JP2010169598A - Water quality estimating apparatus and water quality estimating method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To grasp a more accurate BOD of water without measuring the BOD of evaluation object water. <P>SOLUTION: A water quality estimating apparatus includes at least an arithmetic device 2 accepting turbidity of water, electrical conductivity (EC), concentration of dissolved oxygen (DO), and the biochemical oxygen demand (BOD). The arithmetic device 2 comprises: a ratio calculating section 24; a time period selecting section 25; a measurement value acquiring section 26 acquiring each measurement value of the BOD, the turbidity, and the concentration of the DO; a first power regression creating section 27 creating a first power regression which takes each acquired measurement value of the BOD and the turbidity as each coordinate; a BOD calculating section 28 calculating an estimation value of the BOD by the first power regression formula; a second power regression formula creating section 29 creating a second power regression formula which takes a ratio of the measurement value of the BOD to the estimation value of the BOD and the measurement value of the concentration of the DO as each coordinate; and an estimation formula creating section 30 creating a BOD estimation formula for calculating the estimation value of the BOD by both the formulas. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a water quality estimation apparatus and a water quality estimation method for estimating water quality during rainwater.

  As a result of the revision of the Enforcement Ordinance of the Sewerage Law, the water quality standards (biochemical oxygen demand) of effluent water when the influence of rainwater due to rainfall stipulated by the ministerial ordinance is specified for the combined sewerage system, and discharge that satisfies the standard It was stipulated that water quality inspections be conducted at least once a year to confirm that water quality was obtained.

  However, monitoring of runoff in rainy weather is generally done by manual sampling during rainfall, and in the current situation where it is difficult to predict natural phenomena, it is not possible to perform appropriate sampling that meets the legal requirements. In terms of time and cost, it is a heavy burden for those who are obliged to inspect water quality by local governments.

  On the other hand, with the progress of improvement measures for combined sewerage such as introduction and diversion of storage facilities and treatment facilities, the need for water quality measurement for the purpose of operation management of the facilities and grasping the effect of measures will increase. The need for is expected to increase further. Therefore, it is an urgent task to improve the efficiency of monitoring rainwater runoff for the purpose of reducing time and cost.

  As a method for improving the efficiency of monitoring stormwater runoff, estimation of biochemical oxygen demand (BOD) using a turbidimeter has been studied (see, for example, Patent Document 1). ). Also, in order to improve the disadvantage that turbidity is easily affected by water bubbles, etc., a method for evaluating water pollution based on the detection of electrical conductivity using the correlation between turbidity and electrical conductivity is known. (For example, refer to Patent Document 2).

JP 2006-125930 (Claims) JP 2002-005863 (Claims, FIG. 3)

  However, as for the correlation between the turbidity of water and BOD, there are places where the correlation is high, while there are places where the correlation is extremely low. Therefore, it is difficult to accurately estimate the BOD based on the turbidity by the method of Patent Document 1. Even if the turbidity can be determined more accurately from the electrical conductivity as in the method of Patent Document 2, it is difficult to accurately estimate the BOD as in the method of Patent Document 1.

  The present invention has been made to solve the above-described problem, and an object thereof is to grasp a more accurate BOD without actually measuring the BOD of water to be evaluated.

  In order to achieve the above-mentioned object, the water quality estimation apparatus of the present invention accepts each measured value of turbidity of water, electrical conductivity of water, concentration of dissolved oxygen dissolved in water, and biochemical oxygen demand. And at least a computing device for creating a formula for estimating the biochemical oxygen demand of water, the computing device having electrical conductivity in rainy weather in the same time zone as that in fine weather A ratio calculation unit for calculating the ratio, a time zone selection unit for selecting a time zone in which the ratio is less than a predetermined value, an actual measurement value of biochemical oxygen demand in the selected time zone, an actual measurement value of turbidity, and The actual value acquisition unit that acquires the actual measured value of the dissolved oxygen concentration, and the first power regression equation that passes the points closest to each other with the acquired measured values of biochemical oxygen demand and turbidity as coordinates. The first power regression formula creation section to be created, Substituting the measured value of turbidity into the regression equation to calculate the estimated value of biochemical oxygen demand, and the biochemical oxygen demand for the estimated value of biochemical oxygen demand A second power regression equation creation unit that creates a second power regression equation that passes through a plurality of points closest to each other with the ratio of the actual measurement value of the quantity and the actual measurement value of dissolved oxygen as coordinates, and the first power regression equation Use the second power regression equation to create an estimation formula that creates a biochemical oxygen demand estimation formula to calculate an estimated value of biochemical oxygen demand from each measured value of turbidity and dissolved oxygen concentration A part. For this reason, by using this water quality estimation device, it is possible to create an estimation formula for obtaining accurate BOD information without measuring the BOD of water during rainwater.

  In the water quality estimation apparatus of the present invention, the ratio calculation unit further calculates the ratio of the electrical conductivity in rainy weather to be measured in the same time zone as that in fine weather to the electrical conductivity in fine weather, and the time zone selection unit Then, select a time period in which the ratio is less than the predetermined value, and the actual value acquisition unit acquires each actual measurement value of turbidity and dissolved oxygen concentration in the selected time zone at the time of measurement, and Substituting the measured values of the obtained turbidity and dissolved oxygen concentration into the biochemical oxygen demand estimation formula created in this way, and estimating the biochemical oxygen demand during rainy weather to be measured An oxygen demand estimation unit is provided. Therefore, by using this water quality estimation device, it is possible to obtain BOD information more accurately and quickly simply by actually measuring the electrical conductivity, turbidity, and dissolved oxygen concentration of water during rainwater for which BOD is to be measured. .

  In the water quality estimation apparatus of the present invention, the ratio calculation unit calculates the ratio by using the electrical conductivity at the time of fine weather on the same day in the past, which was traced back from the time of rain. For this reason, the influence of other conditions other than the weather (for example, the outflow situation of external water to the water to be measured) on the electrical conductivity of the water can be further reduced, so the electrical conductivity mainly depends on the difference in weather. A ratio is obtained.

  The water quality estimation method of the present invention is a water quality estimation method for estimating the biochemical oxygen demand of water by using a water quality estimation device having at least a calculation device for performing calculation for estimating water quality. The first reception step for receiving the measured values of the turbidity of water, the electric conductivity of water, the concentration of dissolved oxygen dissolved in water, and the biochemical oxygen demand by the computing device, A first ratio calculating step for calculating a ratio of electrical conductivity in the rainy weather in the same time zone as that for the fine weather, and a first time zone selecting step for selecting a time zone in which the ratio is less than a predetermined value; A first actual measurement value acquisition step for acquiring each actual measurement value of biochemical oxygen demand, measured turbidity, and dissolved oxygen concentration in a specified time period, and the obtained biochemical oxygen demand and turbidity Each measured value for each seat The first power regression formula creation step that creates the first power regression formula that passes through the points closest to each other, and the measured value of turbidity is substituted into the first power regression formula to calculate the biochemical oxygen demand The coordinates of the biochemical oxygen demand calculation step for calculating the estimated value, the ratio of the measured value of the biochemical oxygen demand to the estimated value of the biochemical oxygen demand, and each measured value of the dissolved oxygen concentration Using the second power regression formula creation step to create the second power regression formula that passes through the points closest to each other, and the first power regression formula and the second power regression formula, the turbidity and dissolved oxygen concentration An estimation formula creating step for creating a biochemical oxygen demand estimation formula for calculating an estimated value of the biochemical oxygen demand from each measured value is performed. Therefore, by using this water quality estimation method, it is possible to create an estimation formula for obtaining accurate BOD information without measuring the BOD of water during rainwater.

  In the water quality estimation method of the present invention, after the estimation formula creation step, the calculation device calculates the ratio of the electrical conductivity in the rainy weather that is the measurement target in the same time zone as that in the fine weather to the electrical conductivity in the clear weather. Two ratio calculation steps, a second time zone selection step for selecting a time zone in which the ratio is less than a predetermined value, and respective measured values of turbidity and dissolved oxygen concentration in the selected time zone at the time of measurement Substitute the actual measured values of the obtained turbidity and dissolved oxygen concentration into the biochemical oxygen demand estimation formula created in the second actual measurement value acquisition step and the estimation formula creation step, and A biochemical oxygen demand estimation step for estimating the biochemical oxygen demand is further performed. For this reason, by using this water quality estimation method, it is possible to obtain BOD information more accurately and quickly simply by actually measuring the electrical conductivity, turbidity, and dissolved oxygen concentration of water during rainwater whose BOD is to be measured. .

