CN108664647B - Basin fine management system of integrated water environment model - Google Patents
Basin fine management system of integrated water environment model Download PDFInfo
- Publication number
- CN108664647B CN108664647B CN201810471185.2A CN201810471185A CN108664647B CN 108664647 B CN108664647 B CN 108664647B CN 201810471185 A CN201810471185 A CN 201810471185A CN 108664647 B CN108664647 B CN 108664647B
- Authority
- CN
- China
- Prior art keywords
- pollution
- water quality
- unit
- river
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 174
- 238000000034 method Methods 0.000 claims abstract description 37
- 238000012544 monitoring process Methods 0.000 claims abstract description 36
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 35
- 231100000719 pollutant Toxicity 0.000 claims abstract description 35
- 238000004458 analytical method Methods 0.000 claims abstract description 20
- 230000008901 benefit Effects 0.000 claims abstract description 17
- 230000004044 response Effects 0.000 claims abstract description 14
- 238000003911 water pollution Methods 0.000 claims abstract description 4
- 238000007726 management method Methods 0.000 claims description 33
- 238000004088 simulation Methods 0.000 claims description 29
- 238000004364 calculation method Methods 0.000 claims description 28
- 238000012790 confirmation Methods 0.000 claims description 24
- 238000012821 model calculation Methods 0.000 claims description 15
- 238000011144 upstream manufacturing Methods 0.000 claims description 15
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 230000015556 catabolic process Effects 0.000 claims description 7
- 238000006731 degradation reaction Methods 0.000 claims description 7
- 230000007613 environmental effect Effects 0.000 claims description 7
- 238000005094 computer simulation Methods 0.000 claims description 3
- 238000012937 correction Methods 0.000 description 59
- 239000010865 sewage Substances 0.000 description 20
- 244000144972 livestock Species 0.000 description 12
- 244000144977 poultry Species 0.000 description 12
- 238000001556 precipitation Methods 0.000 description 12
- 239000002689 soil Substances 0.000 description 12
- 238000009395 breeding Methods 0.000 description 10
- 230000001488 breeding effect Effects 0.000 description 10
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 description 9
- 239000003337 fertilizer Substances 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 6
- 239000000126 substance Substances 0.000 description 6
- 241000283690 Bos taurus Species 0.000 description 4
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 4
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 4
- 230000008859 change Effects 0.000 description 4
- 229910052760 oxygen Inorganic materials 0.000 description 4
- 239000001301 oxygen Substances 0.000 description 4
- 229910052698 phosphorus Inorganic materials 0.000 description 4
- 239000011574 phosphorus Substances 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 241000209140 Triticum Species 0.000 description 3
- 235000021307 Triticum Nutrition 0.000 description 3
- 239000004927 clay Substances 0.000 description 3
- 230000029142 excretion Effects 0.000 description 3
- 210000003608 fece Anatomy 0.000 description 3
- 239000010871 livestock manure Substances 0.000 description 3
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 2
- 241000282887 Suidae Species 0.000 description 2
- 230000001174 ascending effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000009792 diffusion process Methods 0.000 description 2
- 230000014759 maintenance of location Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 229920000742 Cotton Polymers 0.000 description 1
- 241000287828 Gallus gallus Species 0.000 description 1
- 244000068988 Glycine max Species 0.000 description 1
- 235000010469 Glycine max Nutrition 0.000 description 1
- 241000219146 Gossypium Species 0.000 description 1
- 240000005979 Hordeum vulgare Species 0.000 description 1
- 235000007340 Hordeum vulgare Nutrition 0.000 description 1
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 241001494479 Pecora Species 0.000 description 1
- 240000006394 Sorghum bicolor Species 0.000 description 1
- 235000011684 Sorghum saccharatum Nutrition 0.000 description 1
- 240000008042 Zea mays Species 0.000 description 1
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 description 1
- 235000002017 Zea mays subsp mays Nutrition 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 239000003513 alkali Substances 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 235000015278 beef Nutrition 0.000 description 1
- 238000005842 biochemical reaction Methods 0.000 description 1
- 239000000356 contaminant Substances 0.000 description 1
- 235000005822 corn Nutrition 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010790 dilution Methods 0.000 description 1
- 239000012895 dilution Substances 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000009313 farming Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 239000002957 persistent organic pollutant Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 239000002352 surface water Substances 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
- 210000002700 urine Anatomy 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 239000002351 wastewater Substances 0.000 description 1
- 238000013316 zoning Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/152—Water filtration
Landscapes
- Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a watershed fine management system integrated with a water environment model, which is provided with a database, wherein the database records hydrology, meteorology, pollution sources and water quality monitoring data, meanwhile, a watershed is divided into sub-computing units through watershed and river network grid dividing information stored in a river network grid dividing module, sub-computing unit grids of the whole watershed water system are finally determined, the model computing module is used for simulating the pollutant concentration of each sub-computing unit grid in the watershed, and a water pollution accident analysis method, a pollution source response and treatment project benefit analysis method and a water quality standard exceeding reverse tracing influence pollution source method are constructed on the basis of the water environment model, so that the dynamic and fine management of the pollution sources, projects, water quality and the like in the watershed is realized.
Description
Technical Field
The invention belongs to the field of water environment monitoring and management, and particularly relates to a basin fine management system integrated with a water environment model.
Background
With the rapid development of internet and computer technologies, information technology has been widely applied in various industries. Among them, the level of informatization of the environmental monitoring technology is also increasing. At present, multi-level environment monitoring sites are formed in China, the number of environment monitoring mechanisms established in various industries and departments is continuously increased, and in an environment monitoring system, the use of an informatization technology greatly improves the efficiency of monitoring work, so that cross-region cooperation becomes possible.
Besides the environmental monitoring technology, the informatization technology can play an important role in environmental management. The environment informatization level represents the comprehensive strength and competitiveness of environment management of one region to a certain extent, and is a basic guarantee for realizing scientific management and decision-making of the environment.
In particular to water environment management, a plurality of factors such as pollution sources, water quality, water amount, treatment projects and the like in a water environment flow domain are in dynamic change, and influence factors are complex, so that the fine management of the water environment is very difficult.
Disclosure of Invention
The invention solves the technical problem that the refined management of the water environment in the prior art is very difficult, and further provides a dynamic water environment management system with high refinement degree.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a basin fine management system of an integrated water environment model comprises: a database unit storing: the hydrological database is used for recording hydrological monitoring data in a flow domain; the pollution source database is used for recording the emission data of various pollution sources in the drainage basin; the drainage basin geographic information database is used for recording the geographic information data of the drainage basin; the meteorological and water quality monitoring database is used for recording water quality data in a flow field and meteorological monitoring data corresponding to a meteorological station point; the drainage basin social and economic database is used for collecting drainage basin social and economic and demographic information data; basin fine management system still is provided with water quality simulation unit, water quality simulation unit includes: the river network meshing module is used for storing river network meshing information of a river basin, the river basin is firstly preliminarily divided into a plurality of non-uniform river sections, then each river section is divided into a plurality of sub-computing units, and finally sub-computing unit meshes of the whole river basin water system are determined; the coefficient setting module is used for setting a production and pollution discharge coefficient, a river entering coefficient and a pollutant degradation coefficient; the water quality simulation unit is also provided with a model calculation module, and the model calculation module stores a watershed one-dimensional river network hydrodynamic water quality model and a watershed non-point source production pollution discharge model; the model calculation module is respectively connected with the database unit, the river network grid division module and the coefficient setting module; the model calculation module is suitable for calling data information of the database unit, the river network grid division module and the coefficient setting module and simulating the pollutant concentration of each sub-calculation unit grid in the flow domain.
