CN113673118A - A method for predicting the pH value of lake water - Google Patents
A method for predicting the pH value of lake water Download PDFInfo
- Publication number
- CN113673118A CN113673118A CN202111041821.6A CN202111041821A CN113673118A CN 113673118 A CN113673118 A CN 113673118A CN 202111041821 A CN202111041821 A CN 202111041821A CN 113673118 A CN113673118 A CN 113673118A
- Authority
- CN
- China
- Prior art keywords
- lake
- carbon dioxide
- value
- algae
- water body
- 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.)
- Granted
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 87
- 238000000034 method Methods 0.000 title claims abstract description 24
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims abstract description 112
- 229910002092 carbon dioxide Inorganic materials 0.000 claims abstract description 57
- 239000001569 carbon dioxide Substances 0.000 claims abstract description 57
- 241000195493 Cryptophyta Species 0.000 claims description 29
- 238000009792 diffusion process Methods 0.000 claims description 19
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 9
- 229910052799 carbon Inorganic materials 0.000 claims description 9
- 238000004090 dissolution Methods 0.000 claims description 9
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 6
- 229910052760 oxygen Inorganic materials 0.000 claims description 6
- 239000001301 oxygen Substances 0.000 claims description 6
- QGZKDVFQNNGYKY-UHFFFAOYSA-O Ammonium Chemical compound [NH4+] QGZKDVFQNNGYKY-UHFFFAOYSA-O 0.000 claims description 3
- 239000002028 Biomass Substances 0.000 claims description 3
- 241000195628 Chlorophyta Species 0.000 claims description 3
- 241000192700 Cyanobacteria Species 0.000 claims description 3
- 238000010521 absorption reaction Methods 0.000 claims description 3
- 230000012010 growth Effects 0.000 claims description 3
- 230000037323 metabolic rate Effects 0.000 claims description 3
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 3
- 238000001514 detection method Methods 0.000 description 5
- 230000003851 biochemical process Effects 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 230000005791 algae growth Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012851 eutrophication Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004173 biogeochemical cycle Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 239000013049 sediment Substances 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- 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
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Mathematical Optimization (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Computer Hardware Design (AREA)
- Operations Research (AREA)
- Evolutionary Computation (AREA)
- Algebra (AREA)
- Geometry (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Micro-Organisms Or Cultivation Processes Thereof (AREA)
- Separation Of Suspended Particles By Flocculating Agents (AREA)
Abstract
本发明公开了一种预测湖泊水体pH值的方法，包括以下步骤：S1、构建二氧化碳浓度控制方程、湖泊碱度控制方程和湖泊pH值控制方程；S2、根据二氧化碳浓度控制方程和湖泊碱度控制方程，得到预测的湖泊二氧化碳浓度和预测的湖泊碱度；S3、根据预测的湖泊二氧化碳浓度和预测的湖泊碱度，基于湖泊pH值控制方程，得到预测的湖泊水体pH值；本发明解决了现有湖泊水体pH值模型无法准确预测湖泊水体pH值的问题。
The invention discloses a method for predicting the pH value of lake water, comprising the following steps: S1, constructing a carbon dioxide concentration control equation, a lake alkalinity control equation and a lake pH value control equation; S2, according to the carbon dioxide concentration control equation and the lake alkalinity control equation equation to obtain the predicted lake carbon dioxide concentration and the predicted lake alkalinity; S3, according to the predicted lake carbon dioxide concentration and the predicted lake alkalinity, and based on the lake pH value control equation, the predicted lake water body pH value is obtained; the present invention solves the problem of There is a problem that the pH value model of lake water cannot accurately predict the pH value of lake water.
Description
技术领域technical field
本发明涉及湖泊水质监测领域，具体涉及一种预测湖泊水体pH值的方法。The invention relates to the field of lake water quality monitoring, in particular to a method for predicting the pH value of lake water.
