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GEOLOGICAL SURVEY OF FINLAND Industrial environments and recycling Kuopio 10.1.2016 66/2016
WaterSmart-project case report - Groundwater modeling at Luikonlahti and
Siilinjärvi mine sites
Kimmo Hentinen
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Documentation page
Table of contents
1 introduction 3
2 Luikonlahti mine site 3
2.1 Introduction 3
2.2 Data review 4
2.3 Conceptual model 5
2.3.1 Modelling domain 5
2.3.2 Modelling objectives 8
2.4 Numerical model 8
2.4.1 Model Setup 8
2.4.2 3D configuration 9
2.4.3 Boundary conditions 9
2.4.4 Meshing and fracture modelling 11
2.4.5 Material properties 12
2.4.6 Fracture properties 13
2.5 Simulations 14
2.6 Calibration 15
2.7 Simulation results 17
3 Siilinjärvi Mine Site 22
3.1 Introduction 22
3.2 Data review 23
3.3 Conceptual model 23
3.3.1 Modelling domain 23
3.3.2 Modelling objectives 25
3.4 Numerical Model 25
3.4.1 Model setup 25
3.4.2 3D configuration 26
3.4.3 Boundary conditions 27
3.4.4 Meshing and fracture modelling 27
3.4.5 Material properties 31
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3.4.6 Fracture properties 32
3.5 Simulations 33
3.6 Calibration 33
3.6.1 Calibration results 34
3.7 Simulation results 34
4 GROUNDWATER and Surface water model coupling In siilinjärvi mine site 41
4.1 Introduction 41
4.2 WSFS-model 41
4.3 Coupling of WSFS-model and FEFLOW-model 41
4.4 Coupled simulation 43
5 Discussion 45
Literature Appendices: Appendix 1. FEFLOW IFM- plug-in source code for coupling WSFS-model with groundwater model
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1 INTRODUCTION This report is related to the survey done in WaterSmart-project. In this project the objective was to create water balance model for mine sites including surface and subsurface waters. By water balance we refer to the amount of water entering the site and the amount of water leaving the site. If water isn’t stored anywhere, the input and output should be the same. This report describes the groundwater modelling case studies as a part of the water balance modelling. Water management and water balance in mine sites is very important for mines. Water management in dry areas has to be done in a way that there is enough water for mining operations but on the other hand in wet conditions water management has to take care that contaminated waters are controlled and released according to the limits. Water balance models provide information about the volumes and if possible about the quality of the water and mass balances to guide water management. The design of water management can be made easier if water balance in the future can be predicted with the models. For studying groundwater balance, groundwater flow models were created for two mine sites, New Boliden Ab Luikonlahti and Yara Suomi Oy Siilinjärvi mines, in eastern Finland. Groundwater flow models were created with FEFLOW-groundwater modelling tool. Siilinjärvi model is also coupled with surface water model provided by the Finnish Environment Institute (SYKE). In this report the groundwater models and their results are described as well as the results of the coupled model.
2 LUIKONLAHTI MINE SITE
2.1 Introduction Luikonlahti mine site (Figure 1) in Finland is located at Kaavi and owned by New Boliden Ab. There is no mining at the site but the ore is imported from Kylylahti mine in Polvijärvi, 40 km from Luikonlahti, and it is enriched at Luikonlahti ore refinery. A numerical groundwater flow model for the Luikonlahti mine site was developed during the Minera –project. This model was created by Antti Pasanen (GTK) and Soile Backnäs (GTK) with FEFLOW-groundwater modeling software. Model presented at the case-report of the Minera-project (Pasanen & Backnäs, 2013) is the basis for the model presented in this report. FEFLOW was selected as the modeling tool because the previous model for Luikonlahti was also created with it. Flexibility in model discretization was also one reason to use FEFLOW (Wels, et al., 2012). FEFLOW also has very good built in features for fracture modeling and open programming interface (IFM) (DHI-WASY GmbH, 2013).
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Figure 1. Location of the Luikonlahti mine site.
2.2 Data review Data used in this Luikonlahti model is mainly the same as the data used in Minera-project. Airborne laser scanning data by National Land Survey of Finland was used for creating ground surface topography. Bedrock surface profile was interpolated from drilling and geophysical measurement data. Some of the fracture properties were estimated using geophysical and hydraulic measurement data.
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Initial values for hydraulic conductivities are defined according to literature (Airaksinen, 1978; Mälkki, 1999) and hydraulic slug-tests performed in some of the drill holes. Values for specific yield, specific storage and recharge to groundwater from precipitation (i.e. percolation) were defined according to literature (Airaksinen, 1978; Mälkki, 1999; Mustonen, 1986). Percolation was estimated using the average precipitation of the previous ten year period received from the Finnish meteorological institute. Groundwater levels were observed in 34 observation wells. These water levels were used for defining boundary conditions and for model calibration.
2.3 Conceptual model
2.3.1 Modelling domain Map of the modelling area is presented in Figure 2. Modeling area is the same as in Minera-project. Area is bounded from the west by Luikonlahti-bay, Retunen-lake and Uittokanava-channel connecting the previous two. From the north area is bounded by topographic high ridge. Northeast corner of the area coincides with the northeast corner of Palolampi-bond. From the east area is bounded by topographic lows, streams and bonds (including Iso Ahvenlampi and Iso Rupanlampi). From the south a small river leading into Luikonlahti bounds the modeling area. Main waterbodies inside the modeling area (Palolampi, Heinälampi and Pieni-Petkelampi) are included in the model (Figure 3). In vertical direction model extends from 0 m a.s.l. to the ground surface and for our purposes is divided into two stratigraphic units: bedrock and soil (Figure 4). Ground surface DEM-profile is presented in Figure 5. Soil is quite shallow compared to the scale of the model and thus it’s considered as one layer. Different soil types with specific properties are taken into account by horizontal variability of the hydraulic properties. Fracture interpretations are the same as in previous Minera-model (Figure 2). As we don’t have specific measured data about the fractures, they are modelled as vertical high conductivity zones extending from the bottom of the model to the top of the bedrock layer.
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Figure 2. Modeling area and fractures of the Luikonlahti mine site.