The water quality simulation unit is also provided with: the hydrologic information confirmation module is suitable for calling the data information of the hydrologic database, confirming the data information of the hydrologic data and issuing a confirmation instruction; the pollution source information confirmation module is suitable for calling the data information of the pollution source database, confirming the data information of the pollution source data and issuing a confirmation instruction;
when the hydrologic information confirmation module and the pollution source information confirmation module issue confirmation instructions, the model calculation module automatically calls the data information of the database unit, the river network grid division module and the coefficient setting module to simulate the pollutant concentration of each sub-calculation unit grid in the flow domain.
The water quality pollution monitoring system is characterized by further comprising a pollution accident analysis unit, wherein the pollution accident analysis unit is provided with an input module used for inputting a pollution accident numerical value, the pollution accident analysis unit carries out dynamic simulation calculation on water quality pollution based on the input of the pollution accident numerical value, and the duration and the influence range of a pollution accident are checked through a simulation result.
The river water quality simulation system is also provided with a pollution source response and treatment project benefit unit, wherein the pollution source response and treatment project benefit unit stores information of new pollution source projects and treatment project schemes, each new pollution source project and treatment project scheme is correspondingly provided with a pollutant discharge amount increasing numerical value or reducing numerical value corresponding to a project, water quality simulation is carried out by selecting different project schemes, and the environmental benefits of the new pollution source projects and the treatment projects on the river water quality can be checked through the simulation results.
The water quality overproof backtracking influence pollution source unit analyzes according to monitoring data of water quality sections of a month in a certain year, and displays overproof conditions and overproof ranges of water quality and pollution sources which possibly cause overproof.
The method for retroactively influencing the overproof water quality to identify the pollution source unit possibly causing the overproof pollution source comprises the following steps: (1) selecting a water quality standard exceeding control section to be analyzed, and identifying the water quality section from the standard exceeding section to the upstream of the drainage basin until no water quality standard exceeding section exists; (2) determining control units corresponding to all identified water quality standard exceeding sections; (3) identifying a pollution source which discharges the overproof factor in the control unit determined in the step (2) according to the overproof factor of the selected water quality overproof section to be analyzed; (4) and further identifying the pollution sources which discharge the exceeding factors, namely corresponding to the pollution sources which possibly cause the exceeding.
The system is characterized by further comprising a map module, wherein a drainage basin map is stored in the map module, and the map module is respectively connected with the pollution accident analysis unit, the pollution source response and treatment project benefit unit and the water quality standard exceeding backtracking influence pollution source unit.
The system is characterized by further comprising a map module, wherein a drainage basin map is stored in the map module, and the map module is respectively connected with the pollution accident analysis unit, the pollution source response and treatment project benefit unit and the water quality standard exceeding backtracking influence pollution source unit.
The basin fine management system of the integrated water environment model has the advantages that:
the watershed fine management system integrating the water environment model is provided with a database, the database records hydrology, meteorology, pollution sources and water quality monitoring data, the watershed is divided into sub-computing units through river network grid division information of the watershed stored in a river network grid division module, sub-computing unit grids of the whole watershed water system are finally determined, the model computing module is used for simulating the pollutant concentration of each sub-computing unit grid in the watershed, and a water pollution accident analysis method, a pollution source response and treatment project benefit analysis method and a water quality standard exceeding back tracing influence pollution source method are constructed on the basis of the water environment model, so that dynamic and fine management of the watershed pollution sources, projects, water quality and the like is realized.
In order to make the technical scheme of the basin fine management system of the integrated water environment model more clearly understood, the invention is further described in detail below with reference to specific drawings and embodiments.
Drawings
FIG. 1 is a schematic diagram of a watershed refinement management system of an integrated aquatic environment model according to the present invention;
wherein the reference numerals are:
1-basin fine management system; 2-a database unit; 3-a water quality simulation unit; 31-a river network meshing module; 32-coefficient setting module; 33-a model calculation module; 34-a hydrologic information confirmation module; 4-a pollution accident analysis unit; 5-pollution source response and treatment project benefit unit; 6-water quality exceeding and back tracing to influence a pollution source unit; 7-map module.
Detailed Description
The embodiment takes a Qinghai watershed as an example, and provides a watershed refinement management system 1 integrated with a water environment model, a schematic diagram of the system is shown in fig. 1, and the system includes: a database unit 2, the database unit 2 storing: the hydrological database is used for recording hydrological monitoring data in a flow domain; the pollution source database is used for recording the emission data of various pollution sources in the drainage basin; the drainage basin geographic information database is used for recording the geographic information data of the drainage basin; the meteorological and water quality monitoring database is used for recording water quality data in a flow field and meteorological monitoring data corresponding to a meteorological station point; the drainage basin social and economic database is used for collecting drainage basin social and economic and demographic information data;
basin fine management system 1 still is provided with water quality simulation unit 3, water quality simulation unit 3 includes: a river network meshing module 31, where the river network meshing module stores river network meshing information of a river basin, and the method of river network meshing is as follows: the method comprises the following steps of firstly, preliminarily dividing a watershed into a plurality of non-uniform river sections, then dividing each river section into a plurality of sub-computing units, and finally determining sub-computing unit grids of the whole watershed water system;
in this embodiment, the flashy river area is preliminarily divided into 134 non-uniform river segments according to the water environment function zoning conditions, wherein the non-uniform river segments refer to the same hydraulic power and water quality parameter characteristics in the same river segment, and the hydraulic power and water quality parameter characteristics include gradient, flow velocity and pollutant degradation coefficient; the characteristics of water power and water quality are different among river reach. On the basis, dividing 134 non-uniform stream sections into sub-computing unit grids which are basically equal in length and are basically 1000m long; then, traversing all the river reach, and seeing whether there is a water quality monitoring section and a water environment functional area node on the river reach, and breaking the river reach at the section position, and finally dividing the whole moisture river basin into 2820 sub-computing unit grids. The sub-calculation unit grid is a basic unit for water quality simulation analysis and calculation. Non-point sources and the in-out and out-flow of point sources may be within any river segment or grid of sub-computing units.
For each computing unit grid divided in the moisture domain, starting from the upstream bast temple river source on the water of the 10, numbering in an ascending order from 1 to downstream, and continuing to numbering in an ascending order from the tributary source to the tributary downstream when arriving at a tributary, thereby generalizing all dry tributaries in the whole moisture domain into a series of sub-computing unit grids connected end to end.
