CN101858065B - Method for estimating ecological water amount of shallow lake under pollution stress - Google Patents

Abstract

The invention provides a method for estimating the ecological water amount of a shallow lake under the pollution stress. The method comprises the following steps of: firstly, selecting a key ecological index and determining the ideal ecological water amount by adopting an ecological water level method; secondly, determining an important water quality index by means of a principal component analysis method and building a model of water quality simulation; thirdly, adopting a scenario analysis method on the base, i.e., stimulating the water environment information under different conditions through setting a certain combine scenes (including management objective, wastewater treatment level, conditions of inflow rate, conditions of outflow rate and the like); and finally, comprehensively determining the ecological water amount of the lake under the pollution stress by combining different management requirements and ecological water levels. The action of pollution stress in the current situation is fully considered, the water quality model is coupled to the evaluation for the ecological water amount of the shallow lake, the ecological water amount of the shallow lake is estimated from water quality and water amount demand, so that the ecological water amount is more effectively applied to the actual water resources allocation, and the practicability of the method for estimating the ecological water amount is enhanced.

Description

A kind of shallow lake water demand for natural service amount evaluation method of considering pollution stress

Technical field

The invention belongs to field of environment protection, relate to a kind of shallow lake water demand for natural service amount evaluation method of considering pollution stress.

Background technology

Water demand for natural service is the key factor that water resources configuration and ecosystem protection institute must consider, the reasonable distribution of determining to benefit water resource of reasonable water demand for natural service amount helps keeping the health of whole aquatic ecosystem simultaneously.Existing water demand for natural service method for determination of amount focuses mostly on aspect the river, as runoff period song method, 7Q10 method, the Tennant method based on hydrological analysis; R based on hydraulic parameter ₂CROSS method, wetted perimeter method; Based on the IFIM method on ecological basis and from the BBM method of entire system and overall evaluation method etc.At present, lake ecological water need determines that method mainly contains water balance method, exchange water cycle method, minimum water level method, functional approach and correlation curve method etc.Water balance method and exchange water cycle method are followed nature lake water yield dynamic equilibrium basic principle and the basic law of the lake water amount exchange of coming in and going out, and are applicable to alternately inflow-outflow lake that closes Liu Hu, abundant water and city artificial lake that artificial disturbance is less.Minimum water level method is to determine a kind of method of lake minimum ecological water requirement by lake minimum ecological water level and area, and its data demand for sensitive species is higher.Functional approach is according to ecological basic theories, follows ecological preferential, compatible, maximum value and principle of hierarchy, and system calculates the water demand for natural service amount of each component of lake all sidedly.The correlation curve method refers to set up the ecological functions index system according to the concrete condition in dissimilar lakes, in index historical data and corresponding least quantity input model, set up the water yield and selected ecological functions index correlogram, and determine lake minimum ecological water requirement by seeking knee of curve.But above method is started with from natural water circulation angle mostly, seldom considers water quality factors and social factor, has ignored the intension of water demand for natural service " matter ", and theoretical research and actual Water Resources Allocation are separated.Especially in recent decades the deterioration of water quality has seriously restricted the utilizability of water resource, and the water demand for natural service that makes these methods draw is difficult to satisfy the actual demand of aquatic ecosystem.

Summary of the invention

Determine the deficiency of method at existing water demand for natural service: only consider, ignored the influence of water quality factors for actual water demand for natural service from natural water circulation angle.The technical problem to be solved in the present invention is to set up a kind of new water demand for natural service to determine method, based on the definite water demand for natural service of this technology, can satisfy the demand of the lake aquatic attitude system under the pollution stress effect, and significant for the improvement of aquatic ecosystem with reparation.It is as follows that the present invention solves this technical problem the technical scheme of being taked: at first adopt ecological water level method to determine desirable water demand for natural service amount; Then, select important water quality index, make up the simulation of water quality model by means of PCA; On this basis, adopt scenario analysis, by setting water environment information under certain combination sight (comprising management objectives, sewerage treatment level, inbound traffics condition, outflow condition etc.) simulation different situations; At last, in conjunction with different management expectancys, set the lake ecological water need amount under the pollution stress effect.Concrete steps are as follows:

1. adopt ecological water level method to determine desirable water demand for natural service

According to the state of ecological environment of existing fossil data and survey region, select suitable key ecological index, adopt the desirable water demand for natural service of ecological water level method preresearch estimates.

