Modelling Nitrate Transport And

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Modelling nitrate transport and turnover in a

lowland catchment system

Gunter Wriedt *, Michael Rode

UFZ Centre for Environmental Research Leipzig-Halle, Department of Hydrological Modelling, Brueckstrasse 3a,D-39114 Magdeburg, Saxony-Anhalt, Germany

Received 22 February 2005; received in revised form 21 September 2005; accepted 12 December 2005

Summary Nitrate transport in groundwater dominated lowland catchment systems is influ-

enced by complex and spatially distributed physical and chemical interactions. A modelling

approach was developed combining a distributed soil nitrogen model with a three-dimensional

groundwater model and a reactive transport model linking nitrate turnover and availability of

reaction partners such as pyrite and organic matter. The modelling approach was applied to a

hypothetical case study based on data from the pleistocene lowland catchment ‘‘Schaugraben’’(20 km2) in the North of Saxony-Anhalt, with focus on the investigation of interactions of spa-

tially distributed transport and chemical processes. The modelling approach could successfully

simulate transport and turnover of nitrate in a groundwater dominated catchment. The

advancement of the nitrate front and the corresponding depletion of pyrite as well as the dis-

tribution of seepage fluxes and nitrate concentrations in seepage water in the channel system

showed distinct spatial variation. Surface water nitrate concentrations corresponding to the

average soil leachate concentrations were not completely reached after a simulation period

of 200 years for a conservative transport simulation. Under reactive conditions, about 80% of

the nitrate was lost due to denitrification. Given a uniformly distributed input of nitrate, drain

loads developed in a sigmoidal curve defined only by travel time distribution. The average tra-

vel time was 93 years. A distributed input of nitrate resulted in reduction of travel time to 80

years due to the different arrangement of source areas and flow.

The modelling approach is a step towards bridging the gap between simple large scale mod-

els and detailed small scale studies, maintaining process orientation while allowing to consider

landscape heterogeneity.

ª 2005 Elsevier B.V. All rights reserved.

KEYWORDSDiffuse pollution;

Reactive transport;

Groundwater;

Denitrification;

Modelling;Catchment;

Nitrate

Introduction

In lowland areas of Northern Germany, groundwater trans-port plays a key role for transport of nitrate from the soils

0022-1694/$ - see front matter ª 2005 Elsevier B.V. All rights reserved.doi:10.1016/j.jhydrol.2005.12.017

* Corresponding author. Tel.: +49 391 8109672; fax: +49 3918109699.

E-mail address: [email protected] (G. Wriedt).

Journal of Hydrology (2006) 328, 157 – 176

a v a i l a b l e a t w w w . s c i e n c ed i r e c t . c o m

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / j h y d r o l

mailto:[email protected]

mailto:[email protected]



into the surface water system. Denitrification processes andlong residence times in the groundwater result in surfacewater loads that often do not reflect the actual input situa-tion (Bohlke and Denver, 1995; Meissner, 2000; Behrend,1996; Reiche, 1994). Also mixing of older and youngergroundwater of different pollution determines surfacewater loads.

Factors influencing the fate of nitrate are, e.g. distribu-

tion of N-sources to soils and groundwater, chemical char-acteristics such as the distribution and availability ofreactive substances maintaining denitrification reactions,and physical properties like sediment heterogeneity, i.e.distribution of hydraulic conductivities and pore space,and density of the drainage network, determining residencetimes and flow paths in the catchment.

Transport and turnover processes are complex anddifficult to observe and quantify in the field. Processescannot be clearly separated by chemical data and spatialand temporal characteristics of N-transport phenomenaare difficult to resolve with available experimentalmethods. Models are a useful help for estimation of dif-fuse pollution of groundwater resources. They are essen-

tial for spatial and temporal inter- and extrapolation ofpoint measurements and snap-shots as for assessmentof scenarios such as management alternatives. In thecase of nitrogen pollution, ground- and surface watersin lowland areas respond slowly to a given input situationover years and decades. Thus there is a need to investi-gate possible future developments and system responseto define priority of measures and to target measureseffectively.

Considerable progress has been made in the field of soilnitrogen modelling and reactive groundwater transportmodelling. Coupling of soil and groundwater modelling is astraightforward approach for the investigation of interac-

tions between various processes related to the N-problem.However, although various integrated hydrological modelshave been developed, process-oriented modelling ap-proaches implementing coupled N-transport and turnoverin soils and groundwaters of lowland watersheds are stillmissing.

The main objectives of this study are to (i) test an inte-grated modelling approach combining selected modellingtools for simulation of N-transport and turnover in soilsand groundwater in a typical pleistocene lowland catchmentof Northern Germany on various spatial scales (lysimeter,transect and catchment), (ii) investigate the impact ofheterotrophic and autotrophic transformation processes onN-transport and (iii) analyse the interactions of spatially dis-

tributed nitrogen input with transport and turnover fromthe soil and groundwater passage to the surface water sys-tem on a catchment scale.

The study was intended to reveal interactions betweencatchment characteristics (such as land use distribution,geochemistry, channel and river system) and nitrogenconcentrations. Special attention was paid to the potentialN-load exfiltrating to surface waters with base flow. In thispaper, we outline the general modelling approach andpresent the results of an introductory nitrate transportsimulation in a hypothetical lowland catchment systembased on data from our experimental catchment‘‘Schaugraben’’.

Theoretical background

Hydrology of lowland catchment systems in

Northern Germany

Pleistocene landscapes are characterized by a mosaic of up-land areas and depressions. Height differences are in therange of metres and decametres. Wetlands and semi-terre-

stric soils cover wide areas. An intensive drainage is neces-sary and a more or less dense network of natural streamsand artificial drain channels can be found.

The sedimentary cover is made up of pleistocene andholocene sediments (glacial sand, till and loam, glacio-flu-vial deposits, cover sands, peat, alluvial deposits). Theaquifer system in pleistocene lowlands consists of more orless continuous and different groundwater floors forming lo-cal and regional flow systems. Correspondingly, solutetransport includes short and long distance components withtransit times of years to decades.

In semi-terrestric areas (wetlands), capillary rise fromgroundwater can play an important role, resulting in a de-

creasein netgroundwaterrechargeor even cause netground-water consumption. In these areas, leaching of substancescan also be partly reversed. In lowland areas characterizedby loose sediments, total discharge originates almost com-pletely from fast and slow baseflow according to Kunkel andWendland (1998). A dense river and drainage network will en-hance the contribution of fast flow components, decreasingthe ratio of slow components like deep groundwater flow.

Transport and turnover of nitrogen in soil and

vadose zone

Soil and vadose zone modelling of soil nitrogen dynamics re-

quires integration of various biogeochemical and physico-chemical processes as well as soil water and vegetationdynamics. The soil nitrogen cycle is an assembly of inputand output fluxes, N-pools and internal fluxes. The mainsources of nitrogen are (i) input of organic and mineral fer-tilizer from agriculture, (ii) incorporation of plant residuesinto soil organic matter, (iii) fixation of atmospheric nitro-gen by specialized symbiontic bacteria and fungi, and (iv)atmospheric deposition. The various inputs are incorporatedinto the soil as soil organic matter (organic N), ammonium-N, and nitrate-N. Mineralization, nitrification and denitrifi-cation processes control transformation of nitrogen be-tween the various pools. An effective removal of nitrogenfrom soil takes place by (i) plant uptake and relocation by

harvest, (ii) leaching of nitrate to groundwater caused bypercolation and (iii) denitrification, causing a transforma-tion into gaseous nitrogen (N2). For a detailed discussionof soil nitrogen processes see standard literature of soil sci-ence, e.g. Miller and Donahue (1995).

In soil systems, organic matter is the most importantelectron donor stimulating denitrification reactions. Thepool of soil organic matter is constantly regenerated bynet plant production and decomposition of plant residues.Therefore, soil denitrification might be limited by availablecarbon, but denitrification capacity is sustained. Subsoildenitrification is mainly driven by leaching of organic carbonfrom the topsoil and denitrification can be strongly limited

158 G. Wriedt, M. Rode



according to studies by Brye et al. (2001). Chemical trans-formation and sorption processes resulted in a constant de-crease of instable organic matter with depth (Siemenset al., 2003; Jorgensen et al., 2004). It can therefore be as-sumed, that the vadose zone is of low importance for nutri-ent turnover and denitrification because of the lowavailability of organic matter. Intensive turnover, however,is possible if a carbon source is available (Jorgensen et al.,

2004).

Groundwater nitrogen dynamics

Denitrification can be considered as the most importantnitrogen turnover reaction in groundwater. A review ofdenitrification in groundwater is given by Korom (1992).The general requirements for denitrification are in principlethe same as in soils: lack of oxygen, presence of denitrifyingbacteria and suitable electron donors. According to variousauthors cited by Wendland and Kunkel (1999), oxygen con-centrations limiting denitrification in groundwater range be-tween 1 and 5 mg/l. The most important denitrification

pathways are (i) organo-heterotrophic denitrification,where organic substances serve as electron donor, and (ii)litho-autotrophic denitrification, where reduced iron(Fe(II)) or reduced sulphur compounds act as electron do-nor. Pyrite (FeS2) is the most typical source of reduced sul-phur. Other possible electron donors are manganese andiron ions of a low oxidation stage (Mn(II),Mn(III),Fe(II)).