背景技术Background technique
pH值是湖泊水生态系统的重要理化指标，可改变湖泊水体环境的酸碱度和碳酸盐平衡系统，进而影响藻类生长、沉积物营养盐循环等湖泊关键生化过程。pH值的检测方法已相对成熟，主要有玻璃电极等方法。但采用pH值检测方法只能掌握检测断面处、检测时刻的pH值，无法掌握水体pH值的时空特征，尤其是对大型湖泊，检测方法很难反映出pH值的时空异质性。pH value is an important physical and chemical index of lake water ecosystem, which can change the pH and carbonate balance system of lake water environment, and then affect the key biochemical processes of lakes such as algae growth and sediment nutrient cycle. The detection method of pH value has been relatively mature, mainly including glass electrode and other methods. However, the pH value detection method can only grasp the pH value of the detection section and the detection time, and cannot grasp the spatiotemporal characteristics of the pH value of the water body. Especially for large lakes, the detection method can hardly reflect the spatiotemporal heterogeneity of pH value.
数学模型作为生化过程的数学化表达，可定量模拟出生化过程的时空特征，近几十年来越来越受到水环境管理领域的关注。但当前湖泊水体pH值模型研究尚不深入，存在对藻类与pH值之间耦合过程考虑不足等问题，亟需研发一种可准确预测湖泊水体pH值的方法。As a mathematical expression of biochemical processes, mathematical models can quantitatively simulate the spatiotemporal characteristics of biochemical processes, and have attracted more and more attention in the field of water environment management in recent decades. However, the current research on the pH value model of lake water is not in-depth, and there are problems such as insufficient consideration of the coupling process between algae and pH value. It is urgent to develop a method that can accurately predict the pH value of lake water.
提出定量化预测湖泊水体pH值的方法，识别湖泊水体pH值时空分布规律，对湖泊理化特性、藻类生长繁殖和富营养化防治等研究具有重要意义。A method for quantitatively predicting the pH value of lake water is proposed, and the temporal and spatial distribution of pH value in lake water is identified, which is of great significance to the study of lake physical and chemical characteristics, algal growth and reproduction, and eutrophication control.
发明内容SUMMARY OF THE INVENTION
针对现有技术中的上述不足，本发明提供的一种预测湖泊水体pH值的方法解决了现有湖泊水体pH值模型无法准确预测湖泊水体pH值的问题。In view of the above deficiencies in the prior art, the present invention provides a method for predicting the pH value of a lake water body, which solves the problem that the existing lake water body pH value model cannot accurately predict the pH value of the lake water body.
为了达到上述发明目的，本发明采用的技术方案为：一种预测湖泊水体pH值的方法，包括以下步骤：In order to achieve the above-mentioned purpose of the invention, the technical scheme adopted in the present invention is: a method for predicting the pH value of lake water, comprising the following steps:
S1、构建二氧化碳浓度控制方程、湖泊碱度控制方程和湖泊pH值控制方程；S1. Construct carbon dioxide concentration control equation, lake alkalinity control equation and lake pH value control equation;
S2、根据二氧化碳浓度控制方程和湖泊碱度控制方程，得到预测的湖泊二氧化碳浓度和预测的湖泊碱度；S2. According to the control equation of carbon dioxide concentration and the control equation of lake alkalinity, the predicted lake carbon dioxide concentration and the predicted lake alkalinity are obtained;
S3、根据预测的湖泊二氧化碳浓度和预测的湖泊碱度，基于湖泊pH值控制方程，得到预测的湖泊水体pH值。S3. According to the predicted lake carbon dioxide concentration and the predicted lake alkalinity, and based on the lake pH value control equation, the predicted lake water body pH value is obtained.
进一步地，所述步骤S1中二氧化碳浓度控制方程为：Further, the carbon dioxide concentration control equation in the step S1 is:
其中，C为湖泊水体的二氧化碳浓度，t为时间，u为x方向上的水流流速，v为y方向上的水流流速，w为z方向上的水流流速，x,y,z为建立的空间坐标系，Kx为x方向上的扩散系数，Ky为y方向上的扩散系数，Kz为z方向上的扩散系数，S1为大气交换引起的二氧化碳源汇项，S2为藻类引起的二氧化碳源汇项。Among them, C is the carbon dioxide concentration of the lake water, t is the time, u is the water flow velocity in the x direction, v is the water flow velocity in the y direction, w is the water flow velocity in the z direction, and x, y, z are the established space Coordinate system, Kx is the diffusion coefficient in the x direction, Ky is the diffusion coefficient in the y direction, Kz is the diffusion coefficient in the z direction, S1 is the carbon dioxide source - sink term caused by atmospheric exchange, and S2 is the carbon dioxide source caused by algae remittance item.