  In the water quality estimation method of the present invention, the first ratio calculating step or the second ratio calculating step calculates the ratio using the electrical conductivity at the time of fine weather on the same day in the past that has gone back from the time of rain. For this reason, the influence of other conditions other than the weather (for example, the outflow situation of external water to the water to be measured) on the electrical conductivity of the water can be further reduced, so the electrical conductivity mainly depends on the difference in weather. A ratio is obtained.

  According to the present invention, a more accurate BOD can be grasped without actually measuring the BOD of water to be evaluated.

FIG. 1 is a simplified external view showing an embodiment of a water quality estimation apparatus according to the present invention. FIG. 2 is a functional block diagram showing the configuration of the arithmetic unit shown in FIG. 1 divided into functions. FIG. 3 is a flowchart showing a main process flow for creating a BOD estimation formula, which is an embodiment of the water quality estimation method according to the present invention. FIG. 4 is a diagram showing an example of information acquired or created in the course of each process shown in FIG. FIG. 5 is a diagram showing an example of information acquired or created in the course of each process shown in FIG. 3 following FIG. FIG. 6 is a flowchart showing a main process flow for estimating the BOD, which is an embodiment of the water quality estimation method according to the present invention. FIG. 7 is a graph for explaining that the BOD estimated using the BOD estimation formula is close to the actual BOD.

DESCRIPTION OF SYMBOLS 1 Water quality estimation apparatus 2 Arithmetic apparatus 21 Display part 22 Input part 23 Information reception part 24 Ratio calculation part 25 Time zone selection part 26 Actual value acquisition part 27 First power regression formula creation part 28 BOD calculation part (biochemical oxygen demand amount) Calculation part)
29 Second power regression formula creation unit 30 Estimation formula creation unit 31 BOD estimation unit (biochemical oxygen demand estimation unit)
32 Recording unit

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described with reference to the drawings.

1. Water Quality Estimation Device FIG. 1 is a simplified external view showing an embodiment of a water quality estimation device according to the present invention.

  The water quality estimation device 1 includes a calculation device 2, a turbidity detector 3, an electrical conductivity detector 4, and a dissolved oxygen concentration detector 5. The turbidity detector 3 is a detector for detecting the turbidity of water (in this embodiment, “sewage” is taken as an example. The same applies hereinafter). The electrical conductivity detector 4 is a detector for detecting the electrical conductivity (Electrical Conductivity: EC) of sewage. The dissolved oxygen concentration detector 5 is a detector for detecting the concentration of dissolved oxygen (Dissolved Oxygen: DO) dissolved in the sewage. However, the turbidity detector 3, the electrical conductivity detector 4, and the dissolved oxygen concentration detector 5 are not essential for the water quality estimation device 1, but one of the detectors 3, 4, 5 from the water quality estimation device 1. Alternatively, two or more detectors may be excluded. In that case, it is preferable that the measured value measured by each detector can be input to the arithmetic unit 2 via the input unit 22 described later.

  The computing device 2 includes a display unit 21 and an input unit 22, and is connected to the turbidity detector 3, the electrical conductivity detector 4, and the dissolved oxygen concentration detector 5 so as to receive an electrical signal. ing. The arithmetic unit 2 also inputs various detection signals from the turbidity detector 3, the electrical conductivity detector 4 and the dissolved oxygen concentration detector 5 and the value of biochemical oxygen demand (BOD). Is an apparatus for creating a formula for estimating the BOD of sewage.

  FIG. 2 is a functional block diagram showing the configuration of the arithmetic device 2 divided into functions.

  In addition to the display unit 21 and the input unit 22 described above, the computing device 2 includes an information receiving unit 23, a ratio calculation unit 24, a time zone selection unit 25, an actual measurement value acquisition unit 26, a first power regression equation creation unit 27, A BOD calculation unit 28, a second power regression equation creation unit 29, an estimation equation creation unit 30, a BOD estimation unit 31, and a recording unit 32 are provided.

  The display unit 21 is a part that displays information input by the user, information from the various detectors 3, 4, and 5 described above, information obtained by calculation from each information, and the like. However, the display unit 21 is not an essential configuration, and may be the arithmetic device 2 that does not include the display unit 21.

  The input unit 22 is a component for a user to input information, and is a part having an arbitrary form such as a keyboard, a pointing device, a touch panel type switch, and a voice input device. The input unit 22 can be used, for example, when the user inputs an actual measurement value of BOD. Further, the user can also input each data of turbidity, EC or DO concentration (hereinafter referred to as DO concentration) from the input unit 22.

  The information receiving unit 23 is a component that receives the detection signals from the various detectors 3, 4, and 5 and the signal input from the input unit 22. The information receiving unit 23 sends one or more types of information based on the received various signals to the recording unit 32 for recording.

  The ratio calculation unit 24 is a component that calculates a ratio of EC in rainy weather in the same time zone as that in sunny weather (EC in rainy weather / EC in sunny weather) to EC in sunny weather. What kind of method is EC in clear weather, such as EC obtained by measurement by a user in clear weather, or EC obtained by automatically judging that the weather is clear from humidity, temperature and other information It may be obtained in The same applies to EC in rainy weather. Preferably, EC is measured at regular intervals regardless of the weather, and weather information is input by the user and determined by automatic judgment as described above, or externally using a communication line or the like. And the weather information obtained thereby is associated with the detected EC at each fixed time. Since sewage during rainy weather is diluted by water flowing in from the outside due to rain water, the EC during rainy weather is lower than the EC during clear weather with little such dilution. For this reason, EC in rainy weather / EC in fine weather takes a value in the range of 0-1.

  The time zone selection unit 25 is a component that selects a time zone in which the ratio calculated by the ratio calculation unit 24 is less than a predetermined value. Here, it does not matter whether the predetermined value is a fixed specific numerical value or a numerical value that can be arbitrarily set. Moreover, although a predetermined value is not limited to a specific numerical value, Preferably it is 0.8-0.95, More preferably, it is 0.85-0.92, More preferably, it is 0.90. The time zone in which the ratio is less than the predetermined value is a time zone in which sewage is affected by rainwater, and is a time zone in which BOD is measured. The time zone selection unit 25 selects such a time zone. Such a time zone is recorded in the recording unit 32 as appropriate.

  The actual measurement value acquisition unit 26 is a component that acquires an actual measurement value of BOD, an actual measurement value of turbidity, and an actual measurement value of DO concentration in the time zone selected by the time zone selection unit 25. For example, assuming that the selected time zone is “9 am to 2 pm”, the actual measurement value acquisition unit 26 selects BOD, turbidity, and DO concentration from 9 am to 2 pm. Become. The value of BOD is usually unknown only after about 5 days from sampling. Therefore, at the stage of creating the estimation formula, water is sampled at regular intervals to measure the BOD of the sewage so that the BOD in the time zone selected by the actual measurement value acquisition unit 26 does not exist. Is preferred. Turbidity and DO concentration can be measured in a shorter time than BOD. For this reason, the measurement for every fixed time is continued and the actual measurement value acquisition part 26 should just acquire BOD, turbidity, and DO density | concentration in the selected time slot | zone. The acquired BOD, turbidity, and DO concentration are recorded in the recording unit 32 as appropriate.

The first power regression equation creation unit 27 obtains a first power regression equation that passes through a plurality of points with the measured BOD actual value and the turbidity actual value acquired by the actual value acquisition unit 26 as coordinates. Part. Specifically, the first power regression equation creation unit 27 plots the plurality of points on the xy plane having the turbidity as the x-axis and the measured value of BOD (referred to as measured BOD) as the y-axis, Y = a × X ^b (Y: turbidity estimation BOD, a: coefficient, X: turbidity, b: multiplier of X), which is the equation of the curve closest to each plot, b is specified.

  The BOD calculation unit 28 corresponds to a biochemical oxygen demand calculation unit, substitutes the measured value of the turbidity in the first power regression equation, and estimates the BOD (this is estimated only by the turbidity). Since this is a BOD, it is a component that calculates “turbidity estimation BOD”.

The second power regression equation creation unit 29 uses a ratio of the measured value of the BOD to the estimated turbidity BOD (measured BOD / turbidity estimated BOD) and a plurality of points having the measured value of the DO concentration as coordinates at the nearest point. It is a component which calculates | requires the 2nd power regression equation to pass. Specifically, the second power regression equation creation unit 29 displays the measured value of DO concentration and the measured BOD / turbidity on the xy plane with the DO concentration as the x axis and the measured BOD / turbidity estimated BOD as the y axis. A plurality of points having the estimated BOD as x and y coordinates are plotted, and W = c × V ^d (W: measured BOD / turbidity estimated BOD, c: Coefficient, V: measured value of DO concentration, d: multiplier of V), and c and d in the equation are specified.

The estimation formula creation unit 30 uses the first power regression equation (Y = a × X ^b ) and the second power regression equation (W = c × V ^d ) to measure the measured turbidity and the measured DO concentration. It is a component that creates a BOD estimation formula for calculating an estimated value of BOD from the value. As a result, a BOD estimation formula “actual measurement BOD = a × X ^b × c × V ^d ” is obtained. Here, “actually measured BOD” corresponds to the BOD to be estimated.

The BOD estimator 31 corresponds to a biochemical oxygen demand estimator, and the obtained measured value of the turbidity and the measured value of the DO concentration are respectively represented by a BOD estimation formula (actually measured BOD = a × X ^b × c This is a component that estimates the BOD during the rain of the measurement target by substituting for X and V of × V ^d ). The BOD estimated here takes into account not only turbidity but also DO concentration. Prior to the above processing of the BOD estimation unit 31, the information reception unit 23, the ratio calculation unit 24, the time zone selection unit 25, and the actual measurement value acquisition unit 26 perform the following processing.

  The information receiving unit 23 receives EC, turbidity, and DO concentration during rainy weather, which is a measurement target, and EC during clear weather before that. The EC, turbidity, and DO concentration during the rain are usually data measured on that day. On the other hand, EC at the time of fine weather is data measured before the rainy day. The ratio calculation unit 24 calculates the ratio of EC in rainy weather (EC in rainy weather / EC in rainy weather) to be measured in the same time zone as that in sunny weather with respect to EC in sunny weather. The time zone selection unit 25 selects a time zone in which the ratio is less than a predetermined value (for example, 0.9). The actual measurement value acquisition unit 26 acquires an actual measurement value of turbidity and an actual measurement value of DO concentration in a selected time zone at the time of measurement. After that, as described above, the BOD estimation unit 31 can substitute these acquired measured values of turbidity and measured values of DO concentration into the BOD estimation formula to estimate the BOD without bothering to actually measure it. (This estimated BOD is referred to as “estimated BOD”).

  The recording unit 32 is a component that records one or more of turbidity, DO concentration, EC, estimated BOD, and the like. The recording unit 32 can record data other than those described above, for example, an image for graphing, weather, temperature, humidity, and various programs.

  The arithmetic device 2 is a computer and includes at least the following hardware configuration. That is, the arithmetic device 2 includes at least a central processing unit (CPU), a read-only memory (Read Only Memory: ROM), and a readable / writable memory (Random Access Memory: RAM). The ROM may also include an EEPROM. The CPU may also include an MPU. Information reception unit 23, ratio calculation unit 24, time zone selection unit 25, actual measurement value acquisition unit 26, first power regression formula creation unit 27, BOD calculation unit 28, second power regression formula creation unit 29, estimation formula creation unit 30 And each process of the BOD estimation part 31 is a process mainly performed by cooperation with CPU and the computer program stored in the recording part 32. FIG. Based on the received information and various information recorded in the recording unit 32, the CPU executes each process shown in FIGS. 3 and 6 to be described later while reading the computer program. The recording unit 32 corresponds to a broad memory including a ROM and / or a RAM, and stores the above-described computer program. The input unit 22 corresponds to the aforementioned input means such as a keyboard and a pointing device. When the arithmetic device 2 has a display, the display unit 21 corresponds to a CPU and the display. Since the display unit 21 is not an essential component, a display may not be present.

2. 2. Water Quality Estimation Method 2.1 Creation of Estimation Formula FIG. 3 is a flowchart showing a main processing flow for creating a BOD estimation formula, which is an embodiment of the water quality estimation method according to the present invention. 4 and 5 are diagrams showing examples of information acquired or created in the course of each process shown in FIG.

