RIVER WATER QUALITY MANAGEMENT USING MATHEMATICAL MODELLING

J.M.P. VIEIRA(*), J.L.S. PINHO(*), A.A.L.S. DUARTE(*)

(*)Department of Civil Engineering, University of Minho, 4719 Codex, .

ABSTRACT: A mathematical model has been calibrated and run for a range of River Cavado flow conditions to predict river water quality changes after pollutant loads. Biochemical oxygen demand (BOD), dissolved oxygen (DO) and faecal coliforms (FC) bacteria were used as water quality control parameters to assess critical situations near the proposed site for the construction of a new water treatment plant for the portuguese metropolitan area of Oporto.

1. INTRODUCTION Frequently, urban areas management authorities have to deal with high water demands for different uses, as well as with the progressive deterioration of available water resources quality, mainly due to intensive urbanisation and industrialisation policies. A wide range of mathematical models has been developed and applied to predict water quality changes in receiving waters, and it appears to be a useful tool for water quality management. However, the selection of the right model for a given management problem represents a hard task for decision makers: the more accurate and feasible the model, the more expensive monitoring programmes needed. The river Cavado basin, located in the north-western region of Portugal, has a very intensive use for water supply, irrigation and hydropower generation. In the last years pollution of water has increased due to industrial and domestic wastewater discharges, and, simultaneously, new water treatment plants (WTP) (Braga, ), and wastewater treatment plants (WWTP) (, , Braga, Esposende) have been installed. In the near future, a very important water supply project to the Oporto metropolitan area (that will serve seven municipalities - Esposende, Barcelos, Póvoa de Varzim, V.N. Famalicão, Vila do Conde, S.to Tirso, Maia, with a population of 0.9 million inhabitants and a design flow of 2.7 m3/s) will introduce new challenges in the river water quality management. Previous technical studies (PGIRHN, 1992) were conducted in order to determine the best site for WTP construction. Since the River Cavado flow regime is artificially controlled by reservoirs located upstream in its the mountain region, a flow discharge policy is needed. Moreover, the consideration of wastewater loads in the basin (WWTP effluent discharges, untreated industrial wastewater discharges and agricultural diffuse pollution) must be considered to guarantee adequate river water quality for supply purposes. In this paper a brief description of objectives, assumptions and structure of a slightly complex mathematical model (DUFLOW) is given. Its applicability is worked out in the simulation of water quantity and quality of the river Cavado basin, considering various planning scenarios concerning with the new WTP performance.

2. CHARACTERISATION OF THE STUDY AREA The river Cavado basin is located in the north-western region of Portugal, oriented from WSW to ENE, and includes the territory of eight municipalities (see Fig.1).

FRANCE

ITALY

ATLANTIC OCEAN

PORTUGAL SPAIN

RIVER CAVADO

Vilarinho das Furnas dam Alto Cavado dam

MONTALEGRE

Paradela dam

River Homem TERRAS DO BOURO River Rabagão

Caniçada dam Alto Rabagão dam VILA VERDE Salamonde dam AMARES

VIEIRA DO MINHO Venda Nova dam

POVOA DE LANHOSO

BARCELOS ESPOSENDE BRAGA - WTP - Existing / under construction - WTP - Planned - WWTP - Existing / under construction

- WWTP - Planned

0510 km

Fig. 1 General layout of the river Cavado Basin.