The last determined minimum numbering (No. 1) unit of the river network computing unit in the watershed is located at the 10 upstream 10 fair source hempsey river source, and the maximum numbering (No. 2719) unit is located at the exit of the watershed. The sub-calculation units of the two branches of the salt water ditch and the Longzhi ditch are numbered from 2720 to 2820, and the two branches are individually numbered.
The water quality simulation unit 3 is also provided with a coefficient setting module 32 and a model calculating module 33, wherein the coefficient setting module 32 is used for setting a production and pollution discharge coefficient, a river entering coefficient and a pollutant degradation coefficient; in this embodiment, the coefficient setting module 32 is inputted with the product and sewage discharge coefficient, the river entering coefficient, and the pollutant degradation coefficient by manual entry. Wherein the pollution discharge coefficient includes but is not limited to the domestic pollution discharge coefficient (unit: g/person.day) of urban residents, the daily excretion coefficient (kg/head.year) of livestock and poultry excrement and urine, the pollution discharge coefficient of the planting industry, the domestic pollution discharge coefficient of rural residents and the like.
The model calculation module 33 in this embodiment stores a watershed one-dimensional river network hydrodynamic water quality model and a watershed non-point source pollution discharge model; the model calculation module 33 is respectively connected with the database unit 2, the river network meshing module 31 and the coefficient setting module 32; the model calculation module 33 is suitable for retrieving data information of each module and simulating the pollution load concentration of each sub-calculation unit grid in the flow domain. The watershed one-dimensional river network hydrodynamic water quality model method comprises a river constant pollution discharge one-dimensional steady-state water quality degradation model.
The specific method comprises the following steps: (1) extracting data stored in the database unit 2, and calculating the non-point source pollutant generation amount in the pollution source by adopting a drainage basin non-point source pollution discharge coefficient model; the non-point sources comprise urban living sources, livestock breeding sources, planting industry surface sources, rural living surface sources and urban non-point sources; (2) determining the hydrological conditions of the river reach by adopting a hydrological calculation method; analyzing hydrological meteorological characteristics of the river reach, analyzing the availability of hydrological data, and selecting an applicable hydrological interpolation method: if hydrologic monitoring sites are arranged at the upstream and the downstream of the existing river reach, extracting flow data in the hydrologic, meteorological and water quality monitoring databases, and calculating the flow of the river reach by adopting a natural runoff reduction method; when the river reach lacks upstream and downstream hydrological monitoring sites, hydrological data of the drainage basin can be extracted, the river reach with basically the same hydrological conditions is found, and the flow of the river reach is estimated by adopting a hydrological comparison method; further calculating the water surface area and the water volume of the river reach based on the flow; (3) based on the calculation data of the steps (1) and (2), simulating the water quality of the sub-calculation unit by adopting a watershed one-dimensional river network hydrodynamic water quality model method, wherein the method comprises the following steps: the method comprises the following steps of firstly, extracting position information of a pollution source, a sewage discharge outlet and a water intake in a database, and generalizing adjacent sewage discharge outlets in the same sub-computing unit; extracting various point source discharge data in a database and the calculation result in the step (1), and further calculating the river entering sewage quantity and the pollution load concentration of the pollutants at the generalized sewage discharge outlet according to the river entering coefficient of the model parameters; calculating the flow speed condition of the river reach by adopting a river water dynamic model method according to the calculation result of the step (2); the river water dynamic model method comprises a river water level-flow relation method and a Manning formula method; secondly, verifying and calibrating the one-dimensional water quality model by adopting independent data, so that the simulation precision of the one-dimensional water quality model is not lower than 80%; and calculating the grid pollution load concentration of each sub-calculation unit by adopting the verified and calibrated water quality model.
Wherein, the hydrological calculation method in the step (2) comprises the following steps:
each tributary of the water basin has 16 main hydrological monitoring sites. Wherein, the major hydrological stations on the water trunk flow include 5 kayan three stations, a source station, a xining station, a ledu station, a min station, and a station, among other branches, the major hydrological stations on the north river include 3 cow stations, five bridgehead stations, and a yang facing station, the major hydrological stations on the liquid medicine river include 1 hollander three station, the west river includes 1 hollander two station, the black river includes 1 black river 1 hydrological station, the south river includes 1 kawa estuary station, the shatang river includes 1 kazai two station, the little south river includes 1 queensland station, the attraction ditch includes 1 irie bridge three station, and the baoba river includes 1 kamikazakh station.
In this embodiment, for a certain river reach sub-calculation unit, if there is an actual hydrologic monitoring site on the river reach of the water environment functional area to which the river reach sub-calculation unit belongs, the actual measurement flow value of the hydrologic monitoring site is directly used as the incoming flow condition of the current reach. In consideration of the uneven characteristic of the distribution of the actual hydrologic monitoring sites, many river reaches actually do not measure hydrologic data. For the river reach sub-calculation unit, if the river reach of the water environment functional area to which the river reach sub-calculation unit belongs does not have an actual hydrologic monitoring site, the original hydrologic data needs to be preprocessed according to the production convergence relation in the river reach, and other river reach without actually measured hydrologic data are restored through interpolation.
When the water environment work of a certain sub-computing unitWhen hydrologic stations are arranged at the upstream and downstream of the river reach of the energy region, the actual monitoring value (Q) in the month of the upstream and downstream monitoring stations can be usedOn the upper part、QLower part) And estimating the average flow of the river reach of the water environment functional area by an interpolation method, wherein the calculation formula is as follows:
wherein Q is the result of accounting the flow of a river section lacking hydrologic monitoring data, m3/s；QOn the upper part、QLower partMeasured flow of a month, m, of upstream and downstream hydrological stations, respectively3S; a is the average water yield of the river basin above the control section of the data station for many years, m3；AOn the upper part、ALower partAverage water yield m in many years in the watershed controlled by upstream and downstream hydrological stations respectively3。
For non-data areas, hydrological analogy (analogy) methods may also be used. Firstly, finding out a drainage basin which is similar to the climate lacking the data drainage basin and the natural geographic condition, has little difference in drainage basin area and has longer-term actual measurement data as a reference (analog) drainage basin, and transferring the statistical parameters of the runoff quantity or the runoff process of the reference drainage basin time period to the data-lacking drainage basin after correction, wherein the calculation formula is as follows:
the meteorological data in this embodiment is derived from the average precipitation per year data in the resource and environment scientific data center of the academy of sciences in china, and the average precipitation distribution data over many years in the water allocation domain is intercepted with the aid of the ArcGIS spatial data processing technique. Obtaining the average rainfall distribution and the water runoff producing deep space of the 10 water flow domain 1956 + 2000 years.
