Simulation and evaluation of the water purification function of Zhalong ...

SCIENCE CHINA Technological Sciences • RESEARCH PAPER •

July 2012 Vol.55 No.7: 1973–1981 doi: 10.1007/s11431-012-4887-5

Simulation and evaluation of the water purification function of Zhalong Wetland based on a combined water quantity-quality model LI HongYan1,2, ZHANG GuangXin1* & SUN GuangZhi3 1

Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130012, China; 2 Jilin Geological Environment Monitoring Station, Changchun 130021, China; 3 School of Engineering and Physical Sciences, James Cook University, Townsville, QLD 4811, Australia Received October 19, 2011; accepted March 28, 2012; published online May 28, 2012

The water purification function of natural wetland systems is widely recognized, but rarely studied or scientifically evaluated. Extensive studies have been carried out by various international wetland research communities to quantify the water quality improvement ability of the natural wetlands, in order to maintain such ability and wetland ecological health. This study aims to evaluate the purification function of Zhalong Wetland in China for removing total nitrogen (TN) and phosphorus (TP), based on ex-situ experiments and the development of a combined water quantity-quality model. Experiments and model predictions were carried out with different input TP and TN concentrations. Statistical analyses demonstrated that the relative errors between model simulations and experimental observations for TN and TP were 8.6% and 12.4%, respectively. With water retention time being maintained at 90 d, the removal rate of these pollutants could not reach the required Grade V standards, if the inflow TN concentration was over 42 mg L1, or the input TP concentration was over 14 mg L1. The simulation results also demonstrated that, even with Grade V quality standard compliance, when the water inflow from surrounding industries and agriculture lands into Zhalong Wetland reaches 0.3×108 m3 a1, the maximum TN and TP loads that the reserve can cope with are 1.26×103 t a1 and 0.42×103 t a1, respectively. Overall, this study has produced a significant amount of information that can be used for the protection of water quality and ecological health of Zhalong Wetland. combined water quantity-quality model, water purification function, WASP model, Zhalong Wetland Citation:

Li H Y, Zhang G X, Sun G Z. Simulation and evaluation of the water purification function of Zhalong Wetland based on a combined water quantity-quality model. Sci China Tech Sci, 2012, 55: 19731981, doi: 10.1007/s11431-012-4887-5

1 Introduction In recent years, non-point water pollution due to agriculture activities is causing increasing environmental and social concerns. Excessive amounts of nutrients, such as nitrogen and phosphorus, often overflow into natural wetlands, exerting a pollution load that seriously threatens wetland eco*Corresponding author (email: [email protected]) © Science China Press and Springer-Verlag Berlin Heidelberg 2012

systems. Known as the ‘kidney’ of the earth, natural wetland is one of the natural ecosystems that have the most significant self-purification capability. Functioning as a link between land and water bodies, the wetland purifies polluted waters by removing nitrogen and phosphorus through a series of physicochemical processes [1–5]. However, such purification capacity is limited. If the optimal function of the wetland is to be maintained, precaution must be taken to prevent pollution and deterioration of wetland water quality [6–8]. tech.scichina.com

www.springerlink.com

1974

Li H Y, et al.

Sci China Tech Sci

Presently, many studies are being carried out, nationwide and worldwide, on the topics of wetland systems. Studies on inorganic nutrients in many European countries indicated that the purification efficiencies of nitrogen and phosphorus can generally reach 50% or above in a wetland [9, 10]. South China Institute of Environmental Sciences reported promising purification effects of eutrophic water in Xingyun Lake under high hydraulic loading; the removal rate of BOD5, TN, NH4-N and NH3-N was 60.8%, 68.8%, 54.1% and 20%, respectively, and removal efficiency of blue-green algae was also significant [11]. Study of retention effect for nitrogen and phosphorus in Phragmites australis, Spartina anglica, Spartina alterniflora and sullage in Yancheng of China shows that reed wetland with nonscheduled irrigation and drainage can retain TN and TP at rates of 0.095 and 0.026 t hm-2, respectively [12]. The water purification functions of the wetlands have also become an intensive research topic worldwide [13, 14]. Current studies primarily focus on the remediation of contaminants [15–17], environmental factors [5, 18–20], and assessment of wetland functionality [21–25]. However, studies have rarely been made on wetland water quality modeling, especially with combined water quantity-quality model; such combined model represents an innovative approach to simulate the water purification ability of Zhalong Wetland in China. In order to protect the ecological health of the wetlands, it is now an important task for the international community to establish quantitative models, and to carry out extensive research in wetland purification function and maximal load-carrying capability with the models. Since 1992, Zhalong Nature Reserve has been included in the “Directory of Important Wetlands in the World”. It is the largest natural wetland reserve in China that provides a habitat for rare birds, such as cranes. Currently, large-scale inflows of waters, with rich nutrient (such as nitrogen and phosphorus) contents, pose the most serious threat to the wetland reserve and its ecosystem [26–29]. In this study, a combined water quantity-quality model has been established to quantitatively analyze and evaluate the water purification function and the maximal load-bearing ability of Zhalong Wetland. The study has incorporated actual wetland conditions, and collected relevant data from ex-situ experiment with corresponding environmental parameters. The study aims to focus on severe, realistic problem of non-point pollution in Zhalong Wetland, provide the scientific basis for the protection of water quality and ecological health, and explore novel ideas and study approach of quantitative evaluation of wetland water purification functions.