进一步地，所述大气交换引起的二氧化碳源汇项S1的公式为：Further, the formula of the carbon dioxide source - sink term S1 caused by the atmospheric exchange is:
S1＝Kr(Cs-C) (2)S 1 =K r (C s -C) (2)
其中，Kr为水体二氧化碳与大气的交换速率，Cs为水体饱和二氧化碳浓度，C为湖泊水体的二氧化碳浓度。Among them, K r is the exchange rate of carbon dioxide in the water body with the atmosphere, C s is the saturated carbon dioxide concentration in the water body, and C is the carbon dioxide concentration in the lake water body.
进一步地，所述藻类引起的二氧化碳源汇项S2的公式为：Further, the formula of the carbon dioxide source-sink term S2 caused by the algae is:
其中，x为某类藻类，c为蓝藻，d为硅藻，g为绿藻，PNx为x藻类对铵的吸收率，Px为x藻类的生长速率，FCDx为x藻类的常数，DO为溶解氧浓度，KHRx为x藻类的溶解氧半饱和常数，BMx为x藻类的新陈代谢速率，AOCR为呼吸作用中二氧化碳与碳的比率，Bx为x藻类的生物量。where x is a certain type of algae, c is cyanobacteria, d is diatom, g is green algae, PN x is the absorption rate of ammonium by x algae, P x is the growth rate of x algae, FCD x is the constant of x algae, DO is the dissolved oxygen concentration, KHR x is the dissolved oxygen half-saturation constant of x algae, BM x is the metabolic rate of x algae, AOCR is the ratio of carbon dioxide to carbon in respiration, and B x is the biomass of x algae.
进一步地，所述步骤S1中湖泊碱度控制方程为：Further, in the step S1, the lake alkalinity control equation is:
其中，Ca为湖泊水体的碱度，t为时间，u为x方向上的水流流速，v为y方向上的水流流速，w为z方向上的水流流速，x,y,z为建立的空间坐标系，Kx为x方向上的扩散系数，Ky为y方向上的扩散系数，Kz为z方向上的扩散系数。Among them, Ca is the alkalinity of the lake water body, t is the time, u is the water flow velocity in the x direction, v is the water flow velocity in the y direction, w is the water flow velocity in the z direction, x, y, z are the established In the spatial coordinate system, Kx is the diffusion coefficient in the x direction, Ky is the diffusion coefficient in the y direction, and Kz is the diffusion coefficient in the z direction.
进一步地，所述步骤S1中湖泊pH值控制方程为：Further, in the step S1, the pH value control equation of the lake is:
其中，
综上，本发明的有益效果为：To sum up, the beneficial effects of the present invention are:
(1)本文明提出了一种可准确预测湖泊水体pH值的方法，该方法考虑了藻类对pH值的影响过程，实现了对湖泊水体pH值的定量化预测，可为湖泊富营养化防治等水环境管理工作提供有力科学支撑。(1) This civilization proposes a method that can accurately predict the pH value of lake water. This method takes into account the influence process of algae on pH value, and realizes the quantitative prediction of the pH value of lake water body, which can be used for the prevention and control of lake eutrophication. Provide strong scientific support for water environment management.
(2)对于pH值不达标的湖泊，可采用本发明提出的湖泊水体pH值预测方法，分析控制入湖河流碱度等pH值调控措施的实施效果，为湖泊pH值调控提供可行的定量化分析手段。(2) For lakes whose pH value is not up to the standard, the pH value prediction method of lake water body proposed by the present invention can be used to analyze the implementation effect of pH value regulation measures such as controlling the alkalinity of rivers entering the lake, and provide feasible quantification for lake pH value regulation analytical tools.