The steady-state flow balance equation is suitable for each simulated river reach, and the water balance equation of the river reach unit is as follows:
Qi＝Qi-1+Qin,i-Qout,i
in the formula, QiFlow rate of river reach i into river reach i +1, m3/s；Qi-1Is the flow rate of the upstream river reach i-1 flowing into the river reach i, m3/s；Qin,iI point source and non-point source total inflow of the river reach m3/s；Qout,iI point source and non-point source total output flow of river reach m3/s。
All incoming flows from the source can be expressed as:
wherein Q isps,i,jIs the flow of the j point source into the river reach i, m3Psi is the number of all point sources in the river reach i, Qnps,i,jIs the flow of the jth non-point source flowing into the river section i, m3And/d, npsi is the number of all non-point sources in the river reach i.
All the outgoing flow from the source can be expressed as:
wherein Q ispa,i,jIs the flow of the source intake at the jth point of the river reach i, m3The number of water intakes of all point sources of the river reach i is/d, pai, Qnpa,i,jIs the flow of the jth non-point source water intake of the river reach i, m3And/d, npai is the number of all non-point source water intake ports of the river reach i.
The water quality model in the embodiment estimates the average flow velocity condition according to the flow by adopting a water level flow relation curve method based on the principle of mass conservation. The specific idea is that the relationship between the flow velocity and the flow and the relationship between the depth and the flow in the river reach unit can be described by a power exponent equation:
U＝aQb
H＝cQd
wherein Q is the flow rate, m3S; u is the average flow velocity, m/s; h is the average water depth, m; a. b, c and d are empirical constants and can be obtained by calculating intercept and slope from a water level-flow relation curve of a cross section。
The details of each model are as follows:
the one-dimensional river network hydrodynamic water quality model is a one-dimensional advection-diffusion and mass conservation equation, is suitable for a dendritic river, allows the discharge of wastewater from a plurality of point sources along the river, the intake of non-point sources, the intake of water and the inflow of branches to analyze the influence of the total discharge amount and specific discharge positions of pollutants on the water quality of a received water body, and can be used as a steady-state model or a time-varying dynamic model for simulating sudden water environmental pollution accidents and the like.
The river reach sub-calculation unit is considered to be in a stable state, namely the concentration of the pollutants in the river reach is only related to the position of the sewage discharge outlet and is not related to the time, the time control is determined by the hydraulic retention time, and the hydraulic retention time is determined by the length of the river reach and the average flow speed of the river reach. Consider advection diffusion, dilution, and biochemical reactions of the material components themselves, interactions between water quality components, and the influence of external source and drain of components on component concentrations.
For the water quality change caused by point source and non-point source blowdown along the moisture trunk, performing simulation analysis by adopting a constant blowdown one-dimensional steady state degradation water quality model:
for the case that the flow velocity of the small branch flow surface has little change, the formula is as follows:
C0＝(CpQp+ChQh)/(Qp+Qh)
after the sudden water environment risk accident pollution discharge process is analyzed, accident pollution discharge influences water quality change of the trunk branch of the lower water, and degradable pollutants, such as COD, ammonia nitrogen and other conventional pollutants, degradable toxic and harmful organic pollutants, acid and alkali and the like, have the following formula:
in the formula, CbThe background concentration value of the river accident pollutant is mg/l; c (x, t) is x from the occurrence risk accident, and the pollutant concentration at the t moment after the accident occurs is mg/L; x is the distance from the sewage outlet, m; u is the cross-sectional flow velocity, m/s; k is the comprehensive attenuation coefficient of pollutants discharged by the risk accident, 1/s; (ii) a DxIs the longitudinal dispersion coefficient of the contaminant, m2S; m is the quality of one-time emission of the sudden water environment risk accident pollutants, g
The embodiment adopts the output coefficient model as the watershed non-point source pollution discharge model to account for the generation amount of the non-point source pollutant in the watershed. The output coefficient method is firstly proposed in North America in the early 70 th of the 20 th century, and is characterized in that the method can directly utilize data such as land utilization conditions, planting industry structures and the like, and utilizes the pollutant output coefficient to estimate the non-point source pollution load output by a drainage basin, so that the method is a lumped non-point source pollution load simple and convenient estimation method.
The output coefficient model is a concrete embodiment of an output coefficient method, is a mathematical weighting formula for calculating annual average pollution such as total nitrogen, total phosphorus and the like on a watershed scale by using a semi-distributed approach, and is a semi-distributed lumped model in essence. Because the source pollution load of the drainage basin is closely related to the land utilization type in the drainage basin, the relationship between the drainage basin land utilization type and the non-point source pollution output quantity is directly established by utilizing data such as the drainage basin land utilization type which is relatively easy to obtain through multivariate linear correlation analysis, and then the total load of the area pollution is obtained by summing the pollution loads from different sources.
The generation amount of urban living pollution is determined according to pollution discharge coefficients of town and town population in the water distribution domain, as shown in the following formula:
W＝3.65AF
wherein W is the urban life pollution load, t/a; a is urban population, ten thousand; f is the domestic pollution discharge coefficient of urban residents, g/person.day.
According to the pollution discharge coefficient and the use instruction of the Source of Life (2011 revision) and the quota of Water consumption for Qinghai province (DB63T 1429) 2015) and combining the development level of local socioeconomic, the quota of the urban population domestic water of Wening city and Shandong city in the Water flow area is 230L/person.day, the pollution coefficient of COD (chemical oxygen demand) product is 72 g/person.day, the pollution coefficient of ammonia nitrogen product is 8.06 g/person.day, and the pollution coefficient of total phosphorus product is 0.89 g/person.day; the daily water quota of residents in urban areas of other counties and towns and general towns is 150L/person.day, the COD yield pollution coefficient is 61 g/person.day, the ammonia nitrogen yield pollution coefficient is 7.41 g/person.day, and the total phosphorus yield pollution coefficient is 0.63 g/person.day.
In this embodiment, the non-point source pollution load of livestock and poultry breeding industry is calculated as follows:
Q＝∑Ai*Ti*Ej
in the formula: q is non-point source pollution load discharge amount of livestock and poultry breeding industry, ton/year, AiThe number of breeding stocks for the breeding species of the i-type livestock and poultry is the number of the breeding stocks (only); t isiThe coefficient of the dirt production of the i-type livestock and poultry breeding is gram/day; ejThe treatment efficiency of j breeding manure treatment modes is improved.
Considering the stock keeping amount of cattle, pigs, sheep and poultry as a relatively stable feeding amount in the current year according to the estimation method of related research, and on the premise of not considering the feeding period, the livestock and poultry breeding pollutant production coefficient (T)i) The calculation formula is as follows:
production of livestock and poultry pollutants (T)i) Daily excretion coefficient of livestock and poultry manure (kg/head-year) x pollutant content of manure (g/kg).
The excretion coefficients of 5 livestock and poultry such as pigs, cows, beef cattle, laying hens, broilers and the like, and the contents of various pollutants such as COD, ammonia nitrogen, total phosphorus and the like in excrement of the livestock and poultry refer to the recommended value of the original national environmental protection Bureau and the first national pollution Source general survey: a livestock and poultry breeding industry source pollution discharge coefficient manual (2009) recommended value.