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Figure 3. Main waterbodies of the Luikonlahti model.
Figure 4. Luikonlahti model stratigraphic units. View of the clipped model from SW towards NE. Depth dimension is scaled by factor of 3.
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Figure 5. Luikonlahti ground surface DEM-profile. Values are m a.s.l.
2.3.2 Modelling objectives Objective of the modelling at Luikonlahti site was to create a simple groundwater model for the area and to study the groundwater balance of the area. Also an objective was to study how FEFLOW software and the fracture modelling with discrete feature elements perform in this type of environment.
2.4 Numerical model
2.4.1 Model Setup Mathematically Luikonlahti model is an unconfined (phreatic) groundwater system. Final model is quasi-steady state model which means that it is transient but all the parameters are time-independent. Quasi-steady state model is used because simulation convergence was obtained with this setup. Model calibration was performed with steady state model. Transportation modelling from the Minera-project model has been discarded.
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2.4.2 3D configuration Horizontal scale of the modelling area is about 4.2 km x 5.7 km (E-W x N-S). Vertically the model reaches from 0 m a.s.l. to ground surface (90,5 -190,5 m a.s.l.). In vertical direction model is numerically divided into two layers which represent bedrock and soil. Minera-project model data is used for bedrock surface and ground profiles. If soil thickness is between zero and 0.2 m, the thickness of 0.2 m is set for soil at these points. According to soil raster the bedrock reaches ground surface in multiple locations. Numerically these areas in the first layer are assigned to have the same properties as the bedrock layer. Figure 6 illustrates soil and bedrock elemental areas.
Figure 6. Stratigraphic units of the numerical model.
2.4.3 Boundary conditions At the western model boundary the hydraulic head of the groundwater is assumed to have a value of 101,2 m a.s.l. which is about the same value as the elevation of the water bodies (Luikonlahti 101,0 m a.s.l. and Retunen 101,5 m a.s.l.) that bound the area. For eastern and southern boundaries the hydraulic head is assumed to have a value of 1 meter below the elevation of the ground surface. Rivers and streams in these boundaries are assumed to estimate the hydraulic head. For the northern boundary a no-flow boundary condition is assumed (Figure 7).
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Figure 7. Luikonlahti model boundary conditions.
It’s assumed that there is no flow through the bottom of the domain. At the top of the model, inside the three main waterbodies, hydraulic head of the groundwater is assumed to have fixed value of:
• Palolampi, 117,9 m a.s.l. • Heinälampi, 126,3 m a.s.l. • Pieni-Petkellampi, 114,6 m a.s.l.
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In addition main streams and rivers at the top of the model are modelled as drains (Figure 7) where water can be removed from the model depending hydraulic head but no water is added to the model if hydraulic head falls below the ground surface elevation. No flow through the other areas at the top of the model is assumed.
2.4.4 Meshing and fracture modelling Most radical change to the model developed in the Minera-project is the implementation of fractures. In the Minera-model fractures were modelled using a separate layer for the fractures. In this project the fracture layer was deleted leaving us with a two layer model. The fractures are implemented using FEFLOW’s discrete features. Fracture interpretations (Figure 2) from the Minera-project were used in order to draw single horizontal lines to represent fractures. In order to model fractures more accurately, the mesh was modified and refined locally around the fracture-lines. New mesh is presented in Figure 8. Total node count is about 3.7x104.
Figure 8. Finite element mesh for the Luikonlahti mine site. Local refinement around fractures.
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Projected from the fracture lines, 2D high hydraulic conductivity vertical faces are defined inside the bedrock (Figure 9). Fracture in the north-south direction is defined as a one discrete feature and other fractures as one. With this definition different conductivities for the two fracture sets can be assigned easily.
Figure 9. Luikonlahti fracture modelling.
2.4.5 Material properties Material properties are assigned separately for soil and bedrock. In this chapter by soil and bedrock we refer to the elemental areas illustrated in Figure 6. Some material properties of the previous model are also used in this new model. Initial material properties for the Luikonlahti model are presented in Table 1. Recharge from precipitation isn’t really a material property but it is introduced here because it is listed under material properties in FEFLOW. Hydraulic conductivity distribution for soil is set by interpolating the results of the slug tests from the groundwater observation boreholes. Sand areas from the soil raster are defined separately into the model with 15 m/d hydraulic conductivity. Figure 10 illustrates the initial hydraulic conductivity in x-direction. The conductivity distribution is later adjusted during the model calibration. Recharge to the groundwater from precipitation is assumed to be 13 % of the precipitation value (Mustonen, 1986) provided by Finnish meteorological institute.
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Material Properties Bedrock Soil
Hydraulic conductivity in x-direction (K_xx) 0.005 m/d 0.2-20.75 m/d
Hydraulic conductivity in y-direction (K_yy) 0.005 m/d 0.2-20.75 m/d
Hydraulic conductivity in z-direction (K_zz) 0.005 m/d 0.2-20.75 m/d
Recharge from precipitation (In/outflow on top/bottom)
0 m/d 2.25 x 10-4 m/d
Specific yield (Drain-/fillable porosity) 0.05 0.35
Specific storage (compressibility) 0.0001 1/m 0.0001 1/m
Table 1. Initial material properties. FEFLOW notation in brackets.
Recharge from precipitation isn’t really a material property but it is introduced here because it is listed under material properties in FEFLOW. Hydraulic conductivity distribution for soil is set by interpolating the results of the slug tests from the groundwater observation boreholes. Sand areas from the soil raster are defined separately into the model with 15 m/d hydraulic conductivity. Figure 10 illustrates the initial hydraulic conductivity in x-direction. The conductivity distribution is later adjusted during the model calibration. Recharge to the groundwater from precipitation is assumed to be 13 % of the precipitation value (Mustonen, 1986) provided by Finnish meteorological institute.
2.4.6 Fracture properties In FEFLOW the fractures are modelled using the Darcy law. Parameters and initial values for Darcy law are listed in Table 2.
Fracture properties North-South fracture Other fractures
Thickness 25 m 25 m
Hydraulic conductivity 30 m/d 300 m/d
Specific storage 0.0001 1/ m 0.0001 1/m
Table 2. Fracture properties.