2 Materials and methods 2.1

Survey of study area

Zhalong Wetland is located in the Western Songnen Plain,

July (2012) Vol.55 No.7

along the lower Wuyuer River and Shuang Yang River basin (Figures 1(a) and 1(b)), a typical riverside wetland with a total area of 2100 km2 . Reed marsh, which is the largest and most widely distributed landscape feature in Wuyuer River basin, is an important feature of Zhalong Wetland. Figure 2 illustrates the landscapes of Zhalong Wetland in 2006 [30]. Because of vegetation deterioration, the reed pond area is now only about 1000 km2 [31]. Many reed ponds are invaded and mixed with couch grass, because of the lack of water or fluctuation of water levels. Pollutants in Zhalong Wetland mainly come from surrounding industries, domestic sewage discharge, and farmland runoff. Diffuse pollution by fertilizer and pesticide is particularly serious. Nearby irrigation area is estimated to be 400.68 km2, with the application rates of fertilizer and pesticide reaching up to 10200 and 90 t a1, respectively [32]. In addition, reduced water flow and deterioration of reeds, are potential causes of the deteriorated water purification ability and pollution of the wetland reserve. According to the results from three years monitoring by environment protecting department and hydrographic department, the concentrations of TP, TN and NH3-N in the wetland are 8.2, 2.4, and 1.1 times, respectively, of those recommended in quality III Standard of Surface Water (GB3838-2002)[31]. Considering the serious pollution threat posed by nitrogen and phosphorus input into Zhalong Wetland, it is critical to carry out an in-depth study of its purification function and limitation. 2.2

Lab experiment apparatus

In June 2009, a typical swamp wetland was chosen as the prototype of simulation (Figures 1(a) and 1(b)), based on outdoor investigations and tests. This area was the main load-bearing area of drainage with geographical coordinate of 124°11′38″–124°14′14″ of east longitude, and 47°10′19″– 47°13′16″ of north latitude. Alongside water and reeds, soil samples (with depth reaching 45 cm) were collected from the wetland, which were used as the bottom material of pilot-scale wetlands in the experiment. Soil sample was enclosed in the pilot-scale wetlands with naturally packed density and original order (the disturbed samples were collected, bagged on site and filled as its order in laboratory because of large soil mass and distant range). The characters and background of soil were given in Table 1. The reeds were cut into small fragments of about 2–3 cm with each having a dormant bud. Each fragment with a dormant bud was planted per 10 cm×20 cm area of the pilot-scale wetland, 2 cm below the surface land. The dormant buds were observed to sprout up under unsaturated condition, then pouring water every other day to maintain the water level.Three months later, when the reeds grew to maturity and roots grew rapidly, experiment began. Two pilot-scale wetlands, each 200 cm long and 50 cm wide, were installed and operated in the experiments for repetition

Li H Y, et al.

Figure 1

Sci China Tech Sci

1975

July (2012) Vol.55 No.7

Schematic diagram of Zhalong Wetland and range of sampling Table 1

Background characters of soil in Zhalong Wetland

NH3-N Phosphate Nitrite nitrogen Nitrate nitrogen (mg kg1) (mg kg1) (mg kg1) (mg kg1) Background 0.091 3.077 4.385 0.908 black; grades are of equal distribution; percentage content of 0.01mm−0.1mm solids is 88.9%; content of clay is 30%−40%; water content 5.49%. The soil consists of many Characters hydrophilic clay minerals: percentage SiO2, Fe2O3 and Al2O3 are 43%−55%, 1%−3.5% and 20%−25%, respectively.

Figure 2

Picture of landscape type of Zhalong Wetland.

and comparison. A photo of the experiment apparatus is shown in Figure 3. Water flow was controlled by BT100-2J peristaltic pump.

3 Development of combined water quantityquality model Calculation of water quality in wetland includes two parts:

Figure 3

Installation of lab experiment.

calculation of quantity and quality. In this paper, the water purification effect of the wetlands was evaluated by combining the hydrodynamic model, which was based on Saint-Venant equations, and the water quality analysis simulation program which was modified by USEPA. The Hydrodynamic Modeling was used to simulate the water

1976

Li H Y, et al.

Sci China Tech Sci

July (2012) Vol.55 No.7

movement to provide Ux flow data in model of quality, while quality model was used to simulate the migration and interaction of pollutants. 3.1

Gj 

j

The hydrodynamic modeling based on the Saint-Venant equations is widely used, because of generally higher measurement precision and fewer assumption conditions; it includes continuity equations and momentum equations.   Z 1 Q  t  B x  0,   2 gQ Q   Q    Q   gA Z    0,  t x  A  x G 2 AR 

(1)

1 n  j   jn1 , 2





 jn11   jn 1  jn1   jn    (1   ) , x x j x j    t



n 1 j





n j 1

2t

n j

,

Q  Q  C j Z  C j Z  D j ,  n 1 n 1 n 1 n 1  E j Q j  G j Q j 1  F j Z j 1  F j Z j   j . n 1 j

n 1 j 1

n 1 j

B n 1 x j In these equations: C j  q Dj 

j

1 2

x j

 x j



1



j

2

2t

;

(Q nj 1  Q nj )  C j ( Z nj 1  Z nj ); n

 gu  Ej   u    x j ; 2 2t  2 c R  j n j

x j

1  (uQ) nj 1  (uQ) nj  (Q nj 1  Q nj )  2t   1  ( gA) n 1 ( Z nj 1  Z nj ).



3.2

j

2

Water quality modeling

(2) (3)

   C  ( AC )   U x AC  Ex A  A( S L  SB )  AS K , (6) t x  x 

(4)

where superscripts represent time scale, subscripts represent space scale, xj is the length of river number j; t, span of time; n, time’s number; , weight factors (01.0). Weight factors should not be less than 0.5 for the stability of difference equations. Combining eqs. (2), (3) and (4) with continuity equations and momentum equations (1) yields the following linear equations [33]: n 1 j 1

j 

2

The WASP model designed by USEPA is a water quality analysis simulation program. It can simulate various types of surface water, such as river, lake, bay, port, wetland, marsh, pond and reservoir, in one, two or three dimensions. It has been proved to be a valuable tool for solving many problems (for example, eutrophication, transportation of toxicants, or temperature layer). As such, WASP is noted as a universal model [34]. This study has calculated and analyzed the conversion process of nutrient elements in the interface of water, soil and gas. The WASP equation is shown below:

where Q is the quantity of water; B, the width of water in wetland; Z, water level; A, area of water-bearing section; g, gravity constant; G, Xiecai coefficient; R, radius; x, space coordinates; t, time coordinates. The equations were normalized using Preissman weighted implicit four-point scheme. For any , it can be expressed as

n 1 j 1

 gu   u nj 1    x j ; 2 2t  2 c R  j 1

Fj  ( gA) n 1 ;

Hydrodynamic modeling

 ( x, t ) 

n

x j

(5)

where C is the concentration, mg L1; t, time, d; A, crosssectional area, m2; Ux, longitudinal velocity, m s1; Ex, dispersion coefficient, m2 s1; SL, SB, SK are the loading rate of dispersion, boundary and transmittal rate of total power, mg L1 d1. Ux was determined by flow quantity Q and water lever Z, and Ex is linked to Ux . The normalization of equation was carried out with explicit differentiation scheme-forward Euler for time, center for space. The differential equation is as follows: C nj 1  C nj t   Ex  j

n

 C nj  C nj 1 C nj 1  C nj 1   (U x ) nj 1  2    x x  

C nj 1  2C nj  C nj 1

 x 

2

  SL  j   SB  j   SK  j , n

n

n

(7)

where  is the convection factor. The specification of Ux value can proceed with backward differential, and center differential with υ being 0 and 0.5, when ≠0. There can be numerical dispersion, so υ always ranges from 0.0 to 0.4 in the model. 3.3 Spatial simulation experiment Simulation experiments in laboratory have been conducted to derive necessary parameters such as Ex, SL, SB and SK,

Li H Y, et al.

Sci China Tech Sci

and compare and validate the parameter with values from the actual wetland. The upper boundary area was the outflow of farm land, the lower one was the outflow of the wetland, the side boundary conditions were wetlands’ natural conditions, the upper boundary was interface of water and gas, and the lower boundary was bottom mud of wetland. According to the investigation, the main pollution source of water body was the outflow from farm land located on the west of the wetland. In the spatial arrangement of the pilot-scale wetland apparatus, there is no differentiation in vertical direction, the water depth is relatively shallow, and the characters of soil and water do not vary significantly in vertical direction either. There are 20 grids and 21 cross sections. The paper reported analysis results from sampling points 1, 3, 5, 6, 8 and 10 in Figure 4(b). In simulation, water depth was 10 cm, and direction of water flow was from left to right, and flow crossed the inflow of water, SV1-1 to SV6-6 and effluent of water, totally 8 water quality monitoring sections. The flooding water and effluent were single. There was an intake and outlet respectively in inflow and effluent of water which were in the middle of the pilot-scale wetland. Height of intake hose was adjustable, inflow height was 57 cm above the bottom and 10 cm above the surface of the soil; effluent height was 52 cm above the bottom and the flow was 5 mL min-1 during the experiment. Water sample was collected from the aperturebeing 5 cm above the interface of water and soil; four samples were taken from each point, analyzed, and averaged, to determine water quality. 3.4 Major parameters in the model The main parameter is roughness coefficient (n) indicating the effect of wetland bottom surface roughness on the flow

July (2012) Vol.55 No.7

1977

of water. The roughness coefficient relates to the roughness of the packed soil, flow rate, depth and vegetation. Roughness coefficient is a basic parameter for Xiecai coefficient. The Xiecai coefficient is obtained by Chezy formula (G=n1R2/3I1/2), and the roughness coefficient n is obtained with experience-analogy. The flow of water was considered non-uniform flow. The roughness coefficient derived in this study not only reflects the roughness, but also stands for the roughness around, plane pattern of water, geometrical shape, vegetation, hydraulic conditions’ change, slope, flow velocity, depth and effect of measurement error [35]. The parameters of volume, boundary concentration and time function are all set by installation and operating conditions. In model calculation (hydrodynamic modeling), the roughness coefficient was taken as 0.023, and 0.14 d1 was taken as nitrification rates, 0.09 d-1 as denitrification rates, 0.22 d1 as mineralization rates of dissolved organic nitrogen, and 0.25 d1 as mineralization rates of dissolved organic phosphorus according to experience and model description (WASP model).

4 4.1

Result and discussion Validation of the model

The background parameters in model (i.e. water level, quantity, and quality) were set by the values measured in the actual wetland. The initial concentration of inflow water was determined by analyzing the samples collected from the outlets of the nearby irrigation water outflows, which yield the inflow concentration of NH3-N, nitrate nitrogen, PO43, TN and TP as 1.47, 2.38, 0.64, 6.94 and 1.05 mg L1, re-

Figure 4 Meshing of installation of experiment. (a) Sidewise photograph of experiment installation; (b) longitudinal sectional drawing of experiment installation, 1−10 are the water pipes, the paper selected the analysis results with numbers 1, 3, 5, 6, 8, and 10; (c) sketch of grids.

1978

Li H Y, et al.

Sci China Tech Sci

July (2012) Vol.55 No.7

spectively. The simulation time is four weeks (28 days). The sampling frequency from sampling points 1, 3, 5, 6, 8 and 10 was once per week, and the sampling frequency of the effluent is twice per week. Results and data are shown in Tables 2 and 3; the errors between the simulated and observed data are illustrated in Figures 5–8 (x-coordinate 2–7 stand for sampling points 1, 3, 5, 6, 8 and 10 in Figure 4).

Figure 7 Comparison between the simulated and observed data of PO43-P. ——, First week simulation; — —, second week simulation; -----, third week simulation; ―•―•, fourth week simulation; ■, observed data of the first week; ◆, observed data of the second week; ▲, observed data of the third week; ●, observed data of the fourth week.

Figure 5 Comparison between the simulated and observed data of NH4+-N. ——, First week simulation; — —, second week simulation; -----, third week simulation; ―•―•, fourth week simulation; ■, observed data of the first week; ◆, observed data of the second week;▲, observed data of the third week; ●, observed data of the fourth week.

Figure 8 Comparison between the simulated and observed data of TP. ——, First week simulation; — —, second week simulation; -----, third week simulation; ―•―•, fourth week simulation; ■, observed data of the first week; ◆, observed data of the second week;▲, observed data of the third week; ●, observed data of the fourth week.

Figure 6 Comparison between the simulated and observed data of TN. ——, First week simulation; — —, second week simulation; ------, third week simulation; ―•―•, fourth week simulation; ■, observed data of the first week; ◆, observed data of the second week; ▲, observed data of the third week; ●, observed data of the fourth week.

Table 2

The WASP model not only considers the convection load, and dispersion load, but also the boundary load. It is a common practice to use the simulated curves of concentration of pollutants to represent migration and transformation of TN and TP. The concentration was reduced relatively quickly, when the pollutant was close to the inlet, repre-

Comparison between the simulated and observed data of TN and NH4+-N (unit: mg L1)

Monitoring section SV1-1 SV2-2 SV3-3 SV4-4 SV5-5 SV6-6 Effluent

Time (d) observed data simulated data observed data simulated data observed data simulated data observed data simulated data observed data simulated data observed data simulated data observed data simulated data

7 0.28 0.85 0.37 0.59 0.15 0.49 0.14 0.43 0.21 0.40 0.16 0.36 0.42 0.33

NH4+-N 14 21 0.34 0.16 0.59 0.40 0.68 0.12 0.41 0.24 0.26 0.06 0.31 0.19 0.71 0.08 0.27 0.17 0.42 0.09 0.23 0.15 0.39 0.05 0.19 0.13 0.10 0.05 0.18 0.10

28 0.19 0.29 0.10 0.15 0.12 0.11 0.19 0.09 0.22 0.07 0.33 0.05 0.06 0.04



7 4.69 4.69 3.87 3.73 3.61 3.46 3.35 3.34 3.22 3.11 3.07 2.98 2.84 2.85

TN 14 3.07 3.36 2.74 2.51 2.26 2.26 2.41 2.15 2.18 2.06 1.90 2.01 1.77 1.83

21 2.68 2.90 2.03 2.05 1.85 1.67 1.66 1.66 1.62 1.59 1.41 1.51 1.23 1.43

28 2.14 2.40 1.66 1.65 1.35 1.44 1.17 1.37 1.10 1.34 1.03 1.32 0.87 1.31

Li H Y, et al.

Table 3

Sci China Tech Sci

1979

July (2012) Vol.55 No.7

Comparison between the simulated and observed data of TP and PO43–P (unit: mg L1))



7 0.42 0.47 0.27 0.31 0.25 0.25 0.20 0.21 0.18 0.18 0.25 0.16 0.10 0.15

PO43-P 14 21 0.32 0.27 0.34 0.27 0.16 0.13 0.23 0.18 0.14 0.14 0.19 0.13 0.15 0.15 0.15 0.11 0.17 0.07 0.12 0.07 0.17 0.06 0.10 0.06 0.12 0.12 0.09 0.05

28 0.15 0.21 0.11 0.12 0.10 0.08 0.08 0.06 0.09 0.05 0.08 0.03 0.06 0.03

senting the obvious effect of boundary load on it. Meanwhile, diffusion and transference of pollutants were faster because of the major concentration gradient. In the migration process of far from inlet, the concentration gradient decreased, diffusion and transference became steady, so the effect of boundary load gradually decreased gradually, and pollutant concentrations reduction became slower. During weeks 1−4, different deviations between the observed and simulated concentrations of nitrogen and phosphorus were found, which was believed to be caused by pollutant—— microorganism interactions in the wetlands. The calculating formula of errors between the simulated and observed data is as follows:

 

Xo  Xs Xo

,

where Xo is the observed data, Xs is the simulated data. Table 4 shows the relative error of TN and TP between the observed and simulated data of the 28-day simulation calculation period. The result of statistical analysis shows that the relative error between the observed and simulated data for TN and TP was 8.55% and 12.39%, respectively. The trend of pollutant concentration changes, which was forecasted by the simulation, generally matching the observed data. The selected background parameters played an important role, as the simulation was affected by the background parameters, especially the lower initial concentration; the simulation accuracy is expected to improve with higher initial pollutant input concentrations. Therefore, this study demonstrates that it is feasible and effective to use the combined water quantity and WASP model to simulate the water quality of Zhalong Wetland. 4.2 Simulation and forecast result of Zhalong Wetland’s water purification ability Based on pilot-scale experiments results, this study further simulated and forecast the purification ability of Zhalong



TP 7 0.82 0.86 0.66 0.69 0.58 0.59 0.56 0.54 0.48 0.49 0.42 0.42 0.35 0.40

14 0.72 0.72 0.53 0.57 0.50 0.46 0.45 0.42 0.39 0.38 0.34 0.33 0.28 0.31

21 0.55 0.58 0.44 0.43 0.32 0.36 0.32 0.31 0.24 0.28 0.23 0.25 0.19 0.23

28 0.50 0.53 0.19 0.38 0.23 0.27 0.16 0.23 0.15 0.19 0.15 0.16 0.14 0.15

Table 4 Relative error of accuracy of the observed and simulated data of TN and TP Pollutant

Test period

TN

first week second week third week fourth week -

Relative error (%) 2.11 6.19 6.30 19.58 -

28 d

8.55

TP

first week second week third week fourth week -

4.44 5.49 9.97 29.66 -

28 d

12.39

Monitoring Relative error section (%) SV1-1 7.45 SV2-2 3.40 SV3-3 5.14 SV4-4 7.05 SV5-5 8.15 SV6-6 10.99 effluent 17.64 7 monitoring 8.55 sections SV1-1 4.08 SV2-2 28.59 SV3-3 9.90 SV4-4 14.27 SV5-5 11.28 SV6-6 4.58 effluent 13.30 7 monitoring 12.39 sections

Wetland Reserve, using the combined model, with different initial concentrations of TP and TN. Because 90-day average HRT (hydraulic retention time) was estimated according to water flow time from the inlet to the outlet of the reserve, it was selected as the HRT in the model, while other factors were the same as those used in the pilot-scale experiments. When the initial concentrations of TN and TP were 6.94 and 1.05 mg L1, respectively, the changes of concentrations in flow direction are shown in Figures 9 and 10; other results are presented in Table 5. When initial concentrations of TN and TP were 42 and 14 mg L1, respectively, the concentration in the effluent just attained the standards of Grade V (limits of TN and TP are 2.0 and 0.2 mg L1, respectively, according to Surface Water Environmental Quality Standard GB 3838-2002 of China), As such, the bearing ability of Zhalong Wetland for nitrogen and phosphate input is limited by initial concentration and corresponding sewerage flow. In the simulation, the condition was under the unit discharge. It should have

1980

Li H Y, et al.

Sci China Tech Sci

July (2012) Vol.55 No.7

of TN, it can be derived that N C N  Q  Cthreldshold Q  M N,

42.00 mg L1  0.3  1011 L a 1  M N , M N  1.26  103 t a 1 .

From the limits initial concentration and sewerage flow of TP, it can be derived that P C P  Q  Cthreldshold Q  M P,

14.00 mg L1  0.3  1011 L a 1  M P , Figure 9

Comparison between the simulated and observed data of TN.

Figure 10

Table 5 Pollutant TN

TP

Comparison between the simulated and observed data of TP.

Removal rate of control experiment（90d）for TN, TP inflow concentration (mg L1) 4.00 6.94 8.00 16.00 32.00 42.00 56.00 0.50 1.05 4.00 8.00 12.00 14.00 24.00

removel rate (%) 67.3 82.3 83.9 90.4 94.3 95.2 96.2 92.0 90.2 81.4 80.1 85.7 98.6 98.7

effluent concentration (mg L1) 1.31 1.24 1.29 1.53 1.82 2.00 2.41 0.040 0.049 0.099 0.142 0.186 0.200 0.316

considered the whole cross section of wetland when it was adopted in the actual conditions. According to the Environmental Impact Statement of Production Capacity Construction Plan of Hundred Billion Jin (Chinese “jin” equals 0.5 kg) in Heilongjiang Province, water inflows from industries and agriculture surrounding Zhalong Nature Reserve were estimated to be about 0.3×108 m3 a-1 in 1998. Therefore, Q=Total quantity of industrial wastewater+Total quantity of outflow of farm land=0.3×108 m3 a1. From the limits initial concentration and sewerage flow

M P  0.42  103 t a 1 .

The maximum capability of Zhalong Wetland for TN and TP was 1.26×103 and 0.42×103 t a1, respectively. The result matches the standards recommended by Li et al. [36] for the removal of nitrogen and phosphate in reed area in Liaohe River Delta Region. However, this result should be seen as relatively conservative, because the present water inflow is greater than that in 1998, and the nutrient input selected was based on the water quality standard, not the actual flow of nitrogen and phosphate into the reserve. In summary, the combined water quantity and WASP model has been used to predict the water purification efficiency of Zhalong Nature Reserve and estimate its maximum pollutant bearing ability, to help maintain the stability and ecological health of the wetland

5 Conclusions (1) Simulation experiments and simultaneous model predictions have been performed according to typical conditions of Zhalong Wetland, in order to obtain representative results. (2) Combining the wetlands’ actual situation, literatures, and background parameters in pilot-scale experiments, this study simulated the purification function of Zhalong Nature Reserve using a combined water quantity-quality model. The results showed that the relative errors of TN and TP between the observed and simulated data were 8.6% and 12.4%, respectively, and model predictions generally match the observed data. As such, the model is valid and effective to use. (3) The study simulated the purification situation with different initial concentrations of TP and TN using the combined model. When the initial concentrations varied, the results were different. Under the certain concentration range, the removal rate of TN in the wetland was found to increase with the concentration of nitrogen and phosphate. With 90d’ HRT, when the initial concentration of TN was over 42 mg L1, or that of TP was over 14 mg L1, the removal rate of pollutant in the wetland will not warrant Grade V standard. When the inflow water of industry and agriculture was 0.3×108 m3 a1 with Grade V water quality standard, the

Li H Y, et al.

Sci China Tech Sci

maximum capability of Zhalong Wetland for TN and TP was 1.26×103 t a1 and 0.42×103 t a1, respectively. (4) Results from pilot-scale experiments and simulation by the combined model demonstrate that the trends of decrease of TN, TP in the wetland are the same as those for NH4+-N, PO43-P. This result indicates that the mineralization and attenuation of NH4+-N and PO43-P have a major effect on the change of TN and TP concentrations in the wetland.

July (2012) Vol.55 No.7

16

17

18

19

20 This work was supported by the Knowledge Innovation Programs of Chinese Academy of Sciences (Grant No. KZCX2-YW-Q06-2) and the National Basic Research Program of China (“973” Program) (Grant No. 2010CB428404).

21

22 1

2

3 4

5 6

7 8

9

10

11

12

13 14

15

Li W D, Liu Y G, Tian K, et al. Research on purification effect of Jian Lake Zizania latifolia wetland lakefront zone in northwest of Yunnan Plateau on nitrogen and phosphorus of agricultural non-point source. Agr Sci Technol, 2010, 11(7): 109–112, 150 Xu H S, Zhao T Q, He Y X, et al. Effect of different vegetation types on agricultural non-point nitrogen pollution in riparian wetlands (in Chinese). Acta Ecol Sin, 2010, 30(21): 5759–5768 Yao X, Yang G H. Progress on the study of water purification ability of natural wetlands (in Chinese). Prog Geogr, 2009, 28(5): 825–832 Zhu W F, Liu Y J, Ma Y S. Research on the purity effect of agricultural non-point pollution that natural wetlands to Hamatong river basin in Sanjiang Plain (in Chinese). J Northeast Agr Univ, 2009, 40(5): 58–61 Vymazal J. Removal of nutrients in various types of constructed wetlands. Sci Total Environ, 2007, 380(1-3): 48–65 Wen B L, Liu X T, Wang J F. Current state of water environment quality and pollution prevention countermeasures of wetlands in Daqing oil development zones (in Chinese). Wetland Sci, 2010, 8(4): 312–319 Xu D X, Zhang G X. Impact of Human activities on coastal wetlands in China (in Chinese). Wetland Sci, 2007, 5(3): 282–288 Sun Z G, Mo X J, Chen X B, et al. Actualities, problems and suggestions of wetland protection and restoration in the Yellow River Delta (in Chinese). Wetland Sci, 2011, 9(2): 107–115 Steinmann C R, Weinhart S, Melzer A. A combined system of lagoon and constructed wetland for an effective wastewater treatment. Water Res, 2003, 37: 2035–2042 Mantovi P, Marmiroli M, Maestri E, et al. Application of a horizontal subsurface flow constructed wetland on treatment of dairy parlor wastewater. Bioresour Technol, 2003, 88: 85–94 Ji G D, Sun T X, Chang S J, et al. Study on subsurface-flow wetland system for treating thick oil produced water. Acta Scientiae Circumstantiae, 2001, 21(5): 619–621 Gao J H, Ou W X, Yang G S. Distribution characteristics of nitrogen and phosphorus in the ecological region in wetland in northern Jiangsu Province. Proceeding of International Symposium on geography (in Chinese). Guangzhou: Sun Yat-sen University, 2004 Yin S B, Lv X G. Discussion on Some Problems of Rapid Assessment of Wetland Function (in Chinese). Wetland Sci, 2006, 4(1): 1–6 Fu J Y, Ding Z H. Research progress on wetland ecosystem service and its valuation (in Chinese). Chin J Appl Ecol, 2007, 18(3): 681– 686 Wu Z B, Cheng S P, He F, et al. Design and purification performance of vertical flow constructed wetland (in Chinese). Chin J Appl Ecol, 2002, 13(6): 715–718

23 24

25

26

27

28

29

30

31

32

33 34

35

36

1981

Liu S Y, Yan B X, Wang L X. Segregation effect of purification for nitrogen and phosphate pollution in the subsurface flow constructed wetlands (in Chinese). Environ Sci, 2011, 32(3): 723–728 Kohler E A, Poole V L, Reicher Z J, et al. Nutrient, metal, and pesticide removal during storm and nonstorm events by a constructed wetland on an urban golf course. Ecol Eng, 2004, 23(4-5): 285–298 Janjit I, Su W Y, Jae S R. Nutrient removals by 21 aquatic plants for vertical free surface-flow (VFS) constructed wetland. Ecol Eng, 2007, 29(3): 287–293 Li S S, Tian K, Liu Y G, et al. Compare the purification effects of sewage by the wetland plant community composition and spatial patterns (in Chinese). Ecol Environ Sci, 2010, 19(8): 1951–1955 David A K, Mark B D, Lowell E G, et al. Effectiveness of constructed wetlands in reducing nitrogen and phosphorus export from agricultural tile drainage. J Environ Qual, 2000, 29 (4): 1262–1274 Kent D M, Reimold R J, Kelly J. Wetlands Delineation and Assessment. Technical Report to the Connecticut Department of Transportation. Bureau of Planning in Washington in USA, 1990 Larson J S, Mazzarese D B. Rapid assessment of wetlands: History and application to management. In: Mitsch W J, ed. Global Wetlands: Old World and New. Amsterdam: Elsevier, 1994 Yin S B, Lv X G. Discussion on Some Problems of Rapid Assessment of Wetland Function (in Chinese). Wetland Sci, 2006, 4(1): 1–6 Fu J Y, Ding Z H. Research progress on wetland ecosystem service and its valuation (in Chinese). Chin J Appl Ecol, 2007, 18(3): 681– 686 Guo J G, Tang Z Q. Analysis of resource and Functions in Nanwenghe Natural Reserve (in Chinese). Inner Mongolia Forestry Investigation and Design, 2008, 31(5): 11–14 Wang D W, Ding J S, Liu L C. The Water Resources Present Situation and the Countermeasure Study of ZhaLong Wetlands (in Chinese). Water Conserv Sci Technol Economy, 2010, 16(10): 1105– 1107 Li H Y. Study of purification function and mechanism of Zhalong Nature Reserve (in Chinese). Doctoral Dissertation. Changchun: Northeast Institute of Geography and Agroecology of Chinese Academy of Sciences, 2011 Zhou L F, Xu S G, Sun W G. Comprehensive evaluation on water environment quality of Zhalong Wetland based on grey clustering method (in Chinese). J Dalian Univ Technol, 2007, 47(2): 240–245 Wang L, Zhang G X. Responds of Zhalong Wetland to Wuyu'er River hydrological characters (in Chinese). J Arid Land Resour Environ, 2006, 20(6): 94–98 Wo X T. Study on Zhalong Wetland land use and sustainable developments evaluation based on climate change (in Chinese). Doctoral Dissertation. Harbin: Northeast Agricultural University, 2010 Li X C. Study on water requirement of wetland in songnen plain of China (in Chinese). Doctoral Dissertation. Changchun: Jilin University, 2006 Zhang D P, Sun H J. The main ecological environmental problems in Zhalong nature reserve and the improving measures (in Chinese). J Geol Hazards Environ Preserv, 2005, 16(1): 58–62 Wang C H, Li G Z. Calculation of River Floe Practical (in Chinese). Nanjing: Hehai University Press, 2006 Li W. Progress of Environmental Hydraulics (in Chinese). Wuhan: Wuhan University of Hydraulic and Electrical Engineering Press, 1995. 335–344 Ye C M, Chang Y Y, Zhang J Y, et al. Study Mthods and Applications of Mechanism on Oganic Pollution (in Chinese). Beijing: Haiyang Press, 1990. 23–27 Li X Z, Xiao Z N, Hu M Y, et al. Spatial modeling on nutrient reduction in the wetlands II. Finalization and application (in Chinese). Acta Ecol Sin, 2002, 22(4): 486–495