In the embodiment, the non-point source loss of the planting industry is estimated by adopting a standard farmland method. The standard farmland refers to a farmland in plain, with wheat as a planted crop, loam as a soil type, a fertilizer application amount of 25-35 kg/mu per year and a precipitation amount within the range of 400-800 mm.
For an actual farmland, factors such as an actual gradient, crop planting types, soil properties, fertilizer application amount, precipitation distribution and the like need to be considered, and on the basis of a standard farmland, a source intensity coefficient is corrected necessarily:
A. slope correction
The land gradient is below 25 degrees, and the loss coefficient is 1.0-1.2; over 25 degrees, and the loss coefficient is 1.2-1.5. According to the research, the average gradient of the cultivated land is analyzed under an ArcGIS platform according to the DEM data of the drainage basin and the land utilization data, and a corresponding correction factor is determined.
B. Crop type correction
The method is characterized in that main crops such as corn, sorghum, wheat, barley, rice, soybean, cotton, oil plants, sugar materials, economic forests and the like are used as research objects, and the pollutant loss correction coefficients of different crops are determined. The correction coefficient needs to be verified through scientific research experiments or empirical data. The central watershed mainly plants the crop type being wheat.
C. Soil type correction
Farmland soil is classified according to texture, namely according to the proportion of clay to sandy soil in soil components, the soil is classified into sandy soil, loam and clay. Taking loam as 1.0; the sand correction coefficient is 1.0-0.8; the clay correction coefficient is 0.8-0.6. And taking 0.9-1.0 according to the soil type of the drainage basin.
D. Chemical fertilizer application amount correction
The application amount of the fertilizer per mu is below 25kg, and the correction coefficient is 0.8-1.0; the correction coefficient is 1.0-1.2 between 25-35; above 35kg, the correction coefficient is 1.2-1.5.
E. Precipitation correction
The annual rainfall is below 400mm, and the loss coefficient is 0.6-1.0; taking the loss coefficient to be 1.0-1.2 in areas with annual rainfall between 400 and 800 mm; the annual rainfall in the area with the annual rainfall above 800mm is taken to have the loss coefficient of 1.2-1.5. The average annual precipitation of the drainage basin is 600-300 mm, and a precipitation correction factor is determined according to an annual precipitation map and a farmland distribution map of the drainage basin.
The formula of the load discharge amount of the planting industry is as follows:
in the formula, EPlantingThe discharge amount of the load is ton/year for the drainage basin planting industry; eStandard farmlandThe loss coefficient is the loss coefficient of the planting mode of the 'standard farmland' in the drainage basin, namely kilogram/mu.year; a. thePlanting Pattern iAdopting planting area of i-th planting mode for the drainage basin, mu; a isSlope correctionThe gradient correction factor is a non-dimensional gradient correction factor; bCrop type correctionThe crop type is corrected, and the method is dimensionless; c. CSoil type correctionThe soil type correction is carried out, and the dimension is not needed; dChemical fertilizer application amount correctionThe fertilizer application amount is corrected, and no dimension is needed; e.g. of the typePrecipitation correctionThe method is used for correcting the precipitation amount and is dimensionless;
the pollution discharge coefficient of the planting industry covers the farmland fertilizer loss coefficients of different planting modes of main planting areas, planting modes, farming modes, farmland types, soil types, terrain and main crop types in China according to 'first national pollution source census-agricultural pollution source (fertilizer loss coefficient)' (2009) published by a lead group office of the first national pollution source census of the State institute.
In this embodiment, the emission situation of the rural domestic pollution in the water watershed is determined according to the pollution load emission of the rural population and the average rural population of each control sub-control unit, as shown in the following formula:
W＝3.65AF
in the formula, W is the rural area source load discharge amount, ton; a is rural population, ten thousand people; f is the coefficient of pollution discharge of rural residents, g/(man-day).
According to the socioeconomic statistics data of the watershed, there are 155.8 ten thousand rural demographics in 2015 year in 12 counties of the watershed. The rural resident life emission coefficient of the watershed is 80L/person/day according to the Qinghai province water quota (DB63T1429-2015), the rural life main pollution load generation coefficient reference and the town life coefficient are respectively calculated by 61 g/person/day, 7.41 g/person/day and 0.63 g/person/day.
The embodiment adopts a standard urban pollution discharge coefficient method to estimate the urban runoff surface source runoff quantity. The definition of the so-called standard city is: is located in plain zone, the urban non-agricultural population is between 100 and 200 thousands, and the area of the built-up area is 100km2And on the left and right, the annual precipitation is between 400 and 800mm, the popularity of the urban rainwater collection pipe network is between 50 and 70 percent, and the standard urban source intensity coefficient is COD 50 tons/year and ammonia nitrogen 12 tons/year.
The method considers a plurality of factors influencing urban runoff, and further performs coefficient correction on the basis of a standard city by comparing specific conditions such as planned evaluation of urban built-up area topographic features, urban population, urban area, rainfall, pipe network coverage and the like:
A. coefficient of terrain correction
The city is divided into 3 conditions of plain city, mountain city and hill city according to terrain, and terrain correction coefficients are respectively given. Wherein, the landform correction coefficient of the plain city is 1; the correction coefficient of the mountain city is 3.8; and the correction coefficient of the hill city is 2.5.
B. Population correction factor
Population correction coefficients are respectively given for 4 cases of urban non-agricultural population of less than 100 ten thousand, 100 ten thousand to 200 ten thousand, 200 ten thousand to 500 ten thousand and more than 500 ten thousand. Wherein, the population correction coefficient is 0.3 for less than 100 ten thousand persons; the correction coefficient is 1 between 100 ten thousand and 200 ten thousand; the correction coefficient is 2.3 between 200 and 500 ten thousand; more than 500 ten thousand correction coefficients are taken as 3.3.
C. Area correction factor
The area integral of the built city is 75km275-150 km below2、150～250km2、250km2In the above 4 cases, the areas are given separatelyAnd (5) correcting the coefficient. Wherein, 75km2The area correction factor is taken as 0.5; 75-150 km2Taking a correction coefficient as 1; 150 to 250km2Taking the correction coefficient to be 1.6; 250km2The correction factor was taken to be 2.3.
D. Rainfall correction factor
And (3) respectively giving rainfall correction coefficients for the annual rainfall under 400mm, 400-800mm and over 800 mm. Wherein the rainfall correction coefficient is 0.7 when the rainfall correction coefficient is less than 400 mm; taking a correction coefficient of 1 between 400 and 800 mm; the correction coefficient is 1.4 when the thickness is more than 800 mm.
E. Pipe network correction factor
The coverage rate of the rainwater collection pipe network is divided into 4 conditions of less than 30%, 30-50%, 50-70% and more than 70%, and pipe network correction coefficients are respectively given. Wherein, the rainwater collection pipe network coverage rate is below 30%, and the pipe network correction coefficient is 0.6; taking the correction coefficient of 0.8 when the coverage rate is between 30 and 50 percent; taking a correction coefficient of 1 when the coverage rate is 50-70%; the correction coefficient for a coverage of 70% or more was 1.2.
