CN116384630B - Method for estimating agricultural non-point source pollution load in intersection area based on mechanism model - Google Patents
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Abstract
The invention discloses a method for estimating agricultural non-point source pollution load of a junction area based on a mechanism model, which is implemented according to the following steps: step 1, selecting a typical intersection area by acquiring basic data required by building a model; step 2, completing SWAT model construction; step 3, using a hydrologic and water quality verification model with a long time sequence to enable the model to reach an evaluation standard; and 4, calculating to obtain the agricultural non-point source pollution load of the typical intersection area. The invention solves the problems that the hydrologic station and the water quality detection section in the prior art are less in the situation that the hydrologic station and the water quality detection section are arranged in the river junction area, and a great deal of time, financial resources and manpower are consumed when the field monitoring is carried out.
Description
Technical Field
The invention belongs to the technical field of measurement technology and model simulation, and particularly relates to a method for estimating agricultural non-point source pollution load in an intersection area based on a mechanism model.
Background
Due to unreasonable agricultural production activities, agricultural non-point source pollutants mainly represented by nitrogen and phosphorus are brought. Contaminants are transported from soil to waters in a wide range, widely dispersed, low concentration form by osmotic diffusion and migration. If the pollutant load exceeds the self-cleaning capacity of the water body, the problem of water quality degradation is unavoidable, and thus the problem of water ecological environment is caused. River is the most common commonly accepted body of water for both surface source pollution and point source pollution. In recent years, the pollution control of the point source is fierce, and the threat degree of the non-point source pollution to the water environment gradually exceeds the point source pollution.
The source area of agricultural non-point source pollutant is wide, the migration path and the conversion mechanism are complex, and the quantitative work of agricultural non-point source pollutant is difficult. Empirical statistical methods and model simulation methods are often applied to the study of agricultural non-point source pollutants, and both methods can be used as quantitative studies of agricultural non-point source pollutants in a study area with a river basin. The application of a mechanism model under the combination of a series of external conditions such as high-precision underlying surface data, meteorological factors, agricultural production activities and the like and the physicochemical properties of non-point source pollutants greatly promotes the research progress of agricultural non-point source pollution. However, when agricultural non-point source pollution is studied by using a mechanism model, water quality concentration at the outlet of a river basin and pollutant load in the river basin are often focused, and transmission migration and interception of the non-point source pollutant in the river are ignored in an important area on the river reach. The river junction area where the tributaries merge into the main stream is a severely neglected object of investigation. The intersection area is an important area of agricultural production, and compared with the main flow, the intersection area has small branch flow water quantity, weak dilution effect and bearing capacity on pollutants, can carry high-concentration pollutants into the main flow, and is easier to cause agricultural non-point source pollution and influence the ecological health of water in the intersection area. The intersection area relates to the intersection of two rivers, has complex hydraulic characteristics, and agricultural non-point source pollutants which are used as solutes in a water body migrate to the downstream along with the water flow, and are related to water tangent when being flushed to the river bank or deposited on the river bottom. The current hydrologic station and water quality detection section are arranged in the river junction area in a small number, and a large amount of time, financial resources and manpower are consumed if on-site monitoring is performed. Moreover, under the background that the Chinese river networks are dense, the intersection areas are numerous and the agricultural non-point source pollution forms are more severe, the method for researching the agricultural non-point source pollution in the intersection areas based on the mechanism model is realized, so that not only is the upstream non-point source pollution conditions of main flows and tributaries known, but also the condition of the agricultural non-point source pollution input in the downstream of the river after receiving the tributary water bodies can be mastered, and the method is favorable for understanding the agricultural non-point source pollution in a deeper layer and multiple aspects.
Disclosure of Invention
The invention aims to provide a method for estimating agricultural non-point source pollution load in a junction area based on a mechanism model, which solves the problems that in the prior art, hydrologic stations and water quality detection sections are less in the situation that the water stations and the water quality detection sections are arranged in the junction area of a river, and a large amount of time, financial resources and manpower are consumed in the field monitoring.
The method for estimating agricultural non-point source pollution load in the intersection area based on the mechanism model is implemented according to the following steps:
step 1, selecting a typical intersection area by acquiring basic data required by building a model;
step 2, completing SWAT model construction;
step 3, using a hydrologic and water quality verification model with a long time sequence to enable the model to reach an evaluation standard;
and 4, calculating to obtain the agricultural non-point source pollution load of the typical intersection area.
