A prediction method for runoff pollutant removal by a buffer zone vegetation-soil system

Abstract

The present application discloses a prediction method for the removal of runoff pollutants by a buffer zone vegetation-soil system, including: monitoring the dynamic rainfall of rainfall events, the inflow runoff volume and runoff concentration of the buffer zone, the outlet runoff volume and runoff concentration, and the outlet seepage concentration; through sunny day soil moisture monitoring, analyzing the relationship between soil moisture content and the previous sunny time, predicting the initial soil moisture content before rain under the target rainfall; constructing a runoff prediction model to predict the runoff and seepage under the target rainfall; constructing a runoff removal concentration and seepage removal concentration prediction model, combining the runoff and seepage, predicting the buffer zone runoff removal load and seepage removal load under the target rainfall. The input parameters of this method are easy to obtain, and the calculation is simple and convenient. The prediction results of runoff reduction, seepage, runoff removal load, and seepage removal load of the vegetation buffer zone under different rainfall conditions can be quickly obtained, providing technical support for the effective design of farmland runoff pollution engineering measures.

Description

Technical Field

[0001] The present application relates to the technical field of agricultural pollution control, and in particular to a method for predicting the removal of runoff pollutants by a buffer zone vegetation-soil system. Background Art

[0002] Agricultural non-point source pollution is characterized by high randomness, wide distribution, large scale of harm, and great difficulty in monitoring, evaluation, and control. Its governance difficulty is far greater than that of point source pollution. Most agricultural non-point source pollution is carried by rainfall runoff, which is transferred from land to water bodies. Buffer zones are the last line of defense for farmland runoff to enter water bodies and are generally considered to be the most economical and effective means of controlling farmland runoff pollution. Especially in plain river network areas, the terrain is flat, the buffer zone is wide, the slope is small, and the plants grow densely. The rainfall runoff in this area is fully blocked and the speed is reduced, and pollutants can be effectively intercepted.

[0003] Under different rainfall conditions, there are differences in the moisture and pollution removal loads of the buffer zone, such as vegetation interception, soil infiltration, surface runoff, etc. during runoff generation. The interception efficiency of vegetation-soil on agricultural runoff and non-point source pollution is still unclear, which brings difficulties to the refined evaluation of non-point source pollution interception in buffer zones under the influence of multiple factors and multiple objective requirements.

[0004] Although some scholars at home and abroad have done some research on the vegetation-soil hydraulic connection in the buffer zone, the hydrodynamic process between the subsurface layer and surface water, and the quantitative calculation of runoff and seepage water, due to the complex characteristics of rainfall changes, there are differences in the quantitative distribution of water and pollution load in the process of surface runoff interception by vegetation in the buffer zone and soil infiltration. It is not easy to quantitatively measure the soil moisture and its infiltration in the buffer zone in the long term.

[0005] my country's water environment improvement work has been taken seriously and carried out rapidly, and has achieved phased and local results. With the interception and treatment of point sources, my country's farmland non-point source pollution has become one of the main sources of water pollution. With the improvement of the country's requirements for water environment pollution prevention and control, new requirements have been put forward for the assessment of non-point source pollution reduction loads in relevant assessment indicators. Therefore, how to effectively predict the vegetation-soil system in the buffer zone of the plain river network area to remove runoff pollution, to reveal the quantitative distribution mechanism of water and pollution load in different rainfall types and different vegetation buffer zones, and to refine and quantitatively calculate the reduction of non-point source pollution in the buffer zone under different rainfall conditions, is a technical problem that technicians in this field need to solve urgently. Summary of the invention

[0006] In view of this, the purpose of the present invention is to provide a prediction method for the removal of runoff pollutants by the vegetation-soil system in the buffer zone, which can quickly obtain the prediction results of the runoff inflow, runoff outflow, seepage, runoff removal load, and seepage removal load of the vegetation buffer zone under different rainfall conditions, and provide technical support for the effective design of farmland runoff pollution engineering measures. The specific scheme is as follows:

[0007] A method for predicting the removal of runoff pollutants by a buffer zone vegetation-soil system, comprising:

[0008] Monitor the dynamic rainfall of rainfall events, and count the rainfall, peak rainfall, average rainfall intensity, rainfall duration, and previous sunny days of rainfall events;

[0009] Continuously monitor soil moisture content every day, establish a prediction model of soil moisture content and previous sunny day time based on the relationship between soil moisture content and previous sunny day time, and obtain soil saturated moisture content;

[0010] Monitor the inflow runoff volume and runoff concentration, outlet runoff volume and runoff concentration, and outlet seepage concentration of the buffer zone, and calculate the runoff removal concentration and seepage removal concentration;

[0011] According to the monitored inflow runoff, statistical rainfall, and the catchment area of ​​farmland with inflow in the buffer zone, an inflow runoff prediction model is constructed;

[0012] According to the monitored inflow runoff concentration, statistical rainfall, rainfall duration, rainfall peak and average rainfall intensity, an inflow runoff concentration prediction model is constructed;

[0013] Based on the monitored inflow runoff, outlet runoff, obtained soil saturation moisture content, initial soil moisture content before rain, vegetation interception water, statistical rainfall, average rainfall intensity and rainfall duration, a forecast model for outlet runoff and seepage volume is constructed;

[0014] According to the calculated runoff removal concentration, statistical rainfall peak value and rainfall duration, a runoff removal concentration prediction model is constructed;

[0015] Based on the calculated seepage removal concentration and the monitored inflow runoff concentration, a seepage removal concentration prediction model is constructed;

[0016] The runoff, seepage, runoff removal load and seepage removal load under target rainfall are predicted by the inflow runoff prediction model, the inflow runoff concentration prediction model, the outlet runoff and seepage prediction model, the runoff removal concentration prediction model and the seepage removal concentration prediction model.