At first, from the hydrologic condition of survey region, analyze the hydrological data (waterlevel data commonly used is preferably more than 50 years) of its long sequence, determine that by the water level frequency histogram higher water level appears in frequency for many years, as the comparatively suitable hydrologic condition in this zone.The making step of frequency histogram is as follows:

1) finds out the minimum value and the maximum value of sample observations respectively;

$x_1^{*}=\min (x_1,x_2,...,x_n),$ $x_n^{*}=\max (x_1,x_2,...,x_n)---\left(1\right)$

2) suitably choose and be slightly larger than

Several a and be slightly larger than

Several b, and use branch a=t ₀＜t ₁＜t ₂＜...＜t _L-1＜t _l(a b) is divided into 1 subinterval, i.e. (a, t to=b the interval ₁), (t ₁, t ₂) ..., (t _I-1, t _i) ..., (t _L-1, b);

3) all sample observations are assigned in each subinterval one by one, and the calculating sample observations drops on the frequency n in each subinterval _iAnd frequency f _i:

4) each subinterval of intercepting on the x axle is the end with each subinterval, with f _i/ (t _i-t _I-1) make minor matrix, the area Δ S of each minor matrix for height _iBe sample observations and drop on frequency in this subinterval, so the area sum of minor matrix is 1.When sample capacity was enough big, the frequency that stochastic variable X drops in each subinterval was approximately equal to probability, i.e. f _i=P (t _I-1＜X＜t _i).

f _i＝n _i/n (i＝1，2，…，l) (2)

ΔS _i＝(t _i-t _i-1)*f _i/(t _i-t _i-1)＝f _i (i＝1，2，…，l) (3)

Secondly, the biology that selected part upgrowth situation and lake level correlation are bigger is as the ecological index of key.Correlation analysis can be selected the grey relational grade method for use.List reference data (water level) and be compared data (biology) according to the research needs, and carry out nondimensionalization and handle, obtain ordered series of numbers matrix Y, Y in the formula _IjRepresent the i factor, the value of j period, Y _1j(j=1,2 ..., m) be waterlevel data row, Y _Ij(i=2,3 ... n); J=1,2 ..., m) be biological data rows, in n-1 biological data row, the data of total m period.Matrix Y is carried out conversion, can get degree of association coefficient matrix r, r in the formula _IjBe i biological data the j period to the waterlevel data incidence coefficient of j period.

$\begin{array}{cc}Y=\left[\begin{array}{cccc}{y}_{11}& y_{12}& ...& y_{1m}\\ y_{21}& y_{22}& ...& y_{2m}\\ ...& ...& ...& ..\\ y_{n1}& y_{n2}& ...& y_{\mathrm{nm}}\end{array}\right]& r=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1m}\\ r_{21}& r_{22}& ...& r_{2m}\\ ...& ...& ...& ...\\ r_{n-\mathrm{1,1}}& r_{n-\mathrm{1,2}}& ...& r_{n-1,m}\end{array}\right]\end{array}$

The general expression formula of the degree of association is:

$R_i=\frac{1}{m}\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{r}_{\mathrm{ij}}---\left(4\right)$

At last, find out the different year of high-frequency water level correspondence, the ecological index of these different year compared, ecological ragime relatively preferably water level be the ecological water level of average ideal for many years, and the relatively poor relatively water level of ecological ragime is the minimum ecological water level.According to the corresponding relation of the water level and the water yield, can further calculate desirable water demand for natural service amount and minimum ecological water requirement.

2. crucial water quality index is determined

Means by spot sampling, water quality monitoring are replenished existing water quality data, and employing Principal Component Analysis Method etc. is carried out A+E to water pollution type and degree of contamination, and determines crucial water quality index.For the apparent in view survey region of pollution type, can directly select corresponding with it water quality index; Otherwise, can utilize factorial analysis to determine.