The urban non-point source accounting formula is as follows:
Ecity＝EStandard city×TCity×PCity×ACity×RCity×Pn city
In the formula, ECityThe discharge amount of urban runoff non-point source load is ton/year; eStandard cityThe standard urban runoff load emission intensity defined in the flow field is ton/year; t is an urban terrain correction coefficient and is dimensionless; n is a radical ofCityThe urban population correction coefficient is dimensionless; a. theCityThe urban area correction coefficient is dimensionless; rCityThe correction coefficient is a correction coefficient of the urban precipitation, and is dimensionless; pn cityThe correction coefficient is a correction coefficient of the urban rainwater pipe network and is dimensionless.
The embodiment solves the problem of water-land coupling between a pollution source and a river water system through the sewage draining exit generalization. Point source and non-point source pollution loads must be distributed to the corresponding waste outlets. While the model allows a single drain to correspond to virtually any number of point or non-point sources of pollution.
The point source determines the sub-calculation unit to which the point source belongs according to the actual position of the point source, a plurality of adjacent point source sewage outlets or water intakes are simplified into a concentrated sewage outlet or water intake, and the distance between the combined sewage outlet and the upstream section can be calculated by the following formula:
in the formula, L is the distance, km, from a generalized sewage discharge outlet to a control section at the upstream of a river reach; qiThe amount of water of the ith sewage discharge outlet m3/s：CiThe pollutant concentration of the ith sewage outlet is mg/L; l isiThe distance, km, from the ith sewage draining exit to the upstream control section of the river reach.
The non-point source sewage draining exit or water intake is generalized to be a line draining source or a line water intake along the river reach. The model takes the point positions of the initial point and the terminal point of each non-point source influence river reach as boundary lines, and the non-point sources are evenly distributed to each unit according to the distance in the area to calculate the water quality.
In the established moisture model of the watershed, the association processing steps of the pollution source and the drain outlet are as follows: 1) firstly, establishing a drain outlet-pollution source attribute table, and determining the relation between a drain outlet (water) and a pollution source (land); 2) calculating the sink entering distance from the point source to the sewage outlet; 3) determining river entering coefficients according to the river entering distance; 4) and accumulating all pollution sources of a certain sewage discharge outlet to obtain the river sewage amount and the pollution load concentration of the sewage discharge outlet.
In the embodiment, for the quality of source head water of each trunk branch river of the lunge river, the quality of type II water is considered according to the quality standard of surface water environment (GB3838-2002), wherein the concentration of COD source water is 10mg/L, and the concentration of ammonia nitrogen is 0.25 mg/L.
And (3) distributing 19 main water quality monitoring sections in the watershed, and verifying the parameters by using a set of data which is independent of parameter rate timing. In this embodiment, the average relative errors of the actually measured chemical oxygen demand and the ammonia nitrogen water quality concentration of the water quality monitoring sections of three main river segments, i.e., the dry, flat and rich water trunk flow zailong-xining bridge segment, the small isthmus bridge-bay bridge segment, the bay bridge-civilian and bridge segment, etc., in 2014 are selected as error detection indicators, and from simulation and verification results, the overall average relative error of the chemical oxygen demand of the dry water trunk flow is 7.6%, and the overall average relative error of the ammonia nitrogen is 11.5%, that is, the total accuracy of the chemical oxygen demand reaches 92.4%, and the total accuracy of the ammonia nitrogen reaches 88.5%. The model parameter verification result shows that the simulation precision of the one-dimensional water quality model is basically over 85 percent, the response characteristics of drainage basin pollutant discharge and water quality can be accurately reflected, and the simulation precision is high.
The refinement management system in the embodiment is further provided with a hydrological information confirmation module 34 and a pollution source information confirmation module, wherein the hydrological information confirmation module 34 is suitable for calling data information of the hydrological database, confirming the data information of the hydrological data and issuing a confirmation instruction; the pollution source information confirmation module is suitable for calling the data information of the pollution source database, confirming the data information of the pollution source data and issuing a confirmation instruction; when the hydrologic information confirmation module 34 and the pollution source information confirmation module both issue confirmation instructions, the model calculation module 33 automatically retrieves data information of each module, and simulates the pollution load concentration of each sub-calculation unit grid in the flow domain. This arrangement increases the degree of management of the system, allowing the underlying data information to be further validated prior to the simulation operation.
The fine management system in the embodiment is further provided with a pollution accident analysis unit 4, the pollution accident analysis unit 4 is provided with an input module for inputting a pollution accident numerical value, the pollution accident analysis unit 4 carries out dynamic simulation calculation on water pollution based on the input of the pollution accident numerical value, and the duration and the influence range of a pollution accident are checked through a simulation result.
The fine management system is further provided with a pollution source response and treatment project benefit unit 5, information of new pollution source projects and treatment project schemes is stored in the pollution source response and treatment project benefit unit 5, each new pollution source project and each treatment project scheme is correspondingly provided with a pollutant discharge amount increasing numerical value or a pollutant discharge amount reducing numerical value corresponding to the project, water quality simulation is carried out by selecting different project schemes, and the environmental benefits of the new pollution source projects and the treatment projects on the river water quality can be checked through simulation results.
The fine management system is further provided with a water quality standard exceeding backtracking influence pollution source unit 6, the water quality standard exceeding backtracking influence pollution source unit 6 analyzes according to monitoring data of a water quality section in a month in a certain year, and displays standard exceeding conditions, standard exceeding ranges and pollution sources possibly causing standard exceeding of water quality. The method for identifying the pollution source which possibly causes the overproof pollution source by the water quality overproof backtracking influence pollution source unit 6 comprises the following steps: (1) selecting a water quality standard exceeding control section to be analyzed, and identifying the water quality section from the standard exceeding section to the upstream of the drainage basin until no water quality standard exceeding section exists; (2) determining control units corresponding to all identified water quality standard exceeding sections; (3) identifying a pollution source which discharges the overproof factor in the control unit determined in the step (2) according to the overproof factor of the selected water quality overproof section to be analyzed; (4) and further identifying the pollution sources which discharge the exceeding factors, namely corresponding to the pollution sources which possibly cause the exceeding.
The fine management system in the embodiment is provided with a map module 7, a drainage basin map is stored in the map module 7, and the map module 7 is respectively connected with the pollution accident analysis unit 4, the pollution source response and treatment project benefit unit 5 and the water quality standard exceeding backtracking influence pollution source unit 6. And the display unit is used for displaying the operation result of each unit.
The units and modules in the present embodiment can be implemented by using hardware devices in the related art, such as a computer or a server.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the claims.
Claims (5)
1. A basin fine management system of an integrated water environment model is characterized by comprising:
a database unit storing: the hydrological database is used for recording hydrological monitoring data in a flow domain; the pollution source database is used for recording the emission data of various pollution sources in the drainage basin; the drainage basin geographic information database is used for recording the geographic information data of the drainage basin; the meteorological and water quality monitoring database is used for recording water quality data in a flow field and meteorological monitoring data corresponding to a meteorological station point; the drainage basin social and economic database is used for collecting drainage basin social and economic and demographic information data;
basin fine management system still is provided with water quality simulation unit, water quality simulation unit includes: the river network meshing module is used for storing river network meshing information of a river basin, the river basin is firstly preliminarily divided into a plurality of non-uniform river sections, then each river section is divided into a plurality of sub-computing units, and finally sub-computing unit meshes of the whole river basin water system are determined; the coefficient setting module is used for setting a production and pollution discharge coefficient, a river entering coefficient and a pollutant degradation coefficient;
the water quality simulation unit is also provided with a model calculation module, and the model calculation module stores a watershed one-dimensional river network hydrodynamic water quality model and a watershed non-point source production pollution discharge model; the model calculation module is respectively connected with the database unit, the river network grid division module and the coefficient setting module; the model calculation module is suitable for calling data information of the database unit, the river network grid division module and the coefficient setting module and simulating the pollutant concentration of each sub-calculation unit grid in the flow domain;
the watershed fine management system is also provided with a water quality exceeding and backtracking influence pollution source unit, and the water quality exceeding and backtracking influence pollution source unit analyzes according to monitoring data of a water quality section in a month in a certain year, and displays the exceeding condition, the exceeding range and a pollution source which possibly causes the exceeding;
the method for retroactively influencing the overproof water quality to identify the pollution source unit possibly causing the overproof pollution source comprises the following steps: (1) selecting a water quality standard exceeding control section to be analyzed, and identifying the water quality section from the standard exceeding section to the upstream of the drainage basin until no water quality standard exceeding section exists; (2) determining control units corresponding to all identified water quality standard exceeding sections; (3) identifying a pollution source which discharges the overproof factor in the control unit determined in the step (2) according to the overproof factor of the selected water quality overproof section to be analyzed; (4) and further identifying the pollution sources which discharge the exceeding factors, namely corresponding to the pollution sources which possibly cause the exceeding.
2. The fine management system for the drainage basin according to claim 1, wherein the water quality simulation unit is further provided with:
the hydrologic information confirmation module is suitable for calling the data information of the hydrologic database, confirming the data information of the hydrologic data and issuing a confirmation instruction; the pollution source information confirmation module is suitable for calling the data information of the pollution source database, confirming the data information of the pollution source data and issuing a confirmation instruction;
when the hydrologic information confirmation module and the pollution source information confirmation module issue confirmation instructions, the model calculation module automatically calls the data information of the database unit, the river network grid division module and the coefficient setting module to simulate the pollutant concentration of each sub-calculation unit grid in the flow domain.
3. The basin fine management system according to claim 1 or 2, further comprising a pollution accident analysis unit, wherein the pollution accident analysis unit is provided with an input module for inputting a pollution accident numerical value, the pollution accident analysis unit performs dynamic simulation calculation on water pollution based on the input of the pollution accident numerical value, and checks the duration and the influence range of the pollution accident through a simulation result.
4. The fine management system of the drainage basin according to claim 3, further comprising a pollution source response and treatment project benefit unit, wherein the pollution source response and treatment project benefit unit stores information of new pollution source projects and treatment project schemes, each new pollution source project and treatment project scheme is provided with a pollutant discharge amount increase numerical value or a pollutant discharge amount decrease numerical value corresponding to a project, water quality simulation is performed by selecting different project schemes, and environmental benefits of the new pollution source projects and the treatment projects on river water quality can be checked through simulation results.
5. The basin fine management system of the integrated aquatic environment model according to claim 4, further comprising a map module, wherein a basin map is stored in the map module, and the map module is connected to the pollution accident analysis unit, the pollution source response and treatment project benefit unit, and the water quality exceeding backtracking influence pollution source unit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810471185.2A CN108664647B (en) | 2018-05-17 | 2018-05-17 | Basin fine management system of integrated water environment model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810471185.2A CN108664647B (en) | 2018-05-17 | 2018-05-17 | Basin fine management system of integrated water environment model |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108664647A CN108664647A (en) | 2018-10-16 |
| CN108664647B true CN108664647B (en) | 2021-07-06 |
Family
ID=63778521
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810471185.2A Active CN108664647B (en) | 2018-05-17 | 2018-05-17 | Basin fine management system of integrated water environment model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108664647B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116564431A (en) * | 2023-06-02 | 2023-08-08 | 江苏捷利达环保科技有限公司 | Pollution source online analysis system and method based on big data processing |
Families Citing this family (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523144B (en) * | 2018-10-25 | 2021-08-06 | 国科创（北京）信息技术有限公司 | Watershed water environment business operation management system and method |
| CN109583723A (en) * | 2018-11-19 | 2019-04-05 | 北京英视睿达科技有限公司 | Method, electronic equipment and the device of water environment hot spot grid are determined based on pollution sources |
| CN109544427B (en) * | 2018-11-19 | 2024-01-16 | 北京英视睿达科技股份有限公司 | Water environment monitoring method and device based on hot spot grid |
| CN109444232B (en) * | 2018-12-26 | 2024-03-12 | 苏州同阳科技发展有限公司 | Multichannel intelligent polluted gas monitoring device and diffusion tracing method |
| CN110264052B (en) * | 2019-06-06 | 2023-05-30 | 郑州市污水净化有限公司 | Urban river water quality improving system |
| CN110516343A (en) * | 2019-08-22 | 2019-11-29 | 中国水利水电科学研究院 | Lake and reservoir environmental capacity of water based on Water Functional Zone water quality objective refines regulation method |
| CN110737874B (en) * | 2019-09-02 | 2021-04-20 | 中国科学院地理科学与资源研究所 | Watershed water quality monitoring abnormal value detection method based on spatial relationship |
| CN111103414A (en) * | 2019-12-18 | 2020-05-05 | 上一环境科技（金华）有限公司 | Intelligent river channel supervision system |
| CN111291305B (en) * | 2019-12-24 | 2023-08-29 | 四川省环保科技工程有限责任公司 | Method for calculating river basin pollution source river entering coefficient based on one-dimensional water quality model |
| CN111508044B (en) * | 2020-04-24 | 2020-12-08 | 中国水利水电科学研究院 | Control unit division method for GIS basin comprehensive treatment |
| CN111693672B (en) * | 2020-06-19 | 2022-09-30 | 广东理行生态环境科技有限公司 | Drainage basin pollutant monitoring system and monitoring method thereof |
| CN111815062B (en) * | 2020-07-16 | 2024-03-26 | 山东省科技发展战略研究所 | Pollution source tracing system based on pollution information analysis |
| CN112163322A (en) * | 2020-09-07 | 2021-01-01 | 中国地质大学（武汉） | Method for automatically dividing and coding one-dimensional model calculation unit of river network area |
| CN112116229A (en) * | 2020-09-08 | 2020-12-22 | 深圳市广汇源环境水务有限公司 | Drainage basin water quality scheduling management method, system and platform |
| CN112182866B (en) * | 2020-09-21 | 2022-06-07 | 武汉大学 | Water quality rapid simulation method and system based on water environment coupling model |
| CN112612784B (en) * | 2020-11-09 | 2024-08-06 | 中国再保险(集团)股份有限公司 | River basin calculation unit automatic dividing method and device and computer equipment |
| CN112417788A (en) * | 2020-11-30 | 2021-02-26 | 重庆市生态环境大数据应用中心 | Water environment pollution analysis system and method based on big data |
| CN113011034B (en) * | 2021-03-25 | 2022-04-12 | 山东省海洋资源与环境研究院(山东省海洋环境监测中心、山东省水产品质量检验中心) | Sea area section pollutant transport flux determination method and system |
| CN113156075B (en) * | 2021-03-25 | 2022-04-08 | 北京市环境保护科学研究院 | Drinking water source information management system |
| CN113222351B (en) * | 2021-04-20 | 2022-08-16 | 南京南瑞水利水电科技有限公司 | Urban emergency water supply fine scheduling method based on water evolution change |
| CN113282577B (en) * | 2021-07-23 | 2021-11-19 | 重庆华悦生态环境工程研究院有限公司深圳分公司 | Sewage pipe network monitoring method and device, electronic equipment and storage medium |
| CN114065498B (en) * | 2021-11-10 | 2024-07-19 | 上海园林绿化建设有限公司 | Eutrophication control method and system for river basin target water body |
| CN115952246B (en) * | 2022-11-29 | 2023-07-04 | 中国环境科学研究院 | Grid-based factory boundary pollutant measuring and displaying method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101976380A (en) * | 2010-09-14 | 2011-02-16 | 华北电力大学 | Method for performing real-time regulation and control and digital management on water environment |
| CN102061677A (en) * | 2010-12-09 | 2011-05-18 | 河海大学 | Full-section water wetland purification system suitable for normal water level of river |
| CN105893763A (en) * | 2016-04-01 | 2016-08-24 | 中山大学 | South tidal river network area water flow and water quality coupling simulation system |
| US9521858B2 (en) * | 2005-10-21 | 2016-12-20 | Allen Szydlowski | Method and system for recovering and preparing glacial water |
| US9734220B2 (en) * | 2012-12-04 | 2017-08-15 | Planet Os Inc. | Spatio-temporal data processing systems and methods |
-
2018
- 2018-05-17 CN CN201810471185.2A patent/CN108664647B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9521858B2 (en) * | 2005-10-21 | 2016-12-20 | Allen Szydlowski | Method and system for recovering and preparing glacial water |
| CN101976380A (en) * | 2010-09-14 | 2011-02-16 | 华北电力大学 | Method for performing real-time regulation and control and digital management on water environment |
| CN102061677A (en) * | 2010-12-09 | 2011-05-18 | 河海大学 | Full-section water wetland purification system suitable for normal water level of river |
| US9734220B2 (en) * | 2012-12-04 | 2017-08-15 | Planet Os Inc. | Spatio-temporal data processing systems and methods |
| CN105893763A (en) * | 2016-04-01 | 2016-08-24 | 中山大学 | South tidal river network area water flow and water quality coupling simulation system |
Non-Patent Citations (2)
| Title |
|---|
| 承德市滦河流域输入响应模型应用研究;赵康平 等;《环境污染与防治》;20160330;全文 * |
| 葫芦河宁甘省界河段水体严重污染与治理措施;郑自宽，曹宇廷;《甘肃水利水电技术》;20130630;全文 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116564431A (en) * | 2023-06-02 | 2023-08-08 | 江苏捷利达环保科技有限公司 | Pollution source online analysis system and method based on big data processing |
| CN116564431B (en) * | 2023-06-02 | 2024-01-09 | 江苏捷利达环保科技有限公司 | Pollution source online analysis system and method based on big data processing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108664647A (en) | 2018-10-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108664647B (en) | Basin fine management system of integrated water environment model | |
| CN108287950B (en) | Water quality simulation method based on water environment quality target management of control unit | |
| CN110728035B (en) | Pollutant total amount control method based on control of section water quality reaching standard | |
| CN112765800B (en) | Design method of distributed water resource configuration model | |
| CN113689099B (en) | Method for determining pollution load contribution rate of water quality assessment section of annular river network water system based on water quantity composition | |
| Luo et al. | Evaluating the coordinated development of social economy, water, and ecology in a heavily disturbed basin based on the distributed hydrology model and the harmony theory | |
| Wang et al. | A method coupled with remote sensing data to evaluate non-point source pollution in the Xin'anjiang catchment of China | |
| Hua et al. | An innovative approach to identifying agricultural pollution sources and loads by using nutrient export coefficients in watershed modeling | |
| Pai et al. | Identifying priority subwatersheds in the Illinois River drainage area in Arkansas watershed using a distributed modeling approach | |
| CN106530172A (en) | Method of dividing watershed pollution control unit | |
| CN115115485B (en) | Water environment capacity verification method based on control unit water quality target classification management | |
| CN111899126B (en) | Three red line control index dividing method based on water circulation simulation | |
| CN114169266B (en) | River pollution source analysis and pollutant migration calculation method and system | |
| Kalin et al. | Evaluation of sediment transport models and comparative application of two watershed models | |
| CN106599562A (en) | Probability weighting FDC method-based river ecological water demand calculation method | |
| CN110728062A (en) | SWMM-based rural non-point source pollution simulation method | |
| Bui et al. | Linking hydrological, hydraulic and water quality models for river water environmental capacity assessment | |
| Tavakoly et al. | A GIS framework for regional modeling of Riverine nitrogen transport: Case study, San Antonio and Guadalupe basins | |
| CN114462698B (en) | Phosphorus emission pollution load prediction method for drainage basin catchment area | |
| Guo et al. | Identification method and application of critical load contribution areas based on river retention effect | |
| CN115713448A (en) | Catchment unit-based method for quickly tracing conventional factors of basin water pollution | |
| Cho et al. | Watershed model calibration framework developed using an influence coefficient algorithm and a genetic algorithm and analysis of pollutant discharge characteristics and load reduction in a TMDL planning area | |
| Xia et al. | Urban water system theory and its model development and application | |
| CN112287613B (en) | Pollutant reduction method for watershed water environment control section | |
| Wang et al. | Development of load duration curve system in data-scarce watersheds based on a distributed hydrological model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 100041 courtyard 15, Shixing street, Shijingshan District, Beijing Applicant after: Environmental Planning Institute of the Ministry of Ecology and Environment Address before: No.8 Dayangfang, Anwai, Chaoyang District, Beijing Applicant before: CHINESE ACADEMY FOR ENVIRONMENTAL PLANNING |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |