and Griffies2000) and includes an explicit free surface, an openboundary condition to the North Sea and freshwaterdischarge with rivers. A thermodynamic ice model is usedto simulate ice cover. A horizontally and vertically extendingmodel grid was used. High horizontal resolution (3 nauticalmiles) was applied in the south-western Baltic Sea. Towardsnorth and east the grid size gradually increased up to9 nautical miles. Altogether 77 vertical layers were assumed.The upper 100 m are resolved with a layer thickness of 2–3 m and below a constant thickness of 6 m is applied.

The biogeochemical model consists of nine state varia-bles. The nutrient state variables are dissolved ammonium,nitrate, and phosphate. Primary production is provided bythree functional phytoplankton groups: diatoms, flagellatesand cyanobacteria (blue-green algae). Diatoms representlarger cells which grow fast in nutrient-rich conditions.Flagellates represent smaller cells with an advantage at lowernutrients concentrations especially during summer con-ditions. The cyanobacteria are able to fix and utilizeatmospheric nitrogen, and therefore, the model assumesphosphate to be the only limiting nutrient for cyanobacteria.Due to the ability of nitrogen fixation, cyanobacteria are anitrogen source for the system. A dynamically developingbulk zooplankton variable provides grazing pressure onphytoplankton. Dead particles are accumulated in a detritusstate variable. The detritus is mineralized into dissolvedammonium and phosphate during the sedimentation process.A certain amount of the detritus reaches the bottom, where itis accumulated in the sedimentary detritus. Detritus in thesediment is buried in the sediment, mineralized or resus-

Nitrogen management in coastal waters

pended into the water column, depending on the velocity ofnear-bottom currents. The development of oxygen in themodel is coupled to the biogeochemical processes viastoichiometric ratios. Oxygen concentration controls pro-cesses as denitrification and nitrification. The biogeo-chemical model is coupled to the circulation model bymeans of advection diffusion equations for the statevariables. Neumann (2000) provides a detailed modeldescription, Neumann et al. (2002) shows the modelvalidation for the Baltic Sea, and Neumann and Schernewski(2005); Schernewski and Neumann (2005); Neumann (2007)present model applications and details about the datarequirements as well as possibilities and limits of the model.However, it can be regarded as a reliable tool for waterquality simulations.

To ensure correct lateral transport and mixing processes,ERGOM always simulates the entire Baltic Sea, even ifonly smaller areas are of interest. However, in this study werestrict ourselves spatially and present only water qualityresults of the Oder Lagoon and the southern Baltic Sea. Thesimulation covered the years between 1960 and 2000. Themost important input data were the water discharge andthe nutrient loads in the Oder River. This data was suppliedby the river basin model MONERIS. Data for atmosphericnitrogen deposition between 1960 and 2000 was calculatedon the basis of HELCOM (2002, 2005). Meteorologic data

was taken from the ERA-40 re-analysis for the entire periodbetween 1960 and 2000. Therefore, all simulations between1960 and 2002 are based on real weather, discharge andload data. In ERGOM, the lagoon and the Pomeranian Bayare described by a grid of 3 nautical miles. This spatialresolution allows only a general description of the lagoonand does e.g. not fully reflect the exchange between lagoonand bay.

MONERIS—the river basin model

MONERIS was applied to calculate the nutrient inputs andloads in the entire Oder River basin. The model calculatesthe annual nutrient load into the coastal waters, resultingfrom point and various diffuse sources. MONERIS is basedon a geographical information system (GIS), whichincludes various digital maps and extensive statisticalinformation.

To be able to run the model, large amounts of spatialinformation had to be compiled and transferred into theGIS: The river system, catchment and administrativeborders, land use classifications, soil maps, topographicalinformation, ground water tables, hydro-geological andhydro-meteorological information as well as data onatmospheric deposition, river flow and water quality.Details about sources and data quality are given in

Fig. 2 Conceptual diagram and basic information about the three-dimensional coastal water and Baltic Sea model ERGOM (background picturemodified after LOICZ, Turner et al. 1998)

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Behrendt and Dannowski (2005). Figure 3 gives anoverview about MONERIS. Point discharges from wastewater treatment plants and industrial entering the riversystem directly, but diffuse emissions into surface watershave very different pathways and have to be modelledseparately. Altogether six diffuse pathways are consideredin MONERIS: point sources, atmospheric deposition,erosion, surface runoff, groundwater, tile drainage andpaved urban areas. Along the pathway from the emissionsource into the river many transformation, retention andloss processes have to be taken into account.

The use of a GIS allows a regional differentiatedquantification of nutrient emissions into river systems. Incontrast to the study of Behrendt and Dannowski (2005) therecent results on the long term changes of the nutrient loadsin the Oder has been carried out with a higher spatialresolution of the river basin. Altogether 484 different riversub-catchments where calculated separately. Later, the datahas been aggregated for larger units and the entire riversystem. Because of data availability and funding reasons,detailed model calibrations and validations took place forthe period 1993 until 1997 and 1998 to 2002. For theseperiods detailed and spatially high resolved data ondifferent nitrogen sources are available and formed the

basis for the formulation of the scenario. Details about themodel, processes and validations are given in Behrendt andDannowski (2005). In this study, the output of MONERISwas used as input for ERGOM. We transformed the annualriver load data from MONERIS into monthly data, byapplying a typical annual dynamic of the nitrogen loads.This means, that results with a temporal resolution of amonth are in general reliable, but do not reflect realconditions. This has no consequences for this study, butmeans that no interpretation of model results with a hightemporal resolution should take place. Monthly averagesare the limit.

Nitrogen river loads: scenario and long-term trends

Definition of the “optimal” nitrogen scenario

Behrendt et al. (2005) calculated several scenarios, whichdescribe the effect of single management measures or setsof measures in the river basin on the nutrient loads into theOder river and the coastal waters. We focus on only onescenario, which links all best-practise measures in the river-basin and shows to what extent the nitrogen input in the

Fig. 3 Simplified conceptual diagram of the river-basin model MONERIS with its nutrient pathway sub-models (background picture modifiedafter LOICZ, Turner et al. 1998)

Nitrogen management in coastal waters

Oder River can be reduced. To 95%, the Oder River basinbelongs to Poland and the Czech Republic. Both countriesare member states of the European Community, but theirsewage water treatment quality does not comply with ECstandards, yet.

This optimal scenario is based on following assumptionsand measures: The emissions from point sources in the entireriver basin meet the requirements of the Urban Waste WaterTreatment Directive (91/271/EEC). The following thresholdsshall not be exceeded: Biologically Oxygen Demand(BOD) = 25 mg O2/l, Chemical Oxygen Demand (COD) =125 mg O2/l, SS = 35 mg/l, total phosphorus (TP) = 2 mg/l,total nitrogen (TN) = 15 mg/l for municipalities with apopulation between 10,000 and 100,000 as well as 1 mgTP/l and 10 mg TN/l for municipalities with more than100,000 inhabitants. The use of phosphorus free detergentsis assumed in Poland and the Czech Republic.

It is assumed that best management practices on arableland are implemented to reduce the load from diffusesources. Soil erosion is strongly reduced, as well. Con-servation tillage is applied on all arable land in the Oderbasin. The nitrogen surplus (difference between nitrogenfertilization and uptake by plants) is decreased by 20–30%.The nutrient load reduction in this scenario is realistic andthe required measures could be implemented during thenext two decades. However, we call it the optimal scenario.More details are given in Behrendt et al. (2005).

The total nitrogen emissions from all sub-basins for theperiod 1993–1997 are shown exemplary in Fig. 4. In 1993–1997 the average nitrogen load in the Oder was 118,400 t/a(Fig. 5). For the scenario, the model calculates a nitrogenemission of 77,600 t/a into the river (Fig. 5). In the scenario,the nitrogen emission is about 35% lower compared to1993–1997. These data cover the area upsteam until KrajnikDolny. At the Oder mouth, the emissions are about 5%higher, because the small rivers basins of Ina and Peoniacontribute additional nitrogen emissions into the river. In theoptimal scenario, a clear shift between the nitrogen sourcesis visible. Loads from point sources were reduced efficiently.The effect of best agricultural practices on a reduction ofnitrogen loads from diffuse sources is by far not that strong.In the scenario, tile drainage and groundwater contribute70% of the total loads, compared to 50% between the years1993–1997.

Nitrogen loads during the last decades

Figure 6 shows the long-term development of DissolvedInorganic Nitrogen (DIN) loads and Oder river discharge(Q) at the station Krajnik Dolny over the last 40 years. Thebars represent 5-year load averages. Basis for the loadcalculations are observed water discharge data which, in thefirst case “observed load”, were multiplied with riverine

nitrogen concentrations of the monitoring programme. Thesecond bar “calculated load” is based on observed waterdischarge multiplied with calculated MONERIS nitrogenconcentrations. The differences between the two bars givean indication about the uncertainties in load calculations.We base our study on the MONERIS calculations, whichare consistent over time and allow the comparison betweendifferent time periods.

The dissolved inorganic nitrogen loads for the mid1990’s, shown in Fig. 6, are the loads in the river. InFigure 5, the total nitrogen emissions into the river systemare shown and the retention in the river during the transportis not taken into account. Therefore, the loads in Fig. 5 arehigher.

The nutrient loads in the Oder River increased until thelate 1980s, declined steeply during the early 1990s, andslightly increased afterwards (Fig. 6). In wet years, the N-load discharged by the Oder can be up to twice as high as indry years. The decline of nutrient loads observed in theearly 1990s was largely an effect of the warm, dry yearsand cannot be attributed mainly to anthropogenic nutrientload reductions (Schernewski and Wielgat 2001). Duringthe last decade the slight decrease of loads reflect improve-ments in water treatment in the river basin, especially onthe Polish territory.

Figure 6 shows that in late 1960’s, the nitrogen load wasabout 35% lower compared to 1993–1993. Therefore, the

Fig. 4 Average annual total nitrogen emissions in sub-basins of theOder River and in the catchment of the Oder Lagoon during the period1993–1997 (modified after Behrendt et al. 2005)

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late 1960’s represent the nitrogen load of the optimalnitrogen scenario. This offers an opportunity for ouranalysis. There is no need to carry out new, largelyhypothetical model simulations with ERGOM to analysethe potential impact of a 35% nitrogen load reduction(optimal scenario) on coastal waters. Instead we cananalyse historical monitoring data and can utilise modelsimulations based on historical data, which hindcast thedevelopment in the coastal waters during the last 40 years.

The first step is to have a closer look at the water qualitydata in the estuary of the late 1960’s to get an impressionwhat the consequence of an optimal nitrogen managementin the river basin for the estuarine ecosystem would be.Data for this period is scarce. Therefore, we carried out

model simulations, covering the period from 1960 to 2000,and rely our analysis exclusively on these simulations. Ofcourse, this approach has several short-comings, which willbe discussed later in detail.

Impact on coastal waters

Late 1960’s (optimal scenario) versus mid 1990’s: temporalanalysis

The increase and decrease of nitrogen loads during thelast decades (Fig. 6) is well reflected in nitrogen (andphosphorus) concentrations in the lagoon. The average totalnitrogen concentrations show a decline between the late1980s and late 1990s from 160 to 130 μmol dm−3.However, intensive algal blooms, low water transparency,oxygen depletion in some parts, and fish kills are stillcommon. Toxic blooms of cyanobacteria, mainly Micocystisaeruginosa, have also been observed. Depending on thetrophic system, the present state can be classified aspolytrophic (LUNG) or hypertrophic (OECD 1982). Figure 7shows the average annual nitrate concentrations over the1990’s in the eastern (Wielki Zalew) and the western bay(Kleines Haff). It reflects the biological activity in thesesystems. During winter we observe the highest concentrationsand a steady decrease towards summer season takes place,because nitrate is taken up by phytoplankton and largelydepleted in the water column. Nitrate is a major nutrient forthe phytoplankton and during summer transformed into andstored in form of organic compounds. During winter nitrogenis abundant. Ammonium, a result of mineralization of organicmatter, is an additional source of nitrogen.

The annual dynamics of nitrate in the Pomeranian Bay isvery similar to the lagoon. With increasing distance fromthe Oder River the availability of nitrogen in the lagoon and

Fig. 6 Long-term development of Dissolved Inorganic Nitrogen(DIN) loads and Oder river discharge (Q) at the station Krajnik Dolny(5 year averages). MONERIS calculated the annual concentrations inthe river for the period 1960 until 2002. The loads were calculatedbased on discharge monitoring data and on MONERIS dischargecalculations. The results were aggregated to 5 year averages

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Average 1993–1997 Optimal scenario

Total N emissions118,400 [t/a] 77,600 [t/a]

Contribution of different sources [%]

Fig. 5 Average annual totalnitrogen emissions into the OderRiver (Krajnik Dolny) duringthe period 1993–1997 (left) andaccording to the optimal loadreduction scenario (right) (afterBehrendt et al. 2005).All sources apart from“Point sources” belong todiffuse sources

Nitrogen management in coastal waters

the bay decreases. In the eastern part of the lagoon, closeto the Oder River mouth, inorganic nitrogen compounds areeven in summer often available and a limitation of theprimary production due nitrogen shortage is likely only insome years. In the western lagoon the availability of nitrogenduring summer is much lower. In August, inorganic nitrogenis an important limiting resource in most years. However, inthe lagoon the nutrients levels are always sufficient tomaintain a very high algae biomass. In the open, off-shorePomeranian Bay, nitrogen is certainly the limiting elementduring the entire summer. In the Kleines Haff and thePomeranian Bay, phosphorus can play a limiting role in latespring, as well.

As mentioned before, an optimal nitrogen managementscenario in the river basin would cause a load reduction ofabout 35%, which is similar to the load situation in the late1960’s. To get an impression what the consequences of anoptimal load reduction scenario on the coastal waters wouldbe, we have a detailed look at water quality data of the late1960’s. Data is sparse, available only for the centre of thelagoon’s western bay and not all nitrogen compounds were

analysed. However, all nitrate data are shown in Fig. 7. Thecomparison of the concentrations of the late 1960’s with the1990’s does not reveal clear differences. The annual courseas well as the level of nitrate concentrations is very similar.It suggests that a nitrogen load reduction would have noeffects on nitrogen levels in the lagoon. However, thismight be an artefact and a mere result of the poor dataavailability.

The model simulations with ERGOM covering the 1960and 2000 provide alternative and more consitent informa-tion. Figure 8 shows a comparison between the simulatedconcentrations of Dissolved Inorganic Nitrogen (DIN) anddata for the mid 1990’s. DIN summarises the compoundsnitrate, nitrite and ammonium and gives an impression ofthe total available nitrogen for phytoplankton and primaryproduction. Taking into account that the model data wasaggregated to monthly values and that the monthly nitrogenload in the Oder River (a main model input) was derivedfrom annual load data, the results are very reasonable. Thedifferences in 1997 are partly due to the effects of theextreme river flood in summer and the simplified interface

Fig. 7 Nitrate concentrations (μmol/l) in the Wielki Zalew, KleinesHaff and the Pomeranian Bay. The figures show the average annualcourse of concentrations during the years 1990–1999. The red dotsindicate all available data from the 1960’s. The picture shows a blue-green algae bloom during August in the harbour of Mönkebude (Oder

Lagoon) 2001 (photo: Schernewski). Data sources: State Agency ofEnvironment, Protection of Nature and Geology Mecklenburg-Vorpommern (LUNG) and West Pomeranian Voivodeship Inspectoratein Szczecin (WIOS)

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between lagoon and bay. Altogether, we can conclude thatthe model is generally suitable for the simulation of ahistoric water quality.

Figure 9 shows the relative difference of DissolvedInorganic Nitrogen concentration between mid 1990’s andlate 1960’s, which reflect the nitrogen loads of the optimalscenario. Shown is the average annual course in the westernlagoon and in the Pomeranian Bay. According to the modelsimulation, the reduced nitrogen loads in the late 1960’sresult (in average) in 34.5% lower DIN concentrations inthe western lagoon. In the Pomeranian Bay, we receive a23% lower concentration. This reflects the retentionfunction of the lagoon for nutrients as well as the lateralmixing and transport processes in the Pomeranian bay. Thelatter means that the Pomeranian bay is not entirely drivenby the Oder loads. Especially for August, the model shows70% lower DIN concentrations in the lagoon and 60%lower concentrations in the Pomeranian bay compared tothe 1990’s. The nitrogen availability during summer, whennitrogen is the limiting nutrient, decreased and indicates asignificantly stronger limitation situation in the late 1960’s.

Late 1960’s versus 1990’s-a spatial analysis in the estuary

The spatial pattern of nitrate concentrations in the OderLagoon are dominated by the discharge of the Oder Riverinto the south-eastern part of the Wielki Zalew. The

concentrations show a decrease with increasing distancefrom the river mouth. Only in spring (and winter), thedischarge of lagoon water into the Baltic Sea via the Swinachannel shows pronounced gradients. At that time theconcentrations in the lagoon are very high and the uptakeby phytoplankton is still minor (Fig. 10). The figure isbased on measured monitoring data because the spatialmodel resolution is still too coarse for detailed spatialanalyses in the lagoon.