(3)对于涉及湖泊的调水工程，可采用本发明提出的湖泊水体pH值预测方法，研究调水对湖泊pH值的影响，为调水工程的论证分析提供定量化的研究方法。(3) For water transfer projects involving lakes, the pH value prediction method of lake water body proposed by the present invention can be used to study the effect of water transfer on lake pH value, and provide a quantitative research method for the demonstration and analysis of water transfer projects.
附图说明Description of drawings
图1为一种预测湖泊水体pH值的方法的流程图。Figure 1 is a flow chart of a method for predicting the pH of lake water.
具体实施方式Detailed ways
下面对本发明的具体实施方式进行描述，以便于本技术领域的技术人员理解本发明，但应该清楚，本发明不限于具体实施方式的范围，对本技术领域的普通技术人员来讲，只要各种变化在所附的权利要求限定和确定的本发明的精神和范围内，这些变化是显而易见的，一切利用本发明构思的发明创造均在保护之列。The specific embodiments of the present invention are described below to facilitate those skilled in the art to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Such changes are obvious within the spirit and scope of the present invention as defined and determined by the appended claims, and all inventions and creations utilizing the inventive concept are within the scope of protection.
如图1所示，一种预测湖泊水体pH值的方法，包括以下步骤：As shown in Figure 1, a method for predicting the pH value of lake water includes the following steps:
S1、构建二氧化碳浓度控制方程、湖泊碱度控制方程和湖泊pH值控制方程；S1. Construct carbon dioxide concentration control equation, lake alkalinity control equation and lake pH value control equation;
S2、根据二氧化碳浓度控制方程和湖泊碱度控制方程，得到预测的湖泊二氧化碳浓度和预测的湖泊碱度；S2. According to the control equation of carbon dioxide concentration and the control equation of lake alkalinity, the predicted lake carbon dioxide concentration and the predicted lake alkalinity are obtained;
S3、根据预测的湖泊二氧化碳浓度和预测的湖泊碱度，基于湖泊pH值控制方程，得到预测的湖泊水体pH值。S3. According to the predicted lake carbon dioxide concentration and the predicted lake alkalinity, and based on the lake pH value control equation, the predicted lake water body pH value is obtained.
步骤S1中二氧化碳浓度控制方程为：The carbon dioxide concentration control equation in step S1 is:
其中，C为湖泊水体的二氧化碳浓度，t为时间，u为x方向上的水流流速，v为y方向上的水流流速，w为z方向上的水流流速，x,y,z为建立的空间坐标系，Kx为x方向上的扩散系数，Ky为y方向上的扩散系数，Kz为z方向上的扩散系数，S1为大气交换引起的二氧化碳源汇项，S2为藻类引起的二氧化碳源汇项。Among them, C is the carbon dioxide concentration of the lake water, t is the time, u is the water flow velocity in the x direction, v is the water flow velocity in the y direction, w is the water flow velocity in the z direction, and x, y, z are the established space Coordinate system, Kx is the diffusion coefficient in the x direction, Ky is the diffusion coefficient in the y direction, Kz is the diffusion coefficient in the z direction, S1 is the carbon dioxide source - sink term caused by atmospheric exchange, and S2 is the carbon dioxide source caused by algae remittance item.
大气交换引起的二氧化碳源汇项S1的公式为：The formula of carbon dioxide source - sink term S1 caused by atmospheric exchange is:
S1＝Kr(Cs-C) (2)S 1 =K r (C s -C) (2)
其中，Kr为水体二氧化碳与大气的交换速率，Cs为水体饱和二氧化碳浓度，C为湖泊水体的二氧化碳浓度。Among them, K r is the exchange rate of carbon dioxide in the water body with the atmosphere, C s is the saturated carbon dioxide concentration in the water body, and C is the carbon dioxide concentration in the lake water body.
