CN105243250A - Auto-control water source layering water taking method and system based on three-dimensional algae ecology model - Google Patents
Auto-control water source layering water taking method and system based on three-dimensional algae ecology model Download PDFInfo
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Abstract
The invention provides an auto-control water source layering water taking method and system based on a three-dimensional algae ecology model. The method comprises the steps that 1, water quality, hydrology and meteorology data of a water intake in a water source water body are collected through a data collecting system; 2, the obtained water quality, hydrology and meteorology data are processed through a simulation forecasting system, the pollution load of rainfall runoff entering the water body is calculated in a simulating mode through a watershed hydrologic model, the algae distribution condition in the water source water body is predicted in a simulating mode through a water quality ecology model, and vertical distribution data of algae at the water intake are obtained; 3, the vertical distribution data of the algae at the water intake are analyzed by an automatic control system to determine a lowest algae concentration water layer at the water intake, and a water taking device is controlled to take water at the lowest algae concentration water layer. According to the method, it can be scientifically guaranteed that the algae concentration of the taken water is lowest within the range of the water intake, the phenomenon that water plant production even user health are threatened due to the problem of outbreak growth of the algae is effectively avoided, and the important significance on urban safety water supply is achieved.
Description
Technical field
The present invention relates to urban safety hydrotechny, be specifically related to a kind of automatic control water source stratified pumping method and system based on three-dimensional Algal Ecology model, be applicable to there is algae and break out risk or have algae to break out the source water water intaking of history.
Background technology
Water is the material base that the mankind depend on for existence, drinking water safety is related to the healthy of the people and life security, carry out the safety guarantee work of potable water, be the practical manifestation ensureing the most fundamental interests of numerous people, drinking water safety problem is shown great attention to always in recent years.
According to " water resources in china publication in 2013 " that Ministry of Water Resources issues, to 2013, to the whole nation 262 large reservoirs, 381 medium-sized reservoirs and 24 small reservoirs, totally 667 major reservoirs have carried out water quality assessment.Annual water quality is that the reservoir of I class has 31, accounts for and evaluates 4.7% of reservoir sum; II 301, class reservoir, accounts for 45.1%; III 211, class reservoir, accounts for 31.6%; IV 66, class reservoir, accounts for 9.9%; V 25, class reservoir, accounts for 3.7%; Bad 33, V class reservoir, accounts for 5.0%.Evaluate the nutritional status of 646 reservoirs, the reservoir of Middle nutrition state has 375, and the reservoir of slight eutrophic state has 214,55, moderate eutrophy reservoir, 2, severe eutrophy reservoir.As can be seen here, the situation is tense for the pollution of Drinking Water in China source.
The risk that Reservoir Eutrophication can cause reservoir to there is algae breaking out, and algae break out the influent quality that directly can have influence on waterworks.In recent years, for Shenzhen, 2 ~ April Tie Gang, often multiply the diatom being not easy to be oxidized and to remove in stone rock reservoir water, these phycobionts are constantly assembled, are piled up in the upper water of filter tank, Shi Yitie hilllock reservoir is the new peace at Yuan Shui water source, Zhu Ao water factory and to be Yuan Shui water source vertical new, filter tank latch up phenomenon appears in phoenix, Chang Liupo, Shang Nandeng water factory in succession with stone rock reservoir, filter cycle significantly foreshortens to 8-9h even 3 ~ 4h by 24h, and then cause water factory's production capacity to die-off, have a strong impact on the safety and stability water supply function of these water factories.
For the production capacity decline problem that water factory produces because water inlet algae concentration is high, no doubt corresponding technological measure can be taked in water factory inside, but be proven and mainly can take measures mostly to exist that cost is high, the series of problems such as accessory substance and noxious material whereabouts unknown, therefore, it may be necessary very much the grasp to source water algae concentration space distribution situation, take Optimized Operation or optimize the means of fetching water, realizing the water intaking of low algae concentration.