Fracture thickness was estimated using the geophysical ERT (Electrical Resistivity Tomography) measurements (Pasanen & Backnäs, 2013). Initial conductivity is approximately the same as in previous model. Fracture conductivity is adjusted during the model calibration.
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Figure 10. Initial hydraulic conductivity distribution in x-direction (Kxx). Distribution is the same in all directions (Kyy and Kzz).
2.5 Simulations Steady state simulations with this model revealed a convergence issue. It turned out that this issue was due to very low soil thickness in multiple locations. The hydraulic head (water table) tends to cross the slice between the bedrock and the soil. This causes the model not to converge properly. Residual magnitude was about 10-2 which can’t be considered as good convergence. With this residual the solution seemed reasonable but water balance wasn’t zero. The same non-convergence behaviour was repeated with a FEFLOW tutorial model when water table was forced to cross the interface between different hydraulic conductivity layers by using boundary conditions. Refining the mesh in vertical direction by adding more layers to the model (7 inside soil and 16 inside bedrock) didn’t solve the problem either. Neither did defining a transition zone between the soil and bedrock. A test was conducted where 15 layers were added below the soil and in this zone hydraulic conductivities were defined in a way that a smooth logarithmic transition comprised from bedrock to soil. This transition zone had only a minor effect on convergence. Changing the model setup from unconfined to confined simplified the situation. In unconfined case the problem is non-linear but in confined case the problem is linear. With specific setup the model seemed to give reasonable results, but calibration revealed that deviation from the specific setup caused the model to produce unreal results.
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Redefining boundary conditions was also tried in order to solve the convergence issue. Fixed hydraulic head values were set at the boundaries in a way that hydraulic head had a value that was inside the soil layer. This didn’t have any effect on convergence probably due to the fact that soil thickness is quite low in multiple locations inside the modelling area. Convergence issue was handled by using quasi-steady model. Model is run as transient but all the parameters are time independent.
2.6 Calibration Calibration of the model was done using FEPEST which is a PEST-code integrated with FEFLOW projects. For calibration the steady state model had to be used because of the computational cost of the transient model. Calibration parameters are presented in Table 3. In pilot point method the parameter values are adjusted in fixed pilot points and the parameter distribution is interpolated using the pilot points. In calibration the objective is to achieve a good correlation between the measured and the simulated hydraulic head values at observation points. Observation points for Luikonlahti model are presented in Figure 11. Calibrated hydraulic conductivities in x- and z-direction are presented in Figure 12 and Figure 13. Calibrated hydraulic conductivities of the fractures are presented in Table 4.
Parameter Soil Bedrock
Hydraulic conductivity Kxx 58 pilot points Single value for whole domain
Hydraulic conductivity Kyy 58 pilot points, Tied to Kxx
Tied to Kxx
Hydraulic conductivity Kzz 58 pilot points Single value for whole domain
N-S fracture hydraulic conductivity Single value for whole fracture
Other fractures hydraulic conductivity
Single value for other fractures
Table 3. Calibration parameters.
Parameter N-S fracture Other fractures
Hydraulic conductivity 34.04 m/d 99,23 m/d
Table 4. Calibrated hydraulic conductivity of the model fractures.
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Figure 11. Groundwater level observation points.
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Figure 12. Soil layer hydraulic conductivity distribution in x-direction after calibration.
Figure 13. Soil layer hydraulic conductivity distribution in z-direction after calibration.
2.7 Simulation results The following results are obtained by configuring the calibrated steady state model into quasi-steady model and performing a 10 year simulation period. In ten year simulation the model finds a “steady state” as none of the model parameters are time dependent. Simulated groundwater hydraulic head distribution at the top of the model is presented in Figure 14. Error bars represent the difference of simulated value respect to the measured one with ±2,5 m confidence interval. Correlation between the measured and simulated hydraulic head values are presented in Figure 15. Groundwater pressure distribution with zero pressure isolines is presented in Figure 16. If pressure is greater than zero the groundwater hydraulic head value exceeds the ground elevation. This probably doesn’t happen at Luikonlahti site in reality. Flow rates in and out of the model are presented in Table 5. The total amounts in and out aren’t the same due to the model top layer storage properties in transient simulations. If the water table rises above the model top layer elevation, the specific yield of the top layer is extended to the parts where hydraulic head is above the ground elevation (DHI-WASY GmbH, 2013). Imbalance is due to the storage fluctuations. Flow rates for different slices of the model are also presented in Figure 17, Figure 18 and Figure 19. Size and colour (blue for outflow, red for inflow) of the sphere represents the rate of flow.
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Figure 14. Simulated groundwater hydraulic head distribution in the model top slice and comparison with measured values at observation points. Red bars indicate a simulated value outside the ±2,5 m confidence interval.
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Figure 15. Correlation of simulated and observed hydraulic head values. ±2,5 m confidence interval, red points outside the confidence interval.
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Figure 16. Simulated groundwater pressure distribution in the model top slice. Zero pressure isolines in white.
Source/Sink In Out Model edges 1360 m3/d 10360 m3/d Waterbodies 10190 m3/d 320 m3/d Drains 0 m3/d 2610 m3/d Percolation 2120 m3/d 0 m3/d Total 13670 m3/d 13290 m3/d
Table 5. Flow rates in and out of the Luikonlahti model.
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Figure 17. Flow rates in and out of the top of the Luikonlahti model. Fractures in dashed line.
Figure 18. Flow rates in and out of the bedrock top of the Luikonlahti model. Fractures in dashed line.
Figure 19. Flow rates in and out of the bottom of the Luikonlahti model. Fractures in dashed line.
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3 SIILINJÄRVI MINE SITE
3.1 Introduction Another site modelled in the WaterSmart project is Siilinjärvi mine site in Finland (Figure 20). Mine and production plants are owned by Yara Suomi Oy. Phosphate ore is extracted from the open pit mine and refined to phosphoric acid, fertilizers and other industrial chemicals. There isn’t any previous model for this mine site and the model has to be created from scratch. The aim at first is to develop a very simple groundwater model of this area.
Figure 20. Siilinjärvi mine site location.