At first, get n monitoring point, there is p water quality monitoring variable each monitoring point, forms math matrix X.Earlier variable is carried out standardization, the mathematic expectaion that makes each variable is zero, obtains standardized data matrix Z.

$\begin{array}{cc}X=\left[\begin{array}{cccc}{x}_{11}& x_{12}& ...& x_{1p}\\ x_{21}& x_{22}& ...& x_{2p}\\ ...& ...& ...& ...\\ x_{n1}& x_{n2}& ...& x_{\mathrm{np}}\end{array}\right]& Z=\left[\begin{array}{cccc}{z}_{11}& z_{12}& ...& z_{1p}\\ z_{21}& z_{22}& ...& z_{2p}\\ ...& ...& ...& ...\\ z_{n1}& z_{n2}& ...& z_{\mathrm{np}}\end{array}\right]\end{array}=[z_1{z}_2{z}_3...z_p]$

Then, standardized data is handled, found the solution covariance matrix, be the correlation matrix R of original variable.Solve λ from characteristic equation R-λ I=0 ₁〉=λ ₂〉=λ ₃λ _p＞0 and corresponding characteristic vector u _i(i=1,2 ..., p), obtain eigenvectors matrix U.

$r_{\mathrm{ij}}=S_{\mathrm{ij}}=\frac{\underset{t=1}{\overset{n}{\mathrm{\Σ}}}(x_{\mathrm{ti}}-{\stackrel{\‾}{x}}_i)(x_{\mathrm{tj}}-{\stackrel{\‾}{x}}_j)}{\sqrt{\underset{t=1}{\overset{n}{\mathrm{\Σ}}}{(x_{\mathrm{ti}}-{\stackrel{\‾}{x}}_i)}^2}\sqrt{\underset{t=1}{\overset{n}{\mathrm{\Σ}}}{(x_{\mathrm{tj}}-{\stackrel{\‾}{x}}_j)}^2}}(i,j=\mathrm{1,2},...,p)---\left(5\right)$

According to principal factor analysis (PFA), Y=U ' Z, in the formula Y be one group new uncorrelated each other but be by original variable X ₁X ₂X _pThe new variables matrix of combination.

$U=\left[\begin{array}{c}{y}_1\\ y_2\\ ...\\ y_p\end{array}\right]\·\left[\begin{array}{cccc}\sqrt{{\mathrm{\λ}}_1}& & .& 0\\ & \sqrt{{\mathrm{\λ}}_2}& & \\ ...& ...& ...& ...\\ 0& & & \sqrt{{\mathrm{\λ}}_p}\end{array}\right]\·\left[\begin{array}{c}{y}_1/\sqrt{{\mathrm{\λ}}_1}\\ y_2/\sqrt{{\mathrm{\λ}}_2}\\ ...\\ y_p/\sqrt{{\mathrm{\λ}}_p}\end{array}\right]---\left(6\right)$

Order $f_1=y_1/\sqrt{{\mathrm{\λ}}_1},f_2=y_2/\sqrt{{\mathrm{\λ}}_2},...,f_p=y_p/\sqrt{{\mathrm{\λ}}_p}$

So $Z=\mathrm{UY}=\left[\begin{array}{cccc}\sqrt{{\mathrm{\λ}}_1}{u}_{11}& \sqrt{{\mathrm{\λ}}_2}{u}_{12}& ...& \sqrt{{\mathrm{\λ}}_p}{u}_{1p}\\ \sqrt{{\mathrm{\λ}}_1}{u}_{21}& \sqrt{{\mathrm{\λ}}_2}{u}_{22}& ...& \sqrt{{\mathrm{\λ}}_p}{u}_{2p}\\ ...& ...& ...& ...\\ \sqrt{{\mathrm{\λ}}_1}{u}_{p1}& \sqrt{{\mathrm{\λ}}_2}{u}_{p2}& ...& \sqrt{{\mathrm{\λ}}_p}{u}_{\mathrm{pp}}\end{array}\right]\·\left[\begin{array}{c}{f}_1\\ f_2\\ ...\\ f_p\end{array}\right]---\left(7\right)$

According to practical problem, choose q main gene, q need satisfy

Generally make Q=85%～95%.Get

Z=AF+ ε is then arranged, in the formula:

$A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1q}\\ a_{21}& a_{22}& ...& a_{2q}\\ ...& ...& ...& ...\\ a_{p1}& a_{p2}& ...& a_{\mathrm{pq}}\end{array}\right]=\left[\begin{array}{cccc}\sqrt{{\mathrm{\λ}}_1}{u}_{11}& \sqrt{{\mathrm{\λ}}_2}{u}_{12}& ...& \sqrt{{\mathrm{\λ}}_q}{u}_{1q}\\ \sqrt{{\mathrm{\λ}}_1}{u}_{21}& \sqrt{{\mathrm{\λ}}_2}{u}_{22}& ...& \sqrt{{\mathrm{\λ}}_q}{u}_{2q}\\ ...& ...& ...& ...\\ \sqrt{{\mathrm{\λ}}_1}{u}_{p1}& \sqrt{{\mathrm{\λ}}_2}{u}_{p2}& ...& \sqrt{{\mathrm{\λ}}_q}{u}_{\mathrm{pq}}\end{array}\right]---\left(8\right)$

$\mathrm{\ϵ}=\left[\begin{array}{c}{\mathrm{\ϵ}}_1\\ {\mathrm{\ϵ}}_2\\ ...\\ {\mathrm{\ϵ}}_p\end{array}\right]=\left[\begin{array}{cccc}\sqrt{{\mathrm{\λ}}_{q+1}}{u}_{1q+1}& \sqrt{{\mathrm{\λ}}_{q+2}}{u}_{1q+2}& ...& \sqrt{{\mathrm{\λ}}_p}{u}_{1p}\\ \sqrt{{\mathrm{\λ}}_{q+1}}{u}_{2q+1}& \sqrt{{\mathrm{\λ}}_{q+2}}{u}_{2q+2}& ...& \sqrt{{\mathrm{\λ}}_p}{u}_{2p}\\ ...& ...& ...& ...\\ \sqrt{{\mathrm{\λ}}_{q+1}}{u}_{\mathrm{pq}+1}& \sqrt{{\mathrm{\λ}}_{q+2}}{u}_{\mathrm{pq}+2}& ...& \sqrt{{\mathrm{\λ}}_p}{u}_{\mathrm{pp}}\end{array}\right]\·\left[\begin{array}{c}{f}_{q+1}\\ f_{q+2}\\ ...\\ f_p\end{array}\right]---\left(9\right)$

$F=\left[\begin{array}{c}{f}_1\\ f_2\\ ...\\ f_p\end{array}\right]---\left(10\right)$

At last,, obtain the linear combination of main gene F, and select to contribute several bigger variablees as this regional water quality index main gene about variable X by main gene rotation and main gene score.

F _ij＝b ₁x _i1+b ₂x _i2+…+b _px _ip(i＝1，2，…，n；j＝1，2，…，m) (11)

3. simulation of water quality model construction

Water Environment Simulation is carried out in the lake, can adopt one dimension, two dimension, threedimensional model simulation.Here the NH that adopts the eutrophication module EUTRO in the WASP model to simulate water quality in the water body ₄-N, DO, soluble organic nitrogen (phosphorus) change.The main equation that relates in the simulation process is as follows:

The ammonia nitrogen equation:

$\frac{\∂C_1}{\∂t}=D_p(1-f_{\mathrm{ON}})a_{\mathrm{nc}}{C}_4+k_{71}{\mathrm{\θ}}_{71}^{T-20}\left(\frac{C_4}{k_{\mathrm{mpC}}+C_4}\right)C_7---\left(12\right)$

$-k_{12}{\mathrm{\θ}}_{12}^{T-20}\left(\frac{C_6}{K_{\mathrm{nit}}+C_6}\right)C_1-G_p{a}_{\mathrm{nc}}{P}_{\mathrm{NH}3}{C}_4$

In the formula: f _ONNitrogen is converted into the ratio of organic nitrogen when death of expression phytoplankton and breathing; a _NcThe carbon-nitrogen ratio of expression phytoplankton; k ₇₁The mineralization rate of expression solubilised state organic nitrogen, d ^-1θ ₇₁The temperature coefficient of expression solubilised state organic nitrogen mineralising; k ₁₂Represent the nitrated coefficient of velocity under 20 ℃ of conditions, d ^-1θ ₁₂Represent nitrated temperature coefficient; K _NITThe semi-saturation constant of representing nitrated oxygen supply restriction, mg/L, P _NH3The expression ammonia nitrogen is selected coefficient.