Organo-heterotrophic and litho-autotrophic denitrifica-tion are linked with two other important reaction pathways,decay or mineralization of organic matter and pyrite oxida-tion. A variety of substances may act as electron acceptor.O2, NOÀ

3 , Mn(IV), Fe(III), and SO2À4 are possible electron

acceptors used for oxidation of organic matter, being re-

duced to H2O, N2, N x Oy , Mn(II), Fe(II) and HSÀ

. The electronacceptors are utilised in a more or less defined sequenceaccording to their energy yield, expressed as redox poten-tial. Pyrite oxidation takes place utilizing O2 and NOÀ

3 aselectron acceptors in this sequence. Oxidation of pyritecauses a release of Fe2+, also acting as an electron donorfor reduction of nitrate.

The sequential oxidation of pyrite and organic mattercombined with groundwater flow results in a distinct zoningof hydrogeochemical conditions within the aquifer: Afterconsumption of oxygen nitrate will be used as electronacceptor. If pyrite is present, pyrite oxidation results in adistinct production of sulphate. After consumption of ni-trate, sulphate will be used as electron acceptor for oxida-

tion of organic matter (desulfurication), resulting in aproduction of hydrogen sulfide. As discussed by Postmaet al. (1991), this zoning is more or less well expressed infield, depending on reaction rates, amounts of reactive sub-stances and flow characteristics.

There are only few studies available, providing field mea-surements of reaction kinetics. Frind et al. (1990) found aNOÀ

3 -half-life constant for autotrophic denitrification of1.0–2.3 years and for desulfurication a SO2À

4 -half-life con-stant of 70–100 years assuming a first-order unlimited de-cay. In contrast, Molenat and Gascuel-Odoux (2002)reported half life constants for autotrophic denitrificationof 2.1–7.9 days and complete heterotrophic denitrification

within a few hours, based on investigations in pyrite-richschist aquifers of the Kervidy catchment, Brittany. Patschet al. (2003) reported half life for denitrification between1.3–3.4 years, in a pleistocene aquifer near Thulsfeld, Low-er Saxony. These discrepancies show that denitrificationrates are aquifer specific.

The reduction of nitrate by organic matter is thermody-namically favoured to nitrate reduction by pyrite. However,

if pyrite is present in the aquifer, denitrification is mainlycontrolled by pyrite oxidation. Pyrite oxidation is kineticallyfavoured, probably due to the different microbial availabil-ity of pyrite and organic matter (Postma et al., 1991,Bottcher et al., 1991). Considerable heterotrophic denitrifi-cation was not detected in pyrite-rich aquifers but may takeplace after consumption of pyrite. Half life times of hetero-trophic denitrification in the order of 100 years are sug-gested for forecasting purposes (Bottcher et al., 1991).

Soil organic matter does maintain groundwater denitrifi-cation in hydromorphic soils, where the groundwater tableis at least periodically located within the root zone (Wellet al., 2005). The denitrification capacity of deeper ground-waters is based on pools of sedimentary electron donors

only. These pools (sedimentary organic matter and pyrite)are limited, thus denitrification processes inevitably de-crease denitrification potential of the aquifer (Postmaet al., 1991; Korom, 1992).

Residence times in pleistocene groundwater systemsrange between years and decades. Kunkel and Wendland(1999) showed that in the Elbe river basin residence timesrange between less than one year and up to 250 years. Halfof the catchment area had residence times greater than 25years. Denitrification reactions cause attenuation of nitratein the aquifer system. As these reactions are slow reactionswith half life times of years, surface water pollution result-ing from groundwater exfiltration is influenced by the

arrangement of source areas in the catchment as well asthe distribution of reactive pools and the travel time char-acteristics in the catchment. These factors also control out-put into the surface water system.

Intensive experimental studies on the relation of ground-water age, input history, denitrification processes and ni-trate contamination were presented by Bohlke and Denver(1995) and Bohlke et al. (2002). They also point out theimportance of the input history , as the effect of manage-ment changes may interfere with residence times of similartimescales.

Recent modelling studies

In the last decades, numerous soil-nitrogen-models of dif-ferent complexity were developed, for example WHNSIM(Huwe, 1992), CANDY (Franko et al., 1995), ANIMO (Gro-enendijk and Kroes, 1997), RISK-N (Gusman and Marino,1999) and others. Soil-nitrogen-models are generally con-fined to the root zone, as they were developed to serve agri-cultural needs and to quantify soil losses. However,transport and turnover processes in the underlying vadosezone are principally the same. Many models were also ap-plied in distributed simulations for small and medium catch-ments, for example by Huwe and Totsche (1995), Reiche(1994), Kenkel (1999), Patsch et al. (2003).

Modelling nitrate transport and turnover in a lowland catchment system 159



Considerable progress has been made in reactive trans-port modelling of saturated media, including general geo-chemical models as presented by Van Capellen and Wang(1996) and Hunter et al. (1998) or specific studies focussingon nitrate transport as given by Widdowson et al. (1988),Bottcher et al. (1989) and Frind et al. (1990), Kinzelbachet al. (1991) and MacQuarrie and Sudicky (2001). A recentmodelling approach by Chen and MacQuarrie (2004) simu-

lates behaviour of organic carbon, nitrate and nitrogen iso-topes. The consideration of isotope behaviour makes suchan approach especially valuable for field studies, where dif-ferent kinds of field analyses are available to constrain themodel. Only recently a variety of reactive transport modelshas emerged, making flexible implementation of reactionsystems in three-dimensional saturated flow domains possi-ble, such as RT3D (Clement, 1997), PHT3D (Prommer, 2002)and TBC (Schafer et al., 1998). They couple geochemicalmodelling approaches with conventional transport codes.

Combining soil and groundwater models would be astraightforward approach supporting investigation of spatialpatterns of nitrogen distribution in small catchment systems.Still there are only a few studies following this approach to

simulate nitrogen transport in small catchments. Molenatand Gascuel-Odoux (2002) used MT3D to simulate groundwa-ter transport of nitrate in a shist aquifer in Brittany. Theseshists were rich in pyrite and no substrate limitation of auto-trophic denitrification occurred. Therefore a first-order de-cay function was used to simulate denitrification. Recentstudies aimed at the development of software tools for simu-lating changes in agricultural soil use and their effect ongroundwater for small catchment areas (Patsch et al.,2003). This modelling approach is based on the soil–water-and nitrogen-models HERMES (Kersebaum, 1995), SWAP/AN-IMO (Van Dam et al., 1997; Groenendijk and Kroes, 1997)andWAVE(Vanclooster et al.,1994) forsimulating soil andva-

dose zone processes. Groundwater processes are simulatedusing MODFLOW and MT3D, including first-ordernitrate decaycaused by autotrophic and heterotrophic denitrification.Applications of these modelling tools are given by Patschetal.(2003) fora Pleistocene catchmentin Thulsfelde, LowerSaxony, and by Diankov et al. (2003) for a study site of 4 ha inChelopechene, Bulgaria. All of these studies consider nitrateturnover as a first-order decay reaction,using thewidespreadMT3D-code. Heterotrophic denitrification and autotrophicdenitrification are not considered as separate processes anddenitrification is described by one parameter (first-order de-cay constant). The implicit assumption is made that reactivepools are not depleted and do not limit turnover rates withinthe simulation period. However, to study interactions be-

tween physical and chemical catchment properties in heter-ogeneous catchments, it is necessary to account foravailability and consumption of reaction partners. Therefore,groundwater transport simulations need to include full reac-tive approaches.

Material and methods

Outline of the integrative modelling concept

The modelling approach was based on combined applicationof different submodels simulating water flow and nitrogen

transport and turnover in soil and groundwater. The modelswere loosely coupled, using results from the precedingmodel as input for the subsequent model.

Soil processes were simulated using mRISK-N (Wriedt,2004), a combination of the SIMPEL soil water balance mod-el by Hormann (1998) and the soil nitrogen model RISK-N(Gusman and Marino, 1999). Soil water dynamics was simu-lated using a conceptual storage approach with precipita-

tion and potential evapotranspiration as driving variables.The soil nitrogen submodel considered major nitrogen trans-formations including mineralisation, nitrification and deni-trification in soil systems and calculated leaching ofnitrate to groundwater. Ammonia volatilization was consid-ered as a constant fraction of fertilizer input. A fraction of20% was applied for manure and of 10% for mineral fertil-izer. Soil denitrification rates were coupled to temperatureand water content. To account for organic matter content,the denitrification constant was set soil specific allowing fordenitrification rates between 1 kg N/ha/a in sandy soils andup to 25 kg N/ha/a in humic gleyic soils if anaerobic condi-tions occur. The mRISK-N model operated on a one-dimen-sional soil column. Distributed modelling was realized with

a grid-based approach using the software RISKNREGIO(Wriedt, 2004). Based on grids of soil type, land use typeand groundwater level a unique simulation run was set upfor each raster cell. The soil model grid was consistent withthe groundwater model grid such that the soil simulation re-sults could directly be imported into the groundwatermodel.