[0017] Preferably, in the above-mentioned prediction method for removing runoff pollutants by the buffer zone vegetation-soil system provided in an embodiment of the present invention, the inflow runoff prediction model, the inflow runoff concentration prediction model, the outlet runoff, the seepage prediction model, the runoff removal concentration prediction model, and the seepage removal concentration prediction model are used to predict the runoff, seepage, runoff removal load, and seepage removal load under target rainfall, including:

[0018] According to the rainfall of the target rainfall and the farmland catchment area of ​​the region, the runoff inflow under the target rainfall is predicted by the inflow runoff prediction model;

[0019] According to the rainfall amount, rainfall duration, rainfall peak value, and average rainfall intensity of the target rainfall, the runoff inflow concentration under the target rainfall is predicted by the inflow runoff concentration prediction model;

[0020] According to the previous sunny time of the target rainfall, rainfall duration, rainfall intensity, rainfall amount, and vegetation interception water volume, the outlet runoff and seepage amount prediction model is used to predict the outlet runoff and seepage amount under the target rainfall;

[0021] According to the rainfall duration and rainfall peak of the target rainfall, the runoff removal concentration of the target rainfall is predicted by the runoff removal concentration prediction model, and the runoff removal load under the target rainfall is calculated in combination with the outlet runoff volume predicted by the target rainfall;

[0022] According to the runoff inflow concentration of the target rainfall, the seepage removal concentration of the target rainfall is predicted by the seepage removal concentration prediction model, and the seepage removal load under the target rainfall is calculated in combination with the outlet seepage volume predicted by the target rainfall.

[0023] Preferably, in the above-mentioned prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the dynamic rainfall amount of the monitoring rainfall event, and the statistical rainfall amount, rainfall peak value, average rainfall intensity, rainfall duration, and previous sunny days of the rainfall event include:

[0024] The dynamic rainfall of rainfall events is obtained according to the monitoring of rainfall meteorological stations, and the rainfall, peak rainfall, average rainfall intensity, rainfall duration, and number of sunny days in the previous period of rainfall events are counted; each rainfall event is separated by a period of no rainfall greater than 6 hours;

[0025] The continuous monitoring of soil moisture content every day, establishing a prediction model of soil moisture content and previous sunny day time according to the relationship between soil moisture content and previous sunny day time, and obtaining soil saturated moisture content, includes:

[0026] A soil parameter meter is used to continuously monitor the soil moisture content every day, and a scatter plot of soil moisture content and the previous sunny time is made. The soil saturated moisture content is read, and the first relationship is fitted to determine the coefficient. After successful verification, it is determined as a prediction model for soil moisture content before rain, thereby predicting the initial soil water requirement before rain under the target rainfall based on the previous number of sunny days.

[0027] Preferably, in the above-mentioned prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided in the embodiment of the present invention, the monitoring of the inflow runoff volume and runoff concentration, outlet runoff volume and runoff concentration, and outlet seepage concentration of the buffer zone includes:

[0028] The inflow flow rate of the buffer zone is monitored by a flow meter;

[0029] The right-angle triangular weir is used to monitor the outlet runoff of the buffer zone, the water discharge time and water level of the triangular weir are recorded, and the outlet runoff of the buffer zone is obtained according to the area of ​​the buffer zone;

[0030] The runoff collector is used to dynamically collect inflow and outlet runoff water samples, and mixed samples are prepared according to the runoff volume ratio in the dynamic time period of the runoff process. The average concentration of pollutants in the inflow and outlet runoff events during rainfall events is obtained through detection and analysis;

[0031] A PVC pipe underflow is buried at the end of the buffer zone. After the rainfall, a Beagle tube is placed in the PVC pipe to collect seepage water samples. The seepage water samples are mixed according to the average volume method, and the event average concentration of the outlet seepage pollutants is obtained through detection and analysis.

[0032] Preferably, in the above-mentioned method for predicting the removal of runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the calculation of the runoff removal concentration and the seepage removal concentration includes:

[0033] Calculate the runoff removal concentration based on the monitored inflow runoff concentration and outlet runoff concentration;

[0034] The seepage removal concentration is calculated based on the detected inflow runoff concentration and outlet seepage concentration.

[0035] Preferably, in the above-mentioned prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the inflow runoff prediction model is constructed according to the monitored inflow runoff, statistical rainfall, and farmland catchment area, including:

[0036] The second relationship is determined based on the relationship between the monitored inflow and runoff and the statistical rainfall and farmland catchment area;

[0037] Establish a set of equations based on monitoring data and find the optimal solution for the coefficients;

[0038] After successful verification, the second relationship with the optimal solution of the coefficients is determined as the inflow runoff prediction model.

[0039] Preferably, in the above-mentioned prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the inflow runoff concentration prediction model is constructed according to the monitored inflow runoff concentration, statistical rainfall, rainfall duration, rainfall peak value and average rainfall intensity, including:

[0040] The third relationship is determined based on the relationship between the monitored inflow runoff concentration and the statistical rainfall, rainfall duration, rainfall peak value, and average rainfall intensity;

[0041] Establish a set of equations based on monitoring data and find the optimal solution for the coefficients;

[0042] After successful verification, the third relationship with the optimal solution of the coefficients is determined as the inflow runoff concentration prediction model.

[0043] Preferably, in the above-mentioned prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the outlet runoff prediction model is constructed according to the monitored inflow runoff, outlet runoff, vegetation interception water volume, obtained soil saturated moisture content, statistical rainfall, average rainfall intensity and rainfall duration, including:

[0044] The amount of water intercepted by vegetation was obtained according to the vegetation biomass by consulting the manual or literature;

[0045] The amount of soil infiltration water is obtained based on the obtained soil saturated water content, soil water content before rain, statistical rainfall, average rainfall intensity and rainfall duration;

[0046] According to the relationship between the monitored inflow flow and the obtained vegetation interception water and soil infiltration water, the outlet flow can be obtained, and the fourth relationship is established;

[0047] Establish a set of equations based on monitoring data and find the optimal solution for the coefficients;

[0048] After successful verification, the fourth relationship with the optimal solution of the coefficients is determined as the outlet flow rate prediction model.

[0049] Preferably, in the above-mentioned method for predicting the removal of runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the runoff removal concentration prediction model is constructed according to the calculated runoff removal concentration, the statistical rainfall peak value and the rainfall duration, including:

[0050] SPSS software was used to conduct regression analysis on the calculated runoff removal concentration and the statistical rainfall peak value, and the calculated runoff removal concentration and the statistical rainfall duration, to determine the best fitting curve, on this basis, the fifth relationship was determined;

[0051] Establishing a set of equations based on the monitoring data to find the optimal solution of the coefficients of the fifth relationship;

[0052] The fifth relationship with the optimal solution of the coefficients is successfully verified and determined as the runoff removal concentration prediction model.

[0053] Preferably, in the above-mentioned method for predicting the removal of runoff pollutants by the vegetation-soil system in the buffer zone provided by the embodiment of the present invention, the construction of a seepage removal concentration prediction model based on the calculated seepage removal concentration and the monitored inflow runoff concentration includes:

[0054] SPSS software was used to perform regression analysis on the calculated seepage removal concentration and the monitored inflow runoff concentration to determine the best fitting curve, on this basis, the sixth relationship was determined;

[0055] Establishing a set of equations based on the monitoring data to find the optimal solution of the coefficients of the sixth relationship;

[0056] The sixth relationship with the optimal solution of the coefficients is successfully verified and determined as the seepage removal concentration prediction model.

[0057] It can be seen from the above technical scheme that the prediction method for the removal of runoff pollutants by the vegetation-soil system in a buffer zone provided by the present invention includes: monitoring the dynamic rainfall of rainfall events, and counting the rainfall, rainfall peak, average rainfall intensity, rainfall duration, and previous sunny days of rainfall events; continuously monitoring the soil moisture content every day, and establishing a prediction model for the soil moisture content and the previous sunny day time based on the relationship between the soil moisture content and the previous sunny day time, and obtaining the saturated soil moisture content; monitoring the inflow runoff, outlet runoff, inlet and outlet runoff concentrations, and outlet seepage concentration of the buffer zone, and calculating the runoff removal concentration and the seepage removal concentration; and calculating the runoff removal concentration based on the monitored inflow runoff, total precipitation, and total runoff concentration. Based on the rainfall and the catchment area of ​​the buffer zone inflow, a runoff inflow prediction model is constructed; based on the monitored inflow runoff concentration, rainfall, rainfall duration, rainfall peak value, and average rainfall intensity, a runoff inflow concentration prediction model is constructed; based on the monitored inflow runoff, outlet runoff, rainfall, rainfall duration, average rainfall intensity, soil saturated moisture content, initial soil moisture content before rain, and vegetation interception water, an outlet runoff and infiltration prediction model is constructed; based on the calculated runoff removal concentration, rainfall peak value, and rainfall duration, a runoff removal concentration prediction model is constructed; based on the calculated seepage removal concentration and the monitored inflow runoff concentration, a seepage removal concentration model is constructed. On this basis, the buffer zone runoff, seepage, runoff removal load, and seepage removal load under the target rainfall event are predicted.

[0058] The present invention constructs a runoff inflow prediction model, a runoff inflow concentration prediction model, an outlet runoff flow, an infiltration volume prediction model, a runoff removal concentration prediction model, and a seepage removal concentration model through the vegetation-soil parameters of the buffer zone and the on-site farmland runoff inflow, infiltration, runoff and other data under different rainfall conditions. The input parameters are rainfall characteristic factors and vegetation interception water volume parameters, which are relatively easy to obtain and convenient to calculate. The complex and dynamic flow and concentration calculations are simplified, and the pre-rain initial soil moisture content of the vegetation buffer zone under different rainfall conditions, as well as the runoff reduction amount of the vegetation buffer zone on farmland runoff, soil infiltration, runoff removal concentration and load, seepage removal concentration and load and other multi-factor quantitative data can be quickly obtained, so as to provide technical support for evaluating the ecological environmental efficiency of the buffer zone under the influence of multiple factors and multiple target requirements, and effectively designing farmland runoff pollution engineering measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0060] Figure 1 A flow chart of a method for predicting the removal of runoff pollutants by a buffer zone vegetation-soil system provided by an embodiment of the present invention;

[0061] Figure 2 A schematic diagram of a soil plane including a buffer zone and a PVC submersible pipe provided in an embodiment of the present invention;

[0062] Figure 3 A schematic diagram of a soil profile including a buffer zone and a PVC submersible pipe provided in an embodiment of the present invention;

[0063] Figure 4 A scatter diagram of soil moisture content and previous sunny time provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] The present invention provides a method for predicting the removal of runoff pollutants by a buffer zone vegetation-soil system, such as Figure 1 As shown, the following steps are included:

[0066] S101. Monitor the dynamic rainfall of rainfall events, and count the rainfall amount, rainfall peak, average rainfall intensity, rainfall duration, and previous sunny days of rainfall events.

[0067] In practical applications, before executing step S101, on-site survey and data collection can be performed. First, the characteristics of the buffer zone area can be investigated, which can include the length of the buffer zone, the area of ​​the buffer zone, and the area of ​​farmland receiving runoff from the buffer zone, which can be determined through on-site measurements or based on remote sensing interpretation data. Figure 2 and Figure 3 As shown, a runoff collection pipe is set at the inlet of the buffer zone to monitor the runoff inflow; a right-angle triangular weir B is set at the outlet to monitor the outlet runoff; a PVC submerged flow pipe A is buried at the end of the buffer zone to collect seepage water samples, L is the confluence length, and W is the confluence width.

[0068] When executing step S101, determine the rainfall occurrence time in advance according to the weather forecast and arrange field tests. To ensure the number of samples for analysis, the monitored rainfall events cover typical rainfall events with a cumulative frequency of more than 98% in the region. According to the dynamic rainfall data of the rain gauge station (the rainfall data frequency can be 1-5min), the rainfall interval of more than 6h is the separation of two rainfalls. The rainfall amount P (mm), rainfall peak H (mm / h), average rainfall intensity M (mm / h), rainfall duration t (h), and previous sunny time t of each rainfall are counted. s (h).