For the Pomeranian bay monitoring data of the 1960’s islacking and even recent monitoring data does not allowspatial analysis. Therefore, model simulations withERGOM are required to be able to analyse the spatialeffect of different nitrogen loads in the Pomeranian Bay.The results are shown for summer and winter (Fig. 11).

During summer, nitrogen is taken up by algae as soon asit enters the Pomeranian Bay and the nitrogen concentrationdecrease fast with increasing distance to the main outlet, theSwina Channel. In winter, the biological uptake is lackingand the river plume with higher nitrate concentrationscovers a larger area. The size of the river plume iscontrolled by uptake as well as horizontal and verticalmixing processes in the Baltic Sea. Its shape is determinedby the prevailing wind conditions and water currents. Alongthe southern Baltic Sea westerly winds, in average, cause awater flow towards east. Therefore, nutrients released intothe Baltic Sea are most often transported along the Polishcoast.

The comparison of the river plumes of the late 1960’sand the mid 1990’s show strong similarities in shape, butthe spatial size in the 1960’s was significantly lower. Therelative changes between the mid 1960’s and the late 1990’swere calculated on the basis of 2 years: 1968 and 1995(Fig. 11c, f). River plumes in summer and winter situationsof single years are much less smooth in shape and size.Weather conditions and hydrodynamic effects, like flow

Fig. 9 Relative difference [%] of Dissolved Inorganic Nitrogenconcentration between mid 1990’s and late 1960’s (optimal nitrogenload reduction scenario). Shown is the average annual course in thelagoon and in the Pomeranian Bay

Fig. 8 Concentrations of Dissolved Inorganic Nitrogen (DIN) inμmol/l in the lagoon and the Pomeranian Bay between 1993–1997.The line indicates monthly average model concentrations and the reddots the measured raw data. Data source: State Agency of Environ-ment, Protection of Nature and Geology Mecklenburg-Vorpommern(LUNG)

Nitrogen management in coastal waters

pattern, eddies and up-welling processes, play a much moreimportant role and are the reason for the unexpected shapeand pattern of the plume in these figures. The same is truefor Fig. 11c. However, in general, the nitrogen concen-trations in the Pomeranian Bay were much lower in the late1960’s both, in summer as well as in winter. The modelresults suggest that despite nitrogen shortages in the lagoonin summer during the mid 1990’s, significant amounts ofnitrogen passed the lagoon and entered the bay. It seemsthat the function of the lagoon as a retention pond fornitrogen, even in summer, is incomplete. However, moredetailed studies have to be carried out to be able todetermine the function of the lagoon as a transformationand retention unit for nitrogen in different seasons.

The effects of lower nitrogen concentrations in theestuary on algae biomass are shown in Fig. 12. Especiallythe summer situation is of interest, because of the relevancefor tourism and because of the function of nitrogen as alimiting element during that time. The algae concentrationsduring summer in the Pomeranian Bay in the late 1960’sare significantly lower compared to the 1990’s. Figure 11ccompares two concrete summers, 1968 and 1995. Inaverage, the chlorophyll-a concentrations were about 15%lower in 1968. However, the physical processes likecurrents, eddies and up-welling cause strong spatialgradients of chlorophyll concentration differences in thebay.

Discussion

In our river basin model simulation study we calculate thenitrogen loads in the Oder river of an “optimal” nitrogenmanagement in the river basin. We do not use this load datato carry out forecast simulations with our coastal model.Instead, we carry out a long-term hindcast simulation for1960 to 2002 and have a look in which period we find anitrogen load that is similar to this “optimal” scenario. Thisis true for the late 1960’s. The loads during for the late1960’s are about 35% lower compared to the mid 1990’sand in agreement with the load scenario. This approach hasseveral advantages. We can use a well calibrated andvalidated coastal and marine model that gives reliableresults for the late 1960’s. We don’t have the problem thatfuture changes in the ecosystem structure might createproblems for the reliability of the coastal model. Further,we can use highly resolved, real and reliable weather dataand do not have to speculate how the weather in futureyears might look like.

However, this approach has disadvantages, as well. Anitrogen load reduction of 35% which takes place now,might result in slightly different coastal ecosystems than theone observed in the late 1960’s. The most importantdifference is climatic change. The weather conditions inthe next decades will be different to the situation in the late1960’s. Loads are one driver for ecosystem quality, the

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0.55

8.5

2.8

4.3

19 21

34

50

69

1931

0.1

0.1

0.4

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11

3.3

8.3

8.8

13

6.8 26

28

48

85

4328

3.3

7.9

3.7

2.5 October

NO3-N[µmol/l]

Fig. 10 Average (median)spatial interpolation of measurednitrate-N concentrations(μmol/l) between April andOctober during the period 1990–1999. Data sources: StateAgency of Environment, Pro-tection of Nature and GeologyMecklenburg-Vorpommern(LUNG) and West PomeranianVoivodeship Inspectorate inSzczecin (WIOS). Modifiedafter Bangel et al. (2004)

G. Schernewski et al.

environmental conditions are another one. The reducednitrogen loads during the last decade are already influencedby changing environmental conditions, like warm and dryyears and this has implications for our results. Moredetailed analyses are needed to answer the question, howclimate change will interact with nutrient load reductions.

In general, the inter-annual variation of nutrient loads isfar above 35%, and stronger than the effect caused by theload reduction in the optimal nitrogen scenario. Therefore,the results of scenario approaches depend on the concreteyears, which are considered in a study. Inter-annualvariability due to short term weather conditions is muchmore important and superimposes general long-term trendsof Climate Change. However, we have to keep in mind thatthe results of the late 1960’s can only be transferred to thefuture with some uncertainty.

The total loads between the scenario and the late 1960’sis similar but the contribution of different nitrogen sourcesto the total load differs. In the late 1960’s nitrogen in

groundwater contributed only 25% instead of 34% in thescenario. Tile drainage was responsible for 19% instead of36% in the scenario. In general all diffuse, agriculturalscources had a lower relative contribution in the late1960’s. Point sources and especially urban areas had ahigher share. However, this has no consequences for oursimulations.

The definition of our nitrogen scenario is based on dataof the mid 1990’s. During the last decade, a decline ofnitrogen loads in the Oder River is observed and indicatesthat measures in the river basin, like an improved sewagetreatment, are successful. We can say that the nitrogen loadnowadays is already 10–15% lower compared to the mid1990’s. The recent positive development is a result of anongoing implementation of measures also assumed in ouroptimal nitrogen management scenario.

The Oder load causes strong spatial gradients of thenitrogen concentrations in the estuary. The spatial gradientsand the size of the river plume vary much throughout the

Fig. 11 ERGOM simulations ofthe Oder River plume in thePomeranian Bay during summerand winter. The figures showthe average concentrations ofDissolved Inorganic Nitrogen(NO3, NO2, NH4) in μmol/l 1966–1970 (a,c) and 1993–1997 (b,d). Figures e,f show therelative increase from the late1960’s until the 1990’susing the years 1968 and1995 as examples

Nitrogen management in coastal waters

year. These gradients are very important and have to betaken into account in the interpretation of data fromdifferent sampling stations. For example, the nutrientlimitation and its annual course as well as the definitionof reference conditions and a good water quality, accordingto the Water Framework Directive, depend very much onthe concrete location in the estuary. The large lagoon(Wiekli Zalew) behaves different than the small lagoon(Kleines Haff) or the Pomeranian Bay. Even within thesesystems strong spatial differences can be observed. Usually,spatial aspects are not taken into account in an appropriatemanner because of a lack of data. Model simulations canfill this gap.

To what extent can the nitrogen load in the Oder Riverbe reduced? The described optimal nitrogen managementscenario is a realistic aim and can be implemented duringthe next decades. So far, the nitrogen load reductions were aresult of reduced loads from point sources. To tackle diffusesources is much more complicated and during recent years,the diffuse loads did not show a decrease. On the opposite,a slight increase of nitrogen from diffuse sources isobserved. The improvements during recent years werefairly easy to reach and at reasonable costs. Further nutrientload reductions face increasing marginal costs and increas-ing costs might hamper ongoing efforts. Further, Poland’smembership in the European Community might cause agrowing economy and intensified agriculture. The resultcould be an increased nitrogen load from diffuse sources,which would counteract load reduction measures. There-

fore, it is uncertain whether the nutrient load scenario willbecome reality.

What will be the effects of much reduced nitrogen loadson coastal water quality? The comparison between waterquality and nitrogen availability in coastal waters betweenthe mid 1990’s and the late 1960’s gives a clear impressionof the efficiency of nitrogen load reductions. However, ingeneral not much can be expected with respect to animproved water quality. In the 1990’s and in the late 1960’sthe nitrogen availability limits the primary productionduring summer. In the late 1960’s the limitation periodwas most likely slightly longer. Other simulations show thata longer nutrient limitation period in summer would reducethe algae biomass (Schernewski et al. 2006). This is clearlya positive effect but nitrogen limitation periods favour blue-green algae (cyanobacteria) blooms. Blue-green algae areable to fix atmospheric nitrogen and to overcome shortagesof dissolved nitrogen in the water. Under nitrogen limitingconditions, other algae groups are not able to grow. Blue-green algae would face fewer competitors for otherresources (like light) and could possibly form intensivealgae blooms. This effect can be observed in the openBaltic Sea. Blue-green algae blooms would be a seriousthreat, because several species are toxic and are responsiblefor frequent swimming prohibitions along the Baltic coastsin summer already. Wasmund (2002) compiled toxicplankton events along the southern Baltic coast. In July1963 e.g. a blue-green algae bloom (Nodularia spumigena,Microcystis flos-aquae) caused the death of 340 ducks in

Fig. 12 ERGOM simulations ofthe Oder River plume in thePomerania bay during summer.The figures show the averageconcentrations of chlorophyll-ain μg/l 1966–1970 a and 1993–1997 b. c shows the relativeincrease from the late 1960’suntil the 1990’s using the years1968 and 1995 as examples.Picture: Blue-green algae bloomin the Baltic Sea in July 2006(photo: Krüger 2006)

G. Schernewski et al.

the Kleiner Jasmunder Bodden. However, due to a lack ofphytoplankton data for the late 1960’s we cannot say ifintensive blue-green algae blooms were a common featurein the Oder estuary at that time.

Can we reach a “good” water quality status according tothe Water Framework Directive? Recently, reference con-ditions, defining a very good water quality status in GermanBaltic coastal and transitional waters, have been published(BLMP 2007). The Pomeranian Bay belongs to themesohaline outer coastal waters with reference concentra-tions of 12–20 (0.5–0.9) μmol/l for total nitrogen (totalphosphorus). For oligohaline inner coastal waters, like theOder Lagoon, the reference values are not much different.According to Brockmann et al. (2005) a “good” waterquality can be defined up to 50% above the reference value.The concentrations are average concentrations betweenNovember and February. For the Oder River 15 (0.45)μmol/l total nitrogen (total phosphorus) are under discussion.

Nutrient concentrations are only supporting elements inthe European Water Framework Directive. The Directivefocuses on biological elements like phytoplankton, macro-zoobenthos and macrophytes. With respect to phytoplank-ton, chlorophyll a is used as an algae biomass indicator.Concentrations below 1.9 μg/l chl.a in the Pomeranian Bayand below about 2 to 20 μg/l in the lagoon during summerseason can be considered as a good status (Sagert pers.com.). These values are still under discussion. In the late1960’s, the nitrate concentrations between November andFebruary in the lagoon were in the range of 40–50 μmol/l and around 10–15 μmol/l in the Pomeranian Bay. Thechlorophyll concentrations during summer were in therange of 30–40 μg/l. All values are far above the suggestedvalues for a good water quality. The optimal nitrogenmanagement scenario will not be sufficient to decrease thenitrogen or chlorophyll concentrations during summer somuch that a good water quality will be reached.

Schernewski et al. 2006 carried out model simulationsfor the historic state (100 years ago) of the Oder Lagoon.Even 100 years ago, the water quality status was far abovethe suggested values for a “good” water quality accordingto BLMP (2007). Either the definition of a “good waterquality” has to be modified or we have to admit that a“good” water quality (at least in the lagoon) cannot bereached. A river basin of 120,000 km2 discharges itsnutrient load into the comparatively small Oder Lagoon(670 km2). The optimal nitrogen scenario would causewinter nitrogen concentrations of about 11 μmol/l totalnitrogen and ensure a good water quality in the Oder river.However, a good water quality in the river is not sufficientto ensure a good water quality in the lagoon. Its shallownessand the large river basin will keep the lagoon in an eutrophicstate. The system is a natural eutrophic system with limitedpossibilities for a successful water quality management.