  The information receiving unit 23 receives various signals from the turbidity detector 3, the electrical conductivity detector 4, and the dissolved oxygen concentration detector 5 and BOD data from the input unit 22 (step S101: first receiving step). In step S101, preferably, BOD data is received and various signals are received at different times. For example, the information accepting unit 23 can accept the data of the BOD only once at first, and thereafter accept the signals from the various measurement detectors 3, 4 and 5 every day or every other day. The detection signal (EC signal) from the electrical conductivity detector 4 is for both weather conditions during fine weather and rainy weather. In this embodiment, as an example, it is assumed that both a clear weather EC and a rainy EC are measured every hour for 24 hours. In addition, the measurement day for EC in fine weather is the day one week before the measurement date for EC in rainy weather. In addition, when one week before rainy weather is not sunny, the information reception unit 23 can further search the day before one week to find an EC on a past sunny day. As shown in graphs A and B in FIG. 4, the 24-hour clear sky EC from midnight to 12:00 pm is higher than the simultaneous rainy-day EC. This is because sewage during rainy weather is easily affected by rainwater, at which time EC decreases. In addition, the detection signals from the turbidity detector 3 and the dissolved oxygen concentration detector 5 are those of the measurement date of rainy EC, and the BOD data is also of the measurement date of EC in rainy weather.

  The ratio calculation unit 24 calculates the ratio of rainy day EC to rainy day EC (rainy day EC / sunny day EC) (step S102; first ratio calculation step). The calculation result is shown in graph C of FIG. The graph C is a graph in which the ratio decreases from midnight to morning and maintains the decreased ratio thereafter. Next, the time zone selection unit 25 selects a time zone in which the ratio is less than a predetermined value (here, 0.9) (a time zone in which the influence of rainwater on the sewage is large) (step S103: Step No. 1). One time zone selection step). As a result, as shown in graph C of FIG. 4, a time period from 4 am to 12 pm in which the ratio is smaller than 0.9 is selected. Next, the actual measurement value acquisition unit 26 acquires, from the actual measurement values recorded in the recording unit 32, the actual measurement value of BOD, the actual measurement value of turbidity, and the actual measurement value of DO concentration in the selected time zone. (Step S104: First actual measurement value acquisition step).

The first power regression equation creating unit 27 is a first power regression equation (turbidity estimation BOD == passing through a plurality of points having the measured values of actual BOD (measured BOD) and the measured values of turbidity as coordinates, respectively). a × turbidity ^b ) is created (step S105: first power regression equation creating step). An example of each point and the curve that passes through them at the closest point is as shown in graph A of FIG. Next, the BOD calculation unit 28 calculates the BOD estimated value by substituting the measured value of turbidity into the first power regression equation (step S106: biochemical oxygen demand calculation step). Thereby, BOD estimated by turbidity (turbidity estimation BOD) is obtained.

Since it is difficult to estimate an accurate BOD only with turbidity, correction using the measured value of DO concentration is performed next. The ratio of the measured value (actually measured BOD) of the BOD to the estimated turbidity BOD and the second power regression equation (actually measured BOD / turbidity estimated BOD = c × DO ^d ) is obtained (step S107: second power regression equation creation step). An example of each point and the curve that passes through them at the closest point is as shown in graph B of FIG. Next, using the first power regression equation and the second power regression equation, a BOD estimation equation (BOD = a ×) for calculating an estimated value of BOD from an actual measurement value of turbidity and an actual measurement value of DO concentration. turbidity ^b × c × DO ^d) creating a (step S108: estimation expression generation step). With these series of processes, creation of the BOD estimation formula is completed.

2.2 BOD Estimation FIG. 6 is a flowchart showing a main process flow for estimating the BOD, which is an embodiment of the water quality estimation method according to the present invention.

  The information accepting unit 23 accepts various signals from the turbidity detector 3, the electrical conductivity detector 4, and the dissolved oxygen concentration detector 5 during rainy weather when measuring BOD (step S201: second accepting step). The ratio calculation unit 24 calculates the ratio of the detection signal (EC in rainy weather) received from the electrical conductivity detector 4 received in the above step to the EC in clear weather one week before the measurement date (step S202: No. 1). Two ratio calculation step). If one week before the measurement day (rainy day) is not sunny, the information reception unit 23 can further search the day one week before and find an EC on a past sunny day. Next, the time zone selection unit 25 selects a time zone in which the ratio is less than a predetermined value (here, 0.9) (a time zone in which the influence of rainwater on sewage is large) (step S203: second). Time zone selection step).