The present invention is also characterized in that,
in the step 1, the basic data is divided into spatial data and attribute data, wherein the spatial data is an elevation model DEM with digital gradient and slope direction comprising terrain elements, a land utilization distribution map for land in a river basin and a soil type spatial distribution map, the three are subjected to superposition processing under the condition of the same projection coordinate system, and the gradient, the land utilization mode and the soil characteristic factors are divided into combinations with the same flow, flow velocity and hydrologic characteristics of sand content.
In the step 1, the attribute data comprise meteorological data, soil physical attribute data and agricultural production activities, wherein the meteorological data comprise precipitation, temperature, wind speed, relative humidity and radiation, the soil physical attribute data comprise soil effective water content and PH, and the agricultural production activities are the settings of agricultural management measures including crop types, sowing time, fertilization types and fertilization time for utilizing the land in the flow area as the cultivated land.
The step 2 is specifically as follows:
the method comprises the steps of utilizing acquired space data and attribute data to establish a soil and water assessment model SWAT of a typical river junction region, selecting a modeling region comprising a main stream and a tributary part before river junction and a section of river after junction, firstly inputting an acquired typical river basin digital elevation model DEM into a soil and water assessment model SWAT plug-in Arcmap software, utilizing an edition manual tool to respectively set a hydrological station, a water quality monitoring section and a main and sub-stream part which is 1-3 km close to a junction as a sub-river basin outlet, setting the main stream after junction as a river basin outlet on 1-3 km, dividing the junction into three sub-river basins with relatively small areas through the steps, sequentially inputting the acquired land utilization space and attribute data, the soil space and attribute data, weather data and agricultural management measure data, further completing the establishment of the SWAT model, setting a two-year preheating period after the establishment, operating the SWAT model, outputting a file and storing the file as a river output format.
The step 3 is specifically implemented according to the following steps:
and measuring a hydrologic sequence and a water quality sequence which are continuous for a long time and are used for calibrating and verifying a model result, wherein data required by the time sequence are a radial flow value and an ammonia nitrogen value respectively.
The step 3 is specifically as follows:
calibrating one site at a time; firstly, calibrating water quantity and then water quality; firstly calibrating the upstream and then calibrating the downstream, firstly calibrating the whole model, then selecting the correlation coefficient R between the model simulation value and the actual measurement value in the checking period and the verification period of the calculation model according to the calculation formulas of the correlation coefficient and the Nash coefficient 2 And Nash coefficient E ns As an evaluation criterion, the correlation coefficient R 2 Representing the consistency of the variation trend of the analog value and the actual measurement value, and the correlation coefficient R 2 The larger the consistency, the better the Nash coefficient E ns Representing the overall efficiency of the model simulation, nash coefficient E ns The higher the applicability of the proving model is, the better the calculation formulas of the correlation coefficient and the Nash coefficient are respectively:
wherein: q (Q) o t And Q s t Respectively a t-th runoff measured value and an analog value,and->The average value of the actual runoffs measured in the simulation time period and the average value of the simulation are respectively;
when the water quantity and the water quality meet the following conditions during the checking and verification period: correlation coefficient R 2 Exceeding 0.6 and Nash coefficient E ns At no less than 0.5, parameters indicating calibration adjustments enable the SWAT model to simulate in a selected basin.
The step 4 is specifically as follows:
after checking and verifying, according to the type of the parameter, replacing the original default value of the model by using the calibrated and adjusted parameter in the SWAT model, setting a two-year preheating period after replacing the parameter, operating the SWAT model, outputting a river file, and storing the river file in an output format, wherein the model output party is a simulation result applicable to a river basin. In the simulation result, the continuous month ammonia nitrogen load of the output of the three sub-watershed of the intersection area and the upstream sub-watershed of the non-intersection front part of the main flow and the branch flow of the intersection area is found, and the ammonia nitrogen load of the three sub-watershed of the intersection area is calculated according to the relation that the upstream pollutant is received at the downstream, so that the agricultural non-point source pollution condition of the intersection area in different time periods can be represented, and the model basis is provided for the watershed management and the water environment treatment.
The method has the beneficial effects that the agricultural non-point source pollution load estimation method for the intersection area based on the mechanism model is characterized in that when SWAT is established, outlets of the sub-watershed are arranged at the upstream and downstream of the intersection area, and the separated sub-watershed can represent the water collecting area of a typical intersection area; the research area is mainly selected to be concentrated in the intersection area with complex hydraulic characteristics of the river reach, the method realizes the research and analysis of agricultural non-point source pollution load conditions of the river intersection area where the tributaries are converged into the main flow, can help to quantitatively solve the complex problem of the agricultural non-point source pollution load of the intersection area, relieves the serious situation of the pollution load at the downstream of the intersection area, improves the ecological quality of water, and simultaneously saves the cost and time of on-site monitoring. The method is suitable for researching agricultural non-point source pollution in the junction area where the branch flows are converged into the main flow.
Drawings
FIG. 1 is a diagram of geographic locations of intersection areas of a river and a Wei river;
FIG. 2 is a diagram of weather stations in the intersection of a river and a Wei river;
FIG. 3 is a graph of results of a lunar runoff simulation at the saline land and Ma Duwang land;
FIG. 4 is a graph of results of a lunar runoff simulation of Qianyang and Wushan stations;
FIG. 5 is a graph of simulated results of month runoff from Heiyu kou station and Linjicun station;
FIG. 6 is a graph of Qin An station month runoff simulation results;
FIG. 7 is a graph of simulation results of ammonia nitrogen for the back month of the Tianshui cattle;
FIG. 8 is a graph of simulated results of ammonia nitrogen loading in the sub-watershed of the intersection zone.
Detailed Description
The invention will be described in detail below with reference to the drawings and the detailed description.
The invention discloses a method for estimating agricultural non-point source pollution load in a junction area based on a mechanism model, which is implemented according to the following steps:
step 1, selecting a typical intersection area by acquiring basic data required by building a model;
in the step 1, main basic data required by a model built in a typical intersection area are obtained, the basic data are divided into space data and attribute data, the space data are an elevation model DEM with digital gradient and slope direction comprising terrain elements, a land utilization distribution diagram for land in a river basin and a soil type space distribution diagram, the three are subjected to superposition processing under the condition of the same projection coordinate system, and the gradient, the land utilization mode and soil characteristic factors are divided into combinations with the same flow, flow velocity and sand content hydrologic characteristics.
In the step 1, the attribute data comprise meteorological data, soil physical attribute data and agricultural production activities, wherein the meteorological data comprise precipitation, temperature, wind speed, relative humidity and radiation, the soil physical attribute data comprise soil effective water content and PH, and the agricultural production activities are the settings of agricultural management measures including crop types, sowing time, fertilization types and fertilization time for utilizing the land in the flow area as the cultivated land.
Step 2, completing SWAT model construction;
the step 2 is specifically as follows:
using the acquired spatial data and attribute data, a soil and water assessment model SWAT (Soil and Water Assessment Tool) of a typical river junction is created. Because the upstream river flow and water quality can influence the downstream, a modeling area is selected to comprise a main flow and a tributary part before river intersection and a section of river after intersection, firstly, an obtained typical river basin digital elevation model DEM is input into a soil and water assessment model SWAT plug-in Arcmap software, an edition manual tool is utilized to respectively set a hydrological station, a water quality monitoring section and a main and branch flow position close to an intersection of 1-3 km to be a sub-river basin outlet, the main flow of 1-3 km after intersection is set to be a river basin outlet, the intersection can be divided into three sub-river basins with relatively small areas through the steps, the sub-river basins are water collecting areas of the intersection, then, the obtained land utilization space and attribute data, soil space and attribute data, meteorological data and agricultural management measure data are sequentially input, and then, after the establishment of the SWAT model is completed, the SWAT model is set to be operated for two years, and the river file is output to be stored as an output format.
Step 3, using a hydrologic and water quality verification model with a long time sequence to enable the model to reach an evaluation standard;
the step 3 is specifically implemented according to the following steps:
and measuring a hydrologic sequence and a water quality sequence which are continuous for a long time and are used for calibrating and verifying a model result, wherein data required by the time sequence are a radial flow value and an ammonia nitrogen value respectively.
The step 3 is specifically as follows:
after the SWAT model is operated, the output of the model needs to be checked and verified based on the research thought of the hydrologic water quality model, so as to determine the applicability of the model. The simulation accuracy and reliability of the SWAT model are verified and evaluated based on SUFI-2 (Sequential Uncertainty Fitting version 2) algorithm. The method selects a single-station calibration mode with higher precision, so as to determine the model parameters in the selected drainage basin. The basic principle is as follows: calibrating one site at a time; firstly, calibrating water quantity and then water quality; firstly calibrating the upstream and then calibrating the downstream, firstly calibrating the whole model, then selecting the correlation coefficient R between the model simulation value and the actual measurement value in the checking period and the verification period of the calculation model according to the calculation formulas of the correlation coefficient and the Nash coefficient 2 And Nash coefficient E ns As an evaluation criterion, the correlation coefficient R 2 Representing the consistency of the variation trend of the analog value and the actual measurement value, and the correlation coefficient R 2 The larger the consistency, the better the Nash coefficient E ns Representing the overall efficiency of the model simulation, nash coefficient E ns The higher the applicability of the proving model is, the better the calculation formulas of the correlation coefficient and the Nash coefficient are respectively:
wherein: q (Q) o t And Q s t Respectively a t-th runoff measured value and an analog value,and->The average value of the actual runoffs measured in the simulation time period and the average value of the simulation are respectively;
when the water quantity and the water quality meet the following conditions during the checking and verification period: correlation coefficient R 2 Exceeding 0.6 and Nash coefficient E ns At no less than 0.5, parameters indicating that calibration adjustments enable the SWAT model to simulate in a selected basin;
and 4, calculating to obtain the agricultural non-point source pollution load of the typical intersection area.
After checking and verifying, according to the type of the parameter, replacing the original default value of the model by using the calibrated and adjusted parameter in the SWAT model, setting a two-year preheating period after replacing the parameter, operating the SWAT model, and outputting a river file (output. Rch). At this time, the model output side is a simulation result of the applicable and drainage basin. In the simulation result, the continuous month ammonia nitrogen load of the output of the three sub-watershed of the intersection area and the upstream sub-watershed of the non-intersection front part of the main flow and the branch flow of the intersection area is found, and the ammonia nitrogen load of the three sub-watershed of the intersection area is calculated according to the relation that the upstream pollutant is received at the downstream, so that the agricultural non-point source pollution condition of the intersection area in different time periods can be represented, and the model basis is provided for the watershed management and the water environment treatment.
Examples
Wei river is the first major branch of yellow river, and Wei river basin is the most important grain producing area such as corn and wheat in northwest of China. Whether water in a Wei river is used directly or indirectly, the water quality of the Wei river can influence the growth condition of coastal crops and the life quality of people more or less. The river of (2) is remitted into the Wei river in the western An city of Shaanxi province, and western An is regarded as a new first-line city of China, so that the population is dense, and the water environment quality is more important to water resources and water environment management staff. Therefore, the method selects the typical intersection region (shown in figure 1) of the stop river and the stop river, estimates the ammonia nitrogen load value of the agricultural non-point source pollution of the intersection region, and is convenient for enhancing the knowledge of the agricultural non-point source pollution of the stop river intersection region. The specific operation steps are as follows:
a digital elevation database, a soil database, a land use database, and a weather database necessary for constructing the SWAT model. Wherein the digital elevation data, soil and land utilization spatial distribution map must use a unified projection coordinate system, the method adopts a 'WGS_1984_UTM_zone_49N' projection coordinate system according to the geographic position of the research area. The method selects daily value data of 25 national-level ground weather stations (shown in figure 2), including precipitation, temperature, wind speed, sunshine hours and relative humidity. The data input into the model are precipitation, maximum and minimum temperatures, average wind speed, relative humidity and radiation. The radiation is calculated by the geographical latitude and sunlight hours of the site. The agricultural management measures of the method are finally determined through field investigation and reference documents.
And after automatically dividing the river flow direction and the outlet of the sub-river basin according to the elevation data graph with the projection coordinates, adding the positions of the hydrologic station and the water quality monitoring section as the outlet of the sub-river basin. In the method, sub-drainage basin outlets are respectively arranged at the main and branch flows which are 1-3 km close to the junction, and drainage basin outlets are arranged on the 1-3 km main and branch flows after junction, so that the water collecting area of the junction area is determined. And secondly, dividing a sub-drainage basin and a minimum hydrologic unit by using a SWAT model obtained by superposing the digital elevation data and the soil and the land, inputting the manufactured meteorological data and formulated agricultural management measures, finally setting a model 3-year preheating period, operating the model and outputting a result.
And calibrating the parameters of the SWAT simulation result according to the SUFI-2 algorithm. The method adopts a one-station and one-calibration mode, firstly utilizes the runoff quantity obtained by the hydrologic station to calibrate the hydrologic process of the research area, and adjusts the downstream parameters after fixing the upstream parameters if the upstream parameters are adjusted. In this example, a total of 7 hydrologic sites and 1 day buffalo back surface water monitoring sections were selected from the group consisting of Wushan, qin An, qianyang, lin Gucun, xianyang, ma Duwang and Heiyou. As shown in FIG. 1, the station of the salt sun is Yu Wushan, qin An, the station of the Qianyang and the station of the forest home villageDownstream, the calibration of the water volume at the salt-sun station is performed by calibrating the Wushan, qianyang, qin An and after the forest village. The ammonia nitrogen data obtained are concentration values, but in SWAT model calibration, load values are needed for parameter adjustment. Therefore, parameters after calibration are replaced to the SWAT model, the parameters are rerun to obtain the flow value of the outlet of the sub-basin where the dorsum of the tendrils is located, and the monthly average ammonia nitrogen load value of the dorsum of the tendrils is obtained through the relation among the flow, the concentration and the load, so that the parameters of the data of the water quality of the basin are adjusted and calibrated. When the water quality parameters are calibrated, the adjusted parameters related to the flow are fixed, and the SUFI-2 algorithm is used for calibrating the water quality parameters. Up to the Nash coefficient Ens and the correlation coefficient R of the simulation value and the actual measurement value of each hydrological station and the water quality monitoring section 2 The combination of the optimal parameter value and the optimal parameter can be confirmed.
And after the final model checking and verification are passed, the adjusted parameters are replaced back to the SWAT model, and the model is restarted, and the result is output. The ammonia nitrogen load of the intersection area is the sum of the load of the outlet of the flow field after intersection minus the inflow of the main branch before intersection.
Through the above process, the simulated runoff amount and the actual runoff amount process are shown in fig. 3, fig. 4, fig. 5 and fig. 6. Nash coefficients Ens and correlation coefficients R of each hydrologic station in calibration period and verification period 2 The minimum requirement standard is far exceeded, so that the model has excellent simulation capability in the hydrologic process, and the applicability in the streaming domain can be well reflected. Especially, the model output result of the salt-sun site is optimal, and the Nash coefficient Ens and the correlation coefficient R of the month runoff simulation value and the actual measurement value of the calibration period 2 Are 0.90, and the Nash coefficient Ens and the correlation coefficient R during verification 2 And also reaches 0.88. As shown in FIG. 7, the simulation result value of the ammonia nitrogen load model of the water quality monitoring section of the longhorn dorsum is shown. The ammonia nitrogen load output result of the longhorn dorsum model of the water quality monitoring section is determined, nash coefficient Ens and correlation coefficient R of month-average ammonia nitrogen analog value and actual measurement value in calibration period 2 0.64 and 0.61 respectively, and the Nash coefficient Ens and correlation coefficient of the verification period are 0.65 and 0.6 respectively, and the calibration period and the verification period are bothMeets the minimum standard
And (3) replacing original parameters in the SWAT model with parameters after water quality calibration and verification meet the conditions, setting a two-year preheating period, then operating the SWAT model, and obtaining an output result in a river file (output. Rch). The month-average ammonia nitrogen load value input and output values of the sub-watershed where the front-crossing branch flow, the front-crossing main flow and the rear-crossing main flow are located are found, and the annual ammonia nitrogen values of the three sub-watershed where the crossing area is located can be obtained through calculation, as shown in fig. 8.
The method is applied to the intersection region of the dam and the Wei river, the ammonia nitrogen load of the intersection region for many years is measured, and the pollutant load of the intersection region can be estimated, so that the non-point source pollution of the important region on the river reach is deeply known. The method can simply and rapidly acquire the condition of the surface source of the junction area for the pollution of the agricultural surface source with a more serious form, and has positive pushing effect on the treatment of the water environment.
Claims (1)
1. The method for estimating agricultural non-point source pollution load in the intersection area based on the mechanism model is characterized by comprising the following steps:
step 1, selecting a typical intersection area by acquiring basic data required by building a model;
in the step 1, the basic data is divided into spatial data and attribute data, wherein the spatial data is an elevation model DEM with digital gradient and slope-direction-included terrain elements, a land utilization distribution map used by the land in the river basin and a soil type spatial distribution map, the three are subjected to superposition processing under the condition of the same projection coordinate system, and the gradient, the land utilization mode and the soil characteristic factors are divided into combinations with the same flow, flow velocity and sand content hydrologic characteristics;
in the step 1, the attribute data includes meteorological data, soil physical attribute data, and agricultural production activities, wherein the meteorological data includes precipitation, temperature, wind speed, relative humidity and radiation, the soil physical attribute data includes soil effective water content and PH, and the agricultural production activities are settings of agricultural management measures including crop types, sowing time, fertilization types and fertilization time for land utilization as cultivated land in a flow area;
step 2, completing SWAT model construction;
the step 2 specifically comprises the following steps:
the method comprises the steps that a modeling area is selected by using acquired space data and attribute data to establish a soil and water assessment model SWAT of a typical river junction area, wherein the modeling area comprises a main stream and a tributary part before river junction and a section of river after junction, firstly, an acquired typical river basin digital elevation model DEM is input into a soil and water assessment model SWAT plug-in Arcmap software, a hydrological station, a water quality monitoring section and a main and branch stream part which is 1-3 km close to a junction are respectively set as sub-river basin outlets by using an edition manual tool, then, the junction 1-3 km main stream is set as a river basin outlet, the junction area can be divided into three sub-river basins with relatively small areas through the steps, the sub-river basins are water collecting areas of the junction area, then, the acquired land utilization space and attribute data, the soil space and attribute data, weather data and agricultural management measure data are sequentially input, and the establishment of the SWAT model is completed, after establishment of the SWAT model is completed, the SWAT model is run for two years, and the output files are stored as river output formats;
step 3, using a hydrologic and water quality verification model with a long time sequence to enable the model to reach an evaluation standard;
the step 3 is specifically implemented according to the following steps:
measuring a long-time and continuous hydrologic sequence and a water quality sequence of a calibration and verification model result, wherein data required by the time sequence are a radial flow value and an ammonia nitrogen value respectively;
the step 3 specifically comprises the following steps:
calibrating one site at a time; firstly, calibrating water quantity and then water quality; firstly calibrating the upstream and then calibrating the downstream, firstly calibrating the whole model, then selecting the correlation coefficient R between the model simulation value and the actual measurement value in the checking period and the verification period of the calculation model according to the calculation formulas of the correlation coefficient and the Nash coefficient 2 And Nash coefficient E ns As an evaluation criterion, the correlation coefficient R 2 Representative simulationConsistency of value and actual measurement value change trend, and correlation coefficient R 2 The larger the consistency, the better the Nash coefficient E ns Representing the overall efficiency of the model simulation, nash coefficient E ns The higher the applicability of the proving model is, the better the calculation formulas of the correlation coefficient and the Nash coefficient are respectively:
wherein: q (Q) o t And Q s t Respectively a t-th runoff measured value and an analog value,and->The average value of the actual runoffs measured in the simulation time period and the average value of the simulation are respectively;
when the water quantity and the water quality meet the following conditions during the checking and verification period: correlation coefficient R 2 Exceeding 0.6 and Nash coefficient E ns At no less than 0.5, parameters indicating that calibration adjustments enable the SWAT model to simulate in a selected basin;
step 4, obtaining agricultural non-point source pollution load of a typical intersection area through calculation;
the step 4 specifically comprises the following steps:
after checking and verifying, according to the type of the parameters, replacing original default values of the model by using calibrated and adjusted parameters in the SWAT model, after replacing the parameters, setting a two-year preheating period, operating the SWAT model, outputting river files, storing the format as output.
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