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3.2 Data review Map data used in this project is provided by National Land Survey of Finland and ICT Agency HALTIK. Ground surface topography was created from airborne laser scanning data by National Land Survey of Finland. Surface profile for the bedrock is interpolated from GPR-data, drill hole data, bedrock field observation points and water body depth data. GPR data is from the measurements done in this project (Luoma, et al., 2015). Drill hole data is provided by Yara Suomi Oy and bedrock field observation points were provided by GTK. Water body depth data is provided by ICT Agency HALTIK. Bedrock fracture interpretations made by GTK were used for defining fracture lines. Yara Suomi Oy also provided fracture data from the open pit area. This data was more accurate than fracture interpretations by GTK but it was consistent with the interpretations. Groundwater levels at observation points were provided by Yara Suomi Oy. Initial values for soil hydraulic conductivities were interpolated from the slug tests performed in selected groundwater observation drill holes. Other hydrogeological properties (specific yield and specific storage) were estimated using literature (Airaksinen, 1978; Mälkki, 1999). Recharge to groundwater from precipitation i.e. percolation was estimated from the results of the hydrological Watershed simulation and forecasting system (WSFS) –model by the Finnish Environment Institute (SYKE). SYKE also defined the watershed areas (or drainage basins) inside the modelling area.
3.3 Conceptual model
3.3.1 Modelling domain Modelling area for the Siilinjärvi mine site is presented in Figure 21. Modelling area is bounded from south by Siilinjärvi-lake. From west it is bounded by lakes and bonds: Pieni-Sulkava, Sulkavanjärvi, Tuli-Koivula, Peltosenlampi, Kolmisoppi and Syvänlampi; streams and rivers: Siilinjoki, Koivusenjoki, Peltosenjoki, Kolmisopenjoki and Syrjäjoki. From north area is bounded by Tannersuo and Mustinsuo swamp-areas, stream connecting Tannersuo-swamp and Syrjänlampi-bond and stream connecting Mustinsuo-swamp and Pahkapuro-stream. In the east Pahkapuro-stream, Pahkalampi-bond, Saarisenjärvi-bond, Purnulampi-bond, Purnunpuro-stream, Jouhteisenlampi-bond, Pohjalammit-bonds and Kuuslahti-bay bound the modeling area. Main waterbodies at the edges and inside the modeling area are presented in Figure 22.
Open pit mine at the centre of the modelling area is clearly seen in dark blue in the DEM profile in Figure 22. Open pit descends to about -85 m a.s.l. The model bottom layer is defined to be at -100 m a.s.l. Similar to Luikonlahti the model is divided into two stratigraphic units: bedrock and soil (Figure 23). Different soil types are taken into account with horizontal distribution of soil properties. Fractures presented in Figure 21 are modelled as vertical fracture planes extending from the bottom of the model to the bedrock surface, as in Luikonlahti-model.
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Figure 21. The Siilinjärvi mine site modelling area and fracture lines.
Figure 22. Main waterbodies and ground surface DEM of the Siilinjärvi mine site.
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Figure 23. Stratigraphic units of the Siilinjärvi mine site model. Model is clipped in N-S direction and it’s being watched from SW to NE.
3.3.2 Modelling objectives The objective of this groundwater modelling is to produce a simple groundwater model which simulates the flow and water balance of groundwater at the Siilinjärvi mine site. Water balance in mine site includes the groundwater and surface water. The Finnish Environment Institute (SYKE) has a Watershed simulation and forecasting system (WSFS) –model which is a hydrological watershed model including mainly surface waters (Vehviläinen, et al., 2005). This model covers the whole Finland but for this project it is scaled down to describe water balance at the Siilinjärvi mine site. WSFS –model includes groundwater but only its fluctuations. Flow directions and fluxes are not included. Aim is to couple the modified WSFS-model with the 3D groundwater flow model to produce complete water balance model for mine sites. Coupling is only one direction at first. WSFS model simulates percolation for each of the drainage basins inside the modelling area. Percolation data is set as an input to groundwater flow model. At the Siilinjärvi mine site the special interest is on the open pit area and groundwater discharge into the open pit can be estimated with the groundwater model.
3.4 Numerical Model
3.4.1 Model setup Siilinjärvi mine site model is an unconfined quasi-steady groundwater model. Like the Luikonlahti model the calibration is performed with steady state model but the final model is transient. All the properties and parameters are time-independent in the transient model.
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3.4.2 3D configuration Horizontal scale of Siilinjärvi model is about 6,5 x 14,7 km. In vertical direction model reaches from -100 to maximum of 187,5 m a.s.l. Model is vertically divided into two layers. First layer represents the soil and the second layer is the bedrock. Minimum thickness of the soil layer is defined to be 0,5 m. The bedrock was originally divided into 5 layers for computational reasons and the objective was to make the model more accurate. However this caused the model to oscillate very heavily probably due to the thin layers below and around the open pit. In these thin layers some of the elements probably dried which caused the properties of the element to change. This change of properties probably induced the oscillation. As a result, bedrock was described with only one layer. According to soil raster bedrock reaches the ground surface in many locations. Like in Luikonlahti model, these areas in the first layer are assigned to have the same properties as the bedrock layer. This elemental distribution is visualized in Figure 24. The same way as in the Luikonlahti model, thin soil layer causes computational problems.
Figure 24. Elemental bedrock and soil distribution.
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3.4.3 Boundary conditions Boundary conditions for Siilinjärvi model are presented in Figure 25. Fixed hydraulic head boundary condition is defined for all the water bodies at the edge and inside the modelling area. Hydraulic head value in these water bodies is assumed to be the same as the elevation of the water surface (Figure 22). Fixed hydraulic head is also defined for all the boundary sections connecting water bodies. These sections are mainly rivers or streams which are also local topographic lows. Hydraulic head values for these sections are linearly interpolated using the hydraulic head values in the water bodies bounding the section. Linear interpolation was chosen because the boundary of the modelling area doesn’t follow the streams and rivers exactly. Defining the boundary condition according to the elevation at the boundary could cause error if the elevation would be distinctly different than the actual elevation of the stream. If interpolated hydraulic head value in the stream or river section is greater than the ground elevation in that location, the hydraulic head value is corrected to match with the elevation. Hydraulic head boundary condition values were also compared with the groundwater drill hole observations near the boundary. No significant deviations were observed and thus these boundary conditions can be assumed to be realistic. Main rivers and streams inside the modelling area at the top of the model are defined as seepage faces (drains). In these nodes water can be removed from the model if the hydraulic head value is larger than the elevation of the node but no water is injected into the model if hydraulic head has smaller value than the elevation. Open pit area is also defined as seepage face. This way water is allowed to seep into the pit. No flow through the bottom of the model is assumed as well as no flow through the top of the model is assumed excluding the boundary conditions defined earlier.
3.4.4 Meshing and fracture modelling Finite element mesh of the modelling area is presented in Figure 26. Mesh is refined around the fracture-lines and inside the open pit. Total node count is about 295 x 103. Fracture modelling is done using FEFLOW’s discrete features. High conductivity vertical faces along the fracture lines reaching from bottom of the model up to the bedrock surface are defined as 2D discrete features (Figure 27). Properties of the discrete features are defined by the Darcy law.
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Figure 25. Siilinjärvi model boundary conditions.
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Figure 26. Finite element mesh of the Siilinjärvi model.
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Figure 27. Siilinjärvi mine site fractures modelled with discrete features.
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3.4.5 Material properties Initial material properties for soil and bedrock are presented in Table 6. In this chapter by soil we refer to the soil elements in the first layer of the model and bedrock is the bedrock layer plus the bedrock elements in the first layer (see Figure 24). Soil hydraulic conductivity distribution (Figure 28) is interpolated from the slug-test results performed in selected groundwater observation drill holes. During calibration the hydraulic conductivity values are adjusted.
Material Properties Bedrock Soil Hydraulic conductivity in x-direction (Kxx) 0.005 m/d 0.0032-11.23 m/d Hydraulic conductivity in y-direction (Kyy) 0.005 m/d 0.0032-11.23 m/d Hydraulic conductivity in z-direction (Kzz) 0.005 m/d 0.0032-11.23 m/d Recharge from precipitation (In/outflow on top/bottom)
0 m/d 0 - 7.4 x10-4 m/d
Specific yield (Drain-/fillable porosity) 0.05 0.2 Specific storage (compressibility) 0.0001 1/m 0.0001 1/m
Table 6. Initial Siilinjärvi model material properties. FEFLOW notation in brackets.
Recharge from precipitation to soil is estimated by calculating a ten year average for each drainage basin of the WSFS-model percolation results (see Figure 29). Recharge is set to zero in areas where bedrock meets the ground surface. The recharge distribution in Figure 29 is used in the steady state model during calibration. After a calibrated model is achieved the objective is to use the actual percolation values of the WSFS-model as an input to the transient model.
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Figure 28. Initial hydraulic conductivity distribution at the model top slice. Other directions (Kyy and Kzz) have the same distribution.
Figure 29. Distribution of the recharge to the groundwater from precipitation.
3.4.6 Fracture properties Fractures are divided into three groups, presented in Figure 30. Initial properties for these groups are presented in Table 7. Hydraulic conductivities are adjusted during the model calibration.
Fracture properties N-S Fracture SE-NW Fractures Other N-S Fractures
Thickness 25 m 25 m 25 m Hydraulic conductivity
1 m/d 1 m/d 1 m/d
Specific storage 0.0001 1/ m 0.0001 1/m 0.0001 1/m Table 7. Initial Darcy law properties of the fractures in the Siilinjärvi model.
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Figure 30. Fracture groups of the Siilinjärvi model.
3.5 Simulations Same convergence issue as with the Luikonlahti model was also present with this model. Due to small soil thickness the water table tends to cross the interface between soil and bedrock. This causes the model not to converge properly. This problem was handled with the quasi-steady state model.
3.6 Calibration The same way as Luikonlahti model, Siilinjärvi model was calibrated with FEPEST. Calibration parameters are presented in Table 8. In z-direction the hydraulic conductivity is the conductivity in x-direction multiplied by the factor of 0.75. This is due to the assumption that hydraulic conductivity is smaller in vertical direction due to pressure of the material above. Observation points where groundwater levels are known are presented in Figure 31. In each observation point an average of groundwater level observations (provided by Yara Suomi Oy) is used as a reference value in calibration. Soil raster, according to which the hydraulic conductivity distribution is defined, is presented in Figure 32.
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Parameter Soil Bedrock Hydraulic conductivity Kxx Soil raster areas Single value for whole
domain Hydraulic conductivity Kyy Tied to Kxx Tied to Kxx Hydraulic conductivity Kzz Kxx x 0.75 Kxx x 0.75 N-S fracture hydraulic conductivity Single value for the
fracture SE-NW Fractures hydraulic conductivity
Single value for fracture group
Other N-S Fractures hydraulic conductivity
Single value for fracture group
Table 8. Siilinjärvi model calibration parameters.
3.6.1 Calibration results Calibrated hydraulic conductivities in x-direction for the top layer are presented in Figure 33. Whole bedrock has the same conductivities as bedrock areas in Figure 33. Conductivities for different soil types are not necessarily reasonable respect to each other when compared with literature (Airaksinen, 1978; Mälkki, 1999). When conductivities were limited strictly the calibration caused the model to produce unrealistic hydraulic head distribution. Thus the conductivity distribution presented in Figure 33 has to be considered only as an indicative with different conductivities for soil and bedrock. Calibrated fracture properties are presented in Table 9.
Fracture properties N-S Fracture SE-NW Fractures Other N-S Fractures
Conductivity 0.74 m/d 1.41 m/d 35.8 m/d Table 9. Calibrated fracture hydraulic conductivities of the Siilinjärvi model.
3.7 Simulation results The following results are obtained with quasi-steady model after 10 year simulation period. Distributions aren’t shown in the open pit because of the model configuration. Groundwater hydraulic head distribution and the differences between observed and simulated values in the top layer of the model are presented in Figure 34. Correlation between observed and simulated hydraulic head values with ±2.5 m confidence intervals are presented in Figure 36. Pressure distribution and zero pressure line in the model top layer are presented in Figure 35. In areas where pressure is greater than zero the groundwater hydraulic head is above the ground surface elevation. In reality the hydraulic head values are probably not greater than the ground surface elevations. Groundwater hydraulic head distribution around the open pit is presented in Figure 37. Cross section pressure isolines along the black cross section line in Figure 37 are presented in Figure
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38. Flow rates in and out of the model are presented in Table 10. Total amounts in and out aren’t the same due to the model top layer storage properties in transient simulations. Flow rates for different slices of the model are also presented in Figure 39, Figure 40 and Figure 41. Size and colour (blue for outflow, red for inflow) of the sphere represents the rate of flow.
Figure 31. Siilinjärvi model groundwater level observation points.
Figure 32. Soil type raster of the Siilinjärvi model. A single conductivity value is assigned for all the white areas where soil type hasn’t been defined.
36
Figure 33. Calibrated hydraulic conductivity distribution in x-direction.
37
Figure 34. Groundwater hydraulic head distribution in the model top layer. Error bars representing the difference of the simulated value to the measured value at the observation points.±2.5 m confidence interval.
Figure 35. Groundwater pressure distribution at the model top layer. White lines represent the zero pressure isolines.
38
Figure 36. Correlation between observed and simulated groundwater hydraulic head values. ±2.5 m confidence interval.
39
Figure 37. Groundwater hydraulic head around the open pit. Cross section line in black.
Figure 38. Groundwater pressure isolines along the black cross section line in Figure 37. Zero pressure isoline representing the groundwater table.
Area In Out Model edges 2100 m3/d 7120 m3/d Waterbodies 3660 m3/d 3190 m3/d Drains 0 m3/d 4720 m3/d Open pit 0 m3/d 1190 m3/d Percolation (whole domain) 11070 m3/d 0 m3/d Total 16730 m3/d 16220 m3/d
Table 10. Siilinjärvi model flow rates in and out of the modelling domain.
40
Figure 39. Flow volumes in and out of the model at the top of the model. Fractures in dashed lines.
Figure 40. Flow volumes in and out of the model at the top of the bedrock. Fractures in dashed lines.
Figure 41. Flow volumes in and out of the model at the bottom of the model. Fractures in dashed lines.
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4 GROUNDWATER AND SURFACE WATER MODEL COUPLING IN SIILINJÄRVI MINE SITE
4.1 Introduction One objective of the WaterSmart –project is to couple subsurface water balance model with surface water balance model in order to evaluate the water balance at the mine site. Groundwater model was created with FEFLOW system. Surface and part of the subsurface water modelling is done with Watershed simulation and forecasting system (WSFS) model developed by Finnish Environment Institute (SYKE). The WSFS model is normally used for flood forecasting, real time monitoring, nutrient load simulation and climate change research (Vehviläinen, et al., 2005). WSFS-model covers whole Finland but for WaterSmart project it’s modified in a way that only the relevant parts of the mine site and its’ surroundings are included in to the model.
4.2 WSFS-model WSFS-model uses data gathered from multiple measurement stations (temperature, precipitation, potential evaporation, river discharge, water levels and outflow from regulated lakes). Weather forecasts as well as basin area, elevation map, river network map and land use map data are also inputs for modelling (Vehviläinen, et al., 2005). Model output includes real time precipitation, snow, evaporation, soil moisture, ground water storage, runoff, discharge, lake level, ice depth, reservoir storage, hydrological water balance maps. Model also produces hydrological probability forecasts, groundwater level forecasts, nutrient load forecasts and simulations, flood warnings, dam safety simulation and climate change simulation and assessment. In addition to surface water balance and reservoir modelling WSFS also models subsurface waters. Subsurface waters are divided into three storages: soil moisture, subsurface and groundwater. From the soil moisture storage water flows into subsurface storage which recharges the groundwater storage. WSFS-model only describes the changes in storage volumes. Flow routes and transport rate formulas are defined by the user. When coupling WSFS-model with the Siilinjärvi groundwater model presented in this report, the critical information is the groundwater recharge: percolation. In WSFS-model this is the flow from the subsurface storage to groundwater storage.
4.3 Coupling of WSFS-model and FEFLOW-model WSFS-model modified for the Siilinjärvi mine site consists of multiple sub-basins. For each of these sub-basins WSFS-model produces a simulated percolation value. This WSFS-model output is then used as input to FEFLOW groundwater model. Drainage basins inside the groundwater modelling area are presented in Figure 42. Coupling between the two models is made only one-way (data from WSFS to FEFLOW). Source code of the FEFLOW IFM- plug-in is presented in Appendix 1.
42 10.1.2016
WSFS-model produces percolation values for the previous ten years and also produces forecasts for the future percolations. Averages of the percolation history values are used in the calibration of FEFLOW models. Transient FEFLOW model with the percolation forecast as an input is then used for predicting the changes in groundwater levels and fluxes in and out of the model. Coupling was implemented using FEFLOW’s Interface manager (IFM) –plug-in which reads percolation from text file produced by WSFS-model. Plug-in then assigns forecasted percolation values for each drainage basin for each time step according to the state of the simulation.
Figure 42. Drainage basins inside the groundwater modelling area at the Siilinjärvi mine site.
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4.4 Coupled simulation A simulation with preliminary percolation forecast from WSFS-model is presented next. The forecast is for one year time period (6.6.2015 – 5.6.2016). Amount of percolation in that time period is presented in Figure 43. Groundwater hydraulic head values at the model observation points with these percolation values are presented in Figure 44. From the results it can be seen that hydraulic head values reduce from day 0 to day number ~290 and after that the values increase towards the end of the simulation. Changes are quite small but the trend is visible at least in some observation point values. Thus it can be said that model seems to react correctly to the percolation changes. No visible change of the groundwater discharge into the open pit was observed during the simulation. During the simulation an observation was made about the computational storage (hydraulic head above the top of the model). The storage seems to act as a buffer between the percolation value changes and groundwater hydraulic head values. Especially after the amount of percolation increases rapidly (day number ~300) the amount of water captured into the storage increases also rapidly. This storage then slowly is released into the model.
Figure 43. The sum of percolation into the whole Siilinjärvi modelling area.
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Figure 44. Hydraulic head values during the transient simulation respect to the percolation presented in Figure 43.
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5 DISCUSSION Groundwater balance modelling at mine sites proved to be quite challenging. Objective was to create groundwater flow models which could be used for evaluating groundwater balance. Both of the models presented in this report had quite shallow soil depth or no soil at all in some areas. This property caused numerical complexity. With shallow soil depth the water table tends to cross the interface between soil and bedrock layer. This is challenging for FEFLOW and steady state model solution starts to oscillate and it doesn’t fully converge. Steady state model has to be used in model calibration due to computational cost of quasi-steady model which gives better results. Shallow soil depth is also the most probable cause for hydraulic head rising above the ground elevation. As the bedrock is distinctively less conductive than soil, the percolation and water flow causes the hydraulic head to rise above the ground surface. In reality the hydraulic head should only be larger than ground elevation in few locations, not in large areas what the model suggests. The soil thickness is approximated using scattered measurements. Even if we would know the soil thickness exactly everywhere in the domain, we would probably still have these numerical issues. Thus the problem wouldn’t be solved with additional measurements but different modelling approach instead. Numerical complexity caused by thin soil layer is probably the biggest problem with the developed models. In addition, the uncertainty concerning fractures has a great effect on simulation results. As we have quite limited measurement and observations about the fractures, a lot has to be assumed about the location and especially about the properties of the fractures. In the models described in this report the fractures are divided into groups or treated as one group having only one thickness and conductivity per group. This eliminates the variability between separate fractures and spatial variability of their properties. Maybe the most important would be to identify different fractures and acquire information about the properties of a fracture in single point. Then an assumption would be made that the fracture has the same properties throughout the fracture length. Thus in order to make the models more accurate, more measured information about the fractures would be needed. One objective of the WaterSmart project was to create water balance models including surface and subsurface waters. The groundwater flow models presented in this report aren’t good enough to produce results which could be used as basis for other models. Thus a two way coupling between these models and the WSFS-model wouldn’t be reasonable. In the case of Siilinjärvi model the groundwater discharge into the open pit was heavily dependent on the hydraulic conductivity of the N-S fracture. With no measured hydraulic conductivity data of the fracture, the value of the simulated discharge is quite low and there is no point using that information in the WSFS-model. The objective of a model including both surface and subsurface water can’t be met with these groundwater models. WSFS-model includes the fluctuations in the amount of subsurface waters and it can be considered to include subsurface waters to some extent. As a conclusion it could be said that in order to simulate groundwater balance at mine sites with narrow soil layer a different approach should be taken. Perhaps a model without soil-layer could
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be better and computationally more stabile. This could be justified by the fact that in larger scale the bedrock and fracture zones have much more significant role in groundwater flow. Soil layer should be still included in more regional models (open pits, dams, etc.). When a whole mine site water balance is considered the surface water is probably more important than groundwater. This is the case especially in regions with large precipitation and water bodies. WSFS-model by SYKE would be a good option for water balance modelling.
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LITERATURE Airaksinen, J. U. (1978). Maa- ja pohjavesihydrologia. Oulu: Kustannusosakeyhtiö Pohjoinen. DHI-WASY GmbH. (2013). FEFLOW 6.2 User Manual. Mustonen, S. (1986). Sovellettu hydrologia. Helsinki: Vesiyhdistys ry. Mälkki, E. (1999). Pohjavesi ja pohjaveden ympäristö. Helsinki: Kustannusosakeyhtiö Tammi. Pasanen, A.;& Backnäs, S. (2013). MINERA-hankkeen tapaustutkimus: Riskinarviointimenetelmien testaaminen Luikonlahden
ja Kylylahden kaivosalueella. Kuopio: GTK. Vehviläinen, B., Huttunen, M., & Huttunen, I. (2005). Hydrological forecasting and real time monitoring in Finland: the
watershed simulation and forecasting system (WSFS). Innovation, advances and implementation of flood forecasting technology. Tromso.
Wels, C., Mackie, D., & Scibek, J. (2012). Guidelines for Groundwater Modelling to Assess Impacts of Proposed Natural
Resource Development Activities. British Columbia Ministry of Environment, Water Protection & Sustainability Branch. British Columbia Ministry of Environment. Retrieved from http://www.env.gov.bc.ca/wsd/plan_protect_sustain/groundwater/groundwater_modelling_guidelines_final-2012.pdf
Appendix 1 10.1.2016
FEFLOW IFM- plug-in source code for coupling WSFS-model with groundwater model
#include "stdifm.h"
#include "IfmTransientRechargeUpdate.h"
#include <string>
#include <sstream>
#include <fstream>
#include <math.h>
IfmModule g_pMod; /* Global handle related to this plugin */
#pragma region IFM_Definitions
/* --- IFMREG_BEGIN --- */
/* -- Do not edit! -- */
static IfmResult OnBeginDocument (IfmDocument);
static void OnEndDocument (IfmDocument);
static void PreSimulation (IfmDocument);
static void PreTimeStep (IfmDocument);
/*
* Enter a short description between the quotation marks in the following lines:
*/
static const char szDesc[] =
"Please, insert a plug-in description here!";
#ifdef __cplusplus
extern "C"
#endif /* __cplusplus */
IfmResult RegisterModule(IfmModule pMod)
{ if (IfmGetFeflowVersion (pMod) < IFM_REQUIRED_VERSION)
return False;
g_pMod = pMod;
IfmRegisterModule (pMod, "SIMULATION", "IFMTRANSIENTRECHARGEUPDATE", "IfmTransientRechargeUpdate", 0x1000);
IfmSetDescriptionString (pMod, szDesc);
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IfmSetCopyrightPath (pMod, "IfmTransientRechargeUpdate.txt");
IfmSetHtmlPage (pMod, "IfmTransientRechargeUpdate.htm");
IfmSetPrimarySource (pMod, "IfmTransientRechargeUpdate.cpp");
IfmRegisterProc (pMod, "OnBeginDocument", 1, (IfmProc)OnBeginDocument);
IfmRegisterProc (pMod, "OnEndDocument", 1, (IfmProc)OnEndDocument);
IfmRegisterProc (pMod, "PreSimulation", 1, (IfmProc)PreSimulation);
IfmRegisterProc (pMod, "PreTimeStep", 1, (IfmProc)PreTimeStep);
return True;
} static void PreSimulation (IfmDocument pDoc)
{ CIfmtransientrechargeupdate::FromHandle(pDoc)->PreSimulation (pDoc);
} static void PreTimeStep (IfmDocument pDoc)
{ CIfmtransientrechargeupdate::FromHandle(pDoc)->PreTimeStep (pDoc);
} /* --- IFMREG_END --- */
#pragma endregion
static IfmResult OnBeginDocument (IfmDocument pDoc)
{ if (IfmDocumentVersion (pDoc) < IFM_CURRENT_DOCUMENT_VERSION)
return false;
try {
IfmDocumentSetUserData(pDoc, new CIfmtransientrechargeupdate(pDoc));
} catch (...) {
return false;
} return true;
} static void OnEndDocument (IfmDocument pDoc)
{ delete CIfmtransientrechargeupdate::FromHandle(pDoc);
Appendix 1 10.1.2016
} ///////////////////////////////////////////////////////////////////////////
// Implementation of CIfmtransientrechargeupdate
const int nws = 28; //Number of drainage basins
const int days = 365; //Number of simulation days
double defaultperc = 0.29; //Default percolation value
double RechargeDataArray[days][nws] = {}; //Global array to store percolation forecasts for all the drainage basins
double RechargeAreas[nws] = {0, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 201, 301, 302, 303, 304, 305, 306, 307, 308, 309, 401, 402, 403, 404, 501, 502, 503 }; //drainage basins
double PreviousTimeStepDay = -1; //time step is set to -1 at first
// Constructor
CIfmtransientrechargeupdate::CIfmtransientrechargeupdate (IfmDocument pDoc)
: m_pDoc(pDoc)
{ if (IfmGetElementalRefDistrIdByName(pDoc, "RechargeZones") == -1){ // If RechargeZones Elemental Reference distribution is not found, it's created
long RechargeID = IfmCreateElementalRefDistr(pDoc, "RechargeZones"); //RechargeZones spatial distribution is created (is found from User Data at Feflow Data-panel)
int En = IfmGetNumberOfElements(pDoc); //Number of elements
for (int i = 0; i < En; i++) //RechargeZone is set to zero for all elements
{ IfmSetElementalRefDistrValue(pDoc, RechargeID, i, -1.0); // Value for all elements is set to minus one
} } std::string line;
int row = 0, col = 0;
double lines = 0; //parameter file line counter
const char * ppath = IfmGetAbsolutePath(pDoc, "..\\import+export\\parameters.txt", IfmGetProblemPath(pDoc)); //Path for Recharge parameters, parameters.txt file in Import+export folder located one level up from the .fem file
IfmInfo(pDoc, "Parameters will be read from:");
IfmInfo(pDoc, ppath); //Printing out the path
std::ifstream pfile(ppath); //Input file stream
if (pfile.is_open()){
while (!pfile.eof()){ //executed if end of file isn't achieved
Appendix 1 10.1.2016
getline(pfile, line); //Line is read
++lines; //line counter value is increased by one
} pfile.clear(); //ifstream is reset to begining of the file
pfile.seekg(0, std::ios::beg); //ifstream is reset to begining of the file
--lines; //one empty line at the end of the file is ignored
double startline = lines - double(days); //number of the line where the forecast starts
for (double i = 1; i <= startline; i++){ //ifstream is located at the begining of the forecast
getline(pfile, line); } for (int i = 1; i <= days; i++){ //percolation values are read and written into RechargeDataArray
getline(pfile, line); std::stringstream ss(line);
col = 0; while (ss >> RechargeDataArray[row][col]){ //read values are placed in RechargeDataArray
if (col == 0){ RechargeDataArray[row][col] = defaultperc;}
RechargeDataArray[row][col] = (RechargeDataArray[row][col])*0.001; //Unit conversion to [m]
col++; } row++; } double sum = 0;
for (int i = 0; i < days; i++){
sum = 0; for (int j = 1; j < nws; j++){
sum = sum + RechargeDataArray[i][j]; //Sum of percolation values
} RechargeDataArray[i][0] = sum / (nws-1); //Set the average of percolation to basin number zero
} pfile.close(); } else{
IfmInfo(pDoc, "Unable to open 'parameters.txt' from import+export directory");
} } // Destructor
Appendix 1 10.1.2016
CIfmtransientrechargeupdate::~CIfmtransientrechargeupdate ()
{ /*
* TODO: Add your own code here ...
*/
} // Obtaining class instance from document handle
CIfmtransientrechargeupdate* CIfmtransientrechargeupdate::FromHandle (IfmDocument pDoc)
{ return reinterpret_cast<CIfmtransientrechargeupdate*>(IfmDocumentGetUserData(pDoc));
} // Callbacks
void CIfmtransientrechargeupdate::PreSimulation (IfmDocument pDoc)
{ PreviousTimeStepDay = -1; } void CIfmtransientrechargeupdate::PreTimeStep (IfmDocument pDoc)
{ double CurrentTimeStepDay = std::floor(IfmGetAbsoluteSimulationTime(pDoc)); //current time step day
if (PreviousTimeStepDay != CurrentTimeStepDay){ //if date has changed
int En = IfmGetNumberOfElements(pDoc); //Number of elements
long RechargeID = IfmGetElementalRefDistrIdByName(pDoc, "RechargeZones"); //ID of RechargeZones
for (int i = 0; i < En; i++){ //For every element
for (int j = 0; j < 28; j++){
if (IfmGetElementalRefDistrValue(pDoc, RechargeID, long(i)) == RechargeAreas[j]){ //If RechargeZone is the same as index in the parameter table
IfmSetMatFlowRechargeValue(pDoc, i, RechargeDataArray[int(CurrentTimeStepDay)][j]); //Recharge value is assigned according to the parameter table corresponding the index
j = 28; } } } PreviousTimeStepDay = CurrentTimeStepDay; //update of the previous time step day
} }