A large amount of datas shows, algae exists lamination in source water, but layering rule is not unalterable.Traditional concept thinks that the concentration of Measures of Algae in Water Body reduces along with the continuous increase of the degree of depth more, consistent with the intensity of illumination Changing Pattern in water, and the intake of water head site is also follow the level of dead water of this theoretical installation at reservoir mostly at present.But in fact, the vertical distribution of algae concentration, except by except the impact of intensity of illumination, is also subject to the impact of the many factors such as temperature, dissolved oxygen DO, nutritive salt, hydrodynamic condition and himself catenary motion simultaneously.According to the Monitoring Data of 2013-2014 year to the typical reservoir algae vertical characteristics in three, Shenzhen, algae vertical characteristics mainly presents three kinds of rules: > middle level, top layer > bottom; > top layer, middle level > bottom; Bottom > top layer/middle level.Therefore, it may be necessary the minimum water layer of certain means identification algae concentration, directed water intaking.
Along with the continuous upgrading of the hardware of electronical computer and the development of numerical computation technology, phytoplankton growth have also been obtained significant progress.In a model, the change hydrodynamics formula in space describes, and ecology-geochemical process by biology with the process prescription of chemistry, influence factor comprises carbon, nitrogen, phosphorus, silicon, sulphur, oxygen, illumination etc.Vegetation ecology survey is mainly deduced the change procedure of three trophic levels (phytoplankton, animal plankton and fish) and each element (as carbon, phosphorus, nitrogen) Physics, chemistry and biology.At present, existing a large amount of phytoplankton growth is available, as EFDC, Delft3D, WASP, HEM or MIKE model etc.Apply the simulated system that these models effectively can set up different source water different dimensions, realize the dynamic similation of algae concentration.Wherein, if the vertical characteristics situation of algae will be simulated, then need to set up the three-dimensional phytoplankton growth of algae.Meanwhile, countries in the world all establish oneself drinking water source monitoring system, and at present, the departments such as the environmental protection of China, water conservancy, land resources, urban construction and health all have corresponding monitoring function and ability.Have on the basis of monitoring system in all departments, the input data required for Integrated Models simulation system satisfy the requirements.
Reservoir stratified pumping technology just starts application at reservoir as far back as the nineties in 20th century, but the layering water fetching device so far for quality problem is also less, mostly mainly concentrate on the field for large reservoir water at low temperature problem, what minority was relevant to water quality also only relates to ferrimanganic or dissolved oxygen DO, and has no the concentration dependent research with algae.And in recent years along with the development of automatic control technology, automatic controlling gate at home many reservoirs enable, therefore, set up a layering water fetching device automatically controlled and there is not technical matters.
Summary of the invention
In view of the risk that the algae of current many source waters existence breaks out, the invention provides a kind of automatic control water source stratified pumping method based on three-dimensional Algal Ecology model and realize the layering water intaking system of the method, break out risk to adapt to there is algae or have algae to break out the source water water intaking of history.
The present invention is based on the automatic control water source stratified pumping method of three-dimensional Algal Ecology model, comprise the following steps:
(1). by the water quality of intake position in data acquisition system source water, the hydrology and weather data;
(2). by Simulation prediction system, described water quality, the hydrology and the weather data that step (1) obtains is processed, Watershed Hydrologic Models analog computation two Phase flow amount and rainfall runoff is adopted to enter the pollutional load of reservoir generation, adopt algae distribution situation in phytoplankton growth simulation and forecast source water, the intake position algae vertical characteristics data obtained;
(3). by automatic control system, the intake position algae vertical characteristics data described in step (2) are analyzed, determine the minimum water layer of algae concentration of intake position; And control hierarchy water fetching device is in the minimum water layer water intaking of this algae concentration.
In step (2), described Watershed Hydrologic Models can be SWAT(SoilandWaterAssessmentTool), Xinanjiang model, HEC-HMS(TheHydrologicEngineeringCenter'sHydrologicModeli ngSystem), SCS (SoilConservationService) or HSPF (HydrologicalSimulationProgram-Fortran).Described phytoplankton growth can be EFDC (EnvironmentalFluidDynamicCode), Delft3D, WASP (TheWaterqualityAnalysisSimulationProgram), HEM (HydrodynamicEutrophicationModel) or MIKE.