With a drainage area of 1589 km2 and a mean width of 16 km, this mountainous basin has a mean elevation of 564 m with several peaks above 1500 m, and an average population density of 200 inhabitants/km2 (minimum of 22 at Montalegre and maximum of 1770 at Braga). The annual mean rainfall is 2200 mm, 42 % of which is concentrated in the months of December, January and February. The water is intensively used for hydropower generation, domestic and industrial water supply and agricultural irrigation. Due to the river basin characteristics, six large hydropower plants (apart from several other small units) are in operation with an installed power of 377.6 MW and a mean annual energy production of 1535 GWh. A total reservoir volume of 1170 hm3 is possible with these dams, which represents a high regulatory capacity for river flows. For this reason, this water use constitutes a very important factor to be considered in any water management policy adopted for the basin. The study area occupies the lower level part of the basin, where the main residential and industrial areas are located, and distributed for five municipalities: Amares, Vila Verde, Braga, Barcelos and Esposende. All of these municipalities are served by WTP and WWTP, except for Barcelos, where a WWTP is under planning phase and untreated domestic and industrial wastewaters are discharged directly to the river. For modelling purposes, the receiving water begins west of the Caniçada dam (Ponte do Porto) and extend approximately 48 km to the Atlantic Ocean. The flows of the main tributary River Homem are considered as a point discharge downstream from Braga WTP. Waste inputs from the urban areas include Amares and Braga WWTP effluents and untreated domestic and industrial discharges from the municipality of Barcelos.

3. RECEIVING WATER SIMULATION

3.1 Model Description DUFLOW model was designed to cover a large range of applications, such as propagation of tidal waves in estuaries, flood waves in rivers, operation of irrigation and drainage systems and water quality problems. As the relationship between quality and flow gets special attention nowadays and this package is suitable for modelling both, it becomes a useful tool in water quality management. In the water quality part the process descriptions can be supplied by the user. This special concept enables the user to create different types of water quality models. Various types of control structures can be defined such as weirs, culverts, siphons and pumping stations. The basic equations used in DUFLOW and the numerical procedures used to discretize and solve these equations are briefly presented below. The package is based on the one-dimensional partial differential equation that describes non- stationary flow in open channels. These equations, which are the mathematical translation of the laws of conservation of mass and of momentum read:

∂ H ∂ Q B +=0 (1) ∂ t ∂ x and

∂ Q ∂ H ∂(α Qv) g|Q|Q ++gA +=bγφ w2 cos( Φ - ) (2) ∂ t ∂ x ∂ x CAR2 while the relation:

QvA=× (3) holds and where:

t time x distance as measured along the channel axis H(x,t) water level with respect to reference level v(x,t) mean velocity (averaged over the cross-sectional area) Q(x,t) discharge at location x and at time t R(x,H) hydraulic radius of cross-section A(x,H) cross-sectional flow area b(x,H) cross-sectional flow width B(x,H) cross-sectional storage width g acceleration due to gravity C(x,H) coefficient of De Chezy w(t) wind velocity Φ(t) wind direction in degrees φ(x) direction of channel axis in degrees, measured clockwise from the north γ(x) wind conversion coefficient α correction factor for non-uniformity of the velocity distribution in the advection term

Eq.(1) states that if the water level changes at some location this will be the net result of local inflow minus outflow. Eq.(2) expresses that the net change of momentum is the result of interior and exterior forces like friction, wind and gravity. Eq.(1) and Eq.(2) are discretized in space and time using the four-point implicit Preissmann scheme. This scheme is unconditionally stable and allows non-equidistant grids. It computes discharges and elevations at the same point. The quality part of the DUFLOW package is based upon the one dimensional transport equation. This partial differential equation describes the concentration of a constituent in a one dimensional system as function of time and place.

∂(BC) ∂(QC) ∂ ∂ C =− +(AD )P + (4) ∂ t ∂ x∂ x∂ x where:

C constituent concentration Q flow A cross-sectional flow area D dispersion coefficient x x- coordinate t time P production of the constituent per unit length of the section

The production term of the equation includes all physical, chemical and biological processes to which a specific constituent is subject to. The numerical method used to solve the transport equation was adopted from the model FLOWS (Booij, 1978). The method is unconditionally stable and shows little numerical dispersion. Furthermore the method perfectly fits to the discretization of the flow equations. Similar to the flow computations, adjacent sections may be different in length.