How fast can we expect changes in the ecosystem afterthe implementation of load reduction measures? Behrendtet al (2005) calculated the time between the implementationof a measure and a new steady state of nitrogen inputs.While nitrogen inputs by tile drainage show a reaction tomeasures within years, it takes more than 20 years untilmeasures are fully visible in nitrogen concentration ingroundwater. Tile drainage and groundwater are the mostimportant nitrogen sources for the rivers. As a consequence,it will take decades until sets of measures in the river basinshow their full effect on coastal waters.

Coastal waters and especially coastal sediments show acertain memory effect. The water exchange time of about8 months in the lagoon means that concentrations in thewater body react fast to changes in nutrient loads becausethe nutrients are washed out into the Baltic Sea. Sedimen-tation and denitrification are additional efficient sinks in thelagoon and allow a fast adaptation to changing externalloads. During the last decades large amounts of nutrientswere stored in the sediment. Leipe et al (1998) calculatedan 100,000 t of nitrogen and about 30,000 t of phosphorusfor the upper 15 cm of the lagoon’s sediment in the mid1990’s. Recent data by Bachor (2005) support this nitrogenstorage. The amount of nitrogen stored in the sediment isequivalent to the annual Oder load, but only a fractionwould enter the lagoon and be available für the biologyduring a recovery period. With respect to nitrogen, thesediments in the lagoon will not be a long-lasting sourceand would not be able to counteract load reductionmeasures. This is very different for phosphorus.

Is it reasonable to focus our load reduction andmanagement efforts on nitrogen and what are the practicalconsequences for water management? The nitrogen loadreductions have positive effects on water quality in summer.However, aquatic ecosystems can overcome a lack ofnitrogen. Blue-green algae species are able to utiliseatmospheric nitrogen. Nitrogen fixation transfers atmo-spheric nitrogen into the water body and can compensatenitrogen load reductions due to measures in the river basin.If the measures assumed in the optimal managementscenario for nitrogen would take place, it would automat-ically reduce the phosphorus loads as well. The P-loadswould drop from 12,180 t/a to 4,650 t/a. It is not likely thatunder these much reduced loads, phosphorus limitationswill take place during summer but it could have impact onthe limitation of the algae bloom in spring. A managementexclusively focussed on nitrogen is not recommendable. Atleast phosphorus and possibly silicon have to be taken intoaccount, as well. Further studies will show if a managementfocussed on phosphorus will be promising.

Do nitrogen cuts benefit the Baltic Sea? To what extentcan our regional results contribute to this ongoing contro-versial discussion (Boesch et al 2006; Elmgren and Larsson

Nitrogen management in coastal waters

2001)? To neglect the nitrogen loads and to focus entirelyon phosphorus load reductions is, from our regional coastalperspective not recommendable. Nitrogen management hasa positive impact on water quality in our lagoons and innercoastal waters. Increasing blue-green algae blooms are apotential risk but a clear relationship between nitrogenloads and blue-green algae blooms has not been observed,so far. Our results are in agreement with Swedish examples.In the waters of the Stockholm archipelago, nitrogen loadsdeclined by about 50% after 1998 compared with the1980s, and algal production declined by about 15–40% inthe summer (Boesch et al 2006). According to Elmgren(pers. com.) the algae in the waters of the Stockholmarchipelago are short of nitrogen during summertime, likein the Oder estuary, and the decline in production candirectly be related to the nitrogen removal.

Acknowledgements The work has been supported by severalprojects during the last years: IKZM-Oder I, II & III (Federal Ministryfor Education and Research; 03F0403A & 03F0465A), SPICOSA(European Commission, Integrated Project) and “Investigation on thequantity of diffuse entries in the rivers of the catchment area of theOdra and the Pomeranian Bay to develop decision facilities for anintegrated approach on waters protection—Phase III” (UBA; 298 28299). Data has kindly been supplied by the State Agency of Environment,Protection of Nature and Geology Mecklenburg-Vorpommern (LUNG)and the West Pomeranian Voivodeship Inspectorate in Szczecin (WIOS).Super-computing power has been provided by HLRN (NorddeutscherVerbund für Hoch-und Höchstleistungsrechnen). We thank the modellinggroup of the Baltic Sea Research Institute for providing support on thecirculation model.

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