[0069] S102. Continuously monitor the soil moisture content every day, establish a prediction model of the soil moisture content and the previous sunny day time based on the relationship between the soil moisture content and the previous sunny day time, and obtain the soil saturated moisture content.

[0070] Specifically, soil parameter meters were used to monitor soil moisture for at least 2 months (one rainy month and one dry month, with measurements taken once in the morning, noon and evening each day). Soil moisture was negatively correlated with the previous sunny hours. As the sunny hours increased, the soil moisture content eventually approached the wilting point. A scatter plot of soil moisture and previous sunny hours was made using EXCEL, and the soil saturated moisture content (W) was read from the curve. s ), and fit the soil moisture content (W0) and the previous sunny time t s (hours, h) relationship (i.e., the first relationship), determine the coefficient, and verify. When predicting the target rainfall, the soil moisture model can be used to predict the initial soil moisture content before the rain according to the previous sunny time.

[0071] W0=F(t s ) (1)

[0072] S103. Monitor the inflow runoff volume and runoff concentration, outlet runoff volume and runoff concentration, and outlet seepage concentration of the buffer zone, and calculate the runoff removal concentration and seepage removal concentration.

[0073] It should be noted that the above concentrations in the present invention are all event mean concentrations (Event Mean Concentration, EMC) of rainfall events.

[0074] In specific implementation, in the above-mentioned prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided in the embodiment of the present invention, step S103 monitors the inflow runoff and outlet runoff of the buffer zone, which may specifically include:

[0075] During each rainfall period, according to the dynamic flow observation data q(m 3 / min) and rainfall dynamic duration t i (min), calculate the inflow Q into the buffer zone under each rainfall event in (m 3 ), the formula is as follows:

[0076]

[0077] During each rainfall period, a right-angle triangular weir is used to monitor the runoff at the outlet of the buffer zone. The observation starts from the start of runoff generation. The observation frequency can be 2 minutes. The water discharge time and water level of the triangular weir are recorded. According to the area of ​​the buffer zone, the runoff Q at the outlet of the buffer zone is obtained. out (m 3 );

[0078]

[0079] Among them, Q out,t is the outlet flow rate at the end of the buffer zone at time t, m 3 ;H t is the weir crest water level at time t, cm; Δt is the time period between time t and time t+1, s.

[0080] In specific implementation, in the prediction method for removing runoff pollutants by the vegetation-soil system in the buffer zone provided in an embodiment of the present invention, step S103 monitors the inflow runoff concentration, outlet runoff concentration, and outlet seepage concentration of the buffer zone, which may specifically include: using a runoff collector to dynamically take inflow and outlet runoff water samples, configuring a mixed sample according to the runoff volume ratio in a dynamic time period during the runoff process, and detecting and analyzing to obtain the rainfall event average concentration of inflow and outlet runoff event pollutants; burying a PVC pipe undercurrent at the end of the buffer zone, and taking seepage water samples after the rainfall ends using a Beagle tube placed in the PVC pipe, mixing the seepage water samples according to the average volume method, and detecting and analyzing to obtain the event average concentration of outlet seepage pollutants.

[0081] Specifically, the runoff water samples are collected by runoff collectors. The sampling frequency is determined according to the dynamic process of runoff generation. Samples are taken every 5 minutes within 15 minutes, every 15 minutes within 15-30 minutes, every 15 minutes within 30-60 minutes, and every 30 minutes after 60 minutes. Each time, an equal volume of water sample is taken, and the water volume is determined according to the actual pollutants to be analyzed, generally 1-2L. Mixed samples are prepared according to the runoff volume ratio during the runoff process, stored in a refrigerated insulation box at 4°C, and sent to the laboratory for pollutant analysis.

[0082] The runoff mixed sample configuration ratio is calculated using the following formula (4):

[0083]

[0084] Among them, t' is the sampling time, r is the volume ratio of the runoff water sample to the mixed sample at that time, R t' is the runoff from t' to the last sampling time, mm.

[0085] A PVC submerged flow pipe with a diameter of about 100 mm is set at the end of the buffer zone. The buried depth is determined according to the regional groundwater level, generally 50 cm below the local groundwater level during the dry season. Holes with a diameter of 5 mm are opened around the pipe wall, and gravel is filled around the pipe. A bailer pipe is used to collect dynamic water samples in the submerged flow pipe (once every 10-15 minutes). Each time, an equal volume of water sample is taken, with a water volume of 1-2L. The water volume is determined according to the number of pollutant indicators to be analyzed, and is stored in a refrigerated insulation box at 4°C and sent to the laboratory. The seepage water samples are mixed according to the average volume method.

[0086] The runoff removal concentration is calculated using the following formula (5):

[0087] C r,c =C in,EMC -C out,EMC (5)

[0088] Among them, C in,EMC , C out,EMC Average concentration of influent and effluent runoff, mg·L -1 ; C r,c is the average concentration of runoff calculated in the buffer zone under a single rainfall event, mg·L -1 .

[0089] The seepage removal concentration is calculated using the following formula (6):

[0090] C i,c =C in,EMC -C out,i,EMC (6)

[0091] Among them, C out,i,EMCis the event average concentration of seepage, mg·L -1 ; C i,c is the average concentration of the buffer zone calculated under a single rainfall event, mg·L -1 .

[0092] S104. Construct an inflow runoff prediction model based on the monitored inflow runoff, statistical rainfall, and the catchment area of ​​farmland with inflow in the buffer zone.

[0093] Specifically, based on the monitored inflow flow, statistical rainfall P and farmland catchment area A f , constructing an inflow runoff prediction model, which may include:

[0094] SPSS software was used to conduct regression analysis on inflow runoff and rainfall to determine the best fitting curve, i.e., the second relationship;

[0095] After successful verification, the second relational expression with the optimal solution of the coefficients is determined as the prediction model for the inlet flow rate.

