KR100501097B1 - GIS Based Water Quality Modeling Methodology for Fresh Lake Management - Google Patents

Abstract

The present invention includes the steps of calculating the generation load through a predetermined calculation process using the source size and source unit information as input information and storing the corresponding result; Calculating a discharge load through a predetermined calculation process using the calculated generated load and discharge rate as input information and storing a corresponding result value: passing through a predetermined calculation process using the calculated discharge load and a delivery rate as input information Calculating the overload load and storing a corresponding result; Calculating the inflow concentration through a predetermined calculation process using the outflow amount and the calculated overload load as a result of the watershed balance model and storing the corresponding result value: Performing the stream quality model using the inflow concentration as input information Calculating a boundary concentration value and storing a corresponding result value; And it provides a GIS-based water quality modeling method comprising the step of performing an appeal water quality model using the boundary concentration value as input information.

Description

 GIS Based Water Quality Modeling Methodology for Fresh Lake Management

The present invention relates to a water quality modeling method, and more particularly, to a GIS-based water quality modeling method capable of accurately predicting a pollutant load in a watershed and suggesting a systematic and efficient management method in freshwater lake management.

The existing GIS-based water quality modeling method for managing freshwater lakes has recently been attempted to link river and lake water quality models using GIS in Korea.In 1999, a comprehensive agricultural water quality information management system was developed by Korea Agricultural Infrastructure Corporation. It has been. Overseas, the Better Assessment Science Integrated point and Nonpoint Source (BASINS) model has recently been used to manage point and nonpoint sources.

In Korea, the Agricultural Water Quality Information Management System of the Korea Agricultural Infrastructure Corporation conducts water quality surveys and repair surveys for efficient and systematic water quality management of agricultural waters, and implements the linkage between QUAL2E and WASP5 using ArcView, a GIS software. It was.

The detailed features of the water quality modeling process of the Integrated Agricultural Water Quality Information Management System were based on the pollutant database and runoff data per unit basin, and the pollutant load was linked to the stream model. Finally, the water quality modeling support function is provided by linking the boundary concentration value, which is the result of river modeling, to the appeal model data group for freshwater lake water quality prediction.

The BASINS model was developed by the Environmental Protection Agency (EPA) in 1999 by combining AreView, a GIS software, and a water quality model for integrated management of point sources and nonpoint sources. This program evaluates the quality of river water using QUAL2E and TOXIROUTE models, and the quality of rivers and lakes from non-point sources from watersheds using the Non Point Source Model (NPSM) model. Table 1 shows the existing developed technologies.

<Table> Analysis of Existing Development Technology

    Development technology Agricultural Water Quality Information Management System BASINS producer Agricultural Infrastructure Corporation US Environmental Protection Agency Advantages Pollution load estimation and inquiry function.Supports river and lake water quality prediction modeling. Decision support function for alternative water quality improvement. Integrated water management system for point and nonpoint sources. Point and nonpoint pollution modeling for water quality prediction. Disadvantages Applicable model suitable for watershed environment in Korea. User convenience is not considered due to DOS-based modeling environment. System safety is insufficient due to DDE communication. Rather difficult to apply to domestic watersheds.Difficulty in implementing modeling by non-professionals.Require additional design to predict appeal water quality.Insufficient system safety with DDE communication.

On the other hand, the agricultural water quality information management system is difficult to operate because the user convenience is not considered, the safety of the system is difficult to accurately predict the pollutant load in the watershed, and there is also a difficulty in supporting application program development. The BASINS model is developed for all regions of the United States and is used for analysis of water quality data and water quality prediction of watersheds, but it is designed to be suitable for large watersheds, and there is no modeling support system for lake water quality prediction. A separate module design for prediction is required. For this reason, it is difficult to systematically manage freshwater lake water quality because additional design is required due to separation of watershed and appeal modeling by predicting accurate water quality when applied to domestic watershed environment.

The present invention has been made to solve the problems of the prior art, its purpose is to accurately predict the pollution load in the watershed by calculating the pollution generation and discharge load using the raw unit to propose a systematic and efficient management method in freshwater lake management To provide a GIS-based water quality modeling method.

The present invention to achieve the above object,

Calculating the generation load through a predetermined calculation process using the source size and source unit information as input information and storing the resultant value; Calculating a discharge load through a predetermined calculation process using the calculated generated load and discharge rate as input information and storing a corresponding result value: passing through a predetermined calculation process using the calculated discharge load and a delivery rate as input information Calculating the overload load and storing a corresponding result; Calculating the inflow concentration through a predetermined calculation process using the outflow amount and the calculated overload load as a result of the watershed balance model and storing the corresponding result value: Performing the stream quality model using the inflow concentration as input information Calculating a boundary concentration value and storing a corresponding result value; And it provides a GIS-based water quality modeling method comprising the step of performing an appeal water quality model using the boundary concentration value as input information.

In addition, the present invention provides a water quality modeling method, characterized in that the QUALKO model is used in performing the stream balance model constituting the GIS-based water quality modeling method.

In addition, the present invention provides a water quality modeling method characterized in that the WASP5 model is used in the performance of the appeal resin model constituting the GIS-based water quality modeling method.

In addition, the present invention is the step of performing the QUALKO model converting the inlet concentration value stored in the form of GIS data into an input file format suitable for the QUALKO model; Generating an output file by performing a QUALKO model; And it provides a GIS-based water quality modeling method comprising the step of converting the output file in the form of GIS data.

In addition, the present invention includes the step of inputting the conditions and factors required for the model execution, and the step of performing the model, and selecting and outputting only the required information according to the user's request after performing the model. It is to provide a water quality modeling method based on GIS.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT Hereinafter, the present invention will be described in detail with reference to the corresponding drawings in terms of the structural design of the water quality modeling system, the pollution load estimation system, the GIS-based water quality modeling support system, and the linkage system of the pollution load and the water quality model.

Structural Design of Water Quality Modeling System

Development of efficient water quality modeling system by defining linkage between pollutant source data and pollutant load estimation system, linkage information for pollutant load estimation system and river model, stream information for freshwater lake water quality prediction, and linkage information by data group of appeal model. This should be done.

1. Data Flowchart

(1) main data flow chart

Using the GIS database, the system is designed around the flow of data on the entire process from pollutant load calculation, river and lake water quality modeling. Figure 1 shows the main data flow diagram of the water quality modeling system.

Referring to FIG. 1, a figure database and an attribute database are spatially connected to build a GIS. First, when the pollutant load is calculated and the flow rate and boundary concentration are calculated, the hydrological model and the river balance model (preferably, the QUALKO model) are performed, and the result values are input to the appeal water quality model (preferably the WASP5 model). do. The appeal water quality executes a model for the demand of the water quality prediction, and outputs the result value of the water quality prediction desired by the user as a GIS data type.

(2) detailed flow chart

Define the flow of detailed data on the entire process, from GIS-based pollution load estimation to river and lake water quality modeling. Estimation of the discharge load and the dead load is as shown in FIG. 2, and the river and lake water quality modeling is shown in FIG. 3.

Referring to FIG. 2, the discharge load for each subwatershed is calculated based on the discharge load source unit and the changed pollutant source information, and the change history of the basin discharge load is stored therefrom. In addition, the user can select a specific watershed to query the stored watershed discharge load, which is plotted and output. From the discharge load of the detailed sub-basin can be calculated through the predetermined formula for the amount of delivery load, it is possible to calculate the delivery load for each sub-basin, and stores the changes in the flow rate changes by basin. When a user queries the delivered load for a specific watershed, the system plots and prints the data.

Referring to FIG. 3, QUALKO is shown as an example of river water quality modeling, and WASP5 is shown as an example of lake water quality modeling. When changing parameters and boundary concentration is required, the input file is modified to input the change history of model input data, and when a specific watershed is selected to execute the model, the result of executing the water quality model is transmitted to the GIS. In the case of selecting a specific flow and segment, the density for each segment is shown, and when output is requested, it is output in the form of a drawing and a screen. A more detailed description thereof will be provided later.

2. Definition of terms

(1) Pollution load and delivered load

The definitions of each term used for the pollutant load and the runoff load are illustrated below.

1) Pollution Load = Generation Load + Discharge Load, where, Load Generation = Pollution Source × Source Unit, Discharge Load = Pollution Load × Discharge Rate = BOD Discharge Load + TN Discharge Load + TP Discharge Load, BOD Discharge Load = Population + Livestock + Wastewater Discharge Plant + Land Use + Hot Spring + Aquaculture Plant + Environmental Foundation

2) Delivery load = discharge load × delivery rate = monthly BOD delivery load + monthly TN delivery load + monthly TP delivery load, where delivery rate = EXP (-kℓ), where k is the midnight coefficient and ℓ is the delivery distance Indicates.

(2) Modeling river and lake water quality

1) Inflow Concentration = Aqueous Load by Subwatershed ÷ Outflow = BOD + TN + TP + Water Temperature + DO + Org-N + NH ₄ -N + NO ₃ -N + Org-P + PO ₄ -P

2) water quality modeling = QUALKO water quality modeling + WASP5 water quality modeling,

QUALKO water quality modeling = A river modeling + B river modeling + C cloth modeling,

The steel A modeling = steel A input file + steel A output file + steel A graph file,

The steel A input file = steel A reach + steel A element + basic data for model performance + boundary condition and pollutant load data + environmental parameters + initial condition,

The river A output file = water quality items,

WASP5 water quality modeling = DYNHYD5 input file + DYNHYD5 output file + EUTRO5 input file + EUTRO5 output file + EUTRO5 graphs and tables,

The DYNHYD5 input file = simulation and output control + confluence and channel data of the river + weather data + strait boundary data + rainfall and evapotranspiration data + rectification and inflow data.

Pollution Load Estimation System

Pollution Load Estimation System using GIS estimates the generation and discharge load using the unit by grasping the source of pollution and estimates the delivery load using the delivery rate and the flow rate to predict the pollution load from the watershed. 4 shows the overall flow of pollutant load selection.

1. Emission load calculation module

The discharge load estimation module using the surveyed source pollutant source and raw unit stores the calculated load in the form of GIS data so that it can be linked with the spatial information of the watershed. Although information on water pollution sources should be made up of watershed units that can affect a particular water system, point source data such as population distribution or nonpoint source data such as land use status should be in the unit of administrative districts. As it is collected and managed, the present invention includes a process of converting such information into watershed information. The discharge load calculation module may be performed through the procedure as shown in FIG. 5.

Estimation of livestock farm load among the pollutant loads discharged from point sources is calculated using the source unit slightly differently from other estimation methods. Pollution discharges in livestock systems take the form of point pollution discharges and non-point pollution discharges, and are calculated by considering the discharge load of livestock treatment plant considering the area where the livestock wastewater treatment plant is installed. Figure 6 shows the flow of the livestock pollutant load calculation module. The calculated livestock discharge load is included in the total discharge load estimation module to allow the total discharge load in the watershed to be estimated.

In order to obtain the discharge load by subwatershed and the discharge load by subwatershed from the pollutant load calculated on the basis of statutory clearance and the same unit, the procedure as shown in FIG. Since the subwatershed boundaries and administrative boundaries do not coincide exactly, the pollutant load for each subwatershed is calculated by grasping the proportion of administrative areas included in each subwatershed.

It is advisable to develop an emission load estimation interface to support the modules designed in this way to provide the user with an environment for easy estimation and update of the discharge load. The emission load estimation interface is preferably developed based on MapObject and Visual Basic. In the event of changes in watershed source status and renewal at the unit level, emissions calculations should be recalculated. The discharge load calculation method preferably uses the existing environmental load method, and can be selected and calculated individually for items whose raw unit or pollutant data values have been changed so that they can be updated quickly. 8 illustrates an example of selecting a pollutant source item to be recalculated to the pollution load calculation initial screen.

2. Equation formula for emission pollution load

(1) Point pollution load

end. Life

① Calculation formula for generating load

The generation load of the living system is estimated by the source size and the source unit.

Life load generated = Σ (population × source unit)

② Calculation formula of discharge load

Life discharge loads are based on the discharge load of the population in the sewage treatment area, the discharge load when directly discharged from the flushed population in the sewage treatment area, the discharge load of sewage among the collected food in the sewage treatment area, and the untreated population. It is estimated by the sum of the discharge load, the discharge load due to the lack of manure treatment facilities, and the discharge load of the manure treatment facility.

A) Emission load of the population in the sewage treatment area = [(Sorted sewage population × unit of origin) + {combined sewage population × source of origin × (1-septic load ratio)} + {combined sewage population × source unit × manure load ratio × (1-Cleaning Plant Treatment Rate / 100)}-Sewage Terminal Treatment Plant Inflow Sewage Load] + Sewage Treatment Plant Discharge Rate × Discharge Concentration

Here, the purification facility includes a sewage treatment facility and a single purification tank, and the treatment rate of the purification facility in the combined treatment zone preferably applies 50% BOD, 15% TN, and 15% TP. The manure load ratio is the ratio of manure in the population generation unit, preferably 0.35, 0.82, 0.60 for BOD, TN and TP, respectively.

B) the discharge load when discharged directly from the flushing population in the sewage treatment area through the purification facility-if there is a measurement of the purification facility = the discharge amount of the purification facility x the concentration of discharge-

◎ In case of single septic tank = {single septic tank population × source unit × manure load ratio × (1-standard treatment rate / 100)} + {single septic tank population × source unit × (1-manure load ratio)}

◎ In case of sewage treatment facility = Sewage treatment facility population × source unit × (1-standard treatment rate / 100)

C) The discharge load of sewage among the collected food in the sewage treatment area = the collected food population × the unit of population generation × (1-manure load ratio)

D) discharge load by untreated population = untreated population × source unit

E) Discharge load due to lack of manure treatment facility = {(Population type × source unit × manure load ratio) + {Sewage treatment area confluence population × source unit × manure load ratio × (1- sewage treatment area purification facility treatment rate / 100 )} + {Sewage treatment area purification facility population × source unit × manure load ratio × (1-treatment rate of untreated area purification plant / 100)}-Input amount of treatment facility

F) discharge load of manure treatment facility = discharge amount of manure treatment facility × discharge concentration

However, in case of linkage treatment to sewage terminal treatment plant, linkage throughput is excluded from discharge load.

③ Discharge load calculation module

The emission load estimation module should be developed based on Visual Basic to provide users with an environment for easy estimation and update of pollutant loads. In the event of changes in watershed source status and renewal at the unit level, the discharge load should be recalculated. The pollutant load calculation method preferably uses the existing environmental load method.

Next, the emission loads calculated on the screen for calculating the daily pollution loads are automatically updated to subwatershed and subwatershed units. An example of providing a formula on the screen to help the user understand the discharge load calculation is shown in FIG. 9.

I. Industry

① Calculation formula for generating load

Generation loads in the industry are estimated by source size and source unit.

◎ Industry Generated Load = Σ (Wastewater Generation × Unit of Generation)

② Calculation formula of discharge load

The industrial discharge load is estimated by the sum of the discharge loads from the direct discharge from the wastewater discharge facility, from the discharge through the wastewater treatment plant, and from the landfill leachate treatment facility.

A) direct discharge from a wastewater discharge facility;

◎ If there is actual value of treatment facility = discharge amount of wastewater discharge facility × discharge concentration

◎ When there is no actual value of treatment facility = discharge amount of wastewater discharge facility × wastewater discharge facility discharge limit

B) In case of discharge through wastewater treatment facility = discharge amount of wastewater treatment facility × discharge concentration

C) In case of landfill leachate treatment facility = leachate treatment plant discharge × discharge concentration

③ Discharge load calculation module

Next, the discharge load calculated by the industrial pollution load calculation screen was automatically updated in sub-basin and subwatershed units (see FIG. 10).

All. Livestock discharge load

The load generated by livestock raising should be calculated by multiplying the number of heads raised by livestock and the source unit by livestock type. In addition, the discharge load is divided into sales staff and non-storage sources, and the non-storage discharge load is calculated by monthly allocation. The monthly runoff rate was applied to the land use system's discussed runoff rate, and it was calculated using the monthly rate of effective rainfall (more than 10mm / day) by city and load ratio of fertilizer (May ~ August).

① Calculation formula for generating load

◎ Livestock manure incidence = Breeding head number by breeding type ×

◎ Livestock wastewater generation amount = breeding head number by livestock type × livestock wastewater generation unit

◎ Livestock manure generation load = number of breeding heads by livestock type × livestock manure generation load unit

② Calculation formula of discharge load

A) Sales staff and non-storage discharge loads

◎ Clerk discharge load = Breeding head number by livestock type and manure treatment type ×

◎ Non-point source discharge load = Breeding head by type of livestock and manure treatment × Non-point source discharge unit

B) Monthly discharge load

Monthly discharge loads were calculated by classifying the treated and untreated areas.

◎ Monthly discharge load in treatment zone = monthly non-point source discharge + store source discharge-livestock wastewater treatment plant inflow load

◎ Monthly discharge load in untreated zone = Monthly non-sales staff emissions + Sales staff emissions

All). Monthly total discharge load

◎ Monthly total discharge load = discharge load in treatment zone + discharge load in untreated zone + discharge load in livestock wastewater treatment plant

la. Farm discharge load

The pollutant loads of farms are calculated and classified into three types according to the form, such as cages, run-off meals, and challenge farms.

◎ Generation load (monthly) = farm area × source unit by farm type

◎ discharge load = generated load

(2) Nonpoint Pollution Load

end. Land use discharge load

Emission load of land use is classified into five categories such as full, answer, forest, land, and others according to the land use type, and the emission load is calculated by multiplying the area and runoff rate for each category.

◎ Generated load = area of origin × area by category

◎ Discharge Load (Monthly) = Discharge Load × Monthly, Land Runoff Rate

I. Calculate Monthly Runoff Rate

◎ Monthly monthly outflow rate

Discussion The outflow rate depends on the use of fertilizer. In consideration of this, the calculation is divided into fertilizers with high fertilizer use and fertilizers with low fertilizer use.

(Equation 1)

(Equation 2)

Here, A _i and B _i is the effective rain for i month of land load outflow facility, P _ai and P _bi is fertilizing group and a bicyclic non for i month of fertilization group and a bicyclic non, P _a and P _b are fertilizing group ( May-August) and non-fertilizer (September-April) are the total effective rainfall, with α being the load weight of the fertilizer, the value being 0.8.

◎ Monthly outflow rate of before, forest, land and other

(Equation 3)

Here, R _i is a land load outflow facility of i January, P _i is the month of rainfall in May i, P refers to the year the total rainfall.

(3) Estimation of delivered load and inflow concentration module

The delivery load is calculated by subwatershed, li and copper units using the midnight coefficient and the delivery distance to the pollutant discharge load, and the inflow concentration is calculated by dividing the delivery load by the flow rate (Fig. 11).

If the pollutant load for each subwatershed is automatically calculated, the monthly delivery load can be estimated using the runoff rate. Figure 12 shows the interface for the calculation of the monthly delivery load for each subwatershed.

1) Estimation of delivered load

end. Calculation of the rate of delivery

The definition of delivery rate has already been described in the concept of pollution loads, and will be omitted here. The rate of delivery is a function of watershed size, bed situation, delivery time, and flow rate. Among the effects of watershed scale, the rate of delivery is represented by the exponential function of distance, which makes it relatively easy to evaluate. The method of calculating the delivery rate is shown in Equation 4 below.

(Equation 4)

Where f is the delivery rate, k is the midnight coefficient, and x is the delivery distance. Judging distance means the distance from the center of each Redong to the exit.

I. Calculating Midnight Coefficient

① Definition of the midnight coefficient

Pollutants introduced into the river are self-cleaning, reducing the amount of pollution. Self-cleaning means a decrease in the amount of pollutants contained in river water. Although pollutants decrease in time due to biological degradation, sedimentation, and adsorption in rivers, lakes, and waters, the midnight coefficient used as a measure of self-cleaning indicates the rate coefficient of the decrease. It appears as a distribution.

② Midnight coefficient calculation formula

The midnight coefficient calculation formula is the same as Equation 5-7.

◎ BOD Midnight Coefficient: (Eq. 5)

◎ TN midnight coefficient: (Equation 6)

TP Midnight Coefficient: (Eq. 7)

Where k _BOD , k _TN , and k _TP are midnight coefficients for each water quality item, A is subwatershed area (ha), Q is subwatershed runoff (㎥ / sec), and F is subwatershed shape factor.

③ watershed shape factor

Dividing the basin area by the euro extension of the basin is called the average width of the basin. Even in the same average width, there are elongated rivers and wider rivers. The average width of this watershed divided by the extension of the main stream is called Horton 's watershed shape factor, which is used as an indicator of watershed characteristics. The watershed shape factor can be estimated using Equation 8.

(Eq. 8)

Where F is the basin shape factor, A is the subwatershed area (km), and T is the extension of the subwatershed main stream (km).

④ Estimation of the delivery load using the delivery rate

Estimating the delivered load in the relevant water area by multiplying the generation and discharge load by the original unit method considering the delivery distance, and calculating it by dividing it into subwatershed with water quality and subwatershed without water quality.

(A) Subwatershed with water quality measurement

For subwatersheds with water quality measurements, the runoff for each subwatershed is multiplied by the measured water quality.

◎ Deliver Load = Runoff by Subwatershed × Actual Water Quality (BOD, T-N, T-P)

(B) Subwatersheds without water quality measurements

For subwatersheds without water quality measurements, the delivered load should be estimated using the following procedure.

◎ Calculate the midnight coefficient by subwatershed month by water quality item.

◎ Calculate the overload load by subwatershed by using the rate of delivery considering the distance by subwatershed (Equation 9).

(Eq. 9)

Where L is the delivered load (kg / day), L ₀ is the discharge load (kg / day), Is the rate of delivery, k is the monthly coefficient for water quality and monthly, and ℓ is the distance of delivery.

◎ Convert the delivered load by subwatershed again.

2) Inflow concentration calculation

The inflow concentration of the stream can be obtained by dividing the delivered load by the outflow.

◎ Calculation of subwatershed without water quality measurement

For subwatersheds without water quality measurements, the following calculation procedure was used.

-Inflow concentration is obtained by dividing the delivered load by subwatershed by outflow.

-Use the water quality measurements of subwatersheds with actual values to determine the ratios.

-Determine the concentrations of nitrogen and phosphorus by using the concentrations of BOD, T-N, and T-P and the rate of death.

-The calculation of DO is based on the formula.

10)

-Water temperature is properly assumed using actual measurements.

<GIS-based water quality modeling support system>

1. Linkage between water quality model and GIS

In the present invention, the QUALKO model, which is a modified model of QUAL2E, was used as a river water quality prediction model, and the DYNHYD5 model and the EUTRO5 model, which are subprograms of the WASP5 model, were used as the water quality prediction model.

These models generate input files for system modeling in connection with GIS, and the water quality prediction results are converted into GIS data format so that they can be plotted according to user's requirements. Water quality modeling support process used in the present invention can be largely divided into three steps, that is, pre- and post-treatment process using GIS, river and lake water quality modeling process (Fig. 13). In the pretreatment stage, model input data are generated by calculating the pollutant and flow loads by subwatersheds, the division into calculable compartments required for modeling streams and lakes, and the boundary concentrations that flow into each compartment. In the water quality modeling step, each river and lake water quality modeling is performed. Finally, in the post-processing step, the modeling results are converted into GIS data and processed and expressed in graphs or charts.

14 is a flow chart of a water quality modeling support system developed for efficient water quality management of freshwater lakes in the present invention. The water quality modeling support system identifies the effects of pollutant loads spilled from point sources and nonpoint sources on the stream and lake water quality, and provides environmental experts with information to establish water quality management plans. It can help in determining the allowable load of various pollutant sources to achieve this.

(1) QUALKO River Water Quality Modeling

The GIS can be used to implement a river water quality modeling system in which river water quality models are organically integrated, for effective management of river water quality and efficient use of river water quality models. The river water quality model was used by the National Institute of Environmental Research (QUALKO (Joe Soo et al., 1999)), which modified the QUAL2E (US EPA, 1985) model to suit domestic streams and appeals. Input data for the target watershed are automatically generated by estimating contaminant loads and inflow concentrations from the investigated point and nonpoint sources. The implementation stage of the developed river water quality modeling system is divided into three stages: pre-treatment stage, model execution stage, and post-treatment stage. First, in the preprocessing step, the generated input data is grouped into a plurality so that the data can be conveniently created, edited, and stored. Second, the QUALKO model is executed at the model execution stage. The QUALKO model predicts daily average water quality using average values such as flow rate, pollutant load and water temperature. Third, in the post-processing step, the results of model execution can be confirmed with graphs and attribute data using GIS. The river water quality modeling system according to the present invention removes the complexity of the existing DOS-based modeling so that the river water quality can be more efficiently managed and improved to bring more improved effects in water quality management in the appeal.

end. Pretreatment stage

By automating the generation of I / O files necessary for water quality simulation, users can be provided with a more convenient environment when modeling. To do this, the module automatically generates the model execution input file and converts the inflow concentration value stored in the GIS data format into an input file suitable for the QUALKO model. 15 shows data processing in the module.

QUALKO model inputs can be grouped into 24 (see Table 2 below), for example, to create and edit input data. Detailed information for each data group can be obtained. Model input data is managed for each data group, and the generation and editing of input data design a module to more conveniently process the elements necessary for model execution in consideration of the user interface (FIG. 16).

<Table 2> Model Input Data Group

NO. Data group No. Data group 123456789101112 Title Data Program Control Algae, N, P, Light Factor Temp. Correction Factor DATA TYPE2Flow DataComp, Element DataHydraulics DataCOEF of BOD and DOCOEF of N and PCOEF of ALG / OTHERInitial Condition (1) 131415161718192021222324 Initial Condition (2) Increment Inflow (1) Increment Inflow (2) Stream Junction DataHeadwater Data (1) Headwater Data (2) Point Load (1) Point Load (2) DAM ReaerationDownstream Boundary (1) Downstream Boundary (2) Climatology Data

I. Modeling run phase

The procedure for modeling using the model input data generated in the preprocessing step is as follows. The first step is to enter the output file to run the QUALKO model. Input file is output file (* .out), schematic file (* .plt), and model execution result is divided into two files and the result is saved. The output file (* .out) is divided into eight parts. First, the input data and the amount of sunshine and meteorological data that are determined or calculated before starting the full-scale water quality simulation are output. Second, the predicted water quality results for each water quality item to be modeled are output. Third, the results of mathematical calculations such as flow rate, flow velocity, flow time, depth of water, lower width, volume, lower bed area, cross section, and diffusion coefficient are output. Fourth, the values of the response coefficients are summarized. Fifth, the simulation results for the 15 water quality items that are the water quality prediction results are summarized. Sixth, the algae data such as Chl-a concentration, algae growth-dissipation rate, sedimentation rate, NH ₃ preference, algae itself and algae growth rate (μ) are determined. Seventh, estimates of dissolved oxygen data such as water temperature, saturated dissolved oxygen concentration, DO concentration, DO unsaturation concentration, DAM reaeration (mg / L), and nitrification inhibition coefficient (KNITRIF) due to low concentration DO Output. Eighth, a BOD-DO float is output. The second step is to run the actual model. The QUALKO model is executed using the inputted output and schematic file.

All. Post-Processing Step

After modeling, the result file is outputted * .out and * .plt file. Of these, * .out file consists of document type file about model execution result, and * .plt file records model execution result by result item. do. The file descriptor is recorded in the file header, and the result contents are sequentially output in the content part.

In order to process the modeling results, we extracted the elements related to the water quality of the stream, excluding the model control elements, the geometrical elements of the stream, and the meteorological elements from the configuration items of the output file. In order to check the extracted water quality items intuitively for each reach, it is integrated with GIS and processed in the form of graph and attribute data. 17 is graph data, model execution result graph, and attribute data of a watershed in which a model is executed.

(2) WASP5 Lake Water Modeling

WASP5 is implemented in two stages: pre-processor and post-processor. The preprocessing step is to input various conditions and factors required for the model, and the postprocessing step can select and view only necessary information according to the user's request after executing the model. The preprocessing step in WASP5 is preferably composed of 13 input windows (dataset, system, segment, parameter, constant, Xchange, flow, load, boundary, time function, print interval, time step, validate input). ). After running the model by inputting the required values in each input window, select water quality items, hydraulic information of segments, segments, etc. in the post-processing step to select the output contents.

end. Pretreatment stage

The water quality items entered at the pretreatment stage are as follows.

① Data Set

The dataset controls the overall model system, including the type of model execution, simulation period, and linkage with other programs. In the description, define an input file and select EUTRO5 for the Model Type. In Comments, you can enter important information about this data, and enter the model's simulation period in Data and Times. The arguments for the execution of the EUTRO5 model used here are as follows:

◎ Target Basin Setting: Target Basin and Subwatershed Area

◎ River cross section (B), characteristic length (B), partition volume (C)

◎ Velocity, depth coefficient (C): water depth, flow rate, flow rate observation data

◎ Flow rate and flow rate (D): Daily or monthly average data

◎ Concentration by water quality item (E): Daily or monthly average data

◎ Pollution Load (F): Daily or monthly average pollution load

◎ Response coefficient (H): EPA suggested or measured value, coefficient of other researcher

◎ Environmental Data (I): Daily or monthly water temperature, insolation, sunshine rate. Wind speed, photodissipation factor, zooplankton, salinity, temperature, surface coverage

② Systems

There are 8 water quality items to simulate, and select Simulated from the options. In the density section, enter the density for each water quality item, and the maximum and minimum concentrations next to it can be left as they are within the model itself.

③ Segments

The content of the physical terrain data for the segment. First, create segments of the total number of segments using inserts in the segments, and input the volume, flow rate, and depth of each segment. The parameters are input to each segment by selecting parameters having spatially varying characteristics with respect to the water body. Initial concentration represents the initial concentration of each segment and enters the concentration at the start of the simulation. Fraction Dissolved represents the dissolution rate in water for each water quality item

④ Parameter

A parameter is a parameter whose characteristics change spatially with respect to a water body. Select the variable you want to use from the total of 14 parameters and the scale factor is applied to the whole body.

⑤ Constants

Constant is the response coefficient used in the model. Select and enter each response coefficient for eight water quality items. The temperature correction reaction coefficient is left at the initial value. The maximum and minimum values of the response coefficient are automatically entered in the model, and the response coefficient is entered in the value. Adjust the response coefficients of each water quality item so that it is within the scope of the manual so that the actual value is approached.

⑥ Exchanges

X-change refers to exchange in a water body and is divided into diffusion between water layers and diffusion between pore waters. Diffusion between layers is divided into horizontal diffusion and vertical diffusion, and diffusion coefficients are input differently. Select the exchange fields you want to simulate in the Exchange Fields and use the inserts in the Function to create as many functions as the number of adjacent segments where the exchange takes place. Segment pairs select the segments in which the exchange takes place and enter the cross-sectional area and characteristic length between each segment. In time / value pairs, the diffusion coefficients between segments in which exchange takes place are entered over time. The diffusion coefficient changes with time in a distinct linear time function.

⑦ Flows

The flow represents the flow of water and there are six flow fields. In the flow field, select the flow field you want to simulate. The function uses inserts to generate the number of all interfaces with flow inflow and outflow in the body of water. Segment pairs represent the paths through which the flow rate flows in and out. The boundary with outflow and inflow is selected as the boundary and the segments are selected in the flow order of the flow rate in the water body. Must start with a boundary and end with a boundary. The time / belu pair can be entered in consideration of the change over time during the flow in and out of each interface.

⑧ Other

Other inputs to the model include the Print Interval and Time Step. The print interval may determine the output time during the simulation period so that all the output data is output by the output time, and the type step inputs the simulation time interval performed by the model during the simulation period.

I. Model execution step

After checking the input data error of the model, if there is no problem, the model is executed. The execution of the model simulates water quality items by interaction of input data (FIG. 18).

All. Post Processing Step

In order to query the results of the appeal modeling, if you select two conditions of water quality items and the desired month, the watershed will be shown by segment and a graph will be shown (FIG. 19). If you want to search by figure, you can select it.

<Implementation system of pollution load and water quality model>

For systematic water quality management of freshwater lakes, GIS, pollution load estimation system and water quality model should be organically linked to facilitate the management of watershed pollution and water quality prediction. In the present invention, for the organic linkage between the pollution load estimation system and the water quality model, the modeling process is performed by analyzing the input items and the result items of the model and establishing the interconnection loop.

1. Composition of batch processing system

The batch processing system of the pollution load estimation system and the water quality model is composed of a GIS, a pollution source database, a pollution load estimation system, and a water quality model (FIG. 20). These components are modeled through the linkage of each item using shared files of input and output files for mutual linkage. The batch processing system provides a user interface base so that the overall modeling process can be performed conveniently and efficiently, thereby providing access by shared files internally and GUI-based convenience externally. As a result, it is possible to provide a more convenient modeling environment for users who lack expertise in modeling.

2. Flowchart of batch processing system

As a result of analyzing the input / output files for batch processing of the modeling, the necessary items for each modeling process are summarized in detail, and the linking process is illustrated in FIG. 21.

The GIS provides data on water quality and hydrologic models such as slope, area, elevation, and location, which are the characteristics of the watershed, and the hydrological model is modeled based on the watershed characteristics, and the runoff and water intake resulting from the hydrologic model Linked to the model (QUALKO). The stream model is modeled based on runoff, intake and pollutant load data to calculate the boundary concentration. The calculated boundary concentration values are input to the appeal model WASP5, so that final water quality prediction is performed.

3. Integration of modeling by linked system

(1) Linkage with QUALKO model through pollution load calculation

1) Estimation of Pollutant Load and Judging Concentration Using GIS Pollution Source DB

Pollutant loads were calculated in subwatersheds and re-dong units using the midnight coefficient and the dead distance to the pollutant discharge loads calculated by the raw unit calculation method using the GIS source database. In order to convert this data into the input data of the QUALKO model, which is a river water quality model, the flow concentration was obtained by dividing the flow load by the runoff.

2) The link between the flow rate and the QUALKO model

end. Data group division for linkage

The monthly concentration values for each subwatershed are outputted for each concentration level calculated by the module. In order to link these concentration values to the input file of the QUALKO model, the location of the file to be input must be accurately determined by analyzing the input data of the QUALKO model. The calculated concentration values are entered in the Point Load data group of the QUALKO model's input data group. The following is a file input / output screen in which a concentration value is associated with a QUALKO model input file (FIG. 22).

I. Linkage algorithm

The programmatic linkage algorithm for linking the concentration value, which is the result of the concentration calculation, to the point load data group of the input data of the QUALKO model, is completed by providing data to the input data group of the QUALKO model from reading the result of the concentration calculation result. The process of linking crude concentration and QUALKO model is as follows.

◎ Read the result of the concentration calculation.

◎ Store monthly lunar concentration value.

◎ Read input data of QUALKO model.

All data groups except QUALKO's HYDRULICS data groups are stored in a buffer.

◎ Save the stored monthly flow concentration value in the data entry position of REACH input data of Point Load data group.

◎ Save the input file of QUALKO model.

3) QUALKO and WASP5 model linkage

end. Data group division for linkage

Boundary concentrations (NH3, NO3, CHL-A, DO, PO4, NON, NOP, CBOD, etc.), which are QUALKO modeling results, are output for each REACH. In order to link these boundary concentration results to the input file of the WASP5 model, the position of the result data of the QUALKO model and the position of the boundary concentration to be input of the WASP5 input data must be accurately identified. The boundary concentration data group, which is a QUALKO modeling result, is entered in data group E of the input data group of the WASP5 model. The following is a file input / output screen in which a QUALKO modeling result boundary concentration data group file is linked to a WASP5 model input file (FIG. 23).

I. Linkage algorithm

The programming linkage algorithm for linking the QUALKO modeling result to the data group E of the input data of the WASP5 model is completed by providing data to the input data group of the WASP5 model from reading the QUALKO model result file. The linkage process between the hydrological model and the QUALKO model is as follows.

◎ Read QUALKO modeling result file.

◎ Store data by water quality items of boundary concentration data.

Read the input data of the WASP5 model.

◎ All data groups except data group E of WASP5 model are stored in buffer.

◎ Save the saved boundary concentration data in the boundary concentration data input position of the input data by segment of data group E.

◎ Save input file of WASP5 model.

The water quality modeling method according to the present invention can provide a systematic and efficient management method for freshwater lake management by predicting the pollutant load in the watershed by using raw units for accurate prediction of freshwater lake water pollution. In addition, the water quality modeling method according to the present invention can provide convenience to the water quality prediction by integrating the GIS and the water quality prediction model.

As described above, although described with reference to a preferred embodiment of the present invention, those skilled in the art will be variously modified and modified within the scope of the present invention without departing from the spirit and scope of the present invention described in the claims below. It will be appreciated that it can be changed.

1 is a flow chart of the main data of the water quality modeling system according to the present invention

Figure 2 is a detailed flow chart of the discharge load and the dead load calculation according to the present invention

Figure 3 is a flow chart of river and lake water quality modeling according to the present invention

Figure 4 is a process of calculating the pollution load according to the present invention

5 is a flow chart of the point and non-point source discharge load calculation module according to the present invention

Figure 6 is a livestock system discharge load calculation module flow chart according to the present invention

7 is a flow chart of the discharge load calculation for each sub-basin according to the present invention

8 is an exemplary view of the discharge load calculation initial screen according to the present invention

Figure 9 is an illustration of a screen showing a formula for calculating the pollution load of the living system according to the present invention

10 is an exemplary view showing a screen showing an industrial discharge load calculation formula and the like according to the present invention.

11 is a calculation module for delivering load according to the present invention.

12 is an exemplary view of an interface for calculating the dead load according to the present invention.

13 is a water quality modeling research procedure and flow chart according to the present invention

14 is a flow chart for performing water quality modeling according to the present invention

15 is a process diagram of data processing inside a module according to the present invention.

16 is an input data editing module according to the present invention

Figure 17 is a modeling result figure and attribute data according to the present invention

18 is a view illustrating an execution screen of a model according to the present invention.

19 is an exemplary view of the appeal modeling query result screen according to the present invention

20 is a block diagram of a batch processing system according to the present invention.

21 is a flowchart of a batch processing system according to the present invention.

22 is an exemplary view showing the link between the flow rate and the QUALKO model according to the present invention

23 is an exemplary view showing the linkage between the QUALKO model and the WASP5 model.

Claims (5)

Calculating the generation load through a predetermined calculation process using the source size and source unit information as input information and storing the resultant value; Calculating a discharge load through a predetermined calculation process using the calculated generated load and discharge rate as input information and storing a corresponding result value: passing through a predetermined calculation process using the calculated discharge load and a delivery rate as input information Calculating the overload load and storing a corresponding result; Calculating the inflow concentration through a predetermined calculation process using the outflow amount and the calculated overload load as a result of the watershed balance model and storing the corresponding result value: Performing the stream quality model using the inflow concentration as input information Calculating a boundary concentration value and storing a corresponding result value; And performing an appeal water quality model using the boundary concentration value as input information. The QUALKO model is used to predict the daily average water quality using the average value of the flow rate, the pollutant load and the water temperature for the execution of the stream balance model, and the WASP5 model is used for the lake water quality model. The performing of the QUALKO model may include converting an inflow concentration value stored in a GIS data format into an input file suitable for the QUALKO model; Generating an output file by performing a QUALKO model; And converting the output file into a GIS data format. The execution step of the WASP5 model includes inputting conditions and factors required for model execution, and after performing the model, selecting and outputting only the required information according to the user's request, and calculating the monthly outflow rate A _i and B _i are the land load runoff rates for fertilizers and fertilizers in January, P _ai and P _bi are effective rainfall for fertilizers and fertilizers for i- months, and P _a and P _b are fertilizers and fertilizers. Is the total effective rainfall, and α is the load weight of the fertilizer, The monthly runoff rate is calculated according to the difference between the use of fertilizer and the fertilizer used for fertilizer management. Based water quality modeling method. delete delete delete delete