Groundwater flow and solute transport were simulatedusing MODFLOW (McDonald and Harbaugh, 1988) and RT3D(Clement, 1997). MODFLOW is a three-dimensional finite-difference groundwater flow model. RT3D is a three-dimen-sional solute transport model allowing for implementationof reactive processes based on kinetic rate equations.

RT3D offers a broad range of solution algorithms to solvethe three-dimensional convection-dispersion equation formulti-species transport.

To implement nitrate transformations in groundwater, aspecial reaction module was developed for the RT3D model(Wriedt, 2004). This reaction module includes organic mat-ter oxidation by oxygen, nitrate and sulphate as well as oxi-dation of pyrite by oxygen and nitrate. Secondary reactionssuch as desulfurication and nitrification were also consid-ered to track the general development of groundwaterchemistry. The main reactions are given in Table 1. Thereactions were implemented as first-order and monod-typerate expressions (Table 2). All rate constants were compiledfrom literature data. Following Bottcher et al. (1989) we as-

sumed half life constant of 2 years for autotrophic denitrifi-cation and 76 years for desulfurication. The heterotrophicdenitrification rate constant was derived from a field scaletracer experiment conducted in surface-near groundwaterunder gleyic soils within the Schaugraben study area (Blank,oral communications). This rate constant constitutes a con-siderably fast denitrification reaction (half life time 3months). In deep groundwater, heterotrophic denitrificationis limited, however, by the availability and reactivity oforganic matter. Due to biogeochemical transformationand sorption processes, the reactivity of old sedimentaryorganic matter may differ considerably from fresh organicmatter leaching from the soil. To account for the different




reactivity of organic matter, we introduced a release func-tion (Table 2, Reaction (4)) simulating transfer from achemically inert pool of sedimentary organic matter into a

pool of dissolved organic matter available for turnover reac-tions. This conceptual approach controls (and limits) theavailability of sedimentary organic matter for biogeochem-ical processes. Sequential oxidation of organic matter andpyrite by oxygen and nitrate is controlled by inhibitionterms. Temperature dependency of reaction rates was con-sidered using Van’t Hoff’s equation. The groundwater modeldid not include a heat transport model, therefore morecomplex temperature relationships were rejected.

Special tools were developed supporting the setup of agrid based distributed soil simulation, data transfer be-tween the models and analysis of model results. A generalscheme of the modelling approach is given in Fig. 1.

Study area ‘‘Schaugraben catchment’’

The case study was based on data from the ‘‘Schaugraben‘‘

catchment close to Osterburg (Altmark) in the North of Sax-ony-Anhalt. The Schaugraben catchment covers an area of20.1 km2 and is made up from glacial till with cambisolsand luvisols in the upper parts (30–45 m a.s.l.) and glacio-fluvial deposits with gleyic soils in the lower parts (20–35 m a.s.l.). The mean annual precipitation is 548 mm/a,the average annual temperature is 9.0 °C, ranging from0.8 °C in January to 18.1 °C in July. Land use is dominatedby agriculture (66%), followed by pasture land (18%) and for-est (13%). The area is artificially drained using a system ofopen drain channels.

The geology of the area is characterized by glacial tilland glaciofluvial sands deposited during the Saalian

Table 2 Rate expressions used in reaction-module A corresponding to the chemical reactions defined in Table 1

R1 ¼ k1eff Á ½DOM Á ½O2 Á

½DOM

T þ ½DOM 2

Á½O2

T þ ½O2 2

ðR1Þ

R2 ¼ k2eff Á ½DOM Á ½NOÀ

3 ÁI2

I2 þ ½O2Á

½DOM

T þ ½DOM

2

Á½NOÀ

3

T þ ½NOÀ3

2

ðR2Þ

R3 ¼ k3eff Á ½DOM Á ½SO2À

4 ÁI2

I2 þ ½O2Á

I2

I2 þ ½NOÀ3

Á½DOM

T þ ½DOM

2

Á½NOÀ

3

T þ ½NOÀ3

2

ðR3Þ

R4 ¼ k4eff Á ð½rOMmax À ½rOMÞ.½SOM ðR4Þ

R5 ¼ k5eff Á ½O2 Á

½O2

T þ ½O2

2

ðR5Þ

R6 ¼ k6eff Á ½NOÀ

3 ÁI2

I2 þ ½O2Á

½NOÀ3

T þ ½NOÀ3

2

Á½FeS2

T þ ½FeS2

2

ðR6Þ

R7 ¼ k7eff Á

½Fe2þ

K 1m þ ½Fe

2þ

Á½O2

K 2m þ ½O2

Á½Fe2þ

T þ ½Fe2þ

!

2

Á½O2

T þ ½O2

2

ðR7Þ

R8 ¼ k8eff Á

½Fe2þ

K 1m þ ½Fe2þÁ

½NOÀ3

K 2m þ ½NOÀ3

Á½Fe2þ

T þ ½Fe2þ

!2

Á½NOÀ

3

T þ ½NOÀ3

2

ðR8Þ

R9 ¼ k9eff Á

½NHþ4

K 1m þ ½NHþ4

Á½O2

K 2m þ ½O2Á

½NHþ4

T þ ½NHþ4

2

Á½O2

T þ ½O2

2

ðR9Þ

Table 1 Reaction equations of the RT3D reaction module

CH2O þ O2 ! 2Hþ þ CO2À3 ðR1Þ

CH2O þ 0:8NOÀ3 ! 1:2Hþ þ CO2À

3 þ 0:4N2 ðaqÞ þ 0:4H2O ðR2Þ

CH2O þ 0:5SO2À4 þ 2:5Hþ ! CO2À

3 þ 0:5HSÀ þ 2H2O ðR3Þ

CH2OðsÞ $ CH2O ðaqÞ SOM $ DOM ðR4Þ

FeS2 þ 3:5O2 þ H2O ! Fe2þ þ 2SO2À4 þ 2Hþ ðR5Þ

FeS2 þ 2:8NOÀ3 þ 0:8Hþ ! Fe2þ þ 2SO2À

4 þ 1:4N2 ðaqÞ þ 0:4H2O ðR6Þ

FeðOHÞ3ðsÞ þ 2Hþ $ Fe2þ þ 0:25O2 ðaqÞ þ 2:5H2O ðR7Þ

FeðOHÞ3ðsÞ þ 0:1N2 ðaqÞ þ 1:8Hþ $ Fe2þ þ 0:2NOÀ3 þ 2:4H2O ðR8Þ

NHþ4 þ 2O2 $ NOÀ

3 þ H2O þ 2Hþ ðR9Þ

Stoichiometry is referred to the unit electron donator to simplify calculations.


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glaciation. Locally, glaciofluvial sands form an upper aquiferwith a thickness between 2 and 8 m. The upper aquifer isunderlain by heterogeneous glacial tills varying in thicknessbetween 0 and 22 m. Below the till deposits a lower sandy

aquifer with 10–40 m thickness has formed. Few pumpingtests from areas close to the study area indicate conductiv-ities up to 17–34 m/d.

A variety of experimental studies have been carried outinvestigating nitrate transport in soils and groundwater(Meissner, 2000; Meissner et al., 1999), including a monitor-ing of land use and management practices since 1990, anddischarges and substance loads at the central gauging sta-tion P5 since 1997. A map of the study area is provided inFig. 2

Lysimeter data were available from the nearby Lysimeterstation Falkenberg. Data from 4 lysimeters were used cover-ing two management practices and two soil textural classes.

Management practices included (i) grassland (Lysimeter 03and 04) and (ii) integrated management (Lysimeter 05 and07), i.e. crop rotation of sugar beet, wheat, potatoes, bar-ley and maize with organic fertilization and intercrops. Soiltextural classes covered by the lysimeters were sand (Lysim-eter 04 and 07) and loamy sand (Lysimeter 03 and 05). Thelysimeter data included management records, fertilizeradditions, irrigation, amount of crop harvested and N-con-tent of harvested crops for the period from 1982 till 2000.Monthly leaching rates of water and nitrate were given since1991. Initial conditions were determined by repeated simu-lation runs using final conditions as new initial conditions.Model evaluation was based on the period 1991–2000, thepreceding years were taken as an additional warm-up

period.The data used for modelling catchment scale soil water

and nitrogen processes included site-specific land use andmanagement records, including information on crop typesand fertilizer additions, climatic data from the nearby sta-tion in Falkenberg and a soil map 1:50,000 of the study area.Catchment data included a period of 13 years from 1990 to2002. Soil physical properties were derived from texturaldata according to AG Boden (1994). For pasture land, an in-put scenario of N-fertilizer was defined based on total live-stock, average grazing time and the area of pasture land.Average fertilizer additions range between 20 and200 kg N/ha/a as displayed in Fig. 3.

A hydrogeological model defining substrate distributiondown to a depth of 50 m below surface was set up for thestudy catchment and the surrounding area. It extends tothe circumfluent rivers and forms the basis of a regionalgroundwater flow model. The hydrogeological model coversan area of 96 km2 and was constructed based on the geolog-ical map 1:50,000 and 78 borehole profiles. Of those, 28profiles covered a depth less than 10 m and 15 borehole pro-files covered the range between 10 and 20 m. The remaining

profiles extending down to depths between 20 and greaterthan 50 m. Groundwater level observations were availablefor 26 boreholes in that area.

Model setup

The modelling process followed a nested modelling ap-proach based on a regional flow model and a catchmentmodel.

The distributed soil model was run to calculate ground-water recharge and nitrate leaching as input data to thegroundwater models. Based on the soil and land use gridsand the associated soil parameters and management

Figure 2 Map of drainage system and land use in the

Schaugraben study area.

Figure 1 General modelling approach – submodels and modelling software.




records, a distributed soil model was set up. For the catch-ment model, the soil model was revised accounting for thedifferent grid extent and grid resolution. The results werewritten as grid data which could be imported into thegroundwater model preprocessing software.

A three-dimensional, steady-state regional groundwaterflow model was set up for the area covered by the hydrogeo-logical model. The horizontal grid resolution was 100 m, thevertical resolution 7 layers distributed over a depth of 40–50 m below surface. The model boundaries were definedby the surrounding river stages. Hydraulic conductivitieswere set initially to 6.0 m/d for the upper sand aquifer,

0.2 m/d for glacial till and 6.0 m/d for the lower sand aqui-fer. Calibration on groundwater table and average dischargerequired modification of hydraulic conductivity in the upperaquifer to 15.0 m/d, which is close to the observed values gi-ven above. Groundwater recharge of 78 mm/a was takenfrom the distributed soil simulation. The regional groundwa-ter flow model served as a base for delineation of catchmentboundaries and provided necessary boundary conditions(constant head boundaries) for the catchment model. Thecatchment boundary based on the main gauging station P5was derived using a particle tracking analysis. For this catch-ment area a new model grid was defined with a horizontalgrid resolution of 50 m carrying the same geological informa-tion as the regional flow model. Calculated groundwater

heads were then transferred to the catchment model, ini-tializing constant head boundaries and the initial headdistribution.

The catchment model was extended for conservative andreactive nitrate transport simulations. Reaction parametersof the groundwater reaction module were based on litera-ture data (see above and Table 3).

The model starts from an hypothetical initial state withsoil inputs from the beginning and runs over a simulationperiod of 200 years. This time scale was necessary to followthe catchment reaction on continuing nitrate loads, be-cause we expected travel times in the range of several dec-ades. If the simulation period was limited to the period of

13 years where land use data were available, results wouldonly reflect the effect of areas connected to the channelsystem by travel times less than 13 years. Neither historicalland use data nor reasonable future projections of land usewere available during the project and we assumed a con-stant land use over the entire simulation period. The hypo-thetical previous input history has been consideredassuming pyrite depletion in the upper model layer.

Groundwater was considered to be initially free of nitrateand of oxygen. The background content of pyrite was0.01 mass% (0.8 mmol/kg) in the rest of the aquifer. Thisconcentration was chosen to be within the range of typicalvalues of 0.5 and 1.7 mmol/kg (60–200 g S/m3 sediment)reported by Bottcher et al. (1989) and Frind et al. (1990)for the Pleistocene aquifer Fuhrberger Feld in NorthernGermany. The background content of organic matter wasset to 0.1 mass% (5000 mg/l-Water). Below gleyic and histicsoils along the Schaugraben drain channel a higher availabil-ity of organic matter up to 10 mass% was assumed for 10% ofthe area.

Catchment data did not support falsification of the dis-tributed soil model. Therefore the soil model was tested

against groundwater recharge and nitrate leaching from se-lected lysimeters provided by the UFZ lysimeter station inFalkenberg, 15 km North–West of the study area. Themodel was first run with physical properties such as fieldcapacity and hydraulic conductivity derived from texturaldata. The automatic parameter estimation program PEST(Doherty, 2002) was used for model calibration. Becauseof its flexible structure, PEST can be adopted to any kindof model. Additionally, parameter estimation can be doneusing fewer simulation runs than any other estimationmethod. In a second step, chemical parameters such asthe denitrification rate constant or the mineralization rateconstants were calibrated to observed data. The objective

criteria used for soil model testing were the Nash–Sutcliffecoefficient E defined as

E ¼ 1 À

Pni¼1ðOi À P iÞ

2Pn

i¼1ðOi À OÞ2

E 2 À 1; 1

and the volumetric error defined as

VE ¼

POiPP i

À 1

Á 100 ½%.

where O is the mean of the observed value, Oi is the ob-served and P i is the simulated value.

The Nash–Sutcliff coefficient measures the ability to

represent the dynamics of the system, the volumetric errorrepresents the overall mass balance error between modeland observed system.

Potential uncertainty of input data was evaluated by esti-mating error ranges for the nitrogen balance terms atmo-spheric deposition and plant uptake and comparing themwith average nitrate leaching rates as calibration target.

The regional groundwater flow model was calibratedagainst observed water levels and catchment discharge tosatisfy catchment water balance. Additionally, sensitivitiesof the groundwater surface to hydraulic conductivities ofthe aquifer were calculated using the normalized 10% elas-ticity index defined as

Figure 3 Mean annual fertilizer input [kg N/ha] in the

Schaugraben catchment.




e0:1 ¼ O1:

1P À OP 1:1P À P Á P OP

¼ O1:

1P À OP 0:1 Á OP

where P = parameter value, 1.1P = parameter value in-creased by 10%, OP = observation at parameter P ,O1.1P = observation at parameter value 1.1P . The elasticityindex was calculated for each grid cell of the groundwatermodel yielding a map of groundwater surface sensitivity.

The transport model was not validated against observeddata, as available field data did not reflect the temporal andspatial dimension of the relevant processes. With the multi-reactive and multi-species transport approach, both, het-erotrophic and autotrophic denitrification, were consideredby the groundwater model. Total denitrification could cal-

culated from the nitrate balance using nitrate input, outputand aquifer storage. Autotrophic and heterotrophic denitri-fication of nitrate could be quantified from the mass bal-ance of the particular reaction partners (e.g. reduction ofpyrite content or organic matter).

Different input scenarios of nitrate leaching were de-rived from the soil simulation to study the effect of differ-ent input distributions on transport and exfiltration ofnitrate. In the first scenario distributed nitrate leachingwas considered, in the second scenario, nitrate leachingwas averaged over the entire study area, giving a uniforminput, and the third scenario considered distributed nitrateleaching with a buffer stripe of 100 m width along the chan-

nel system, where no nitrate leaching took place. All sce-narios were calculated using reactive and conservativetransport conditions.

For the groundwater simulation constant soil nitrateleaching rates were considered over the total simulationperiod. As the research focus was on the interaction be-tween nitrate transport and catchment properties and noton predicting the effects of land use changes, no assump-tions were made regarding the future or past developmentof nitrate leaching and the present state scenario basedon land use records over 13 years was extrapolated overthe total simulation period. A simulation period of 200 yearswas necessary to follow the output of nitrate into the sur-face water system. The following results were extracted

from the catchment scale simulation:

• Distribution of nitrate concentrations and other sub-stance concentrations (pyrite, sulfate) in the aquiferalong a transect cutting through the model after 50 and200 years of simulation.

• Distribution of nitrate concentrations in different modellayers after 50 and 200 years of simulation.

• Maps of groundwater exfiltration rates into the channelsystem and associated nitrate concentrations.

• Temporal development of average nitrate concentrationsin the channel system resulting from groundwaterexfiltration.

Table 3 Default parameter set of the reaction-module

Parameter Reaction module A Reference A [B]

A. Mineralisation of dissolved organic matter

1. K 1eff 1.92eÀ1 Estimated

2. K 2eff 1.12eÀ1 Based on field scale tracer experiment

IO26.25eÀ6 Estimated

3. K 3eff 2.64eÀ6 Bottcher et al. (1989), Frind et al. (1990)

INO3 1.6eÀ5 Estimated

B. Transfer of SOM to rOM

4. K 4eff 6.0eÀ9 PHT3D/PHREEQC database (Prommer, 2002; Parkhurst and Appelo, 1999)

DOMmax 0.00067 (=20 mg/l)

C. Oxidation of pyrite (FeS2)

5. K 5eff 10eÀ5.3 Kamei and Ohmoto (2000)

RSA 2.69eÀ1 [m2/lbulk ]

6. K 6eff 3.925eÀ12 Bottcher et al. (1989), Frind et al. (1990)

IO26.25eÀ6 (=0.20 mg/l) Estimated

D. Oxidation of Fe2+ by O2 and NOÀ3

7. K 7eff 5eÀ9 Hunter et al. (1998)

MFe 1eÀ5 Min3P database (Mayer et al., 2002)

MO2 3.125eÀ5 Min3P database (Mayer et al., 2002)8. K 8eff 5eÀ9 Hunter et al. (1998)

MFe 1eÀ5 Min3P database (Mayer et al., 2002)

MNO38eÀ5 Min3P database (Mayer et al., 2002)

IO23.125eÀ6 (=0.1 mg/l) Estimated

E. Nitrification

9. K 9eff 1.16eÀ5 MacQuarrie and Sudicky (2001)

MNH46.25eÀ6 (=0.1 mg/l)

MO23.125eÀ6 (=0.1mg/l)




Results

Model verification

The results of the lysimeter simulations including observedand calculated groundwater recharge and N-leaching are gi-ven in Table 4 on an annual basis and are also illustrated inFigs. 4 and 5 for the lysimeters 03 and 05. The annual water

balance was well represented although some larger devia-tions in single years occurred. Mean groundwater rechargerates were 109 and 98 mm/a for the grassland lysimeters03 and 04 and 136 and 110 mm/a for the crop lysimeters05 and 07. Volumetric errors ranged between À6% and 30%and Nash–Sutcliffe coefficients were between 0.88 and0.97 for the calibration period. For the validation period,performance was not good especially in Lysimeters 04 and05 but acceptable with volumetric errors between À3%and +27% and Nash–Sutcliffe coefficients between 0.22and 0.83. The goodness-of-fit criteria of the lysimeter sim-ulations are summarized in Table 5. Using PEST for parame-ter optimization did not yield a good performance comparedto a trial and error calibration with Nash–Sutcliffe indicesbetween 0.53 and 0.93 and volumetric errors betweenÀ38% and 32% during the calibration period, because in-tra-annual soil water dynamics showed a lag compared tothe observed data that was insensitive to model parame-ters. The optimization algorithm forced the model into aminimum error, but without preserving the intra-annual soilwater dynamics. The trial-and-error method facilitated to

consider the representation of seasonal water dynamics asadditional criteria for calibration.

Average nitrate leaching rates of 19 and 16 kg N/ha/a forthe grassland lysimeters and 54 and 49 kg N/ha/a for thecrop lysimeters overestimated observed data by a factorranging between 1.5 and 1.9 (Table 4). The ability to repre-sent inter-annual dynamics was poor. On the one hand,nitrogen dynamics strongly depend on soil water dynamicsand therefore deficits of the latter will propagate throughthe nitrogen simulation. On the other hand, N-leaching ratesare small compared to N-input and the associated potentialerrors (see Discussion).

Table 4 Calculated and observed annual groundwater recharge and nitrate leaching rates of four selected lysimeters

Lysimeter03 (Year)

Recharge (mm/a) N-leaching (kg N/ha/a) Lysimeter04 (Year)

Recharge (mm/a) N-leaching (kg N/ha/a)Calculated Observed Calculated Observed Calculated Observed Calculated Observed

1992 110 101 11.1 60.5 1992 116 82 16.5 16.1

1993 97 58 5.6 11.3 1993 42 61 3.9 11.1

1994 248 260 27.5 14.8 1994 217 236 24.4 18.5

1995 98 126 7.4 11.7 1995 98 140 6.6 13.5

1996 17 0 1.2 0.0 1996 16 0 1.1 0.0

1997 19 21 1.1 7.7 1997 19 47 1.5 18.7

1998 162 111 13.5 23.5 1998 149 134 18.0 45.4

1999 120 150 9.2 8.4 1999 102 149 6.9 8.4

2000 113 91 17.2 33.2 2000 123 76 16.8 10.3

Mean 109 102 10 19 Mean 98 103 11 16

Lysimeter 05 (Year) Lysimeter 07 (Year)

1992 165 126 39.3 117.1 1992 135 124 38 135

1993 127 87 33.6 76.6 1993 84 69 33 79

1994 260 245 22.1 39.9 1994 240 229 35 37

1995 98 106 9.0 35.1 1995 98 106 10 31

1996 61 0 7.0 0.0 1996 21 0 3 0

1997 39 35 5.1 18.4 1997 18 25 4 6

1998 192 151 46.0 99.1 1998 158 136 51 78

1999 142 148 51.3 63.2 1999 117 135 45 54

2000 146 73 36.6 32.9 2000 116 61 40 21

Mean 136 108 28 54 Mean 110 98 29 49

Figure 4 Observed and calculated groundwater recharge and

nitrate leaching for a pasture lysimeter.




The sensitivity of groundwater levels to changes inhydraulic conductivity was low with sensitivity indices be-tween À0.09 and 0.06. Sensitivity increased with distancefrom the channel system (Fig. 6). Catchment dischargeshowed a slightly higher sensitivity to hydraulic conductivi-

ties with sensitivity indices between À0.04 and À0.08 for agroundwater recharge of 90 mm/a (Fig. 7). The groundwa-ter surface is largely determined by drain elevation as a gen-eral head boundary, catchment discharge is constrained bythe catchment water balance, although some of the waterleaves the catchment on subsurface pathways across con-stant head boundaries. The calibrated groundwater surfacewith error bars is given in Fig. 8, and the correspondinggroundwater level observations in Fig. 9. The mean errorof groundwater level was 0.61 m, with groundwater levelsranging between 20 and 36 m a.s.l. Large deviations of upto more than 2 m occurred at some individual observationwells and were observed in all simulations throughout thewhole calibration process.

Soil leaching

The distributed soil simulation provided the basic input sce-nario for the subsequent groundwater simulation. Table 6summarizes basic input data as well as simulated groundwa-ter recharge and N-leaching by land use classes. Groundwa-

ter recharge with an average rate of 78 mm/a and rates of64 mm/a for grassland and 89 mm/a for cropland are con-siderably lower than rates obtained from lysimeter dataand the difference between grassland and cropland is muchmore pronounced. The differences between lysimeter data

Table 5 Model fit based on observed and simulated annual groundwater recharge for different lysimeters for the calibration and

validation period using automatic optimization and trial and error calibration

Calibration of groundwater recharge Nash–Sutcliff model

efficiency

Volumetric error

Initialrun

PESTrun

Trialand error

Initialrun (%)

PESTrun (%)

Trial anderror (%)

Lysimeter 03 Calibration (1991–1996) 0.63 0.91 0.93 32 À15 5

(Pasture) Validation (1997–2001) À0.27 0.69 0.54 43 À20 11

Lysimeter 04 Calibration (1991–1996) 0.53 0.53 0.88 32 32 À6

(Pasture) Validation (1997–2001) À0.78 À0.78 0.22 16 16 À3


(Integrated Management) Validation (1997–2001) 0.3 0.59 0.83 27 À20 27


(Integrated Management) Validation (1997–2001) À0.44 À0.22 0.59 55 À48 15

Figure 6 Sensitivity of the upper groundwater surface to

hydraulic conductivity of glacial till in the regional flow model.

Figure 7 Sensitivity of discharge to changes of hydraulic

conductivity in the upper sand (Sand1), the underlying glacial

till or in the lower sand of the second aquifer (Sand2).

Figure 5 Observed and calculated groundwater recharge and

nitrate leaching for a lysimeter with integrated management.




and catchment simulation result from the different configu-ration of soils in the study area, which are largely underlainby loamy sediments in contrast to the free drainage situa-tion of the lysimeters.

The distribution of nitrate concentrations in the soilleachate (Fig. 10) clearly corresponded to the different lev-els of fertilizer input (Fig. 3) and soil denitrification poten-tial of the single areas. Especially in areas close to thechannel system, presence of gleyic and histic soils rich in or-ganic matter resulted in low nitrate leaching rates becausedenitrification was enhanced. In many agricultural areas in-stead, where soil denitrification potential was low, nitrateconcentrations were distinctly higher.

Propagation of nitrate in the aquifer and

interaction with reactive species

Model results include the spatio-temporal development ofconcentrations of nitrate and other substances within theaquifer. Fig. 11 shows concentration of nitrate in the upperand deep groundwater after a simulation period of 50 yearsfor the reactive and conservative transport simulation. Thedistribution of nitrate is closely related to the distributionof nitrate leaching rates from the soil. In the reactivetransport simulation, nitrate did not arrive in the deep

Table 6 Average nitrate inputs and simulated outputs for land use classes in the study catchment, observation period 1990–

2003

Land use Area [ha] Simulation input data Simulation resultsAtmospheric

depositiona

[kg N/ha]

Mineral

fertilizera

[kg N/ha]

Organic

fertilizera

[kg N/ha]

Gross plant

uptakeb

[kg N/ha]

Ground water

recharge

[mm]

Nitrate

leaching

[kg N/ha]

Pasture 345 60 176 8 210 64 ± 14 80 ± 5

Arable land 1258 60 108 ± 25 35 ± 24 165 ± 39 89 ± 12 160 ± 11

Forest 258 60 0 0 173 49 ± 14 30 ± 2

Settlement 59 60 60 0 39 ± 5 30 ± 2a Data given by mean and standard deviation result from observed data. Where the mean value is given only, data are homogeneous for

land use classes and based upon observations or literature review.b Gross plant uptake equals loss by harvest and N storage in remaining biomass, based upon data taken from the CANDY model data base

(Franko et al., 1995).

Figure 9 Comparison of calculated and observed groundwa-

ter levels.

Figure 8 Calibrated groundwater surface of the regional

groundwater flow model.

Figure 10 Simulated mean nitrate concentrations in ground-

water recharge leaching from the soil.




groundwater and was effectively removed from the aquifer.The propagation and depletion of reactive substances canbe studied in a vertical transect cutting through the catch-ment (Fig. 12). A general idea of flow patterns in the verti-cal transect is given in Fig. 13. The propagation of nitrate

under conservative transport conditions (Fig. 14a and c) de-pends on patterns of flow and transport velocity resulting ina heterogeneous concentration front.

Under reactive transport conditions the presence ofreaction partners and resulting denitrification successfullyslowed down advection of the nitrate concentration(Fig. 14b and d). The corresponding release of sulphateand consumption of pyrite resulting from autotrophic deni-

trification processes is illustrated in Fig. 15 showing the dis-tribution of concentrations at the end of the simulation. Theredox boundary indicated by the sharp decrease of pyritecontent has roughly moved over distances between 10 and20 m within 200 years of simulation (5–10 cm/year).

Areas close to the drain channels were assigned a highercontent of organic matter in the upper layer, as field obser-vations showed presence of histic soils and of gleyic soilsrich in organic matter in these parts of the catchment.These areas were free of nitrate because high denitrifica-tion rates were simulated in these areas. In the remainingparts, reactive substances were homogeneously distributedand therefore patterns of the nitrate concentration frontwere also largely determined by patterns of transport

velocity.

Groundwater exfiltration

Groundwater exfiltration rates showed distinct spatial het-erogeneity in the channel system (Fig. 16a). Nitrate concen-trations in exfiltrating groundwater also showedheterogeneous patterns. These patterns were differentfrom the groundwater exfiltration rates, because they re-sulted from the association of highly polluted areas(Fig. 16b). This was even more pronounced supposing reac-tive groundwater transport, where only three smaller chan-nel segments showed elevated nitrate concentrations

Figure 11 Concentration of nitrate in layer 1 (upper groundwater) and layer 5 (deep groundwater) after a simulation period of 50

years for conservative and reactive transport.

Figure 12 Cross-section for the subsequent illustrations.

Figure 13 Distribution of flow velocities along the cross-

section in [m/d] and indicative flow lines showing generalized

recharge and discharge patterns.




(Fig. 16c). These information supported identification ofhigh-impact channel segments, associated with highly pol-luted agricultural areas upstream of groundwater flow.The distribution of reactive substances in the aquifer fol-lowed quite simple patterns in this simulation and therefore

did not influence spatial patterns of exfiltration and nitrateconcentrations.

During the simulation, nitrate concentrations in exfiltrat-ing groundwater increased following an S-shaped break-through curve under conservative transport conditions(Fig. 17a). The maximum nitrate concentration possible inthe exfiltrating groundwater is the spatially averaged ni-trate concentration in recharge water. After a simulationperiod of 200 years, this theoretical maximum of 70 mg/lcorresponding to average input concentrations, was notyet reached.

In the uniform input simulation, nitrate breakthroughcurve is a function of travel distance and transport veloc-

ity only and therefore equivalent to the travel time distri-bution of the catchment. The corresponding age frequencydistribution is given in Fig. 18. The average solute traveltime for each scenario was calculated as the time neededto raise seepage concentrations of nitrate to a level of 50%of the theoretical maximum of 70 mg/l. The average tra-vel time of the uniform input simulation is 93 years Inthe distributed leaching scenario spatial differentiation re-sulted in deviations from this ideal curve. The 50%-levelwas reached after 80 years, as the spatial arrangementof high and low input areas to the groundwater flow anddrain system became an additional factor of nitratebreakthrough.

A buffer area around the channels caused a reduction oftotal nitrate input into the area. Consequently, the break-through curve approaches a lower maximum concentrationcompared to the unbuffered case. A second effect is a retar-dation of nitrate breakthrough, as areas close to the drainsystem no longer contributed to nitrate loads of thechannel.

Under reactive transport conditions, model behaviourwas principally similar (Fig. 17b). However, final concentra-tions at the end of the simulation period were much lower,reaching 17 mg/l under spatially differentiated nitrate in-put. The curves also did not approach a maximum concen-tration. A continuation of the slow but constant increaseof nitrate concentrations can be expected as long as reac-

tive substances are present within the aquifer.The development of total nitrate mass is given in

Fig. 19 as cumulative sum of inputs from the soil andcumulative sum of nitrate output into the drain system,as well as the corresponding development of daily loads.Assuming a constant nitrate leaching rate from the soil,the total mass of nitrate transferred into the aquifer in-creased constantly. Under conservative conditions 50% ofthe nitrate applied left the aquifer to the surface watersystem, the remaining 50% were still stored in the aquifer.Under reactive transport conditions, only 10% of the ap-plied nitrate left the aquifer, indicating a total denitrifica-tion loss of 80%.

Figure 14 Distribution of nitrate along a cross section cutting the model domain under conservative (a,c) and reactive (b,d)

transport conditions after 50 years (a,b) and 200 years (c,d) of simulation time.

Figure 15 Distribution of sulphate (a) and pyrite (in mg per

liter water) (b) along a cross section cutting the model domain

under reactive transport conditions after 200 years of simula-

tion time.




Figure 16 Groundwater seepage (a) into the channel system and simulated nitrate concentrations of exfiltrating groundwater

after 50 years (conservative (b) and reactive (c) transport simulation).

Figure 18 Simulated groundwater age distribution [a].

Figure 19 Development of cumulative and daily loads of

nitrate-N into groundwater (soil leaching) and from groundwa-

ter into the surface water system (drain load) for conservative

(cT) and reactive (rT) transport.

Figure 17 Development of nitrate concentrations in exfiltrating groundwater under (a) conservative and (b) reactive transport

conditions for the distributed input, uniform input and buffered input model runs.




Discussion

The modelling exercises gave insight in the interaction ofcatchment characteristics and nitrate transport relevanton the catchment scale. The exercise also revealed prob-lems related to the data base, parameterisation, model cal-ibration and uncertainty issues, which still need to beovercome.

The simulations of water and nitrate leaching from se-lected lysimeters served as a test of the soil submodel.The soil model provided a reasonable simulation of annualand seasonal lysimeter water balance and a poor simulationof annual nitrate leaching rates. The poor capability of themodel in simulating annual and intra-annual nitrate leachingrates, however, does not only result from an inappropriatesetting of model parameters or simplified model equations.An evaluation of possible errors inherent to the input datashowed that nitrate leaching rates are smaller than the er-ror range of other nitrate balance terms, mainly plant N-up-take and atmospheric deposition (Wriedt, 2004). AverageNitrate leaching rates from Lysimeters were in the rangeof 10–30 kg N/ha/a. The potential error between observed

bulk deposition and total atmospheric deposition including aso-called atmogeneous deposition (Bohme et al., 2002; Mer-bach, 2002) may be up to 70 kg N/ha/a. Similarly, the po-tential error of plant N-uptake may be between 30 kg N/ha/a and 250 kg N/ha/a (±30 kg N/ha/a in average), calcu-lated as the difference between the observed N-uptake ofharvest and N-uptake calculated from the amount of bio-mass harvested and the average plant N-contents takenfrom the fertilizer guidelines (Landesanstalt fur Landwirts-chaft und Gartenbau Sachsen-Anhalt, 2002). Further uncer-tainty may result from N-fixation and residue incorporation.For a detailed discussion see also (Wriedt, 2004). Conse-quently, these sources of uncertainty will directly affectsimulated N-leaching rates and restrict further optimizationof model parameters. As most nitrogen models refer to sim-ilar data sources, these considerations are not model spe-cific but state a general problem in soil nitrogenmodelling. For the subsequent groundwater simulation,the poor representation of inter-annual dynamics had no ef-fect, as the groundwater simulation was carried out withaverage water and nitrate leaching rates.

The setup and calibration of the groundwater flow modelrevealed further problems of data uncertainty. Although thegeneral patterns of the groundwater surface were reflectedquite well, the average error was quite high. All uncertain-ties in channel elevations directly affect the simulatedgroundwater surface, because channel water levels are a

boundary condition of the groundwater surface. The largedeviations of observed and calculated groundwater levelsin individual wells were inconsistent with the observationsfrom nearby wells. Therefore the deviations were referredto local geological patterns not reflected in the data or re-solved in the model. Although some detailed borehole pro-files were available, the density of boreholes did notreflect substrate heterogeneity.

The catchment based modelling study was designed to beas close to the study area as possible. Many assumptionshave been included in the model setup, however, especiallyregarding nitrate input history and the geochemical andphysical sediment characteristics. Model parameters such

as reaction parameters and hydraulic properties were lar-gely based on values reported in the literature. Thereforesimulation results have hypothetical character not repre-senting the real behaviour of the study catchment. Whilehydrology of the system is largely constrained by the waterbalance, geochemical data and parameters are much moreuncertain. Nevertheless, they give insight in the interactionof solute transport and biogeochemical processes within a

small lowland catchment system. In contrast to a com-pletely hypothetical catchment layout, the real-world basisof the simulation allows to target model deficiencies intodata assessment and experimental layout and to improvethe catchment model concurrently with future field work.The most important differences factors constituting a real-istic model setup are (i) the initial chemical state resultingfrom input history, (ii) background concentrations of pyriteand (iii) travel time distribution. Considerable differencesexist between the specific model setup and the study catch-ment affecting transport behaviour.

The input history, i.e. the development of nitrate loadsover time, has a direct effect on the initial chemical stateof the aquifer and groundwater. In combination with sedi-

ment properties such as conductivities and amount and dis-tribution of pyrite and organic matter, the input historyaffects the location of concentration fronts of oxygen, ni-trate and sulphate (and thus location of the redox front)and the depletion of pyrite and organic matter. Also a ni-trate plume may have developed in the aquifer. To comparesimulation results with a real-world situation, it has to beconsidered that the initial model state was not identicalto the present state, as the initial conditions did not reflectinput history after decades of intensive agriculture. Assum-ing no nitrate pollution in groundwater would rather fit to astate before the period of intensive land use. A more realis-tic representation of the actual present state would be

achieved after a certain simulation period where total ni-trate loads reflect nitrate loads from the actual input his-tory. Given that the period of intensive land use started inthe 1950s and assuming constant nitrate loads on the actuallevel, it would roughly take a simulation period of 50 yearsto get an idea of the present state of aquifer chemistry.With these considerations in mind, the simulation resultsafter 50 years can be considered a hypothetical presentstate. A nitrate plume has already propagated through theaquifer (Fig. 14) and rising nitrate concentrations can be ob-served in the surface water with simulated concentrationsin the order of 20 mg/l for the conservative and 3 mg/l forthe reactive transport simulation (Fig. 17).

The background concentrations of pyrite and organic

matter determine denitrification capacity of the aquifer.In combination with nitrate loads and transport velocity theycontrol progression rates of the redox front. Simulated redoxfront progression was in the order of 10 cm/a (estimatedfrom nitrate progression rate) with a background concentra-tion of 0.8 mmol/kg (0.01 mass%). Postma et al. (1991) sim-ulated redox front progression rates in the order of 0.34 cm/a in vertical direction and up to 23–120 cm/a along the flow-line assuming a pyrite content of 3.6 mmol/kg. They showthat progression rates well exceed 5 cm/a given a pyrite con-tent below 1 mmol/kg. Bohlke et al. (2002) report progres-sion rate of 1.98 cm/a due to autotrophic denitrificationfor a pyrite content of 3.1 mmol/kg. Robertson et al.




(1996) report progression rates of 0.1 cm/a, but pyrite con-tent was considerably higher with 7.3 mmol/kg. Given thelow pyrite content of 0.8 mmol/kg applied in the simula-tions, the simulated progression rates are consequently high-er than in the cited references but fit well in the reportedranges. Application of a more realistic concentration of pyr-ite in the order of 3.1–3.6 mmol/kg would enhance denitri-fication capacity of the aquifer considerably, increasing

removal of nitrate from the aquifer and possibly slowingdown redox front progression considerably. In such a case,deep groundwater passing pyrite rich sediments would notcontribute to nitrate pollution of surface waters at all. Inturn, mixing of surface water with nitrate free groundwaterwould even reduce nitrate pollution from surface waters.

Simulation results indicate average travel times between80 (distributed input) and 93 (uniform input) years, the agefrequency distribution is tailed. The travel time distributionis directly related to sediment properties (porosity, hydrau-lic conductivity) and hydraulic gradients and also dependson aquifer volume and recharge rate (water balance) andaquifer geometry defining distribution of flow paths lengths.The simulated travel times in the order of 90 years (and tra-

vel time distributions) are rather uncertain values consider-ing the little knowledge of aquifer properties. However, theresults are well in accordance with travel times between 1and 250 years reported by Kunkel and Wendland (1999) inthe Elbe-Catchment in Germany and travel times above140 years in the Pleistocene aquifer of the Fuhrberger Feld(Bottcher et al., 1989). Bohlke et al. (2002) report traveltimes between 1 and 40 years based on groundwater datingin a sandy aquifer in Minnesota. The lateral and verticalextent of the aquifer, however, differs considerably fromthe geological conditions in the Elbe-catchment or the Fuhr-berger Feld. Although the real travel time distribution isquite uncertain, we think that an average travel time of

80 years ±40 years is a reasonable estimate for Pleistocenelowlands. Increasing or decreasing the travel time would re-sult in expansion or compression of the travel time fre-quency distribution. Nitrate breakthrough into surfacewaters and migration within the aquifer would changeconcurrently.

The travel time distribution covers a wide range fromhours to centuries according to the distribution of travel dis-tance from the recharge boundary to the seepage face.

Applying a uniform and a distributed (present land use)input scenario to the groundwater simulations could givean idea of the interaction of input heterogeneity and flowsystem. The uniform distribution of nitrate inputs is a hypo-thetical scenario that can serve as a reference for compar-

ison. Total loads were identical in both scenarios. A simplerearrangement of land use at the soil surface would have re-sulted in a modification of the total amount of nitrate lea-ched to groundwater. Nitrate breakthrough into surfacewaters would have resulted from the interplay of soil andgroundwater processes and the changes in total amountsof inputs. In the uniform input scenario, nitrate break-through to surface waters was also directly related to thetravel time distribution. Applying the distributed input situ-ation resulted in a modified distribution of loads in relationto long and short flow paths (and travel times) and the long-term effect on nitrate breakthrough into the surface watersystem was well reflected.

In the simulations, pyrite and organic matter were uni-formly distributed, with the exception of increased organicmatter contents buffering the drain channels and pyritedepletion in the upper model layer. Therefore the distribu-tion of reactive substances had little effect on the spatialpatterns of nitrate exfiltration into the surface water sys-tem. Macro-heterogeneity of the distribution of pyrite andorganic matter affect denitrification capacity along the flow

paths and might change nitrate transport and turnover char-acteristics considerably. Patches of these substances wouldform reactive barriers for nitrate transport, whereas inother parts of the sediment or along other flow paths noretention of nitrate transport would take place.

The information on input distribution, travel time andflow paths and distribution of reaction partners can be usedto target measures effectively on areas characterized byhigh inputs and short travel distances to the surface watersystem. Buffer areas around streams and rivers could be apossible measure reducing contribution from nearby areas.As mentioned above, areas connected to long flow pathsmight be free of nitrate due to the long residence timeand denitrification reactions and therefore do not contrib-

ute to surface water pollution.In contrast to the modelling study, where buffer areas

were present from the beginning, the installation of bufferareas after nitrate breakthrough would have no retardationeffect, as the areas in some distance from the channel (longflow paths) already contributed to surface water loads, de-spite the general reduction of total nitrate loads into thecatchment.

The denitrification capacity of the aquifer cannot be al-tered and the pools of pyrite and organic matter undergodepletion during denitrification. Therefore the denitrifica-tion capacity and depletion rates may be considered to de-fine priority areas for reduction of nitrate loads. However,

modified loads of nitrate or organic matter may result fromchanges in vegetation or soil water dynamics and thereforeinfluence denitrification. Such processes resulting from soil-plant-interaction cannot be considered by the model. Aqui-fer denitrification capacity may buffer nitrate inputs for alimited period of time but it does not substitute the needfor a decrease of N-leaching from the soil by improving man-agement of N-input into the soil.

As indicated before, uncertainty of input data and suit-able validation strategies were major problems in verifica-tion of the complex modelling approach. Many of theinput data are subject to considerable uncertainty (suchas nitrogen input, geology, etc.). In a catchment based sim-ulations, uncertainty can only partly be reduced by further

collection of field data for methodological reasons. Theproblems of model verification are of general nature andhave been widely acknowledged in scientific literature.Konikow and Bredehoeft (1992) state that groundwatermodels cannot be proven or validated, but only tested andinvalidated. Maloszewski and Zuber (1993) showed thatcommon calibration procedures are often ambiguous be-cause the interplay of parameters prevents a proper valida-tion. These problems were widely acknowledged inenvironmental modelling culminating in the concepts ofequifinality (Beven and Binley, 1992) and pareto solutionsets (Gupta et al., 1998). These concepts abandon the ideaof a unique parameter set describing an environmental sys-




tem. Consequently, the simulation results have to be con-sidered a hypothesis of catchment behaviour. Further dataassessment should therefore focus on collecting data suit-able for model falsification rather than verification.

Due to the complexity of the modelling approach, themodel cannot be verified in total, but various attempts havebeen made to verify some of the applied submodels. A spe-cial problem of model verification is the non-congruence of

the spatial resolution of model entities and the observa-tional scale (Heuvelink, 1998). All model results are givenwith a horizontal and vertical resolution defined by themodel grid. The observations are given as point data, suchas soil samples or groundwater wells with distances of hun-dreds of metres up to kilometres, or as integrative mea-sures, such as discharge and channel loads averagingprocesses from a 20 km2 catchment. Considering long traveltime of many decades, the observation period of 13 yearsdoes not allow identification of site specific managementrecords and catchment reaction on changes of soil inputs.

In a complex modelling structure combining differentsubmodels, a good starting point for verification or falsifica-tion might be observations at the boundaries of individual

submodels. During subsequent investigations, observationsof upper groundwater nitrate concentrations at selectedsites within the study catchment were made. These investi-gations showed high nitrate concentrations where the modelpredicted high average nitrate leaching rates from the soiland low concentrations where low leaching rates were pre-dicted. A more detailed assessment of upper groundwaternitrate concentrations could support model evaluationconsiderably.

Due to the complex nature of the modelling approach, avalidation of the model ‘‘in total’’ was not possible. How-ever, a partial validation of the submodels was attemptedusing different techniques such as parameter optimization,

uncertainty assessment and sensitivity analyses and valida-tion with field data. The submodels differed in characteris-tics and available data sources, therefore suitable analyseswere applied individually for each submodel.

It would also be possible to track different interactingsubstances (for example nitrate, sulphate and iron) anduse this information for further assessment of model plausi-bility. Multi-species chemical data also provide additionalinformation useful for inverse simulations to obtain a betterparameterisation of reaction parameters.

Despite the limitations in model calibration and thehypothetical character of the simulations, the modelling ap-proach was a valuable tool illustrating transport and turn-over of nitrate and related solutes in the catchment. The

soil model provided a spatially distributed scenario of ni-trate leaching and the groundwater models simulated thedistribution of solutes in space and time including theirchemical interaction. The natural attenuation of nitratewas simulated as well as the concurrent depletion of reac-tive pools. A quantification of these processes is possiblebased on the solute mass balances and the temporalchanges of mass and concentration. This also supports fur-ther comparison with field data.

None of the modelling studies cited in the backgroundsection considered heterotrophic and autotrophic denitrifi-cation simultaneously but focused on one or the other reac-tion pathway. Many of the studies (MacQuarrie and Sudicky,

2001; Chen and MacQuarrie, 2004; Frind et al., 1990) wererelated to extensive field work providing good data to setup specific reaction models. Large scale studies (Wendlandand Kunkel, 1999; Patsch et al., 2003) for regional mappingof nitrate pollution simplify the reactive processes into afirst-order nitrate decay.

In Pleistocene lowlands pyrite rich glacial till and sandsalternate with surficial wetlands and peat soils or include

layers of organic carbon capable of rapid denitrification.Therefore reduced sulphur as well as organic carbon mightcontribute to total denitrification in the catchment. Theindividual contribution does not only depend on the relativereaction kinetics but also on the distribution in relation toflowpaths. In a sandy aquifer in Minnesota studied by Bohlkeet al. (2002), denitrification was dominated by pyrite oxida-tion, though organic carbon in surficial wetland sedimentswas shown to be capable of supporting rapid denitrification.However, groundwater flow largely avoided passing the wet-lands, therefore the total contribution of heterotropic deni-trification was negligible.

The soil water and nitrogen model could be substitutedby more complex models as well as by observed data (lysim-

eter data for example). However, considering the uncer-tainties of input data, application of a complex soil modelis not justified. The advantage of the mRISK-N model wasto facilitate a reasonable simulation of nitrogen dynamicswhile at the same time keeping the effort of parameterselection and model calibration low with respect to datauncertainty. In contrast to other studies addressing the sim-ulation of groundwater transport of nitrate such as thosepresented above, our approach explicitly defined the quan-titative relation of all relevant substances as well as thetemporal dynamics of substance concentrations resultingfrom reaction kinetics. This was achieved (i) using kineticrate expressions linking turnover reactions to residence

time in the aquifer and (ii) using a stoichiometric reactionsystem, linking nitrate turnover to the availability of reac-tion partners. Such a full reactive view on nitrate transportis essential for a detailed study of interactions betweencatchment properties, input distribution and flow paths(Wriedt, 2004).

If reactive processes were fast enough, that equilibriumor complete turnover is achieved within grid-cell residencetime, instantaneous stoichiometric reactions or equilibriumreaction models are sufficient to simulate the biogeochem-ical reactions. Therefore the reaction module can be simpli-fied especially in regional modelling studies where coarsegrids are applied.

Because of the modular structure of the MODFLOW simu-

lation package, further processes related to groundwaterdynamics could be included, such as evaporation fromgroundwater, wells, river interactions and coupling to a sur-face water model. This makes it possible to set up a modelspecific to a wide range of groundwater dominatedcatchments.

The individual behaviour of any catchment will mainly beinfluenced by (i) geometry and boundaries of the catchmentdefining flow systems, (ii) the chemical characteristics of thesubstrate (availability of reaction partners), (iii) hydraulicconductivities and drainage density influencing transportpaths and travel times in the ground water (reactiontime) and iv) nitrogen management (nitrogen inputs). The




processes implemented into the model, however, are inde-pendent from the individual catchment. Therefore theapproach can be transferred to other lowland catchments.

Concluding remarks

The study presented is a step towards bridging the gap be-tween detailed field scale studies and large scale modelling

approaches for regional risk assessment.The modelling approach was designed to simulate nitrate

transport in small, groundwater-dominated lowland catch-ments maintaining process-orientation in a complex land-scape. In contrast to small scale, specific modellingstudies, heterotrophic and autotrophic denitrification areconsidered in one modelling approach. The approach allowsconsideration of (i) distribution and turnover of solutes andimmobile components in space and time, (ii) developmentof solute concentrations in exfiltrating groundwater as ameasure of groundwater contribution to surface waters pol-lution and (iii) spatial distribution of groundwater exfiltra-tion rates and solute concentrations in the channel

system. A spatially distributed approach and considerationof reactive groundwater transport are a precondition toinvestigate spatial and geochemical interactions and couldbe tested successfully. In a hypothetical modelling studybased on a real-world study catchment we simulated nitratetransport from input into the soil via groundwater passageuntil output into the surface water system and demon-strated the capability of the approach to account for thethree dimensional and process-oriented nature of nitratetransport in a lowland catchment systems.

The work presented was a starting point for investigatingthe complex interactions of physical and chemical catch-ment properties influencing solute transport. Further stud-ies are needed to investigate the effect of input patterns,

distribution of reactive substances, arrangement of thechannel system and transport properties of the sediment.The approach facilitates identification of main sources andsinks of nitrate pollution and therefore can assist in target-ing water protection measures.

An additional aspect for future research is the implemen-tation of transformation processes during transition fromground- to surface water through the hyporheic zone (Jonesand Homes, 1996; Boulton et al., 1998) and in surface watersto complete the transport path from groundwater exfiltra-tion to the catchment outlet. Field observations suggeststrong relations between seasonal dynamics of nitrate con-centrations in the channels and groundwater level dynamicsconnecting and disconnecting agricultural areas from thechannel system. Transient simulations could address thisproblem. As the model setup was based on a given studyarea, model deficiencies encountered so far have guidedcurrent field research and will also target future researchin the study area to improve ground-truthing of the modeland facilitate more realistic simulations for the study area.

Acknowledgements

This study is part of the DFG-research project ‘‘Nitrogentransport and turnover during soil and groundwater passage

and its modelling in the pleistocene lowlands of the Elbe-area’’, carried out in cooperation of the UFZ Centre forEnvironmental Research Leipzig-Halle and the Leibniz-Insti-tute of Freshwater Ecology and Inland Fisheries in Berlin.

We gratefully acknowledge funding of this project by theGerman Research Foundation DFG.

We also gratefully acknowledge the UFZ Lysimeter sta-tion Falkenberg, especially Benjamin Blank and Ralf Meiss-

ner, for support and collaboration with field work, as wellas Helmut Geistlinger (UFZ Halle) for assisting in develop-ment of the reaction module.

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