3.2. Data analysis The receiving water for this study began immediately after the Caniçada dam (Ponte do Porto) and continued for a distance of approximately 48 km downstream up to the river mouth. The simulation procedure was based on loading the study area data obtained from two sources: PGHIRN (1992), and U. Minho (1995). BOD, DO and FC bacteria were used as state variable parameters for defining the river water quality. Model segmentation assumes 27 different reaches each of them including or a tributary input, or a wastewater discharge, or an abstraction water point. Three main weirs have been considered to be determinant for the flow regime. Fig. 2 shows the river Cavado segmentation adopted in this study.

a)

PONTE DO PORTO ATLANTIC OCEAN

12 3 4 5 6 7 8910 11 12 13 1516 19 24 25 2627 28

0 510 15 20 25 30 35 40 [km]

- Water abstraction - Point wastewater discharge b) LEVEL - Tributary river [m] - WTP planned PENIDE DAM

25.0 WEIR 20.0 WEIR 15.0 WEIR 10.0 5.0

5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 Distance from Ponte do Porto [km]

85 m 81 m 129 m 76 m 66 m 66 m

Fig. 2 Hydrodynamic water quality model of River Cavado. a) Schematization of channel sections. b) Longitudinal profile and simplified cross-sections

The flow rates are significantly influenced by upstream hydropower plants operation, which have an impounding effect of 40 % of the basin mean annual runoff. The reservoirs regulatory capacity effect allows monthly low-flow augmentation in dry-weather conditions. However, in a weekly operation basis we can identify flow concentrations in working days as well as peak-hour flows in a daily operation basis. In this study, Ponte do Porto was considered the headwater of the system. A statistical analysis of two-years measurements at Barcelos hydrometric station was performed to determine cumulative frequency distribution of river flow as shown in Table 1. Water quantity calibration procedure consisted of comparing measured flow rates and water levels at several weirs with simulated model output results. The river hydrodynamic behaviour was reached with a water level error of ± 2 cm.

Table 1. Average daily flow frequency at Barcelos (1978/79 to 1989/90)

Flow interval Nº events Frequency Cumulative frequency [m3/s] [%] [%] 0 - 5 50 1.1 1 5 - 10 77 1.8 3 10 - 15 150 3.4 6 15 - 20 227 5.2 11 20 - 30 502 11.5 23 30 - 40 688 15.7% 39 40 - 50 540 12.3 51 50 - 60 352 8.0 59 60 - 70 333 7.6 67 70 - 80 269 6.1 73 80 - 90 165 3.8 76 90 - 100 214 4.9 81 100 - 200 652 14.9 96 200 - 300 58 1.3 98 300 - 500 54 1.2 99 500 - 1000 53 1.2 100 > 1000 0 0.0 100

Assuming that critical situations for water quality happen in late-summer period, dry-weather conditions were considered. The simulated average discharges of river Cavado at Ponte do Porto were estimated at 3, 7, 11 and 15 m3/s. The flow contribution of the tributary river Homem was estimated at a constant value of 1 m3/s, coherently with Vilarinho das Furnas acceptable minimum discharge. In addition to those flow rates it was estimated a global runoff flow discharge at 2.4 m3/s unevenly distributed by the river sections of the study area. At the time of this study, municipal WWTP effluents from Amares, Vila Verde, Braga and Esposende as well as untreated domestic and industrial wastewater from Barcelos was being discharged into river Cavado. The flow and effluent parameters presented in Table 2 were input into DUFLOW model initially for calibration of BOD, DO, and FC in receiving water as shown in Fig. 3. Also for calibration purposes, Churchill equation for reaeration coefficient and first-order decay rates for deoxygenation and faecal coliform die-off were used. A secondary level of treatment for Amares WWTP (BOD = 30 mg/L, and FC = 138 MPN/100mL), and several treatment efficiencies at Braga WWTP were considered as the most relevant factors in the river water quality at the planned WTP site. Abstracted water for Braga, Barcelos, and Esposende were estimated at 0.4, 0.05, and 0.05 m3/s, respectively. These planning parameters were used in the DUFLOW model for all other runs.

3.3. Simulated scenarios After calibration of the DUFLOW model, the receiving water was simulated four various alternative conditions. The scenarios worked out are summarised in Table 3, where variations of flow discharged at Ponte do Porto, Braga WWTP efficiency, and abstracted water flow at planned WTP site are considered.

mg/L 20

19 DO 18 17

16 - Computed profile 15 - Field data 14

13

12 11

10

9

8

7

6

5

4

3

2

1 0 0 5 10 15 20 25 30 35 40 45 50 Length km

mg/L 20

19

18 BOD

17

16 - Computed profile 15 - Field data

14

13

12

11

10 9

8

7

6

5

4

3 2

1

0 0 5 10 15 20 25 30 35 40 45 50 Length km

10^6 mpn/100mL 1.19

1.12 1.05 FC 0.98

0.91 - Computed profile - Field data 0.84

0.77

0.70

0.63

0.56

0.49

0.42

0.35

0.28

0.21

0.14

0.07

0 0 5 10 15 20 25 30 35 40 45 50 Length km

Fig. 3 Model calibration for BOD, DO, and FC bacteria

Table 2. Effluent discharges considered in the model

Wastewater Denomination Discharge BOD Faecal Coli. Distance source [m3/s] [mg/L] [MPN / from mouth 100 mL] [km] 1 Industrial wastewater 0.000 7500.0 - 47.5 2 Amares wastewater 0.005 30.0 138 46.0 3 Industrial wastewater 0.002 1400.0 - 44.0 4 River Homem 1.000 2.4 - 39.5 5 Industrial wastewater 0.200 30.0 - 36.5 6 Industrial wastewater 0.007 130.0 - 33.5 7 Braga WWTP 0.200 450 6000000 33.0 8 Industrial wastewater 0.010 150.0 - 32.5 9 Industrial wastewater 0.012 200.0 - 24.5 10 Industrial wastewater 0.012 150.0 - 22.5 11 Industrial wastewater 0.005 150.0 - 20.5 12 Industrial wastewater 0.004 40.0 - 20.0 13 R. das Pontes stream 0.050 21.0 - 19.5 14 Barcelos wastewater 0.030 267.0 1200000 18.0 15 Industrial wastewater 0.012 19.5 - 17.0 16 Industrial wastewater 0.020 140.0 - 16.5 17 Industrial wastewater 0.006 171.0 - 16.0 18 Industrial wastewater 0.019 104.0 - 15.5 19 Industrial wastewater 0.038 47.0 - 15.0 20 Industrial wastewater 0.010 150.0 - 14.0 21 Industrial wastewater 0.042 150.0 - 12.5

Table 3. Simulated scenarios

WWTP Abstracted Ponte do Porto discharges [m3/s] flow

3 Efficiency [m /s] Qd1 = 3 Qd2 = 7 Qd3 = 11 Qd4 = 15 Qa1 = 0 S1 S2 S3 S4 0 % Qa2 = 2 S5 S6 S7 S8 Qa3= 4 S9 S10 S11 S12 Qa1 = 0 S13 S14 S15 S16 50 % Qa2 = 2 S17 S18 S19 S20 Qa3= 4 S21 S22 S23 S24 Qa1 = 0 S25 S26 S27 S28 90 % Qa2 = 2 S29 S30 S31 S32 Qa3= 4 S33 S34 S35 S36

4. RESULTS AND DISCUSSION The following water quality criteria were considered to identify alternative pollution control facilities: - the minimum receiving water DO concentration shall not be less than 3 mg/L (class A1); - the minimum receiving water BOD concentration shall not exceed 5 mg/L (class A2); - the FC bacteria level shall not exceed 20000 /100 mL (class A3) Simulation results indicate that low DO (less than 3 mg/L) events never occur and that the minimum level always exceed 5 mg/L. This is justified by significant aeration effect due to the presence of several weir in the river. BOD ad FC profiles are depicted if Figs. 4 and 5. These results refer to the most severe situation of Braga WWTP rupture of operation. Three situations are illustrated: planned WTP out of operation and operating at 2 m3/s (future design flow) and at 4 m3/s (long term design flow). Flow dilution effect can be observed immediately after the Braga WWTP effluent with increasing river flow. BOD concentrations do not violate water quality criterion at km 21.5 (planned WTP site). However with water abstractions of 2 and 4 m3/s to planned WTP, BOD concentrations will violate water quality criterion downstream km 30. The selected FC water quality criterion is violated in a length of 15 km that includes km 21.5 and Barcelos water intake (km 30 ) in almost all of the simulation runs.

5. CONCLUSIONS Results of the DUFLOW simulations show that the selected quality criteria for BOD and FC are violated in planned WTP site and in Barcelos region for some critical conditions. These conditions are basically related with the eventual rupture in Braga WWTP operation. While low-flow conditions appears to be more severe to BOD concentrations, wet-weather periods can be regarded as more critical for FC bacteria. High level of quality control of Braga WWTP as well as construction of Barcelos WWTP seems to be the best way to guarantee the desired water quality standards. The possibility of enlargement of Braga WTP instead of construction of the planned WTP, must be equated. Apparently this situation seems attractive in a cost/benefit basis. DUFLOW can be a useful tool in estimating the impact of urban pollution sources on receiving water quality on a continuous, long-term basis. This model can be used to determine the level of pollutant removal required to achieve selected river water quality standards in a metropolitan area.

mg/L 20 19 BOD 18 17 S1 Qd = 3 m3 /s 16 S2 Qd = 7 m3 /s 15 S3 Qd =11 m3 /s 14 S4 Qd =15 m3 /s 13 12 11 10 9 8 7 A3 6 5 A2 4 3 A1 2 1 0 0 5 10 15 20 25 30 35 40 45 50 Length km

mg/L 20 19 BOD 18 17 S5 16 Qd = 3 m3 /s S6 Qd = 7 m3 /s 15 S7 Qd =11 m3 /s 14 S8 Qd =15 m3 /s 13 12 11 10 9 8 7 A3 6 5 A2 4 3 A1 2 1 0 0 5 10 15 20 25 30 35 40 45 50 Length km

mg/L 20 19 18 BOD 17 16 S9 Qd = 3 m3 /s 15 S10 Qd = 7 m3 /s 14 S11 Qd =11 m3 /s 13 S12 Qd =15 m3 /s 12 11 10 9 8 7 A3 6 5 A2 4 3 A1 2 1 0 0 5 10 15 20 25 30 35 40 45 50 Length km Fig. 4 Simulations results for BOD

10^6 mpn/100mL 1.19 1.12 FC 1.05 0.98 S1 Qd = 3 m3 /s 0.91 S2 Qd = 7 m3 /s 0.84 S3 Qd =11 m3 /s 0.77 S4 Qd =15 m3 /s 0.70 0.63 0.56 0.49 0.42 0.35 0.28 0.21 0.14 0.07 0 0 5 10 15 20 25 30 35 40 45 50 Length km

10^6 mpn/100mL 1.19 1.12 1.05 FC 0.98 S5 Qd = 3 m3 /s 0.91 S6 Qd = 7 m3 /s 0.84 S7 Qd =11 m3 /s 0.77 S8 Qd =15 m3 /s 0.70 0.63 0.56 0.49 0.42 0.35 0.28 0.21 0.14 0.07 0 0 5 10 15 20 25 30 35 40 45 50 Length km

10^6 mpn/100mL 1.19 1.12 1.05 FC 0.98 0.91 S9 Qd = 3 m3 /s 0.84 S10 Qd = 7 m3 /s 0.77 S11 Qd =11 m3 /s S12 Qd =15 m3 /s 0.70 0.63 0.56 0.49 0.42 0.35 0.28 0.21 0.14 0.07 0 0 5 10 15 20 25 30 35 40 45 50 Length km

Fig. 5 Simulations results for FC bacteria

6. REFERENCES

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