藻类引起的二氧化碳源汇项S2的公式为：The formula for the carbon dioxide source-sink term S2 caused by algae is:
其中，x为某类藻类，c为蓝藻，d为硅藻，g为绿藻，PNx为x藻类对铵的吸收率，Px为x藻类的生长速率，FCDx为x藻类的常数，DO为溶解氧浓度，KHRx为x藻类的溶解氧半饱和常数，BMx为x藻类的新陈代谢速率，AOCR为呼吸作用中二氧化碳与碳的比率，Bx为x藻类的生物量。where x is a certain type of algae, c is cyanobacteria, d is diatom, g is green algae, PN x is the absorption rate of ammonium by x algae, P x is the growth rate of x algae, FCD x is the constant of x algae, DO is the dissolved oxygen concentration, KHR x is the dissolved oxygen half-saturation constant of x algae, BM x is the metabolic rate of x algae, AOCR is the ratio of carbon dioxide to carbon in respiration, and B x is the biomass of x algae.
由于碱度为保守性物质，因此只存在对流扩散过程，根据碱度的迁移转化特征，构建的湖泊碱度控制方程为：Since alkalinity is a conservative substance, there is only a convective diffusion process. According to the migration and transformation characteristics of alkalinity, the constructed lake alkalinity control equation is:
其中，Ca为湖泊水体的碱度，t为时间，u为x方向上的水流流速，v为y方向上的水流流速，w为z方向上的水流流速，x,y,z为建立的空间坐标系，Kx为x方向上的扩散系数，Ky为y方向上的扩散系数，Kz为z方向上的扩散系数。Among them, Ca is the alkalinity of the lake water body, t is the time, u is the water flow velocity in the x direction, v is the water flow velocity in the y direction, w is the water flow velocity in the z direction, x, y, z are the established In the spatial coordinate system, Kx is the diffusion coefficient in the x direction, Ky is the diffusion coefficient in the y direction, and Kz is the diffusion coefficient in the z direction.
步骤S1中湖泊pH值控制方程为：The control equation of lake pH value in step S1 is:
其中，
在本实施例中，根据二氧化碳浓度控制方程、湖泊碱度控制方程和湖泊pH值控制方程得到预测的湖泊水体pH值的详细过程为：In this embodiment, the detailed process of obtaining the predicted pH value of lake water according to the control equation of carbon dioxide concentration, the control equation of lake alkalinity and the control equation of lake pH value is as follows:
1)、设定二氧化碳浓度控制方程和湖泊碱度控制方程的初始条件和边界条件，由于pH值为二氧化碳和碱度的衍生变量，因此只需设置二氧化碳浓度和碱度的初始条件和边界条件。初始条件为模型初始时刻的湖泊二氧化碳浓度和碱度，边界条件为入湖河流的二氧化碳浓度和碱度时间序列数据。1) Set the initial conditions and boundary conditions of the carbon dioxide concentration control equation and the lake alkalinity control equation. Since the pH value is a derived variable of carbon dioxide and alkalinity, it is only necessary to set the initial conditions and boundary conditions of carbon dioxide concentration and alkalinity. The initial conditions are the lake carbon dioxide concentration and alkalinity at the initial moment of the model, and the boundary conditions are the time series data of the carbon dioxide concentration and alkalinity of the river entering the lake.
2)、求解二氧化碳浓度控制方程和湖泊碱度控制方程，预测二氧化碳浓度和碱度。将二氧化碳浓度控制方程和湖泊碱度控制方程的初始条件和边界条件代入控制方程求解，即可得到二氧化碳浓度和碱度的预测结果。2) Solve the control equation of carbon dioxide concentration and the control equation of lake alkalinity to predict carbon dioxide concentration and alkalinity. Substitute the initial conditions and boundary conditions of the control equation of carbon dioxide concentration and the control equation of lake alkalinity into the control equations to solve, and then the prediction results of carbon dioxide concentration and alkalinity can be obtained.
3)、将湖泊二氧化碳浓度、碱度预测结果代入pH值控制方程，即可得到pH值的预测结果。3) Substitute the predicted results of carbon dioxide concentration and alkalinity into the pH value control equation to obtain the predicted results of pH value.