The nitrate nitrogen equation

$\frac{\∂C_2}{\∂t}=k_{12}{\mathrm{\θ}}_{12}^{T-20}\left(\frac{C_6}{K_{\mathrm{nit}}+C_6}\right)C_1-G_p{a}_{\mathrm{nc}}(1-P_{{\mathrm{NH}}_3})C_4-k_{2D}{\mathrm{\θ}}_{2D}^{T-20}\left(\frac{k_{{\mathrm{NO}}_3}}{k_{{\mathrm{NO}}_3}+C_6}\right)C_2---\left(13\right)$

In the formula: K _2DRepresent the denitrification rate under 20 ℃ of conditions, d ^-1θ _2DExpression denitrification temperature coefficient; k _NO3Represent nitrated oxygen supply restriction semi-saturation constant, mg/L.

The Phos equation

$\frac{\∂C_3}{\∂t}=D_p(1-f_{\mathrm{op}})a_{\mathrm{pc}}{C}_4+k_{83}{\mathrm{\θ}}_{83}^{T-20}\frac{C_4}{K_{\mathrm{mpc}}+C_4}{C}_8-G_p{C}_4{a}_{\mathrm{pc}}-\frac{v_{S3}(1-f_{d3})}{D}{C}_3---\left(14\right)$

In the formula: f _OpExpression phytoplankton phosphorus dead and that breathe transfers the ratio of organophosphor to; a _PcThe phosphorus carbon ratio of expression phytoplankton; k ₈₃The mineralization rate of expression solubilised state organophosphor, d ^-1θ ₈₃The temperature coefficient of expression solubilised state organophosphor mineralising; f _D3The dissolving ratio of expression Phos in water; v _S3The settling rate of expression organic substance.

The phytoplankton equation

Phytoplankton?N $\frac{\∂C_4{a}_{\mathrm{nc}}}{\∂t}=(G_p-D_p-\frac{v_{S4}}{D})C_4{a}_{\mathrm{nc}}---\left(15\right)$

Phytoplankton?P $\frac{\∂C_4{a}_{\mathrm{pc}}}{\∂t}=(G_p-D_p-\frac{v_{S4}}{D})C_4{a}_{\mathrm{pc}}---\left(16\right)$

In the formula: Gp represents the growth rate of phytoplankton; Dp represents the rate of death of phytoplankton.

Carbon biochemical oxygen demand (BOD) equation

$\frac{\∂C_5}{\∂t}=a_{\mathrm{oc}}{k}_{1d}{C}_4-k_D{\mathrm{\θ}}_D^{T-20}\frac{C_6}{k_{\mathrm{BOD}}+C_6}{C}_5-\frac{v_{S3}(1-f_{d5})}{D}{C}_5-\frac{5}{4}\frac{32}{14}{k}_{2D}{\mathrm{\θ}}_{2D}^{T-20}\left(\frac{k_{{\mathrm{NO}}_3}}{k_{{\mathrm{NO}}_3}+C_6}\right)C_2---\left(17\right)$

In the formula: a _OcThe carbon ratio of expression phytoplankton; k _DRepresent the CBOD degradation rate under 20 ℃ of conditions, d ^-1θ _DThe temperature coefficient of CBOD degraded in the expression water body; K _BODThe oxygen restriction semi-saturation constant of expression CBOD degraded, mg/L; f _D5The ratio of expression solubilised state CBOD.