[0096]

[0097] S105. Construct an inflow runoff concentration prediction model based on the monitored inflow runoff concentration, statistical rainfall, rainfall duration, rainfall peak value and average rainfall intensity.

[0098] Specifically, based on the monitored inflow runoff concentration, statistical rainfall, rainfall duration, rainfall peak value and average rainfall intensity, an inflow runoff concentration prediction model is constructed, which may include:

[0099] SPSS software was used to conduct regression analysis on inflow runoff concentration and rainfall, rainfall duration, rainfall peak value, and average rainfall intensity to determine the best fitting curve, i.e., the third relationship.

[0100] After successful verification, the third relationship with the optimal solution of the coefficients was determined as the prediction model for the inlet runoff concentration.

[0101] W in =F(P,t,M,H)·A f (8)

[0102] S106. Construct an outlet runoff and seepage prediction model based on the monitored inflow runoff, outlet runoff, obtained soil saturation moisture content, initial soil moisture content before rain, vegetation interception water, statistical rainfall, average rainfall intensity and rainfall duration.

[0103] In specific implementation, step S106 can construct an outlet runoff and seepage prediction model according to the water balance principle at the inlet and outlet.

[0104] The outlet seepage flow is obtained by subtracting the vegetation interception water volume, the outlet runoff Q from the monitored inflow runoff and the rainfall received by the buffer zone out as follows:

[0105]

[0106] where E is the vegetation intercepted water volume, in mm, obtained by referring to manuals or relevant literature based on the biomass of the vegetation buffer zone; I out is the outlet seepage flow, in m 3 .

[0107] After the water infiltration amount under the buffer zone saturates the soil water content, further infiltration occurs, which is related to the stable infiltration coefficient and the infiltration time. The infiltration depth F (mm) is expressed by the following formula:

[0108] F = a(W s - W0) + f c ·t (10)

[0109] where f c is the stable infiltration coefficient, in mm / h, a is the soil water demand coefficient, and a > 0, 0 < f < 1, t is the infiltration time, characterized by the rainfall duration.

[0110] Rainfall intensity is another factor affecting the infiltration amount. Rainfall with a short duration and high intensity is not conducive to infiltration, while rainfall with a long duration and low intensity is conducive to infiltration. Rainfall amount is also an important factor affecting the seepage flow. Formula (10) is further modified based on the average rainfall intensity and rainfall amount. On this basis, the outlet runoff of the buffer zone is predicted according to the water balance:

[0111]

[0112] where A is the area of the buffer zone, in m 2 , 1000 is the conversion coefficient. According to the outlet runoff Q out of the monitored rainfall events, the inlet runoff Q in , the rainfall duration t, the soil saturation water content W s , the number of sunny days t s before the rainfall, and the vegetation intercepted water volume E, a system of equations is established to solve the optimal solution of the coefficients;

[0113] After the fourth relation with the optimal solution of the coefficients is successfully verified, it is determined as the prediction model of the outlet runoff and seepage flow.

[0114] S107. According to the calculated runoff removal concentration, the statistically obtained rainfall peak value and rainfall duration, construct a runoff removal concentration prediction model.

[0115] It should be noted that for a certain vegetation and a buffer zone of a certain area, the runoff removal concentration is related to the inlet concentration and outlet concentration of the buffer zone. The inlet concentration is related to the rainfall peak value. The greater the rainfall peak value, the greater the concentration of surface runoff pollutants that wash the farmland. The buffer zone outlet concentration is related to the runoff duration. The longer the runoff duration, the more vegetation and soil intercept the runoff pollutants passing through the buffer zone. In specific implementation, in the above-mentioned buffer zone vegetation-soil system prediction method for removing runoff pollutants provided in the embodiment of the present invention, step S107 constructs a runoff removal concentration prediction model based on the calculated runoff removal concentration, the statistical rainfall peak value and rainfall duration, which may include:

[0116] SPSS software was used to conduct regression analysis on runoff removal concentration and rainfall peak value, runoff removal concentration and rainfall duration, and determine the best fitting curve. On this basis, the fifth relationship was determined.

[0117] C r,c =F1(M)+F2(t) (12)

[0118] Establish a set of equations based on monitoring data and find the optimal solution of the last coefficient;

[0119] After successful verification, the relationship with the optimal solution of the coefficients was determined as the runoff removal concentration prediction model.

[0120] S108. Construct a seepage removal concentration prediction model based on the calculated seepage removal concentration and the monitored inflow runoff concentration.

[0121] It should be noted that the seepage removal concentration is mainly related to the runoff inflow concentration, the length, width and soil properties of the buffer zone. For a certain vegetation and a certain area of ​​the buffer zone, the seepage removal concentration is mainly related to the runoff inflow concentration. In specific implementation, in the above-mentioned buffer zone vegetation-soil system prediction method for removing runoff pollutants provided in the embodiment of the present invention, step S108 constructs a seepage removal concentration prediction model based on the calculated seepage removal concentration and the monitored inflow runoff concentration, which may include:

[0122] SPSS software was used to conduct regression analysis on the seepage removal concentration and the inflow runoff concentration to determine the best fitting curve, on this basis, the sixth relationship was determined;

[0123] C i,c =F3(C in ) (13)

[0124] Establish a set of equations based on monitoring data to find the optimal solution for the coefficients of the sixth relationship;

[0125] The sixth relational expression with the optimal solution of coefficients was successfully verified and determined as the seepage removal concentration prediction model.

[0126] S109. Predict the runoff, seepage, runoff removal load and seepage removal load under target rainfall through the inflow runoff prediction model, the inflow runoff concentration prediction model, the outlet runoff, the seepage prediction model, the runoff removal concentration prediction model and the seepage removal concentration prediction model.

[0127] It should be noted that, by executing steps S101 to S108, the dynamic rainfall, buffer zone inflow runoff, outlet runoff, inlet and outlet runoff concentration, and outlet seepage concentration of the rainfall event are monitored; a soil moisture prediction model before rain is constructed based on soil moisture content and previous sunny days; a runoff inflow prediction model is constructed based on total rainfall and the farmland catchment area of ​​buffer zone inflow; a runoff inflow load prediction model is constructed based on rainfall, rainfall duration, rainfall peak value, and average rainfall intensity, and then the runoff inflow concentration is calculated; an outlet runoff and infiltration prediction model is constructed based on inflow runoff, rainfall, rainfall duration, average rainfall intensity, soil saturated moisture content, initial soil moisture content before rain, and vegetation interception water; a runoff removal concentration prediction model is constructed based on rainfall peak value and rainfall duration; and an infiltration removal concentration model is constructed based on inflow runoff concentration. On this basis, the buffer zone runoff removal load and infiltration removal load under the target rainfall event can be predicted.

[0128] In specific implementation, in the above-mentioned buffer zone vegetation-soil system prediction method for removing runoff pollutants provided in the embodiment of the present invention, step S109 predicts the runoff, seepage, runoff removal load, and seepage removal load under target rainfall through an inflow runoff prediction model, an inflow runoff concentration prediction model, an outlet runoff, a seepage prediction model, a runoff removal concentration prediction model, and a seepage removal concentration prediction model, which may specifically include the following steps:

[0129] According to the target rainfall and the regional farmland catchment area, the runoff inflow under the target rainfall is predicted by the inflow runoff prediction model;

[0130] According to the rainfall, rainfall duration, rainfall peak value and average rainfall intensity of the target rainfall, the runoff concentration under the target rainfall is predicted by the inflow runoff concentration prediction model;

[0131] According to the previous sunny time, rainfall duration, rainfall intensity, rainfall amount, and vegetation interception water volume of the target rainfall, the outlet runoff and seepage volume prediction model is used to predict the outlet runoff and seepage volume under the target rainfall;

[0132] According to the rainfall duration and peak value of the target rainfall, the runoff removal concentration of the target rainfall is predicted by the runoff removal concentration prediction model, and the runoff removal load under the target rainfall is calculated in combination with the outlet runoff volume predicted by the target rainfall;

[0133] According to the runoff inflow concentration of the target rainfall, the seepage removal concentration of the target rainfall is predicted by the seepage removal concentration prediction model, and the seepage removal load under the target rainfall is calculated in combination with the outlet seepage volume predicted by the target rainfall.

[0134] In the prediction method for the removal of runoff pollutants by the vegetation-soil system of the above-mentioned buffer zone provided in an embodiment of the present invention, by monitoring the inflow and outflow water volume and water quality data of farmland runoff under different rainfall conditions, a prediction model for inflow runoff volume, inflow runoff concentration, outlet runoff volume, outlet seepage volume, runoff removal concentration, and seepage removal concentration is constructed. The input parameters are the buffer zone area, the catchment farmland area, and rainfall characteristic parameters. They are relatively easy to obtain and convenient to calculate. The prediction results of soil seepage, outlet runoff volume, runoff removal pollution load, and seepage removal pollution load of the buffer zone for farmland runoff can be quickly obtained under different rainfall conditions, providing technical support for evaluating the ecological environmental efficiency of buffer zones under the influence of multiple factors and multiple target requirements, and effectively designing farmland runoff pollution engineering measures.

[0135] The following is an example to illustrate the prediction method for removing runoff pollutants by the above-mentioned buffer zone vegetation-soil system provided by the embodiment of the present invention, which is as follows:

[0136] Covering an area of ​​8,000m on the shore of Dongfeng Port in Qingpu District, Shanghai 2 The "coastal buffer zone test base" selected the Bermuda vegetation buffer zone to establish the prediction method for the removal of runoff pollutants by the above-mentioned buffer zone vegetation-soil system provided by the embodiment of the present invention. The buffer zone confluence width is 19m and the area is 38m 2 , with a slope of 2%. A flow meter is installed at the inlet of the buffer zone to observe the flow. A right-angle triangular weir is installed at the end to observe the outlet runoff water level. Take COD as an example of runoff pollutants.

[0137] During 39 rainfall events, the runoff at the inlet and outlet of the buffer zone was observed with an observation frequency of 2 minutes. The inflow and outflow runoff of the buffer zone were calculated based on the readings of the flow meter and the right-angle triangular weir. Runoff water samples were collected at the inlet and outlet of the buffer zone. The sampling frequency was determined according to the dynamic process of runoff generation. Samples were taken every 5 minutes within 15 minutes, every 15 minutes between 15-30 minutes, every 15 minutes between 30-60 minutes, and every 30 minutes after 60 minutes. Each time, 1L of water sample was taken. According to the volume ratio of the runoff volume within the sampling interval to the total runoff volume of a rainfall event (see formula (4)), 1L of mixed runoff water sample was prepared, the chemical oxygen demand TN concentration was monitored, and the runoff removal concentration was calculated according to formula (5). In the PVC submerged flow pipe at the end of the buffer zone, water samples were collected every 15 minutes. From the beginning of rainfall to 1 hour after the end of rainfall, the water samples were mixed in equal proportions, the chemical oxygen demand COD concentration was monitored, and the seepage removal concentration was calculated according to formula (6). According to the statistics of 39 rainfall events, rainfall above 14.72 mm in the buffer zone will generate runoff.

[0138] The soil water content was monitored using a soil three-parameter instrument in June (rainy season) and November (dry season). Figure 4 As shown in the figure, a soil moisture scatter plot is made, and the relationship between soil moisture content and the number of sunny days in the previous period is fitted as the soil initial moisture content prediction model under the target rainfall. Figure 4 The medium reading soil saturated moisture content is 0.44. The relationship between soil moisture content and the number of sunny days in the previous period is as follows (14):

[0139] W0=-0.057ln(t s )+0.3201 (14)

[0140] Based on the monitoring data, the rainfall, rainfall peak, average rainfall intensity, rainfall duration, and previous sunny time are counted, and the buffer zone inflow runoff, inflow farmland non-point source load, outlet runoff, outlet seepage, outlet runoff removal concentration and load, and outlet seepage removal concentration and load are calculated.

[0141] According to the monitored rainfall P and farmland catchment area A f , using SPSS software, establish the inflow flow rate Q in (m 3 ) and rainfall model:

[0142]

[0143] According to the monitored inflow runoff concentration, rainfall, rainfall duration, rainfall peak, and average rainfall intensity, the inflow runoff load model (mg) was constructed using SPSS software as follows:

[0144]

[0145] Divide the inflow surface source load by the runoff volume to obtain the inflow concentration C in (mg / L):

[0146]

[0147] The amount of water intercepted by vegetation (mm) was obtained by referring to relevant manuals or literature based on the characteristics of vegetation biomass, which was 3.9 mm. According to formula (10), the infiltration depth F (mm) was calculated.

[0148] There is a stress relationship between rainfall intensity and soil infiltration. Two corrected seepage relationship equations are proposed for equation (10).

[0149]

[0150]

[0151] M is the average rainfall intensity, mm / h; K4 is the seepage stress coefficient related to the average rainfall intensity, and K4<0. Since rainfall is the driving factor of infiltration, the infiltration increases slowly with the increase of rainfall, which is mainly related to groundwater stress. Based on formula (10), the correction of rainfall is further added, and two secondary correction calculation methods for infiltration are proposed.

[0152]

[0153]

[0154] Where K5 and K6 are coefficients, and K5>0. The Levenberg-Marquardt+ general global optimization algorithm is used to determine the following formula (22) as a better model, and the coefficient value is determined with an error of less than ±10%, thereby obtaining a permeability calculation model:

[0155]

[0156] According to the seepage flow prediction model, the outlet flow rate is predicted according to formula (11).

[0157] SPSS software was used to conduct regression analysis on runoff removal concentration, rainfall peak value and rainfall duration, and the best fitting curve was determined as follows;

[0158]

[0159] a1, a2, a3, and a4 are coefficients, and a1>0, a2>0, and a3<0, which are obtained by fitting the monitoring data:

[0160] C r,c =0.019·t0.884 -0.022·In(P)+1.356(R 2 =0.902) (24)

[0161] The SPSS software was used to construct the seepage removal concentration and inflow runoff concentration model as follows;

[0162] C i,c =18.173ln(C in )-28.475(R 2 =0.8644) (25)

[0163] Under target rainfall, according to equations (15) and (16), C under target rainfall is predicted in , predict the seepage depth according to formula (22), predict the outlet runoff according to the water balance relationship (11); predict the runoff removal concentration C according to formula (24) and formula (25) r,c and seepage removal concentration C i,c .

[0164] W r,c =C r,c Q out (26)

[0165]

[0166] On this basis, the runoff removal load W under the target rainfall can be calculated according to the above formula: r,c and seepage removal load W i,c .

[0167] In summary, an embodiment of the present invention provides a prediction method for removing runoff pollutants from a buffer zone vegetation-soil system, including: monitoring soil moisture content, measuring farmland catchment area and buffer zone area; monitoring dynamic rainfall of rainfall events, calculating total rainfall, rainfall duration, average rainfall intensity, rainfall peak, and previous sunny days; monitoring the inflow runoff volume and its concentration, outlet runoff volume and its concentration, and outlet seepage concentration of the buffer zone; establishing a prediction model for soil moisture content and previous sunny days based on soil moisture monitoring data; establishing inflow runoff volume and inflow runoff concentration prediction models based on inflow runoff volume, inflow runoff concentration, rainfall characteristic factors, and farmland catchment area; establishing outlet seepage volume and runoff prediction models based on runoff monitoring data using vegetation interception water, soil moisture infiltration principle, and water balance relationship; constructing a runoff removal concentration model based on runoff removal concentration, rainfall peak, and rainfall duration monitoring data; and constructing a seepage removal concentration model based on infiltration removal concentration and inflow runoff concentration monitoring data. On this basis, the inflow runoff and concentration, outflow runoff, seepage, runoff removal concentration and load, and seepage removal concentration and load of the buffer zone under the target rainfall event can be calculated based on simple and easily obtained variables such as rainfall characteristic factors, farmland catchment area, and buffer zone area. This provides technical support for evaluating the ecological and environmental efficiency of buffer zones under multi-factor influences and multi-objective requirements, and for effectively designing farmland runoff pollution engineering measures.

[0168] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0169] The above is a detailed introduction to the prediction method for removing runoff pollutants by the buffer zone vegetation-soil system provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for predicting the removal of runoff pollutants by a buffer zone vegetation-soil system, characterized in that: include: Monitor the dynamic rainfall of rainfall events, and count the rainfall, peak rainfall, average rainfall intensity, rainfall duration, and previous sunny days of rainfall events; Continuously monitor soil moisture content every day, establish a prediction model of soil moisture content and previous sunny day time based on the relationship between soil moisture content and previous sunny day time, and obtain soil saturated moisture content; Monitor the inflow runoff volume and runoff concentration, outlet runoff volume and runoff concentration, and outlet seepage concentration of the buffer zone, and calculate the runoff removal concentration based on the monitored inflow runoff concentration and outlet runoff concentration; calculate the seepage removal concentration based on the monitored inflow runoff concentration and outlet seepage concentration; Determine a second relationship based on the relationship between the monitored inflow runoff and the statistical rainfall and the farmland catchment area of ​​the buffer zone inflow; establish an equation group based on the monitoring data to solve the optimal solution of the coefficients; and determine the second relationship with the optimal solution of the coefficients as the inflow runoff prediction model after successful verification; Determine a third relationship based on the relationship between the monitored inflow runoff concentration and the statistical rainfall, rainfall duration, rainfall peak value, and average rainfall intensity; establish a set of equations based on the monitoring data to solve the optimal solution of the coefficients; and determine the third relationship with the optimal solution of the coefficients as the inflow runoff concentration prediction model after successful verification; Based on the monitored inflow runoff, outlet runoff, obtained soil saturation moisture content, initial soil moisture content before rain, vegetation interception water, statistical rainfall, average rainfall intensity and rainfall duration, a forecast model for outlet runoff and seepage volume is constructed; According to the calculated runoff removal concentration, statistical rainfall peak value and rainfall duration, a runoff removal concentration prediction model is constructed; Based on the calculated seepage removal concentration and the monitored inflow runoff concentration, a seepage removal concentration prediction model is constructed; According to the rainfall of the target rainfall and the farmland catchment area of ​​the region, the runoff inflow under the target rainfall is predicted by the inflow runoff prediction model; According to the rainfall amount, rainfall duration, rainfall peak value, and average rainfall intensity of the target rainfall, the runoff inflow concentration under the target rainfall is predicted by the inflow runoff concentration prediction model; According to the previous sunny time of the target rainfall, rainfall duration, rainfall intensity, rainfall amount, and vegetation interception water volume, the outlet runoff and seepage amount prediction model is used to predict the outlet runoff and seepage amount under the target rainfall; According to the rainfall duration and rainfall peak of the target rainfall, the runoff removal concentration of the target rainfall is predicted by the runoff removal concentration prediction model, and the runoff removal load under the target rainfall is calculated in combination with the outlet runoff volume predicted by the target rainfall; According to the runoff inflow concentration of the target rainfall, the seepage removal concentration of the target rainfall is predicted by the seepage removal concentration prediction model, and the seepage removal load under the target rainfall is calculated in combination with the outlet seepage volume predicted by the target rainfall.

2. The method for predicting the removal of runoff pollutants by the buffer zone vegetation-soil system according to claim 1, characterized in that: The dynamic rainfall amount of the monitoring rainfall event, the statistical rainfall amount, rainfall peak, average rainfall intensity, rainfall duration, and the number of previous sunny days of the rainfall event, include: The dynamic rainfall of rainfall events is obtained according to the monitoring of rainfall meteorological stations, and the rainfall, peak rainfall, average rainfall intensity, rainfall duration, and number of sunny days in the previous period of rainfall events are counted; each rainfall event is separated by a period of no rainfall greater than 6 hours; The continuous monitoring of soil moisture content every day, establishing a prediction model of soil moisture content and previous sunny day time according to the relationship between soil moisture content and previous sunny day time, and obtaining soil saturated moisture content, includes: A soil parameter meter is used to continuously monitor the soil moisture content every day, and a scatter plot of soil moisture content and the previous sunny time is made. The soil saturated moisture content is read, and the first relationship is fitted to determine the coefficient. After successful verification, it is determined as a prediction model for soil moisture content before rain, thereby predicting the initial soil water requirement before rain under the target rainfall based on the previous number of sunny days.

3. The method for predicting the removal of runoff pollutants by the buffer zone vegetation-soil system according to claim 1, characterized in that: The monitoring buffer zone's inflow runoff volume and runoff concentration, outlet runoff volume and runoff concentration, and outlet seepage concentration include: The inflow flow rate of the buffer zone is monitored by a flow meter; The right-angle triangular weir is used to monitor the outlet runoff of the buffer zone, the water discharge time and water level of the triangular weir are recorded, and the outlet runoff of the buffer zone is obtained according to the area of ​​the buffer zone; The runoff collector is used to dynamically collect inflow and outlet runoff water samples, and mixed samples are prepared according to the runoff volume ratio in the dynamic time period of the runoff process. The average concentration of pollutants in the inflow and outlet runoff events during rainfall events is obtained through detection and analysis; A PVC pipe underflow is buried at the end of the buffer zone. After the rainfall, a Beagle tube is placed in the PVC pipe to collect seepage water samples. The seepage water samples are mixed according to the average volume method, and the event average concentration of the outlet seepage pollutants is obtained through detection and analysis.

4. The method for predicting the removal of runoff pollutants by the buffer zone vegetation-soil system according to claim 1, characterized in that: The outlet runoff prediction model is constructed based on the monitored inflow runoff, outlet runoff, vegetation interception water, obtained soil saturation moisture content, statistical rainfall, average rainfall intensity and rainfall duration, including: The amount of water intercepted by vegetation was obtained according to the vegetation biomass by consulting the manual or literature; The amount of soil infiltration water is obtained based on the obtained soil saturated water content, soil water content before rain, statistical rainfall, average rainfall intensity and rainfall duration; According to the relationship between the monitored inflow flow and the obtained vegetation interception water and soil infiltration water, the outlet flow can be obtained, and the fourth relationship is established; Establish a set of equations based on monitoring data and find the optimal solution for the coefficients; After successful verification, the fourth relationship with the optimal solution of the coefficients is determined as the outlet flow rate prediction model.

5. The method for predicting the removal of runoff pollutants by the buffer zone vegetation-soil system according to claim 4, characterized in that: The runoff removal concentration prediction model is constructed based on the calculated runoff removal concentration, the statistical rainfall peak value and the rainfall duration, including: SPSS software was used to conduct regression analysis on the calculated runoff removal concentration and the statistical rainfall peak value, and the calculated runoff removal concentration and the statistical rainfall duration, to determine the best fitting curve, on this basis, the fifth relationship was determined; Establishing a set of equations based on the monitoring data to find the optimal solution of the coefficients of the fifth relationship; The fifth relationship with the optimal solution of the coefficients is successfully verified and determined as the runoff removal concentration prediction model.

6. The method for predicting the removal of runoff pollutants by the buffer zone vegetation-soil system according to claim 5, characterized in that: The method of constructing a seepage removal concentration prediction model based on the calculated seepage removal concentration and the monitored inflow runoff concentration includes: SPSS software was used to perform regression analysis on the calculated seepage removal concentration and the monitored inflow runoff concentration to determine the best fitting curve, on this basis, the sixth relationship was determined; Establishing a set of equations based on the monitoring data to find the optimal solution of the coefficients of the sixth relationship; The sixth relationship with the optimal solution of the coefficients is successfully verified and determined as the seepage removal concentration prediction model.

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