Claims (6)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111041821.6A CN113673118B (en) | 2021-09-07 | 2021-09-07 | Method for predicting pH value of lake water body |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111041821.6A CN113673118B (en) | 2021-09-07 | 2021-09-07 | Method for predicting pH value of lake water body |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113673118A true CN113673118A (en) | 2021-11-19 |
| CN113673118B CN113673118B (en) | 2024-02-13 |
Family
ID=78548526
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111041821.6A Active CN113673118B (en) | 2021-09-07 | 2021-09-07 | Method for predicting pH value of lake water body |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113673118B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003004718A (en) * | 2001-06-26 | 2003-01-08 | Japan Science & Technology Corp | How to measure the amount of carbon dioxide fixed in marine organisms |
| JP2003066023A (en) * | 2001-08-21 | 2003-03-05 | Mitsubishi Rayon Co Ltd | Method for measuring carbon dioxide concentration of artificial carbonated spring, method for controlling the same, and apparatus for producing artificial carbonated spring |
| CN1888895A (en) * | 2005-06-27 | 2007-01-03 | 天津师范大学 | Method and instrument for determining PH value and inorganic carbon form through measuring density of CO2 |
| JP2009264913A (en) * | 2008-04-24 | 2009-11-12 | Kimoto Denshi Kogyo Kk | Underwater total alkalinity measuring method |
| CN101639690A (en) * | 2009-06-19 | 2010-02-03 | 新奥科技发展有限公司 | System and method for controlling reaction of alga |
| CN103513015A (en) * | 2013-10-18 | 2014-01-15 | 丹阳市现代生态水产养殖场 | Water quality ph value monitoring system |
| WO2017110889A1 (en) * | 2015-12-25 | 2017-06-29 | 国立大学法人東京大学 | Precise method of measuring carbonate-based parameters of sea water, and measuring device for use in said method |
| TW201825895A (en) * | 2017-01-06 | 2018-07-16 | 陳思嘉 | detection method |
| CN109275560A (en) * | 2018-12-04 | 2019-01-29 | 中国水产科学研究院黄海水产研究所 | A kind of large ocean algae is acidified the system and research method of adaptation Journal of Sex Research for a long time |
| CN112305149A (en) * | 2020-07-29 | 2021-02-02 | 中国科学院东北地理与农业生态研究所 | Method for estimating water solubility inorganic carbon concentration |
| KR20210017795A (en) * | 2019-08-09 | 2021-02-17 | 강원대학교산학협력단 | A METHOD FOR MEASURING ALKALINITY THROUGH MEASUREMENT OF pH, TEMPERATURE AND INORGANIC CARBON COMPONENTS AND A INSTRUMENT FOR MEASURING ALKALINITY BASED ON THE SAME |
-
2021
- 2021-09-07 CN CN202111041821.6A patent/CN113673118B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003004718A (en) * | 2001-06-26 | 2003-01-08 | Japan Science & Technology Corp | How to measure the amount of carbon dioxide fixed in marine organisms |
| JP2003066023A (en) * | 2001-08-21 | 2003-03-05 | Mitsubishi Rayon Co Ltd | Method for measuring carbon dioxide concentration of artificial carbonated spring, method for controlling the same, and apparatus for producing artificial carbonated spring |
| CN1888895A (en) * | 2005-06-27 | 2007-01-03 | 天津师范大学 | Method and instrument for determining PH value and inorganic carbon form through measuring density of CO2 |
| JP2009264913A (en) * | 2008-04-24 | 2009-11-12 | Kimoto Denshi Kogyo Kk | Underwater total alkalinity measuring method |
| CN101639690A (en) * | 2009-06-19 | 2010-02-03 | 新奥科技发展有限公司 | System and method for controlling reaction of alga |
| CN103513015A (en) * | 2013-10-18 | 2014-01-15 | 丹阳市现代生态水产养殖场 | Water quality ph value monitoring system |
| WO2017110889A1 (en) * | 2015-12-25 | 2017-06-29 | 国立大学法人東京大学 | Precise method of measuring carbonate-based parameters of sea water, and measuring device for use in said method |
| TW201825895A (en) * | 2017-01-06 | 2018-07-16 | 陳思嘉 | detection method |
| CN109275560A (en) * | 2018-12-04 | 2019-01-29 | 中国水产科学研究院黄海水产研究所 | A kind of large ocean algae is acidified the system and research method of adaptation Journal of Sex Research for a long time |