The dissolved oxygen equation

$\frac{\∂C_6}{\∂t}=k_2(C_5-C_6)-k_D{\mathrm{\θ}}_D^{T-20}\frac{C_6}{k_{\mathrm{BOD}}+C_6}{C}_5-\frac{64}{14}{k}_{12}{\mathrm{\θ}}_{12}^{T-20}\frac{C_6}{k_{\mathrm{nit}}+C_6}{C}_1$

(18)

$*\frac{\mathrm{SOD}}{D}{\mathrm{\θ}}_5^{T-20}+G_p(\frac{32}{12}+\frac{48}{14}{a}_{\mathrm{nc}}(1-P_{{\mathrm{NH}}_3}))C_4-\frac{32}{12}{k}_{1R}{\mathrm{\θ}}_{1R}^{T-20}{C}_4$

In the formula: k ₂The reoxygenation velocity constant of representing water body under 20 ℃ of conditions, d ^-1Cs represents saturated dissolved oxygen concentration; SOD represents the bed mud oxygen demand, g/ (m ²D); θ _SODThe temperature coefficient of expression bed mud oxygen demand.

Solubilised state organic nitrogen equation

$\frac{\∂C_7}{\∂t}=k_{\mathrm{diss}}{\mathrm{\θ}}_{\mathrm{diss}}^{T-20}{C}_{14}-k_{71}{\mathrm{\θ}}_{71}^{T-20}\left(\frac{C_4}{K_{\mathrm{mpc}}+C_4}\right)C_7---\left(19\right)$

In the formula: K _MpcThe semi-saturation constant of expression phytoplankton recycling.

Solubilised state organophosphor equation

$\frac{\∂C_8}{\∂t}=k_{\mathrm{diss}}{\mathrm{\θ}}_{\mathrm{diss}}^{T-20}{C}_{15}-k_{83}{\mathrm{\θ}}_{83}^{T-20}\left(\frac{C_4}{K_{\mathrm{mpc}}+C_4}\right)C_8---\left(20\right)$

According to original function division, orographic condition etc., the zone, lake is divided and generalization, will treat that survey region is divided into plurality of sub-regions, determine its primary condition, fringe conditions etc.; According to circumstances set up corresponding time series, make up lake water quality model, utilize historical monitored data that model is debugged and parameter calibration, and simulate the change in time and space of water quality under the tale quale based on WASP.

4. based on the lake ecological water need amount under the pollution stress effect of sight setting method

Utilize the water quality model of being built, the water quality under the different hydrologic regimes in lake, the different sewage processing horizontal is simulated, and further determined lake ecological water need rule based on water pollution.

By simulation of water quality and analysis, under research flood season and non-flood season, the spatial distribution and the variation of the crucial water quality index in lake.

Construction in conjunction with existing sewage treatment facility, hydraulic engineering, set different sight scheme collection (as the different sewage processing horizontal, the input of different face source control strategies, different flow, different lake management objectives etc.), study the variation tendency of the crucial water quality index under the different sight schemes, further disclose the water resource supply, control the influence of source measure water correction.

On the basis of above-mentioned research, towards final definite Baiyang Lake water demand for natural service amount of different management objectives.

The invention has the advantages that: generally be subjected to the reality polluted in various degree in conjunction with domestic lake, take into full account the pollution stress effect, the simulation of water quality model is coupled to the assessment of shallow lake water demand for natural service amount, start with from water quality demand and two angles of water yield demand and to determine the lake ecological water need rule, the result can more effectively be applied in the actual Water Resources Allocation; At the hydrological characteristics of different times, different level of pollution control and different lake management objectives, determine corresponding water demand for natural service respectively, the result that water demand for natural service is estimated is comprehensive more, practicality is stronger.

Description of drawings

Fig. 1 is for considering the shallow lake water demand for natural service amount evaluation method flow chart of pollution stress effect

The specific embodiment

Be that case study on implementation further specifies the present invention with the northern China lake below.

(1) tentatively determines desirable water demand for natural service threshold value

Certain shallow water grass type lake makes a clear distinction between the four seasons, and light and heat condition is good, is suitable for the aquatile procreation.According to historical summary and on-site inspection, determine that the main biocoene in this zone is reed, fish, planktonic organism, zoobenthos etc., adopt ecological water level method to determine that tentatively the monthly average minimum ecological water requirement of this lake whole year is 0.87 * 10 then ⁸m ³, desirable water demand for natural service amount is 2.78 * 10 ⁸m ³

(2) crucial water quality index is determined

The pollution type in this lake is an eutrophication, and crucial water quality index is DO, BOD ₅, NH ₄-N, TN and TP.By principal component analytical method the water pollution situation in lake is estimated, the result shows: the water quality in most of zone, this lake surpasses the III class water quality of surface water environment, and wherein subregion 8 pollutes particularly serious near going into the exit of a lake.

Each regional water quality principal component analysis result of table 1 lake

(3) structure of simulation of water quality model

According to the survey region hydrological characteristics, select suitable hydraulics mode and diffusion coefficient; Set up the time series of basin pollution load, amount of precipitation, evaporation capacity and run-off; Selected influence parameter,, and carry out parameter calibration by simulation as temperature, wind speed, sunshine, bed mud oxygen demand, bed mud ammonia nitrogen and phosphorus burst size, planktonic organism etc.

Dependent constant calibration in the table 3 simulation of water quality model

(4) the lake ecological water need amount of consideration pollution stress effect determines

Under the different external source sewerage treatment levels (10%, 30%, 50%, 80%), the variation of simulating crucial water quality index.The result shows: under 10% and 30% sewerage treatment level, water correction is not obvious, and overall water quality does not still satisfy surface water III class water quality standard; And processing horizontal 50% time, change of water quality has clear improvement.

Different flow input 0m ³/ s, 1.45m ³/ s and 2.1m ³Under/the s, simulate crucial water quality index and change.The result shows: 1.45m ³/ s and 2.1m ³Under/s the situation, water quality has improvement slightly, and input flow rate is big more, improves big more.Dissolved oxygen is lower than 5mg/L, satisfies face of land water environment III class water quality standard, NH in the water ₄-N content is mild downward trend; Org-N and Org-P are still in rising trend, and do not satisfy surface water environment III class water quality standard.

Set different scheme collection (the different processing horizontals that pollute are imported with the different water yields), utilize water quality model to simulate, study estimate Baiyang Lake water demand for natural service amount.According to analog case, input flow rate is 0m under the examination comparison 30% pollution processing horizontal ³/ s, 2m ³/ s, 3m ³/ s, 3.5m ³Input flow rate is 0m under/s and the 50% pollution processing horizontal ³/ s, 1.45m ³/ s, 2m ³/ s, 3m ³The simulation of water quality result of eight kinds of schemes of/s.Show that by this research simulation 30% pollutes processing horizontal guarantees 3.5m down ³/ s input flow rate, 50% pollutes processing horizontal guarantees 3m down ³/ s input flow rate has better action for the improvement of Baiyang Lake water quality.

The different water demand for natural service estimations of polluting under the processing horizontal of table 4

Claims (1)

1. shallow lake water demand for natural service amount evaluation method of considering pollution stress, its determining step is as follows:

(1) adopt ecological water level method to determine the water demand for natural service amount in lake

(2) crucial water quality index is determined

Employing is carried out A+E based on the Water Quality Evaluation method of principal component analysis to water pollution type and degree of contamination, and determines crucial water quality index;

(3) structure of simulation of water quality model

According to function division and orographic condition, the lake water environment situation is carried out the zone divide and generalization, will treat that survey region is divided into plurality of sub-regions, determine its primary condition, fringe conditions; According to circumstances set up corresponding time series, make up lake simulation of water quality model, utilize historical monitored data that model is debugged and parameter calibration, and simulate the change in time and space of water quality under the tale quale;

(4) based on shallow lake water demand for natural service amount estimation under the pollution stress effect of sight setting method

Utilize the simulation of water quality model of being built, the water quality under different lakes, lake management objectives, different hydrologic regime, the different sewage processing horizontal sight simulated, and further determine based on the lake ecological water need amount under the pollution stress effect:

A) by simulation of water quality, analyze under the different hydrologic regimes spatial distribution and the variation of the crucial water quality index in lake;

B) in conjunction with the construction of existing sewage treatment facility, hydraulic engineering, set different sight scheme collection, study the variation tendency of the crucial water quality index under the different sight schemes, further disclose the water resource supply, control the influence of source measure water correction;

C) according to concrete lake management expectancy, the comprehensive shallow lake water demand for natural service suggested design of determining to consider pollution factor.