  Next, the actual measurement value acquisition unit 26 acquires the actual measurement value of turbidity and the actual measurement value of DO concentration in the selected time zone from the recording unit 32 (step S204: second actual measurement value acquisition step). Steps S201 to S204 are similar to steps S101 to S104 in creating the described BOD estimation formula, but differ in that an actual measured value of BOD is not acquired. Next, the BOD estimation unit 31 reads out the BOD estimation formula stored in the recording unit 32, and substitutes the actual measured value of turbidity and the actual measured value of DO concentration acquired in step S204 for the BOD estimated formula. The BOD during rainy weather is estimated (step S205: biochemical oxygen demand estimation step). With these series of processes, the BOD estimation is completed.

3. BOD Estimation Experimental Data Next, the BOD estimation formula was constructed by the process shown in FIG. 3 in the first experiment, and the BOD was estimated by the process shown in FIG. 6 using the estimation formula in the second experiment. When the estimation accuracy was verified. The verification result is shown in FIG. Both the conventional method and the present method were conducted in the first and second experiments.

Graph A in FIG. 7 plots the turbidity obtained in the first experiment and the measured BOD, draws the nearest straight line by a conventional method, and shows a linear expression of turbidity and measured BOD (y = ax + b, y: It is the graph which calculated | required measured BOD, x: turbidity, a: 0.3323, b: 27.217). Further, the graph B in FIG. 5 shows the above-described primary measured BOD as the estimated BOD, and the estimated BOD (referred to as “conventional method estimated BOD”) and the measured BOD based on the turbidity obtained in the second experiment. It is the graph which investigated correlation. On the other hand, graph C in the figure plots the turbidity obtained in the first experiment and the measured BOD, draws the nearest power regression curve by this method, and obtains the first power regression equation (y = 7.2037 ^{× 0.4678).} , Y: measured BOD, x: turbidity). Further, a graph D in the figure is for the purpose of performing correction by DO concentration, and the ratio between the measured value of DO concentration obtained in the first experiment and the measured BOD / turbidity estimated BOD (where turbidity estimated BOD is , BOD estimated by the first power regression equation) and the second power regression equation (y = 1.6472x− ^0.4182 , y: measured BOD / turbidity estimated BOD, x: DO concentration). . Graph E in the figure shows an estimated BOD ("DO corrected turbidity" obtained from the estimated expression based on the second experiment by creating an estimated expression from the first power regression expression and the second power regression expression. It is a graph in which the correlation between the “estimated BOD” and the measured BOD is examined.

  As is clear from a comparison between the graph B and the graph E in FIG. 7, the correlation between the estimated BOD and the measured BOD is higher in the graph E than in the graph B. That is, in the graph E, the plotted points are closer to a straight line of estimated BOD: actually measured BOD = 1: 1. As is clear from this result, it was proved that more accurate BOD can be estimated by correcting with DO concentration.

4). Other Embodiments The present invention is not limited to the above-described embodiments, and can be implemented with various modifications. The above-described water quality estimation apparatus 1 is an apparatus that can create an estimation formula and then estimate a BOD, but the water quality estimation apparatus of the present invention may be only an apparatus that creates an estimation formula. In that case, the BOD estimation unit 31 is not provided in the water quality estimation device 1, and the other components illustrated in FIG. 2 may not perform the processes in steps S201 to S204. Furthermore, the water quality estimation apparatus of the present invention may be an apparatus that inputs an estimation formula created by another apparatus from the outside and estimates the BOD using the estimation formula.

  When the water amount value can be input or when high accuracy is not required, the electric conductivity detector 4 is not provided and the BOD may be estimated using the water amount data. In this case, the ratio calculation unit 24 calculates the ratio of the rainy water amount / the fine weather water amount by replacing the rainy day EC / the fine weather EC with the rainy day water amount / the fine weather water amount, and the time zone selection unit 25 has a predetermined ratio. Select a time zone that is less than the value.

  The present invention can be used for water quality inspection and water quality monitoring.

Claims (6)