In step (2), described intake position algae vertical characteristics data comprise the chlorophyllous vertical characteristics data of blue-green algae chlorophyll, green alga chlorophyll and diatom.
In exemplary embodiments step (2), described two Phase flow amount and described pollutional load adopt SWAT Watershed Hydrologic Models to calculate by described Simulation prediction system, and described two Phase flow amount and pollutional load are participated in the calculating of phytoplankton growth as the initial conditions of EFDC phytoplankton growth.Wherein, described two Phase flow amount is flow path surface, the final water cut of soil and underground runoff three sum.Described pollutional load comprises the nitrate of free water part, organic nitrogen with the defeated dissolved phosphorus that moves of the defeated amount of moving of soil losses, rainwash and organophosphorus and mineral phosphor with the defeated amount of moving of soil losses.
Described water quality, the hydrology and weather data that step (1) obtains transfer to described Simulation prediction system by communication network.
Realize a kind of automatic control water source layering water intaking system based on three-dimensional Algal Ecology model of said method, comprising: data acquisition system (DAS), for gathering the water quality of intake position in source water, the hydrology and weather data; Data transmission system, for transmitting described water quality, the hydrology and weather data that data acquisition system (DAS) obtains; Simulation prediction system, for receiving, processing described water quality, the hydrology and weather data that data transmission system is transmitted, the pollutional load of reservoir generation is entered by Watershed Hydrologic Models analog computation two Phase flow amount and rainfall runoff, by algae distribution situation in phytoplankton growth simulation and forecast source water, the intake position algae vertical characteristics data obtained; Automatic control system, for the intake position algae vertical characteristics data described in analyzing and processing, determines the minimum water layer of algae concentration of intake position; And layering water fetching device, for being received from the steering order of autocontrol system, opens the self-shooter of the minimum water layer of algae concentration being positioned at described intake position, water intaking.
Wherein, described data acquisition system (DAS) comprises routine monitoring data entry system, for the typing of the routine monitoring data by the departments concerned; And real time on-line monitoring system, is made up of on-line monitoring probe, on-line sampling device and on-line automatic analyzer.Described layering water fetching device comprises multiple self-shooter, is configured at the algae vertical characteristics layer of intake position in source water respectively.
The present invention carries out simulation and forecast by the three-dimensional ecological model of algae to intake position algae delamination in source water, two Phase flow amount and the pollutional load of water body is entered by Watershed Hydrologic Models analog computation, the algae vertical layered of three-dimensional phytoplankton growth analog computation source water intake position is adopted to distribute, and then accurately determine the minimum water layer of algae concentration of intake position, and control hierarchy water fetching device is in the minimum water layer water intaking of this algae concentration.
The present invention effectively can not only alleviate the impact to water factory's production capacity when algae breaks out, and can also expand comes realizes algae early warning and the Optimized Operation of source water, has broad application prospects.
Accompanying drawing explanation
Fig. 1 is system chart of the present invention;
Fig. 2 is data acquisition of the present invention and transmission system schematic diagram;
Fig. 3 is the process flow diagram of the inventive method;
Fig. 4 represents water shed model watershed partitioning;
Fig. 5 represents phytoplankton growth stress and strain model, a) Xili reservoir, b) iron hilllock reservoir, c) stone rock reservoir;
Fig. 6 is reservoir level calculated value and measured value comparison diagram, a) Xili reservoir, b) iron hilllock reservoir, c) stone rock reservoir;
Fig. 7 is top layer, Xili reservoir intake position algae result of calculation and measured value comparison diagram;
Reservoir intake position, Tu8Wei Tie hilllock top layer algae result of calculation and measured value comparison diagram;
Fig. 9 is stone rock reservoir intake position top layer algae result of calculation and measured value comparison diagram.
Embodiment
Below by way of the drawings and specific embodiments to the detailed description of the invention.
With reference to Fig. 1, Fig. 2, the present invention is based on the system of the automatic control water source stratified pumping of three-dimensional Algal Ecology model, comprising: data acquisition system (DAS) 1, for gathering the water quality of intake position in source water, the hydrology and weather data; Data transmission system 2, for transmitting described water quality, the hydrology and weather data that data acquisition system (DAS) obtains; Simulation prediction system 3, for receiving, processing described water quality, the hydrology and weather data that data transmission system 2 is transmitted, the pollutional load of reservoir generation is entered by Watershed Hydrologic Models 31 analog computation two Phase flow amount and rainfall runoff, by algae distribution situation in phytoplankton growth 32 simulation and forecast source water, the intake position algae vertical characteristics data obtained; Automatic control system 4, for the intake position algae vertical characteristics data described in analyzing and processing, determines the minimum water layer of algae concentration of intake position; And layering water fetching device 5, for being received from the steering order of autocontrol system, opens the self-shooter of the minimum water layer of algae concentration being positioned at described intake position, water intaking.
In system, described data acquisition system (DAS) 1 comprises: routine monitoring data entry system 11, for the typing of the routine monitoring data by the departments concerned; And real time on-line monitoring system 12, is made up of on-line monitoring probe, on-line sampling device and on-line automatic analyzer.Described layering water fetching device 5 comprises multiple self-shooter, is configured at the algae vertical characteristics layer of intake position in source water respectively.
For western beautiful, Tie Gang, Shi Yan tri-Cascade Reservoirs in Shenzhen, with reference to Fig. 1, process flow diagram 3, the automatic control water source stratified pumping method that the present invention is based on three-dimensional Algal Ecology model is described.
1) that, collects complete above-mentioned multi-reservoir by relevant departments comprises a large amount of data such as landform, meteorology, the hydrology, water quality and algae.
2), utilize SWAT water shed model, analyze Land_use change situation in Cascade Reservoirs basin, Cascade Reservoirs basin is divided into 63 sub basin, as shown in Figure 4.
3), apply SWAT water shed model, calculate and obtain two Phase flow amount and pollutional load, as the runoff initial conditions of three reservoirs in EFDC model.Using flow path surface, the final water cut of soil and underground runoff sum as described two Phase flow amount.Wherein,
Described flow path surface by SCS(SoilConservationService, soil conservation office of United States Department of Agriculture) SCS―CN method formula 1-1 calculates,
1-1
In formula 1-1: Q is flow path surface, mm; P is rainfall amount, mm; I
afor the basin initial abstraction before runoff generation; S is soil maximum possibility infiltration capacity, mm.
The final water cut of described soil is calculated by rainfall runoff formula 1-2,
1-2
In formula 1-2:
sW t for the final water cut of soil, mm;
sW 0for antecedent soil moisture, mm;
tfor time step, d;
r day be
iit rainfall amount, mm;
q surf be
iit rainwash, mm;
e a be
iit evaporation capacity, mm;
w seep be
iit is present in infiltration capacity and the measurement of discharge of soil profile bottom, mm;
q gw be
iit groundwater discharge, mm.
Described underground runoff is calculated by underground runoff formula 1-3,
1-3
In formula 1-3:
for underground runoff, mm;
for calculating the underground runoff of the previous day, mm;
for time step, d;
be the make-up flow of i-th day aquifer, mm;
for the water-break coefficient of base flow.
Simulate described pollutional load in the following manner, wherein, the nitrate of free water part calculates with formula 1-4-1,
1-4-1
In formula 1-4-1,
for the nitrate of free water part, kg/mm;
for the amount of nitrified nitrogen in soil, kg/hm
2;
for the amount of free water in soil, mm;
for factor of porosity;
for saturated soil water content;
Organic nitrogen calculates with formula 1-4-2 with the defeated amount of moving of soil losses,
1-4-2
In formula 1-4-2,
for organic nitrogen is with the defeated amount of moving of soil losses, kg/hm
2;
for the concentration of organic nitrogen in topsoil, kg/t;
for soil loss amount, t;
for the area of hydrology corresponding units, hm
2;
for nitrogen coefficient of concentration, nitrogen coefficient of concentration is the ratio of organic nitrogen concentration with soil losses and upper soll layer organic nitrogen concentration;
The defeated dissolved phosphorus moved of rainwash calculates with formula 1-4-3,
1-4-3
In formula 1-4-3,
the dissolved phosphorus moved for rainwash is defeated, kg/hm
2;
for dissolved phosphorus in soil, kg/hm
2;
for soil solute density, mg/m
3;
for surface depth of soil, mm;
for soil phophorus partition factor, the ratio of dissolved phosphorus concentration in the concentration of dissolved phosphorus and rainwash in topsoil;
Organophosphorus and mineral phosphor calculate with formula 1-4-4 with the defeated amount of moving of soil losses,
1-4-4
In formula 1-4-4,
for organophosphorus and mineral phosphor are with the defeated amount of moving of soil losses, kg/hm
2;
for the concentration of organophosphorus in topsoil, kg/t;
for soil loss amount, t;
for the area of hydrology corresponding units, hm
2;
for phosphorus coefficient of concentration.
4), the computing grid of EFDC model construction three reservoirs is adopted, as shown in Figure 5.In Fig. 5, shade represents the end elevation of reservoir, and Xili reservoir has divided 598 computing grids, and iron hilllock reservoir has divided 1099 computing grids, and stone rock reservoir has divided 484 computing grids, and vertical employing σ coordinate is divided into 5 layers.
5) confirmation boundary condition, is arranged
Arrange the meteorological condition that three reservoirs comprise solar radiation, temperature, rainfall, wind-force, evaporation capacity etc., arrange the runoff conditions that water shed model exports, arrange water project operation data, arrange reservoir Inlet and outlet water water quality data etc., these boundary conditions as model are set in a model.
EFDC phytoplankton growth comprises with lower part:
Equation of momentum 2-1
State equation 2-2
Continuity equation 2-3
Thermohaline equation 2-4
Water quality factor transport equation 2-5
In formula,
z* vertical physical coordinates is represented ,-
hwith
the vertical coordinate of bottom surface and free-water level respectively, H=h+
total depth of water,
uwith
vin curvilinear orthogonal coordinate system respectively
xwith
ythe speed component in direction,
wfor vertical velocity component,
m x with
m y the square root of the diagonal element of metric tensor,
m=
m x m y jacobian,
patmospheric pressure,
the density of water,
the reference density of water,
gfor acceleration of gravity, buoyancy
bbe defined as relative to reference density normalized offset,
twith
stemperature and salinity respectively; In equation of momentum 2-1
fcorrioli's effect parameter,
a v vertical turbulent fluctuation or eddy viscosity,
q u with
q v it is momentum source sink term; In thermohaline equation 2-4,
q s with
q t be respectively the source sink term of salinity and temperature,
a b it is vertical turbulence diffusion coefficient;
In water quality factor transport equation 2-5,
cfor water quality factor concentration,
k v with
k h be respectively vertical and level turbulence diffusion coefficient (when
cwhen representing the concentration of suspended material,
w sc for settling velocity),
q c for source sink term; Adopt Mellor-Yamada2.5 rank turbulent closure model, be coupled with turbulent fluctuation kinetic energy transport equation, vertical mixing constant is provided.
6), model calibration and checking
Historical Monitoring data are adopted to carry out calibration to model, the parameters of Confirming model, design parameter comprises reservoir bottom surface roughness height, algae maximum growth rate, algae metabolic rate, algae prey speed, algae subsidence rate, algae the absorption half saturated constant of nutritive salt, the upper lower limit value etc. of algae optimum growth temperature; By the data of another time period, model is verified again.In above-mentioned three Cascade Reservoirs, the Monitoring Data of the whole year in 2013 can be adopted to carry out calibration to model, adopt the data in the first half of the year in 2014 to verify model, concrete checking index comprises the water quality parameter of the water level of the some key points of reservoir and top layer, middle level, bottom; Wherein water quality parameter mainly comprises temperature, pH, nutritive salt, organism, and blue-green algae, green alga, diatom chlorophyll concentration.For wherein intake position, as shown in Figure 6, for wherein top layer, intake position chlorophyll concentration, its result as shown in figs. 7 to 9 for its water level the result.Fig. 6 is reservoir level calculated value and measured value comparison diagram, a) Xili reservoir, b) iron hilllock reservoir, c) stone rock reservoir.Fig. 7 is top layer, Xili reservoir intake position algae result of calculation and measured value comparison diagram, wherein, upper figure is the comparison diagram of blue-green algae chlorophyll calculated value and measured value, and middle figure is the comparison diagram of green alga chlorophyll calculated value and measured value, and figure below is the comparison diagram of diatom chlorophyll calculated value and measured value.Reservoir intake position, Tu8Wei Tie hilllock top layer algae result of calculation and measured value comparison diagram; Fig. 9 is stone rock reservoir intake position top layer algae result of calculation and measured value comparison diagram.
7) Simulation prediction
According to modelling verification result, suitable adjustment is carried out to model until the error of the result in allowed band after, just model can be used for Simulation prediction.
8) in Simulation prediction, be current data by the boundary condition of model and starting condition real-time update, just effectively can predict current intake position algae vertical characteristics data, change into PLC automatic control signal and science control is carried out to water fetching device, stratified pumping.
Claims (10)
1., based on an automatic control water source stratified pumping method for three-dimensional Algal Ecology model, it is characterized in that, comprise the following steps:
(1). by the water quality of intake position in data acquisition system source water, the hydrology and weather data;
(2). by Simulation prediction system, described water quality, the hydrology and the weather data that step (1) obtains is processed, Watershed Hydrologic Models analog computation two Phase flow amount and rainfall runoff is adopted to enter the pollutional load of reservoir generation, and then by algae distribution situation in phytoplankton growth simulation and forecast source water, the intake position algae vertical characteristics data obtained;
(3). by automatic control system, the intake position algae vertical characteristics data described in step (2) are analyzed, determine the minimum water layer of algae concentration of intake position; And control hierarchy water fetching device is in the minimum water layer water intaking of the algae concentration of this intake position.
2. the method for claim 1, it is characterized in that, in step (2), described Watershed Hydrologic Models is SWAT(SoilandWaterAssessmentTool), Xinanjiang model, HEC-HMS(TheHydrologicEngineeringCenter'sHydrologicModeli ngSystem), SCS (SoilConservationService) or HSPF (HydrologicalSimulationProgram-Fortran); Described phytoplankton growth is EFDC (EnvironmentalFluidDynamicCode), Delft3D, WASP (TheWaterqualityAnalysisSimulationProgram), HEM (HydrodynamicEutrophicationModel) or MIKE.
3. the method for claim 1, is characterized in that, in step (2), and described Simulation prediction Systematic selection SWAT Watershed Hydrologic Models, described two Phase flow amount is flow path surface, the final water cut of soil and underground runoff sum;
By SCS(SoilConservationService) SCS―CN method formula 1-1 calculates described flow path surface;
1-1
In formula 1-1: Q is flow path surface, mm; P is rainfall amount, mm; I
afor the basin initial abstraction before runoff generation; S is soil maximum possibility infiltration capacity, mm;
The final water cut of described soil is calculated by rainfall runoff formula 1-2,
1-2
In formula 1-1:
sW t for the final water cut of soil, mm;
sW 0for antecedent soil moisture, mm;
tfor time step, d;
r day be
iit rainfall amount, mm;
q surf be
iit rainwash, mm;
e a be
iit evaporation capacity, mm;
w seep be
iit is present in infiltration capacity and the measurement of discharge of soil profile bottom, mm;
q gw be
iit groundwater discharge, mm;
Described underground runoff is calculated by underground runoff formula 1-3,
1-3
In formula 1-3:
for underground runoff, mm;
for calculating the underground runoff of the previous day, mm;
for time step, d;
be the make-up flow of i-th day aquifer, mm;
for the water-break coefficient of base flow;
Simulate described pollutional load in the following manner, wherein, the nitrate of free water part calculates with formula 1-4-1,
1-4-1
In formula 1-4-1,
for the nitrate of free water part, kg/mm;
for the amount of nitrified nitrogen in soil, kg/hm
2;
for the amount of free water in soil, mm;
for factor of porosity;
for saturated soil water content;
Organic nitrogen calculates with formula 1-4-2 with the defeated amount of moving of soil losses,
1-4-2
In formula 1-4-2,
for organic nitrogen is with the defeated amount of moving of soil losses, kg/hm
2;
for the concentration of organic nitrogen in topsoil, kg/t;
for soil loss amount, t;
for the area of hydrology corresponding units, hm
2;
for nitrogen coefficient of concentration, nitrogen coefficient of concentration is the ratio of organic nitrogen concentration with soil losses and upper soll layer organic nitrogen concentration;
The defeated dissolved phosphorus moved of rainwash calculates with formula 1-4-3,
1-4-3
In formula 1-4-3,
the dissolved phosphorus moved for rainwash is defeated, kg/hm
2;
for dissolved phosphorus in soil, kg/hm
2;
for soil solute density, mg/m
3;
for surface depth of soil, mm;
for soil phophorus partition factor, the ratio of dissolved phosphorus concentration in the concentration of dissolved phosphorus and rainwash in topsoil;
Organophosphorus and mineral phosphor calculate with formula 1-4-4 with the defeated amount of moving of soil losses,
1-4-4
In formula 1-4-4,
for organophosphorus and mineral phosphor are with the defeated amount of moving of soil losses, kg/hm
2;
for the concentration of organophosphorus in topsoil, kg/t;
for soil loss amount, t;
for the area of hydrology corresponding units, hm
2;
for phosphorus coefficient of concentration;
Described phytoplankton growth adopts EFDC phytoplankton growth.
4. method as claimed in claim 3, it is characterized in that, described EFDC phytoplankton growth comprises with lower part:
Equation of momentum 2-1
State equation 2-2
Continuity equation 2-3
Thermohaline equation 2-4
Water quality factor transport equation 2-5
In formula,
z* vertical physical coordinates is represented ,-
hwith
the vertical coordinate of bottom surface and free-water level respectively, H=h+
total depth of water,
uwith
vin curvilinear orthogonal coordinate system respectively
xwith
ythe speed component in direction,
wfor vertical velocity component,
m x with
m y the square root of the diagonal element of metric tensor,
m=
m x m y jacobian,
patmospheric pressure,
the density of water,
the reference density of water,
gfor acceleration of gravity, buoyancy
bbe defined as relative to reference density normalized offset,
twith
stemperature and salinity respectively; In equation of momentum 2-1
fcorrioli's effect parameter,
a v vertical turbulent fluctuation or eddy viscosity,
q u with
q v it is momentum source sink term; In thermohaline equation 2-4,
q s with
q t be respectively the source sink term of salinity and temperature,
a b it is vertical turbulence diffusion coefficient;
In water quality factor transport equation 2-5,
cfor water quality factor concentration,
k v with
k h be respectively vertical and level turbulence diffusion coefficient (when
cwhen representing the concentration of suspended material,
w sc for settling velocity),
q c for source sink term; Adopt Mellor-Yamada2.5 rank turbulent closure model, be coupled with turbulent fluctuation kinetic energy transport equation, vertical mixing constant is provided.
5. the method as described in claim 1 or 2 or 3, is characterized in that, described water quality, the hydrology and weather data that step (1) obtains transfer to described Simulation prediction system by communication network.
6. the method as described in claim 1 or 2 or 3, is characterized in that, in step (2), described intake position algae vertical characteristics data comprise the chlorophyllous vertical characteristics data of blue-green algae chlorophyll, green alga chlorophyll and diatom.
7., based on the automatic control water source layering water intaking system of three-dimensional Algal Ecology model, it is characterized in that comprising:
Data acquisition system (DAS) (1), for gathering the water quality of intake position in source water, the hydrology and weather data;
Data transmission system (2), for transmitting described water quality, the hydrology and weather data that data acquisition system (DAS) obtains;
Simulation prediction system (3), for the described water quality, the hydrology and the weather data that receive, process data transmission system (2) is transmitted, by the pollutional load that Watershed Hydrologic Models (31) analog computation two Phase flow amount and rainfall runoff produce, by algae distribution situation in phytoplankton growth (32) simulation and forecast source water, the intake position algae vertical characteristics data obtained;
Automatic control system (4), for the intake position algae vertical characteristics data described in analyzing and processing, determines the minimum water layer of algae concentration of intake position; And,
Layering water fetching device (5), for being received from the steering order of autocontrol system, opens the self-shooter of the minimum water layer of algae concentration being configured at described intake position, water intaking.
8. system as claimed in claim 7, is characterized in that: described data acquisition system (DAS) (1) comprises: routine monitoring data entry system (11), for the typing of the routine monitoring data by the departments concerned; Real time on-line monitoring system (12) is made up of on-line monitoring probe, on-line sampling device and on-line automatic analyzer.
9. system as claimed in claim 7, it is characterized in that, described data transmission system (2) comprises communication apparatus (22) and terminal server (23), and communication apparatus (22) is connected with terminal server (23) by communication network.
10. system as claimed in claim 7, it is characterized in that, described layering water fetching device (5) comprises multiple self-shooter, is configured at the algae vertical characteristics layer of intake position in source water respectively.
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| CN108256249A (en) * | 2018-01-26 | 2018-07-06 | 重庆市环境保护信息中心 | A kind of reservoir area of Three Gorges EFDC model integrated methods |
| CN108334702A (en) * | 2018-02-08 | 2018-07-27 | 广州地理研究所 | A kind of unga(u)ged basin hydrologic forecast south China model building method |
| CN109165795A (en) * | 2018-10-11 | 2019-01-08 | 南昌工程学院 | A kind of set Runoff Forecast System and method for based on swarm intelligence algorithm |
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| CN114399103A (en) * | 2022-01-06 | 2022-04-26 | 北京师范大学 | CNN-based land-water integrated river water quality space-time continuous prediction method |
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| CN106096147A (en) * | 2016-06-14 | 2016-11-09 | 珠江水资源保护科学研究所 | Fetch water before ecological dispatching method for reservoir and reservoir dam the determination method of position |
| CN106484976A (en) * | 2016-09-28 | 2017-03-08 | 西安交通大学 | Red tide monitoring early warning system |
| CN106484976B (en) * | 2016-09-28 | 2019-05-07 | 西安交通大学 | Red tide monitoring early warning system |
| CN108256249A (en) * | 2018-01-26 | 2018-07-06 | 重庆市环境保护信息中心 | A kind of reservoir area of Three Gorges EFDC model integrated methods |
| CN108256249B (en) * | 2018-01-26 | 2021-08-03 | 重庆市环境保护信息中心 | Three gorges reservoir area EFDC model integration method |
| CN108334702A (en) * | 2018-02-08 | 2018-07-27 | 广州地理研究所 | A kind of unga(u)ged basin hydrologic forecast south China model building method |
| CN109165795A (en) * | 2018-10-11 | 2019-01-08 | 南昌工程学院 | A kind of set Runoff Forecast System and method for based on swarm intelligence algorithm |
| CN109828091A (en) * | 2019-02-22 | 2019-05-31 | 广东粤港供水有限公司 | Algae monitoring system and method |
| CN114399103A (en) * | 2022-01-06 | 2022-04-26 | 北京师范大学 | CNN-based land-water integrated river water quality space-time continuous prediction method |
| CN117113735A (en) * | 2023-10-25 | 2023-11-24 | 湖南大学 | Algal bloom intelligent early warning method and system based on multilayer ecological model |
| CN117113735B (en) * | 2023-10-25 | 2024-01-02 | 湖南大学 | Algal bloom intelligent early warning method and system based on multilayer ecological model |
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