soya, cereals and vegetables dominate in the lower portion of the basin while forest (coniferous and deciduous trees), hay and pasture are most frequent in the upper portion.

Figure 1. The Noire River basin Base flows were estimated using a filtering technique (Chapman 1991) on total flows at the outlet and at the mid-basin station. These base flows include aquifer water drained by the Noire River as well as water which has travelled only for a short period of time through the saturated zone before emerging on the surface. The filtering technique does not allow distinction between the two components. Base flow analysis on the Noire basin shows that groundwater annually contributes from 41 to 56% of total flow at the outlet. During the winter, groundwater is generally the only contribution to river flows. In general, base flows are highest between March and May, and lowest between June and August. The study area is located on the fringe of the Appalachians, at the southeastern limit of the St-Lawrence Lowlands. In the lower part of the basin, the bedrock corresponds to stratigraphic units composed of limestone and clayey carbonate, red slate, sandstone and

conglomerates (Prichonnet 1984). Towards the southeast, a succession of folded slate, dolomite and quartzites is found. During the upper Wisconsinien and Holocene periods, various sedimentary deposits accumulated on the bedrock, including till, sand and gravel of glacial origin, along with marine sand and clay (Figure 2). Till is observed on 68% of the study area (max 5 m); sand deposits associated with the larger rivers cover 14 % of the area (max 15 m); clayey silt located in the northwestern part of the basin, along the Noire River bed, cover 12% of the study domain (max 20 m); bedrock outcrops over 6% of the basin.

Figure 2. Surface deposits (from Pharand, 2006)

Unit Average

K (m/s)

Reference

Bedrock 2.5 x 10-6 (n=2)

Bolduc et al. (2006)

Sand 3.6 x 10-5 (n=5)

Bolduc et al. (2006)

Till 5.4 x 10-5 (n=10)

7.0 x 10-5 (n=3)

Pharand (2006) Bolduc et al. (2006)

Clayey silt 1.2 x 10-6 (n=13)

Bolduc et al. (2006)

Table 1. Available hydraulic conductivity data

Field (Guelph permeameter) and laboratory (Darcy experiment) measurements of surface deposits hydraulic conductivity show that clayey silts have low K while sand and till are more permeable (Table 1). Pumping tests reported by Bolduc et al. (2006) provide estimates of bedrock hydraulic conductivity. Using electrical resistivity, Djineng Njomo (2002) has shown that fracturation is more important in the upper 10 to 15 m of the aquifer. Clayey silts deposits, offer partial protection to the groundwater and probably limit considerably infiltration. Elsewhere, the aquifer is free.

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A piezometric map (Figure 3) was drawn using 3585 head data from the Système d’Information Hydrogéologique (SIH) (MDDEP, 2006) and using heads measured in 34 private wells (Pharand 2006). This map shows that regional groundwater flows from southeast to northwest. The Noire River influences groundwater flow directions on its entire length while its affluents have only a limited effect on piezometry. Gradients are larger in the uphill area (0.01) than in the lower part of the basin (0.001), and heads follow closely the topography. Piezometric crests are located approximately at the surface watershed limits and the aquifer is considered to flow within this area. Water levels measured monthly in two observation wells until 1993 show that annual head variations are relatively small, from 0.3 to 1.3 m.

Figure 3. Piezometric map of the study area (from Pharand 2006). 2.2 The AGRIFLUX model AGRIFLUX (Banton et al. 1997) simulates the soil water budget and N-cycle in the root zone. It has been used in various studies (e.g., Larocque et al. 2002; Dupuy et al. 1997). AGRIFLUX is a mechanistic and stochastic model using a simplified representation of processes and requiring a limited number of parameters. In this study, only the water budget module was used to simulate infiltration and runoff. The model was used in a deterministic fashion to facilitate verifications.

In AgriFlux, water budget simulation includes precipitation, snowmelt, infiltration, runoff, water uptake by plants, evaporation and vertical water flow. Snow is melted following a degree-days method and evaporation is user-defined (not calculated). Infiltration is calculated as the minimum value between the water input (rain or snow melt) and the available pore volume in the first soil

layer. Runoff occurs when the uppermost layer can not hold the total water input during one day. Percolation is the vertical movement of water out of the unsaturated zone through soil layers represented as compartments. Water flow occurs as a cascade driven by the available pore volume of the underlying compartment and controlled by the unsaturated hydraulic conductivity. Calculations are performed with a daily time step.

Average monthly air temperatures and evaporation were used along with daily precipitation (average from the six weather stations). The soil profile was divided into five layers with a total depth of 1 m, corresponding to the rooting depth. Parameters of the different soil types were obtained from Bolduc (2004), Pharand (2006) and from literature. Plant water uptake, rooting depth and yearly schedule for the different crops identified from the land use map were derived from literature. Soil/land use scenarios were developed using the three surface deposits (clayey silt, sand and till) as support for the eight different crops encountered on the basin. Along with the bedrock, a total of 25 soil/land use scenarios were simulated with AGRIFLUX. Simulations were performed from November 1989 to October 2004.

2.3 The PHYSITEL/HYDROTEL model Surface flow was simulated using the PHYSITEL/HYDROTEL model. PHYSITEL (Fortin et al. 2004) is used to determine the drainage structure of a watershed and to prepare land use and soil type data for the surface flow simulation. In this application, the physical model was developed on a coarse mesh (1 km x 1 km) and the Noire River was used to force the drainage network. The DEM was sufficiently precise to identify relatively well the sub-basins of the Noire River (see shades of grey on Figure 4). These sub-basins are called Relatively Homogeneous Hydrologic Units (RHHU). Each RHHU built in PHYSITEL includes topography data (DEM), land uses (user defined rooting depth and LAI during the growing season), soil types and soil characteristics (choice from a data base). HYDROTEL (FORTIN and Royer 2004) is a physically-based and distributed hydrological model. The vertical water budget includes surface runoff, hypodermic flow, evapotranspiration, snowmelt and contribution from groundwater to surface flow. The downstream transfer of available water at each time step within a RHHU is simulated using a geomorphological unit hydrograph which shape is determined by routing a reference depth of water over all cells of a RHHU using a kinematic wave model. Channel routing is performed using a diffusive wave model. Daily air temperature and precipitation data from the six weather stations located on the Noire watershed were used in the HYDROTEL simulation. Land uses and soil types were described using the same information as in the AGRIFLUX application. Simulations were performed using a daily time step from November 1989 to October 2004.

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Figure 4. PHYSITEL simulated drainage network. 2.4 The MODFLOW model A tridimensional model of the Noire aquifer was developed by Pharand (2006) using the MODFLOW model (McDonald and Harbaugh 1988), a 3D finite differences groundwater flow model. The model developed for the study area has five layers (5, 10, 15, 25 and 40 m) and 500 m x 500 m cells (Figure 5).

Figure 5. The MODFLOW model of the Noire River Watershed limits were used as no flow boundaries for the groundwater flow model and the Noire River was represented using a constant head in the uppermost layer. The Noire River affluents were represented using drains located 2 m below the DEM. Recharge rates were determined using AGRIFLUX simulated infiltration. Water uptake through pumping was considered negligible. Hydraulic conductivities were estimated based on the

work by Bolduc et al. (2004). The simulation was performed in steady state. 3. RESULTS AND DISCUSSION 3.1 Infiltration and recharge using AGRIFLUX Calibration of the AGRIFLUX model was performed by adjusting the depth of the upper soil layers. These layers play an important role in the partitioning of water between runoff and infiltration. For this purpose, average annual base flows at the outlet calculated with the filtering technique were considered equal to total recharge on the watershed. Runoff was estimated by subtracting base flow from total flow at the outlet on a yearly basis. Depth of layers 1 and 2 were calibrated to 4 cm and 16 cm respectively (layers 3, 4 and 5 are 25, 25 and 30 cm respectively) providing the best estimate of both recharge and runoff. It is important to underline that estimation errors from base flow filtering would be directly reflected in the AgriFlux results Figure 6 and Table 2 show that simulated annual infiltration simulated between November 1989 and October 2004 generally underestimates calculated base flows. Runoff is globally better simulated. Overall, it appears that AGRIFLUX simulates better the dryer years and underestimates total flow during the wetter years. This is probably caused by the very simple representation of evapotranspiration (user defined) which appears to be overestimated during wet periods.

0,15

0,20

0,25

0,30

0,35

0,40

0,45

0,15 0,20 0,25 0,30 0,35 0,40 0,45

Estimated flow (mm)

Sim

ula

ted

flo

w (

mm

)

Runoff

Infiltration

Figure 6. Estimated and simulated annual infiltration and runoff Results from the 25 soil/land use scenarios show that infiltration and runoff vary more according to soil type than to land use. Recharge zones are therefore defined following the surface deposits map (Table 3). Recharge is highest over the till and sand covered areas. As expected, it is very low where clayey silts are found and where bedrock outcrops. Although AgriFlux partitions fluxes between runoff and infiltration, it does not provide information on the volume of water that actually reaches

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the regional aquifer as recharge. Part of the infiltration probably flows subhorizontally as hypodermic flow, outcropping nearby downgradient and never recharging the aquifer. A second portion of infiltration probably travels briefly in the saturated zone, reaching the affluents as topography decreases. And the remaining infiltration feeds the regional aquifer. Table 2. Average annual flow comparison between models

Cal

cula

ted

AG

RIF

LUX

HY

DR

OT

EL

MO

DF

LOW

Noire base flow (m3/s) - - - 3,0 Affluents base flow (m3/s)

- - - 7,8

Total base flow (m3/s) 11,2 - 0,6 - Runoff (m3/s) 13,7 14,5 8,7 - Infiltration (m3/s) - 10,0 - - Hypodermic flow (m3/s) - - 14,

9 -

Total flow (m3/s) 24,9 24,5 24,2

-

Table 3. AGRIFLUX-simulated average annual infiltration and runoff Soil type Infiltration

(mm/year) Runoff

(mm/year)

Till 265* 259 Sand 217 293 Clayey silt 36 517 Bedrock

outcrop

1 596

*Average value for the simulation period During the 1989-2004 simulation period, most of the infiltration occurs in April, May and June, immediately following spring snowmelt (Figure 7). In some years, there is another infiltration period in October and November. December to March and July to September are periods with usually very little infiltration.

0

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v

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Ja

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b

Ma

r

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r

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Ju

n

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Au

g

Se

p

Oc

t

Mo

nth

ly in

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rati

on

(m

m)

Figure 7. Recharge distribution during a typical year 3.2 Surface flow using PHYSITEL/HYDROTEL Calibration of the HYDROTEL model was performed by trial and error to reproduce adequately flow rates at the outlet and mid-basin stations from November 1989 to October 1995. Following a procedure developed at INRS-ETE, the calibration procedure was performed sequentially to reproduce prolonged summer drought recessions (adjustment of recession parameter), annual and summer flow volumes (evapotranspiration multiplication factor and depth of third soil layer), summer and fall high flows (depth of first and second soil layer), high flow synchronization (Manning roughness coefficient) and spring runoff resulting from snowmelt (parameters governing snow melt). Figure 8 illustrates measured and simulated snow water equivalent (average measured snow density estimated to be 0.25). Results show that snow dynamics are adequately reproduced in timing as well as in water volume. The evapotranspiration multiplication factor calibrated to reproduce annual and summer flow volumes provided potential evapotranspiration values similar to those estimated at the six weather stations (evapotranspiration was calculated using a simple equation based on minimum and maximum air temperature; actual evapotranspiration was calculated according to land use and period of year, using rooting depth and LAI).

0

50

100

150

200

250

1989-01 1990-01 1991-01 1992-01 1993-01 1994-01 1995-01 1996-01

Sn

ow

wate

r eq

uiv

ale

nt

(mm

)

Measured

Simulated

Figure 8. Snow accumulation and melting Total flow rates are relatively well simulated at the outlet (Figure 9a) and at the mid-basin hydrometric station (Figure 9b), with NASH coefficients of 0.69 for both stations. Simulations performed (without additional

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parameter adjustments) from November 1995 to November 2004 provided NASH coefficients of 0.66, confirming the quality of model calibration. In the calibrated HYDROTEL model, hypodermic flow is much larger than water contributed from the groundwater. However, the sum of hypodermic flow and groundwater flow compares well with base flows obtained with the filtering technique and to those simulated with AgriFlux (Table 2). This result indicates that a significant amount of recharge moves laterally from the soil to the river network, without reaching the regional aquifer. This distribution of flows is probably a result of the specific water budget representation in HYDROTEL and reflects the absence of groundwater flow equations in the model. Also, the manual calibration procedure makes it difficult to verify all realistic parameter combinations and other solutions probably exist.

0

50

100

150

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1989-01 1990-01 1991-01 1992-01 1993-01 1994-01 1995-01 1996-01

Q (

m3/s

)

Measured

Simulated

A) Outlet

0

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500

1989-01 1990-01 1991-01 1992-01 1993-01 1994-01 1995-01 1996-01

Q (

m3/s

)

Measured

Simulated

B) Mid-basin

Figure 9. Measured and simulated flow rates at (a) outlet, (b) mid-basin. 3.3 Groundwater flow using MODFLOW The MODFLOW model was calibrated by adjusting hydraulic conductivities manually in a trial and error process, using heads from the SIH data base and heads measured in May 2003 as calibration targets. The average AGRIFLUX simulated recharge rates (Table 3) were used directly without calibration. The calibrated hydraulic conductivities are as follows: layers 1 and 2 K=5.8x10-5 m/s, layer 3 9.3x10-6 m/s, layer 4 1.1x10-6 m/s and layer 5 1.1x10-7 m/s. These K values are larger than those estimated by Bolduc et al. (2006), but nevertheless reasonable considering cell dimensions. The SIH heads were not considered precise enough to justify a refined spatial calibration of K. The decreasing K values from

layer 2 to 5 correspond to the observations of Djineng Njomo (2002) and indicate that dynamic groundwater flow occurs within the uppermost 50 m of the aquifer. In the lower part of the basin, Kx/Ky=10 while in the uphill area, a ratio of 100 was necessary to maintain heads near topography, as observed in the field. Because of bedrock folding, it is probable that water flows laterally much easier than it flows downwards in this area. Measured and SIH heads are relatively well simulated with mean average error of 9,2 m and RMSE of 13.1 m (Figure 10). The model overestimates slightly measured heads. A total of 61% residuals are within the +/- 5 m range and 78% of the residuals are within the +/-10 m range. Given the available information on the basin, this calibration is considered satisfactory.

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0 50 100 150 200 250 300 350 400 450

Measured heads (m)

Sim

ula

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hea

ds (

m)

SIH heads

Measured heads

Figure 10. Measured and simulated heads In the calibrated model, 28% of total base flow is drained by the Noire River while 72% is drained by its affluents (Table 2). This is coherent with results obtained from the AGRIFLUX and HYDROTEL models, reflecting the fact that part of the recharge flows only briefly in the saturated zone before outcropping in the affluents. However, without measured flowrates on the affluents, these results cannot be verified. Using constant heads to representing the Noire River and drains to represent the affluents undoubtedly constrains the model. Given the available data, this was certainly the simplest and more robust representation available in this case. Although piezometry shows that they do not drain the aquifer as much as the Noire River, the drains were necessary to maintain heads close to the surface, while avoiding flooding. It is clear that both topography, Noire River and drains elevations play a major role in the model’s capacity to simulate adequately measured heads. It is important to note that adjusting recharge rates from AGRIFLUX could lead to a different calibrated model. Using automatic calibration to simultaneously adjust recharge and hydraulic conductivity may provide a different solution.

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4. CONCLUSION This work has provided new insight into the water cycle dynamics on the regional scale Noire River basin. In particular, it has contributed new information to better understand recharge dynamics and links between groundwater flow and surface flow. AGRIFLUX was useful to determine annual recharge for the groundwater flow model. However since model calibration depends entirely on information resulting from the filtering technique, the procedure is not entirely verified. HYDROTEL provided interesting results on the repartition of infiltration between hypodermic flow and base flow. Calibration in this case was based on many processes therefore ensuring global coherence, but the manual process does not ensure unicity of the solution. MODFLOW has proven to be useful to simulate steady state heads and flow. Simulating groundwater flow in a free water table aquifer where the heads follow closely a varying topography has proven to be a challenge. Research is ongoing on the Noire River basin. It includes automatic calibration of the MODFLOW model as well as transient state simulation of groundwater flow. A coupled flow simulation is also in preparation using Hydrogeosphere (Therrien et al. 2005). This model simulates fully coupled flow from the surface to the aquifer, representing surface and groundwater processes. Hydrogeosphere requires a large number of parameters and calculation time is relatively long. Model calibration is not easy due to the large number of required parameters. Nevertheless, preliminary results are promising for the Noire River, indicating that surface flows and water levels can be simulated satisfactorily. 5. ACKNOWLEDGEMENTS This research was performed with the financial contribution of NSERC and FQRNT. The contribution of R. Turcotte, V. Fortin, K. Richard, V. Fournier, S. Bolduc and S. Broda in data acquisition and model calibration is acknowledged. Our thanks also go to M. Laithier for her work illustring this paper. Finally, we would like to thank G. Poisson (MAPAQ) for his help performing field work and all the residents who gave access to their property. References Banton, O. and Larocque, M. (1997) AgriFlux 2.0 –

Manuel d’utilisation. Logiciel d’évaluation des pertes environnementales de nitrates et de pesticides. Rapport INRS-Eau.

Bolduc, S., Larocque, M. and Prichonnet, G. (2006) Vulnérabilité de l’eau souterraine à la contamination par les nitrates sur le bassin versant de la rivière Noire (Montérégie, Québec). Rev. Sci. Eau 19(2):87-99.

Bolduc, S. (2004) Vulnérabilité de l’eau souterraine à la contamination par les nitrates : géologie, hydrogéologie et simulation sur le bassin versant de la rivière Noire (Montérégie, Québec). Mémoire de Maîtrise en sciences de la Terre, UQAM, Montréal, Canada.

Chapman, T.G. (1991) Comment on « Evaluation of automated techniques for base flow and recession analysis » by R.J. Nathan and T.A. McMahon. Water Resour. Res., 27(7):1783-1784.

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Djineng Njomo, G.T. (2002) Utiliser les méthodes géophysiques dans l’étude de la contamination des eaux souterraines par les nitrates sur le bassin de la rivière Yamaska. Rapport de stage de maîtrise en sciences de l’environnement, Montréal, Québec, UQAM.

Dupuy, A., Banton, O. and Razack, M. (1997) Contaminationnitratée des eaux souterraines d’un basin versant agricole hétérogène : I. Évaluation des apports à la nappe (modèle AgriFlux). Rev. Sci. Eau, 10(1):23-40.

Fortin J.P, Lavoie, P. and Royer, A. (2004) Manuel de l'utilisateur - PHYSITEL, version 2.0, INRS-ETE.

Fortin J.P and Royer A. 2004. Manuel de l'utilisateur - HYDROTEL, version 3.0, INRS-ETE.

Larocque, M., Banton, O. and Gagnon, J. (2002) Using models to manage soil inorganic nitrogen in forest tree nurseries. Soil Sci. Soc. Am. J., 66(2): 602-612.

McCormack R. and Lacouline M. (1996) Eaux souterraines - état des connaissances. Comptes-rendus du deuxième colloque sur la gestion de l'eau en milieu rural - Stratégie de gestion : vers une vision commune, 10-11 sept. 1996, Sainte-Foy, Canada.

McDonald M. and Harbaugh A. (1988) A modular 3D finite-difference groundwater flow model. USGS TWRI.

MDDEP (Ministère du Développement Durable, de l’Environnement et des Parcs - Québec) (2006) (Web page), www.mddep.gouv.qc.ca/eau/souterraines/sih/index.htm.

Paré, D. (1978) Étude hydrogéologique, bassin de la Yamaska, Ministère des Richesses Naturelles, Direction générale des eaux.

Pharand, M.C. (2006) Délimitation des écoulements souterrains sur le bassin de la rivière Noire à l’aide de la caractérisation hydrogéologique, de la géochimie de l’eau et de la modélisation. Mémoire de Maîtrise en sciences de la Terre, UQAM, Montréal, Canada.

Prichonnet, G. (1984) Dépôts quaternaires de la région de Granby, Québec: Commission géologique du Canada, Étude 83-30, carte au 1/50 000.

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Therrien, R., Sudicky, E.A., McLaren, R.G. and Panday, S.M. (2005) HydroGeoSphere. A three-dimensional numerical model describing fully-integrated subsurface and surface flow and solute transport. User’s manual.

USGS (United States Geological Survey) (2006) (web page) www.usgs.gov.

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