Accepts the measured values of water turbidity, water electrical conductivity, dissolved oxygen concentration in water, and biochemical oxygen demand, and creates a formula to estimate the biochemical oxygen demand of water At least a computing device for
The arithmetic unit is
A ratio calculation unit for calculating a ratio of the electrical conductivity in the rainy weather in the same time zone as that in the fine weather to the electrical conductivity in the fine weather;
A time zone selector for selecting a time zone in which the ratio is less than a predetermined value;
An actual measurement value acquisition unit for acquiring the actual measurement value of the biochemical oxygen demand in the selected time period, the actual measurement value of the turbidity, and the actual measurement value of the concentration of dissolved oxygen;
A first power regression equation creation unit that creates a first power regression equation that passes through a plurality of points with the coordinates of the obtained biochemical oxygen demand and the measured values of the turbidity as coordinates,
Substituting the measured value of the turbidity into the first power regression equation, a biochemical oxygen demand calculation unit for calculating the estimated value of the biochemical oxygen demand,
A ratio of the measured value of the biochemical oxygen demand to the estimated value of the biochemical oxygen demand and the second power regression equation passing through a plurality of points having the measured value of the concentration of dissolved oxygen as coordinates. A second power regression equation creation unit for creating
Using the first power regression equation and the second power regression equation, a biochemical for calculating the estimated value of the biochemical oxygen demand from the measured values of the turbidity and the concentration of dissolved oxygen. An estimation formula creation unit for creating an oxygen demand estimation formula;
A water quality estimation apparatus comprising: further,
The ratio calculation unit calculates the ratio of the electrical conductivity in rainy weather to be measured in the same time zone as that in fine weather with respect to the electrical conductivity in fine weather,
The time zone selection unit selects a time zone whose ratio is less than a predetermined value,
The actual measurement value acquisition unit acquires each actual measurement value of the turbidity and the concentration of dissolved oxygen in the selected time zone at the time of measurement,
Substitute the measured values of the obtained turbidity and the concentration of dissolved oxygen into the biochemical oxygen demand estimation formula created by the estimation formula creation unit, and the biochemistry during rainy weather to be measured The water quality estimation apparatus according to claim 1, further comprising a biochemical oxygen demand estimation unit that estimates a dynamic oxygen demand.   3. The water quality estimation apparatus according to claim 1, wherein the ratio calculation unit calculates the ratio by using the electrical conductivity in the fine weather on the same day of the week in the past going back from the rainy weather. A water quality estimation method for estimating the biochemical oxygen demand of water using a water quality estimation device comprising at least a calculation device for performing calculation for estimating water quality,
With the arithmetic unit,
A first receiving step for receiving measured values of water turbidity, water electrical conductivity, dissolved oxygen concentration dissolved in water, and biochemical oxygen demand;
A first ratio calculating step for calculating a ratio of the electric conductivity in the rainy weather in the same time zone as that of the fine weather to the electric conductivity in the fine weather;
A first time zone selection step of selecting a time zone in which the ratio is less than a predetermined value;
A first actual value acquisition step of acquiring each actual measured value of the biochemical oxygen demand, the measured value of the turbidity, and the concentration of the dissolved oxygen in the selected time period;
A first power regression equation creating step for creating a first power regression equation that passes through a plurality of points having the coordinates of the obtained biochemical oxygen demand and the measured values of the turbidity as coordinates;
Substituting the measured value of the turbidity into the first power regression equation, and calculating the estimated value of the biochemical oxygen demand, a biochemical oxygen demand calculation step,
The ratio of the measured value of the biochemical oxygen demand to the estimated value of the biochemical oxygen demand and the second power regression that passes through the points closest to each other with the measured values of the dissolved oxygen concentration as coordinates. A second power regression formula creation step for creating a formula,
Using the first power regression equation and the second power regression equation, a biochemical for calculating the estimated value of the biochemical oxygen demand from the measured values of the turbidity and the concentration of dissolved oxygen. An estimation formula creating step for creating an oxygen demand estimation formula;
Water quality estimation method characterized by performing. After the estimation formula creating step,
By the arithmetic unit,
A second ratio calculating step for calculating a ratio of the electrical conductivity in the rainy weather to be measured in the same time zone as that in the fine weather with respect to the electrical conductivity in the fine weather;
A second time zone selection step for selecting a time zone whose ratio is less than a predetermined value;
A second actual measurement value acquisition step of acquiring each actual measurement value of the turbidity and the concentration of the dissolved oxygen in the selected time zone at the time of measurement;
Substituting the measured values of the obtained turbidity and the dissolved oxygen concentration into the biochemical oxygen demand estimation formula created in the estimation formula creating step, the biochemical oxygen in the rainy subject to be measured The water quality estimation method according to claim 4, further comprising a biochemical oxygen demand estimation step for estimating the demand. 5. The first ratio calculating step or the second ratio calculating step calculates the ratio by using the electrical conductivity in the fine weather on the same day of the week in the past going back from the rainy weather. Or the water quality estimation method of 5.

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