| KR20210017795A (en) * | 2019-08-09 | 2021-02-17 | 강원대학교산학협력단 | A METHOD FOR MEASURING ALKALINITY THROUGH MEASUREMENT OF pH, TEMPERATURE AND INORGANIC CARBON COMPONENTS AND A INSTRUMENT FOR MEASURING ALKALINITY BASED ON THE SAME |
| CN112305149A (en) * | 2020-07-29 | 2021-02-02 | 中国科学院东北地理与农业生态研究所 | Method for estimating water solubility inorganic carbon concentration |
Non-Patent Citations (3)
| Title |
|---|
| AW OMTA, P GOODWIN, MJ FOLLOWS: "Multiple regimes of air-sea carbon partitioning identified from constant-alkalinity buffer factors", GLOBAL BIOGEOCHEMICAL CYCLES, vol. 24, pages 1 - 9 * |
| 吴杭纬经, 赵泓睿, 彭苑媛等: "养殖水域二氧化碳交换通量计算", 安徽农业科学, vol. 47, no. 14, pages 55 - 57 * |
| 郭景腾: "MIS 6期以来热带西太平洋上层水体pH和pCO2演变的气候—海洋控制", 中国博士学位论文全文数据库，基础科学辑, no. 2019, pages 010 - 17 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113673118B (en) | 2024-02-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kuo et al. | Eutrophication modelling of reservoirs in Taiwan | |
| CN101858065B (en) | Method for estimating ecological water amount of shallow lake under pollution stress | |
| CN110451661A (en) | The prediction model of microbiology class soluble organic nitrogen and its application in a kind of sewage | |
| Wang et al. | Microscale investigations of temperature-dependent microbially induced carbonate precipitation (MICP) in the temperature range 4–50 C | |
| WO2015109957A1 (en) | Early warning analysis method for eutrophication of planned artificial body of water | |
| Chen et al. | Adaptation and multiple parameter optimization of the simulation model SALMO as prerequisite for scenario analysis on a shallow eutrophic Lake | |
| CN102737156B (en) | In prediction surface water water environment, pollutant is to the method for the ecological risk of biology | |
| CN114996977B (en) | Simulation method and system for water pollution remediation based on hydrodynamic coupling water quality model | |
| CN115879391A (en) | IWIND-LR model-based COD index space-time simulation method and system | |
| CN111398548A (en) | A prediction method of nitrogen and phosphorus concentration in surface flow wetland water based on plant action | |
| Fang et al. | Biofilm growth on cohesive sediment deposits: Laboratory experiment and model validation | |
| CN114202060A (en) | Method for predicting methylene blue adsorption performance of biomass activated carbon based on deep neural network | |
| CN114819407A (en) | Dynamic prediction method and device for lake blue algae bloom | |
| CN103714432B (en) | Method for predicating biomass of submerged plant by establishing growth simulation model | |
| Yan et al. | A concise way to prevent bloom risk in ecological use of reclaimed water: Determination of the threshold by model calculation | |
| CN111735934A (en) | Methods for the effects of temperature and disturbance degree on nitrogen and phosphorus fluxes in lake sediments | |
| CN113673118A (en) | A method for predicting the pH value of lake water | |
| Zhou et al. | Water quality evolution of water-receiving lakes under the impact of multi-source water replenishments | |
| CN115188436A (en) | A calculation method of microplastic flux in complex river network area | |
| CN108046410B (en) | Method for simulating membrane biodegradation of organic sewage based on lattice Boltzmann algorithm | |
| CN119004823A (en) | Prediction method for influence of urban river ecological restoration on microbial-mediated ammonia nitrogen conversion | |
| Hartmann et al. | Growth rate estimation of algae in raceway ponds: A novel approach | |
| CN110427733A (en) | Algae concentration acquisition methods based on phosphorus circulation | |
| CN114814276A (en) | Method for calculating peripheral seawater vertical movement flow velocity caused by operation of offshore wind power equipment | |
| CN115163036A (en) | Novel oil reservoir injection-production flat plate experiment method |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |