Basin nitrogen emission reduction optimization method, device, equipment and storage medium

Abstract

The present invention relates to the field of data analysis, and in particular to a method, device, equipment and storage medium for optimizing nitrogen emission reduction in a watershed, which can analyze various nitrogen emission reduction control schemes in a watershed by comprehensively analyzing the annual emission load data of non-point sources of total nitrogen in a target area and the emission load data of nitrous oxide, thereby solving the problem of limitations caused by optimization based on experience, optimizing the nitrogen emission reduction control scheme in a watershed, and improving the accuracy and efficiency of the optimization of the nitrogen emission reduction control scheme in a watershed.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a method, device, equipment and storage medium for optimizing nitrogen emission reduction in a watershed. Background Art

[0002] In recent years, climate warming and human activities have significantly changed the nitrogen cycle and increased the effectiveness of reactive nitrogen, which has caused a series of environmental problems at the basin, regional and even global scales. Excessive reactive nitrogen in the soil enters the atmosphere and water bodies, causing greenhouse gas emissions, air pollution and water pollution. In the context of climate change, reducing nitrogen emissions in basins has become a major problem in today's society.

[0003] Best management practices (BMPS) are one of the main methods for reducing nitrogen emissions in watersheds. In recent years, researchers have developed many optimization techniques to implement BMPS configuration. However, in the actual BMPS configuration management system, there are usually conflicts between environmental and economic goals that are difficult to coordinate. There are uncertainties in factors such as the allowable nutrient emissions and decision-maker preferences. After implementing certain best management practices, while reducing non-point source TN in water bodies, agricultural nitrous oxide emissions may increase. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a method, device, equipment and storage medium for optimizing nitrogen emission reduction in a watershed, which can comprehensively analyze various nitrogen emission reduction control schemes in the water body of the target area and the nitrous oxide emission load data of non-point sources, solve the limitations caused by optimization based on experience, realize the optimization of the nitrogen emission reduction control scheme in the watershed, and improve the accuracy and efficiency of the optimization of the nitrogen emission reduction control scheme in the watershed.

[0005] In a first aspect, an embodiment of the present application provides a method for optimizing nitrogen emission reduction in a watershed, comprising the following steps:

[0006] Acquire spatial data and attribute data of the target area, wherein the spatial data includes elevation data, land use data, soil distribution data and soil slope data, and the attribute data includes meteorological attribute data and soil attribute data;

[0007] Based on the elevation data, construct a river network of the target area, divide the river network into a number of sub-watersheds, divide the sub-watersheds into a number of hydrological response units according to the combined data of land use data, soil distribution and soil slope data corresponding to each sub-watershed, and construct a hydrological model associated with the target area;

[0008] Input the meteorological attribute data and soil attribute data into the hydrological model, and obtain the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin output by the hydrological model;

[0009] Obtain several watershed nitrogen emission reduction control schemes, and obtain the optimized water body non-point source total nitrogen annual emission load data and optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes according to the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin;

[0010] Based on the optimized annual non-point source total nitrogen emission load data of water bodies and the optimized nitrous oxide emission load data, a nitrogen emission reduction optimization configuration model is constructed. Based on the nitrogen emission reduction optimization configuration model, the nitrogen emission reduction control plan for the target watershed is obtained from the various watershed nitrogen emission reduction control plans.

[0011] In a second aspect, an embodiment of the present application provides an optimization device for a watershed nitrogen emission reduction control scheme, comprising:

[0012] A data acquisition module, used to acquire spatial data and attribute data of a target area, wherein the spatial data includes elevation data, land use data, soil distribution data and soil slope data, and the attribute data includes meteorological attribute data and soil attribute data;

[0013] A hydrological model construction module, for constructing a river network of the target area based on the elevation data, dividing the river network into a plurality of sub-watersheds, dividing the sub-watersheds into a plurality of hydrological response units according to the land use data, soil distribution and soil slope data corresponding to each sub-watershed, and constructing a hydrological model associated with the target area;

[0014] A first emission load data calculation module is used to input the meteorological attribute data and soil attribute data into a hydrological model, and obtain the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin output by the hydrological model;

[0015] The second emission load data calculation module is used to obtain several kinds of watershed nitrogen emission reduction control schemes, and obtain the optimized water body non-point source total nitrogen annual emission load data and optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes according to the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin;

[0016] The optimization module is used to construct a nitrogen emission reduction optimization configuration model based on the optimized annual non-point source total nitrogen emission load data of the water body and the optimized nitrous oxide emission load data, and obtain the target basin nitrogen emission reduction control plan from the various basin nitrogen emission reduction control plans based on the nitrogen emission reduction optimization configuration model.

[0017] In a third aspect, an embodiment of the present application provides a computer device comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the method for optimizing nitrogen emission reduction in a watershed as described in the first aspect are implemented.

[0018] In a fourth aspect, an embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the watershed nitrogen emission reduction optimization method as described in the first aspect are implemented.

[0019] In the embodiment of the present application, the annual emission load data of total nitrogen from non-point sources in water bodies in the target area and the emission load data of nitrous oxide can be integrated to analyze various nitrogen emission reduction control schemes in watersheds, thereby solving the limitations caused by optimization based on experience, optimizing the nitrogen emission reduction control schemes in watersheds, and improving the accuracy and efficiency of the optimization of nitrogen emission reduction control schemes in watersheds.

[0020] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A schematic diagram of a flow chart of a method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application;

[0022] Figure 2 A schematic diagram of the process of S3 in the method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application;

[0023] Figure 3 A schematic diagram of the process of S301 in the method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application;

[0024] Figure 4 A schematic diagram of the process of S302 in the method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application;

[0025] Figure 5 A schematic diagram of the process of S303 in the method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application;

[0026] Figure 6 A schematic diagram of a flow chart of a method for optimizing nitrogen emission reduction in a watershed provided in another embodiment of the present application;

[0027] Figure 7 A schematic diagram of the process of S6 in the method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application;

[0028] Figure 8 A schematic diagram of the structure of an optimization device for a watershed nitrogen emission reduction control solution provided in one embodiment of the present application;

[0029] Fig. 9 A schematic diagram of the structure of a computer device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0030] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0031] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0032] It should be understood that, although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" / "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determination".

[0033] See also Figure 1 , Figure 1 A schematic diagram of a flow chart of a method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application, the method comprising the following steps:

[0034] S1: Obtain spatial data and attribute data of the target area.

[0035] The executor of the watershed nitrogen emission reduction optimization method is the optimization device of the watershed nitrogen emission reduction optimization method (hereinafter referred to as the optimization device). In an optional embodiment, the optimization device can be a computer device, a server, or a server cluster composed of multiple computer devices.

[0036] The spatial data includes elevation data, land use data, soil distribution data and soil slope data; the elevation data is a digital elevation model (DEM), which represents the digitized elevation information of the ground terrain; the land use data reflects the division of land use types, wherein the land use types include cultivated land, forest land, etc.

[0037] The soil distribution data refers to the distribution of soil types, wherein the soil types include red soil, brown soil, brown soil, black soil, etc.

[0038] The attribute data includes meteorological attribute data and soil attribute data. The meteorological attribute data is a set of data reflecting the weather, which can be obtained from various meteorological stations, including annual average temperature data, daily average rainfall, daily average evapotranspiration, daily maximum and minimum temperature data, daily average relative humidity data, daily average solar radiation data, and daily average wind speed data;

[0039] The soil attribute data is a set of data reflecting the properties of the soil, including temperature data of the soil surface, the number of soil layers, soil depth data, the effective water content and saturated water content corresponding to each soil layer, soil layer depth, soil layer bulk density, total porosity, desiccation and crack volume data, and data on the proportion of pores that exclude anions, clay content, effective porosity of the soil layer, and organic carbon content in the humus of the soil layer, etc., wherein the desiccation and crack volume data includes the potential desiccation and crack volume of the soil profile, the desiccation and crack volume of each soil layer, and the maximum desiccation and crack volume of the soil layer.

[0040] In this embodiment, the optimization device can obtain the elevation data, spatial data, and attribute data of the target area through the database.

[0041] S2: Based on the elevation data, construct a river network of the target area, divide the river network into several sub-basins, divide the sub-basins into several hydrological response units according to the combined data of land use data, soil distribution and soil slope data corresponding to each sub-basin, and construct a hydrological model associated with the target area.

[0042] The hydrological model is a type of SWAT (Soil and Water Assessment Tool) model, which is used to simulate the spatiotemporal distribution of nitrogen pollution in the target area. The hydrological model is composed of a number of hydrological response units.

[0043] In this embodiment, the optimization device constructs a river basin network of the target area based on the elevation data in the spatial data, wherein the river basin network includes hydrological and water quality sites and river basin outlets, and the river basin network includes a number of location points, each of which has a corresponding river basin value, and the river basin value is used to display the characteristics of the area where the location point is located.

[0044] According to the preset watershed threshold, the watershed value of each position point is compared. When the watershed value is greater than the watershed threshold, the position point corresponding to the watershed value is used as the target position point, and the position of the hydrological and water quality station and the watershed outlet in the watershed river network in the elevation data is used as the boundary to select the target position point, so as to divide the watershed river network into several sub-watersheds;

[0045] According to the land use data, soil distribution and soil slope data corresponding to each sub-watershed, overlapping combination processing is performed on the land use data, soil distribution data and soil slope data corresponding to the several sub-watersheds to obtain combined data of the combined data of the land use data, soil distribution and soil slope data corresponding to each sub-watershed, thereby dividing the sub-watershed into several hydrological response units and constructing a hydrological model associated with the target area.

[0046] S3: Input the meteorological attribute data and soil attribute data into the hydrological model, and obtain the initial water body non-point source annual total nitrogen emission load data and initial nitrous oxide emission load data corresponding to each sub-basin output by the hydrological model.

[0047] The hydrological model includes a calculation algorithm corresponding to the hydrological data and a calculation algorithm corresponding to the nitrogen emission load data.

[0048] In this embodiment, the optimization device inputs the meteorological attribute data and the soil attribute data into the hydrological model, and based on the hydrological response unit in the hydrological model, extracts the meteorological attribute data and the soil attribute data corresponding to the hydrological response unit from the meteorological attribute data and the soil attribute data, respectively, and obtains the annual non-point source total nitrogen emission load data and the nitrous oxide emission load data of the water body corresponding to each hydrological response unit output by the hydrological model according to the corresponding algorithm in the hydrological model, and combines the annual non-point source total nitrogen emission load data and the nitrous oxide emission load data of the water body corresponding to each hydrological response unit corresponding to the same sub-basin, so as to obtain the initial annual non-point source total nitrogen emission load data and the initial nitrous oxide emission load data of the water body corresponding to each sub-basin.

[0049] See also Figure 2 , Figure 2 The schematic flow diagram of S3 in the watershed nitrogen emission reduction optimization method provided in one embodiment of the present application includes steps S301 to S303, which are specifically as follows:

[0050] S301: Input the meteorological attribute data and soil attribute data into the hydrological model, and based on the hydrological response unit and the corresponding hydrological data acquisition method, obtain the hydrological data corresponding to each sub-basin output by the hydrological model.

[0051] The hydrological data includes soil temperature data and runoff data, wherein the soil temperature data is used to reflect the temperature data of each depth of the soil, and the runoff data includes soil moisture content data and surface runoff data.

[0052] In this embodiment, the optimization device inputs the meteorological attribute data and the soil attribute data into the hydrological model, and obtains the hydrological data corresponding to each sub-basin output by the hydrological model based on the hydrological response unit and the corresponding hydrological data acquisition method, wherein the hydrological data acquisition method includes a soil temperature data acquisition method and a runoff data acquisition method.

[0053] S302: According to the meteorological attribute data, soil attribute data, runoff data and the corresponding nitrogen emission load data acquisition method in the hydrological model, the nitrogen emission load data corresponding to each sub-basin output by the hydrological model is acquired.

[0054] The nitrogen emission load data include surface runoff nitrate emission load data, lateral flow nitrate emission load data, groundwater nitrate emission load data and organic nitrogen emission load data.

[0055] In this embodiment, the optimization device obtains the nitrogen emission load data corresponding to each sub-basin output by the hydrological model according to the meteorological attribute data, soil attribute data, runoff data corresponding to the hydrological response unit and the corresponding nitrogen emission load data acquisition method in the hydrological model, wherein the nitrogen emission load data acquisition method includes a surface runoff nitrate emission load data acquisition method, a lateral flow nitrate emission load data acquisition method, a groundwater nitrate emission load data acquisition method and an organic nitrogen emission load data acquisition method.

[0056] S303: According to the hydrological data and nitrogen emission load data corresponding to each sub-basin, the initial water body non-point source annual total nitrogen emission load data and initial nitrous oxide emission load data corresponding to each sub-basin output by the hydrological model are obtained.

[0057] In this embodiment, the optimization device obtains the initial water body non-point source annual total nitrogen emission load data and initial nitrous oxide emission load data corresponding to each sub-basin output by the hydrological model based on the hydrological data and nitrogen emission load data corresponding to each sub-basin.

[0058] See also Figure 3 , Figure 3 The schematic flow diagram of S301 in the method for optimizing nitrogen emission reduction in a watershed provided in one embodiment of the present application includes steps S3011 to S3012, which are specifically as follows:

[0059] S3011: Acquire soil temperature data corresponding to each sub-basin according to the meteorological attribute data, soil attribute data and soil temperature data acquisition method.

[0060] The soil temperature data acquisition method is to acquire the soil temperature data according to the following formula:

[0061]

[0062] Where, T soil (z,d n ) is the soil temperature data, indicating the dth day of the year n Soil temperature data at soil depth z on the day; λ represents the hysteresis coefficient; df is the depth factor; is the annual average temperature data in the meteorological attribute data, ℃; T ssurf The temperature data of the soil surface layer on that day in the soil attribute data;

[0063] In this embodiment, the optimization device extracts the meteorological attribute data and soil attribute data corresponding to the hydrological response unit from the meteorological attribute data and soil attribute data respectively based on the hydrological response unit in the hydrological model, obtains the soil temperature data corresponding to each hydrological response unit output by the hydrological model according to the soil temperature data acquisition method, and combines the soil temperature data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the soil temperature data corresponding to each sub-basin.

[0064] S3012: Obtain the runoff data corresponding to each sub-basin according to the meteorological attribute data, soil attribute data and runoff data acquisition method.

[0065] The runoff data includes soil moisture data and surface runoff data.

[0066] The runoff data acquisition method is to obtain the runoff data according to the following formula, including soil moisture equation, soil initial moisture equation, surface runoff equation, lateral water flow equation and regression flow equation, wherein the soil moisture equation is:

[0067]

[0068] Where SW t is the soil moisture content data; SW 0 is the initial soil moisture content on the i-th day; t represents time; R day is the precipitation on the i-th day in the meteorological attribute data; Q surf is the surface runoff on the i-th day; E a is the evapotranspiration of the i-th day in the meteorological attribute data; W seep is the amount of infiltration water and bypass water leaving the bottom of the soil profile on day i; Q gw is the water volume of the return flow on the i-th day;

[0069] The surface runoff equation is:

[0070]

[0071] Where S is the retention parameter;

[0072] The initial soil moisture content equation is:

[0073] SW 0 =FC FFCB

[0074] In the formula, FC is the field water holding capacity; FFCB is the ratio of initial soil water content to field water holding capacity;

[0075] The lateral water flow equation is:

[0076]

[0077] In the formula, w perc,ly＝n is the amount of water that seeps out of the bottom layer of the soil on the i-th day; w crk,btm is the bypass water flow through the lower boundary of the soil on the i-th day; crk ly Indicates the amount of cracks in the soil layer; ly indicates the soil layer; crk ly＝nn is the amount of cracks in the deepest soil layer; depth ly＝nn is the depth of the deepest soil layer; n is the number of soil layers;

[0078] in,

[0079]

[0080] In the formula, crk max,ly is the maximum cracking amount of the soil layer; crk max is the potential cracking volume of the soil profile; depth ly is the soil layer depth; coef crk is the adjustment coefficient of dry fissure water flow; FC ly SW is the field water holding capacity of the soil layer; ly is the soil moisture content of the soil layer;

[0081] in,

[0082]

[0083] Where SW ly,excess is the drainable volume stored in the soil layer, when SW ly >FC ly When SW ly,excess =SW ly -FC ly ; When SW ly ≤FC ly When SW ly,excess =0; Δt is the time step; K sat is the saturated permeability coefficient, ρ s is the particle density; ρ b is the bulk density of the soil layer;

[0084] in,

[0085]

[0086] In the formula, m c is the clay content; AWC ly Indicates effective water content;

[0087] The regression flow equation is:

[0088]

[0089] In the formula, aq sh 、aq shthr,q are the first water level threshold and the second water level threshold of the shallow aquifer when the groundwater flows into the main river; Q gw,i , Q gw,i-1 are the water volume of the return flow on the i-th day and the i-1-th day respectively; a gw is the base flow retreat constant, w rchrg is the total recharge of the aquifer; β deep is the permeability coefficient of the aquifer;

[0090] in,

[0091] w rchrg,i =(1-exp[-1 / δ gw ])·w seep +exp[-1 / δ gw ]·w rchrg,i-1

[0092] In the formula, w rchrg,i is the total recharge of the aquifer on day i, δ gw is the delay time for aquifer recharge.

[0093] In this embodiment, the optimization device extracts the meteorological attribute data and soil attribute data corresponding to the hydrological response unit from the meteorological attribute data and soil attribute data respectively based on the hydrological response unit in the hydrological model, obtains the runoff data corresponding to each hydrological response unit output by the hydrological model according to the runoff data acquisition method, and combines the runoff data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the runoff data corresponding to each sub-basin.

[0094] See also Figure 4 , Figure 4 The schematic flow diagram of S302 in the watershed nitrogen emission reduction optimization method provided in one embodiment of the present application includes steps S3021 to S3024, which are as follows:

[0095] S3021: According to the soil property data and the nitrogen migration equation, the soil water nitrate concentration data corresponding to each sub-basin is obtained.

[0096] The soil water body nitrate concentration data is used to reflect the nitrate concentration in the soil water flow in the target area.

[0097] The nitrogen migration equation includes the soil water nitrate concentration equation, the soil nitrate content equation and the soil flow water equation, wherein the soil water nitrate concentration equation is:

[0098]

[0099] In the formula, is the nitrate concentration data of soil and water; NO 3conc is the soil nitrate content; w mobile is the soil flow water volume; θ e is the pore ratio data for excluding anions;

[0100] The soil nitrate content equation is:

[0101]

[0102]

[0103]

[0104] In the formula, NO 3conc,z is the nitrate content at soil depth z; SAT ly is the saturated water content in the soil attribute data; φ soil is the total porosity in the soil property data;

[0105] The soil flow water equation is:

[0106]

[0107] Where f1 is the soil flow water calculation algorithm for the top 10 mm soil layer, f2 is the soil flow water calculation algorithm for the soil layer below 10 mm, Q lat,ly It indicates the amount of water flowing out of this layer through lateral flow on a certain day;

[0108] in,

[0109]

[0110] Where slp is the average slope of each sub-basin in the soil slope data; φ d is the effective porosity of the soil layer in the soil attribute data; L hill is the slope length in the soil slope data;

[0111] In this embodiment, the optimization device extracts the soil attribute data corresponding to the hydrological response unit from the soil attribute data based on the hydrological response unit in the hydrological model, obtains the soil water body nitrate concentration data corresponding to each hydrological response unit output by the hydrological model according to the nitrogen migration equation, and combines the soil water body nitrate concentration data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the soil water body nitrate concentration data corresponding to each sub-basin.

[0112] S3022: According to the soil property data, the soil water nitrate concentration data corresponding to each sub-basin and the surface runoff nitrate emission load data acquisition method, the surface runoff nitrate emission load data corresponding to each sub-basin is acquired.

[0113] The method for obtaining the surface runoff nitrate discharge load data is to obtain the surface runoff nitrate discharge load data according to the following formula:

[0114]

[0115] In the formula, NO 3surf The nitrate discharge load data for said surface runoff; is the seepage coefficient of nitrate; is the soil water nitrate concentration data;

[0116] In this embodiment, the optimization device extracts the soil attribute data corresponding to the hydrological response unit from the soil attribute data based on the hydrological response unit in the hydrological model, obtains the surface runoff nitrate emission load data corresponding to each hydrological response unit output by the hydrological model according to the surface runoff nitrate emission load data acquisition method and the soil water body nitrate concentration data corresponding to each hydrological response unit, and combines the surface runoff nitrate emission load data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the surface runoff nitrate emission load data corresponding to each sub-basin.

[0117] S3023: Acquire the lateral flow nitrate discharge load data corresponding to each sub-basin based on the soil property data, the soil water body nitrate concentration data corresponding to each sub-basin, and the lateral flow nitrate discharge load data acquisition method.

[0118] The method for obtaining the lateral flow nitrate discharge load data is to obtain the lateral flow nitrate discharge load data according to the following formula:

[0119]

[0120] Where, f3 is the calculation algorithm for lateral flow nitrate discharge load of the soil layer with a surface area of ​​10 mm, and f4 is the calculation algorithm for lateral flow nitrate discharge load of the soil layer below 10 mm; NO 3lat,ly is the side stream nitrate discharge load;

[0121] In this embodiment, the optimization device extracts the soil attribute data corresponding to the hydrological response unit from the soil attribute data based on the hydrological response unit in the hydrological model, obtains the lateral flow nitrate discharge load data corresponding to each hydrological response unit output by the hydrological model according to the lateral flow nitrate discharge load data acquisition method and the soil water body nitrate concentration data corresponding to each hydrological response unit, and combines the lateral flow nitrate discharge load data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the lateral flow nitrate discharge load data corresponding to each sub-basin.

[0122] S3024: According to the soil property data, the soil water nitrate concentration data corresponding to each sub-basin and the groundwater nitrate discharge load data acquisition method, the groundwater nitrate discharge load data corresponding to each sub-basin is acquired.

[0123] The method for obtaining groundwater nitrate discharge load data is to obtain the groundwater nitrate discharge load data according to the following formula:

[0124]

[0125] In the formula, NO 3perc,ly Groundwater nitrate discharge loading data for the target area;

[0126] In this embodiment, the optimization device extracts the soil attribute data corresponding to the hydrological response unit from the soil attribute data based on the hydrological response unit in the hydrological model, obtains the groundwater nitrate emission load data corresponding to each hydrological response unit output by the hydrological model according to the groundwater nitrate emission load data acquisition method and the soil water body nitrate concentration data corresponding to each hydrological response unit, and combines the groundwater nitrate emission load data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the groundwater nitrate emission load data corresponding to each sub-basin.

[0127] S3025: According to the soil property data and the method for obtaining the organic nitrogen emission load data corresponding to each sub-basin, the organic nitrogen emission load data corresponding to each sub-basin is obtained.

[0128] The method for obtaining the organic nitrogen emission load data is to obtain the organic nitrogen emission load data according to the following formula:

[0129]

[0130] In the formula, orgN surf is the organic nitrogen emission load data; sed represents the sediment yield on a certain day; A HRU is the area of ​​the hydrological response unit; orgN is the concentration of organic nitrogen in the soil surface layer, where

[0131]

[0132] In the formula, rsd surf is the residue content in the top 10 mm of soil; orgC surf is the organic carbon content in the humus of the soil layer;

[0133] In this embodiment, the optimization device extracts the soil attribute data corresponding to the hydrological response unit from the soil attribute data based on the hydrological response unit in the hydrological model, obtains the organic nitrogen emission load data corresponding to each hydrological response unit output by the hydrological model according to the organic nitrogen emission load data acquisition method and the soil water body nitrate concentration data corresponding to each hydrological response unit, and combines the organic nitrogen emission load data corresponding to each hydrological response unit corresponding to the same sub-basin, thereby obtaining the organic nitrogen emission load data corresponding to each sub-basin.

[0134] See also Figure 5 , Figure 5 The schematic flow diagram of S303 in the watershed nitrogen emission reduction optimization method provided in one embodiment of the present application includes steps S3031 to S3033, which are as follows:

[0135] S3031: Based on the nitrogen emission load data corresponding to each sub-basin and the total nitrogen emission load data calculation algorithm, the initial water body non-point source total nitrogen annual emission load data corresponding to each sub-basin is obtained.

[0136] The total nitrogen emission load data calculation algorithm is:

[0137] SN=orgN surf +NO 3surf +NO 3lat,ly +NO 3perc,ly

[0138] Where, SN is the initial water body non-point source total nitrogen annual discharge load data, orgN surf The organic nitrogen emission load data, NO 3surf The nitrate discharge load data for surface runoff, NO 3lat,ly The sidestream nitrate discharge loading data, NO3perc,ly The groundwater nitrate discharge load data;

[0139] In this embodiment, the optimization device obtains the initial water body non-point source annual total nitrogen emission load data corresponding to each sub-basin based on the nitrogen emission load data corresponding to each sub-basin and the total nitrogen emission load data calculation algorithm.

[0140] S3032: According to the hydrological data corresponding to each sub-basin, the annual emission load data of total nitrogen from non-point sources of the initial water body and the soil nitrous oxide emission load calculation algorithm, the soil nitrous oxide emission load data corresponding to each sub-basin is obtained.

[0141] The soil nitrous oxide emission load calculation algorithm is:

[0142] N 2 O soil =-6.519+1.075×SN+0.246×T soil (z,d n )+0.12×SW t

[0143] Where N 2 O soil is the soil nitrous oxide emission load data,

[0144] In this embodiment, the optimization device obtains the soil nitrous oxide emission load data corresponding to each sub-basin based on the hydrological data corresponding to each sub-basin, the initial water body non-point source total nitrogen annual emission load data, and the soil nitrous oxide emission load calculation algorithm.

[0145] S3033: According to the soil nitrous oxide emission load data corresponding to each sub-basin, the hydrological response unit corresponding to the sub-basin and the nitrous oxide emission load calculation algorithm, the initial nitrous oxide emission load data corresponding to each sub-basin is obtained.

[0146] The nitrous oxide emission load calculation algorithm is:

[0147]

[0148] Where N 2 O SUB,i is the soil nitrous oxide emission load data corresponding to the i-th sub-basin; i is the sub-basin number; k is the hydrological response unit number; N 2 O HRU,k is the nitrous oxide emission load data of the kth hydrological response unit; A HRU,k is the area of ​​the kth hydrological response unit; A SUB,i is the area of ​​the ith sub-basin.

[0149] In this embodiment, the optimization device obtains the initial nitrous oxide emission load data corresponding to each sub-basin based on the soil nitrous oxide emission load data corresponding to each sub-basin, the hydrological response unit corresponding to the sub-basin, and the nitrous oxide emission load calculation algorithm.

[0150] See also Figure 6 , Figure 6 The schematic flow chart of the method for optimizing nitrogen emission reduction in a watershed provided in another embodiment of the present application further includes step S6, which is after step S3 and is specifically as follows:

[0151] S6: Obtain the observed values ​​of the hydrological data and the nitrogen emission load data, and verify the hydrological model using a verification algorithm based on the hydrological data, the nitrogen emission load data and the corresponding simulation values ​​output by the hydrological model of the target area to obtain a verified hydrological model.

[0152] The verification algorithm is the SUFI-2 algorithm, and the selected evaluation index is the Nash-Sutcliffe efficiency coefficient E NS and the coefficient of certainty R 2 Specifically, the verification algorithm is:

[0153]

[0154]

[0155] In the formula, E NS is the efficiency coefficient; t is the unit time, T is the time length; O t is the corresponding observation value at time t, P t is the simulated value of the hydrological data and nitrogen emission load data output by the hydrological model corresponding to the tth moment; is the average value of the observed values; R 2 is the coefficient of certainty; is the average value of the simulation values.

[0156] In this embodiment, the optimization device obtains the observed values ​​of the hydrological data and the nitrogen emission load data, and outputs the efficiency coefficient E using a verification algorithm according to the hydrological data, the nitrogen emission load data and the corresponding simulation values ​​output by the hydrological model of the target area. NS and the coefficient of certainty R 2 , the output efficiency coefficient E NS and the coefficient of certainty R 2 For analysis, when 0.50≤E NS , and R 2 ≥0.60, and the validated hydrological model was obtained.

[0157] S4: Obtain several kinds of watershed nitrogen emission reduction control schemes, and according to the initial annual water body non-point source total nitrogen emission load data and initial nitrous oxide emission load data corresponding to each sub-basin, obtain the optimized annual water body non-point source total nitrogen emission load data and optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes.

[0158] The watershed nitrogen emission reduction control plan is a type of BMPS (Best management practices, BMPS) management plan, including BMPS types, implementation scales and parameters associated with the BMPS types, wherein the BMPS types include plant buffer zones, fertilizer reduction, grassed waterways and contour planting.

[0159] In this embodiment, the optimization device obtains several watershed nitrogen emission reduction control schemes, and based on the initial annual non-point source total nitrogen emission load data of water bodies and the initial nitrous oxide emission load data corresponding to each sub-basin, obtains the optimized annual non-point source total nitrogen emission load data of water bodies and the optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes.

[0160] S5: Based on the optimized annual total nitrogen emission load data of non-point sources in water bodies and the optimized nitrous oxide emission load data, a nitrogen emission reduction optimization configuration model is constructed, and based on the nitrogen emission reduction optimization configuration model, the nitrogen emission reduction control plan for the target watershed is obtained from the various watershed nitrogen emission reduction control plans.

[0161] In this embodiment, the optimization device constructs a nitrogen emission reduction optimization configuration model based on the optimized water body non-point source total nitrogen annual emission load data and the optimized nitrous oxide emission load data, and obtains the target watershed nitrogen emission reduction control plan from the various watershed nitrogen emission reduction control plans based on the nitrogen emission reduction optimization configuration model.

[0162] See also Figure 7 , Figure 7 The schematic flow diagram of S5 in the watershed nitrogen emission reduction optimization method provided in one embodiment of the present application includes steps S501 to 502, which are specifically as follows:

[0163] S501: Construct a fuzzy nitrogen emission reduction optimization configuration model based on the optimized annual total nitrogen emission load data of non-point sources in water bodies and the optimized nitrous oxide emission load data.

[0164] The fuzzy nitrogen emission reduction optimization configuration model is a fuzzy fractional programming model (FFPM), which includes a cost-effectiveness objective function, an initial water body non-point source total nitrogen emission load improvement rate constraint, and an initial nitrous oxide emission load improvement rate constraint, wherein the cost-effectiveness objective function is:

[0165]

[0166] Where max_f is the cost-effectiveness data corresponding to the various BMSP management schemes, i is the sub-basin number, i = 1, 2, ..., m, j is the BMPS type, j = 1, 2, ..., n, N i,0 is the initial water body non-point source total nitrogen annual discharge load data of the ith sub-basin, N i is the optimized annual total nitrogen discharge load data of non-point sources in water bodies of the ith sub-basin, X i,j is the first decision variable, B i,j is the second decision variable, which indicates the implementation scale of the j-th basin nitrogen emission reduction control scheme in the i-th sub-basin; U j represents the unit cost of the j-th basin nitrogen emission reduction control scheme;

[0167] The initial water body non-point source total nitrogen emission load improvement rate constraint condition is:

[0168]

[0169] Where Cr is the fuzzy credibility planning function, N 0 is the sum of the initial annual total nitrogen discharge load data of non-point sources in each sub-basin. is the first triangular fuzzy number associated with the total nitrogen discharge load data from non-point sources in water bodies, σ N Respectively The upper bound and median of , λ is the confidence level parameter;

[0170] The initial nitrous oxide emission load improvement rate constraint is:

[0171]

[0172] In the formula, K i (X i,j ,B i,j ) is the optimized nitrous oxide emission load data of the ith sub-basin, K 0 is the sum of the initial nitrous oxide emission load data of each sub-basin, The second triangular fuzzy number associated with the nitrous oxide emission load data, σ K Respectively The upper bound and median of ;

[0173] S502: converting the fuzzy nitrogen emission reduction optimization configuration model into a deterministic model as the final nitrogen emission reduction optimization configuration model.

[0174] In this embodiment, the optimization device combines fractional programming (FP) and fuzzy credibility chance-constrained programming (FCCP) to convert the first triangular fuzzy number in the fuzzy fractional programming model into a first triangular definite number, and the second triangular fuzzy number into a second triangular definite number, thereby converting the fuzzy fractional programming model into a deterministic model as the nitrogen emission reduction optimization configuration model, wherein the final nitrogen emission reduction optimization configuration model includes a second cost-effectiveness objective function, an optimization constraint on the improvement rate of the total nitrogen emission load of non-point sources in water bodies, and an optimization constraint on the improvement rate of the nitrous oxide emission load, wherein the optimization constraint condition for the improvement rate of the total nitrogen emission load of non-point sources in water bodies is:

[0175]

[0176] The constraint condition for optimizing the improvement rate of nitrous oxide emission load is:

[0177]

[0178] In an optional embodiment, the optimization device uses a PS (Pattern Search) algorithm to solve the nitrogen emission reduction optimization configuration model, and obtains the target basin nitrogen emission reduction control scheme from the various basin nitrogen emission reduction control schemes, wherein the PS algorithm is an optimization method that does not require any objective function gradient information and can handle optimization problems with nonlinear, linear and boundary constraints. The optimization process of the PS algorithm starts from a given initial point (i.e., base point), and each iteration needs to consider three stages, i.e., grid, query, and expansion / contraction, and the PS algorithm includes a grid generation algorithm, an expansion algorithm, and a contraction algorithm.

[0179] The grid generation algorithm is:

[0180] y m +Δ m ×{Ω i}

[0181] In the formula, y m is the current base point; Δ m is the grid size; {Ω i} is the pattern vector.

[0182] In the grid stage, the optimization device uses a preset pattern vector and grid size according to the grid generation algorithm in each iteration, takes the base point as the center, obtains a grid area associated with the grid size, searches within the grid area, obtains several neighboring points, and constructs a target grid point set based on the base point and the neighboring points.

[0183] In the query phase, the optimization device obtains the function values ​​of the base point in the target grid point set and the neighboring points corresponding to the base point, and compares the function value of the base point with the function value of the neighboring points corresponding to the base point respectively. If the function value of the base point is less than the function value of any neighboring point corresponding to the base point, a query success result is obtained, and the neighboring point is used as the base point for the next iteration; if the function value of the base point is greater than or equal to the function value of any neighboring point corresponding to the base point, a query failure result is obtained, and the base point is used as the base point for the next iteration;

[0184] The optimization device executes the expansion phase or the contraction phase in response to the execution instruction according to the query success result, thereby solving the nitrogen emission reduction optimization configuration model and obtaining the target basin nitrogen emission reduction control scheme from the various basin nitrogen emission reduction control schemes, wherein the expansion algorithm is Δ m+1 =β e ×Δ m , β e is the expansion factor; the contraction algorithm is Δ m+1 =β c ×Δ m , β c is the reduction factor.

[0185] Please refer to Figure 8 , Figure 8 A schematic diagram of the structure of an optimization device for a watershed nitrogen emission reduction control scheme provided in one embodiment of the present application. The device can implement all or part of the optimization device for a watershed nitrogen emission reduction control scheme through software, hardware, or a combination of both. The device 8 includes:

[0186] A data acquisition module 81 is used to acquire spatial data and attribute data of a target area, wherein the spatial data includes elevation data, land use data, soil distribution data and soil slope data, and the attribute data includes meteorological attribute data and soil attribute data;

[0187] A hydrological model building module 82 is used to build a river network of the target area based on the elevation data, divide the river network into a plurality of sub-watersheds, divide the sub-watersheds into a plurality of hydrological response units according to the land use data, soil distribution and soil slope data corresponding to each sub-watershed, and build a hydrological model associated with the target area;

[0188] The first discharge load data calculation module 83 is used to input the meteorological attribute data and soil attribute data into the hydrological model, and obtain the initial water body non-point source total nitrogen annual discharge load data and initial nitrous oxide discharge load data corresponding to each sub-basin output by the hydrological model;

[0189] The second emission load data calculation module 84 is used to obtain several kinds of watershed nitrogen emission reduction control schemes, and obtain the optimized water body non-point source total nitrogen annual emission load data and optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes according to the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin;

[0190] The optimization module 85 is used to construct a nitrogen emission reduction optimization configuration model based on the optimized annual total nitrogen emission load data of non-point sources of water bodies and the optimized nitrous oxide emission load data, and obtain the target basin nitrogen emission reduction control plan from the various basin nitrogen emission reduction control plans based on the nitrogen emission reduction optimization configuration model.

[0191] In an embodiment of the present application, spatial data and attribute data of a target area are acquired through a data acquisition module, wherein the spatial data include elevation data, land use data, soil distribution data and soil slope data, and the attribute data include meteorological attribute data and soil attribute data; a hydrological model construction module is used to construct a river basin network of the target area based on the elevation data, divide the river basin network into a number of sub-basins, divide the sub-basins into a number of hydrological response units according to the combined data of land use data, soil distribution and soil slope data corresponding to each sub-basin, and construct a hydrological model associated with the target area; the meteorological attribute data and soil attribute data are input into the hydrological model through a first emission load data calculation module to obtain the hydrological model input. The initial annual non-point source total nitrogen emission load data of water bodies and the initial nitrous oxide emission load data corresponding to each sub-basin are obtained; through the second emission load data calculation module, several kinds of basin nitrogen emission reduction control schemes are obtained, and according to the initial annual non-point source total nitrogen emission load data of water bodies and the initial nitrous oxide emission load data corresponding to each sub-basin, the optimized annual non-point source total nitrogen emission load data of water bodies and the optimized nitrous oxide emission load data corresponding to each sub-basin under various basin nitrogen emission reduction control schemes are obtained; through the optimization module, according to the optimized annual non-point source total nitrogen emission load data of water bodies and the optimized nitrous oxide emission load data, a nitrogen emission reduction optimization configuration model is constructed, and according to the nitrogen emission reduction optimization configuration model, the target basin nitrogen emission reduction control scheme is obtained from the various basin nitrogen emission reduction control schemes. It can analyze various river basin nitrogen emission reduction control plans by integrating the annual non-point source total nitrogen emission load data of the target area and the nitrous oxide emission load data, solve the limitations caused by optimization based on experience, optimize the river basin nitrogen emission reduction control plan, and improve the accuracy and efficiency of the optimization of the river basin nitrogen emission reduction control plan.

[0192] Please refer to Fig. 9 , Fig. 9 The computer device 9 is a schematic diagram of a structure of a computer device provided in an embodiment of the present application. The computer device 9 includes: a processor 91, a memory 92, and a computer program 93 stored in the memory 92 and executable on the processor 91; the computer device may store a plurality of instructions, which are suitable for being loaded and executed by the processor 91 Figures 1 to 7 The method steps of the embodiment shown in the figure can be found in the specific implementation process. Figures 1 to 7 The specific description of the illustrated embodiment will not be repeated here.

[0193] Among them, the processor 91 may include one or more processing cores. The processor 91 uses various interfaces and lines to connect various parts in the server, and executes various functions and processes data of the optimization device 8 of the watershed nitrogen emission reduction control scheme by running or executing instructions, programs, code sets or instruction sets stored in the memory 92, and calling the data in the memory 92. Optionally, the processor 91 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programble Logic Array, PLA). The processor 91 can integrate one or more combinations of a central processing unit 91 (Central Processing Unit, CPU), an image processor 91 (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the touch display; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 91, and it can be implemented by a single chip.

[0194] Among them, the memory 92 may include a random access memory 92 (Random Access Memory, RAM), and may also include a read-only memory 92 (Read-Only Memory). Optionally, the memory 92 includes a non-transitory computer-readable storage medium. The memory 92 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 92 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 92 may also be optionally at least one storage device located away from the aforementioned processor 91.

[0195] The present application also provides a storage medium that can store multiple instructions, which are suitable for the processor to load and execute the above-mentioned Figures 1 to 7 The method steps of the embodiment shown in the figure can be found in the specific implementation process. Figures 1 to 7 The specific description of the illustrated embodiment will not be repeated here.

[0196] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0197] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0198] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0199] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0200] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0201] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0202] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc.

[0203] The present invention is not limited to the above-mentioned embodiments. If various changes or modifications to the present invention do not depart from the spirit and scope of the present invention, and if these changes and modifications fall within the scope of the claims and equivalent technologies of the present invention, the present invention is also intended to include these changes and modifications.

Claims

1. A method for optimizing nitrogen emission reduction in a watershed, characterized in that: The following steps are involved: Acquire spatial data and attribute data of the target area, wherein the spatial data includes elevation data, land use data, soil distribution data and soil slope data, and the attribute data includes meteorological attribute data and soil attribute data; the elevation data is a digital elevation model, which represents the digitized elevation information of the ground terrain, and the land use data reflects the division of land use types; the soil distribution data refers to the distribution of soil types; the meteorological attribute data is a set of data reflecting the weather; and the soil attribute data is a set of data reflecting the properties of the soil; Based on the elevation data, construct a river network of the target area, divide the river network into several sub-basins, divide the sub-basins into several hydrological response units according to the combined data of land use data, soil distribution and soil slope data corresponding to each sub-basin, and construct a hydrological model associated with the target area, wherein the hydrological model is a SWAT model, which is used to simulate the spatiotemporal distribution of nitrogen pollution in the target area; The meteorological attribute data and the soil attribute data are input into the hydrological model, and the soil temperature data corresponding to each sub-basin is obtained according to the meteorological attribute data, the soil attribute data and the soil temperature data acquisition method, wherein the soil temperature data acquisition method is to obtain the soil temperature data according to the following formula: Where, T soil (z,d n ) is the soil temperature data, indicating the dth day of the year n Soil temperature data at soil depth z on the day; λ represents the hysteresis coefficient; df is the depth factor; is the annual average temperature data in the meteorological attribute data; T ssurf The temperature data of the soil surface layer on that day in the soil attribute data; According to the meteorological attribute data, soil attribute data and runoff data acquisition method, the runoff data corresponding to each sub-basin is obtained, wherein the runoff data includes soil moisture data and surface runoff data, and the runoff data acquisition method is to obtain the runoff data according to the following formula, including soil moisture equation, soil initial moisture equation, surface runoff equation, lateral water flow equation and regression flow equation, wherein the soil moisture equation is: Where SW t is the soil moisture data; SW0 is the initial soil moisture content on the ith day; t represents time; R day is the precipitation on the i-th day in the meteorological attribute data; Q surf is the surface runoff on the i-th day; E a is the evapotranspiration of the i-th day in the meteorological attribute data; W seep is the amount of infiltration water and bypass water leaving the bottom of the soil profile on day i; Q gw is the water volume of the return flow on the i-th day; The surface runoff equation is: Where S is the retention parameter; The initial soil moisture content equation is: SW0=FC·FFCB In the formula, FC is the field water holding capacity; FFCB is the ratio of initial soil water content to field water holding capacity; The lateral water flow equation is: In the formula, w perc,ly＝n is the amount of water that seeps out of the bottom layer of the soil on the i-th day; w crk,btm is the bypass water flow through the lower boundary of the soil on the i-th day; crk ly Indicates the amount of cracks in the soil layer; ly indicates the soil layer; crk ly＝nn is the amount of cracks in the deepest soil layer in the soil attribute data; depth ly＝nn is the deepest soil layer depth in the soil attribute data; n is the number of soil layers in the soil attribute data; in, In the formula, crk max,ly is the maximum cracking amount of the soil layer; crk max is the potential cracking amount of the soil profile in the soil attribute data; depth ly is the soil layer depth in the soil attribute data; coef crk is the adjustment coefficient of dry fissure water flow; FC ly SW is the field water holding capacity of the soil layer; ly is the soil moisture content of the soil layer; in, Where SW ly,excess is the drainable volume stored in the soil layer, when SW ly >FC ly When SW ly,excess =SW ly -FC ly ; When SW ly ≤FC ly When SW ly,excess =0; Δt is the time step; K sat is the saturated permeability coefficient, ρ s is the particle density; ρ b is the soil layer bulk density in the soil attribute data; in, In the formula, m c is the clay content in the soil attribute data; AWC ly Indicates effective water content; The regression flow equation is: In the formula, aq sh 、aq shthr,q are the first water level threshold and the second water level threshold of the shallow aquifer when the groundwater flows into the main river; Q gw,i , Q gw,i-1 are the water volume of the return flow on the i-th day and the i-1-th day respectively; a gw is the base flow retreat constant, w rchrg is the total recharge of the aquifer; β deep is the permeability coefficient of the aquifer; in, w rchrg,i =(1-exp[-1 / δ gw ])·w seep +exp[-1 / δ gw ]·w rchrg,i-1 In the formula, w rchrg,i is the total recharge of the aquifer on day i, δ gw delay in recharging the aquifer; Based on the hydrological response unit, the soil water nitrate concentration data corresponding to each sub-basin is obtained according to the soil property data and the nitrogen migration equation, wherein the nitrogen migration equation includes the soil water nitrate concentration equation, the soil nitrate content equation and the soil flow water equation, wherein the soil water nitrate concentration equation is: In the formula, is the nitrate concentration data of soil and water; NO 3conc is the soil nitrate content; w mobile is the soil flow water volume; θ e is the pore ratio data for excluding anions; The soil nitrate content equation is: In the formula, NO 3conc,z is the nitrate content at soil depth z; SAT ly is the saturated water content in the soil attribute data; φ soil is the total porosity in the soil property data; The soil flow water equation is: Where f1 is the soil flow water calculation algorithm for the top 10 mm soil layer, f2 is the soil flow water calculation algorithm for the soil layer below 10 mm, Q lat,ly It indicates the amount of water flowing out of this layer through lateral flow on a certain day; in, Where slp is the average slope of each sub-basin in the soil slope data; φ d is the effective porosity of the soil layer in the soil attribute data; L hill is the slope length in the soil slope data; According to the soil property data, the soil water body nitrate concentration data corresponding to each sub-basin and the surface runoff nitrate emission load data acquisition method, the surface runoff nitrate emission load data corresponding to each sub-basin is acquired, wherein the surface runoff nitrate emission load data acquisition method is to acquire the surface runoff nitrate emission load data according to the following formula: In the formula, NO 3surf The nitrate discharge load data for said surface runoff; is the seepage coefficient of nitrate; is the soil water nitrate concentration data; According to the soil property data, the soil water body nitrate concentration data corresponding to each sub-basin and the lateral flow nitrate discharge load data acquisition method, the lateral flow nitrate discharge load data corresponding to each sub-basin is acquired, wherein the lateral flow nitrate discharge load data acquisition method is to acquire the lateral flow nitrate discharge load data according to the following formula: Where, f3 is the calculation algorithm for lateral flow nitrate discharge load of the soil layer with a surface area of ​​10 mm, and f4 is the calculation algorithm for lateral flow nitrate discharge load of the soil layer below the surface area of ​​10 mm; NO 3lat,ly is the side stream nitrate discharge load; According to the soil property data, the soil water body nitrate concentration data corresponding to each sub-basin and the method for obtaining the groundwater nitrate discharge load data, the groundwater nitrate discharge load data corresponding to each sub-basin is obtained, wherein the method for obtaining the groundwater nitrate discharge load data is to obtain the groundwater nitrate discharge load data according to the following formula: In the formula, NO 3perc,ly Groundwater nitrate discharge loading data for the target area; According to the soil property data and the method for obtaining the organic nitrogen emission load data corresponding to each sub-watershed, the organic nitrogen emission load data corresponding to each sub-watershed is obtained, wherein the method for obtaining the organic nitrogen emission load data is to obtain the organic nitrogen emission load data according to the following formula: In the formula, orgN surf is the organic nitrogen emission load data; sed represents the sediment yield on a certain day; A HRU is the area of ​​the hydrological response unit; org N is the concentration of organic nitrogen in the soil surface layer, where In the formula, rsd surf is the residue content in the top 10 mm of soil; orgC surf is the organic carbon content in the humus of the soil layer in the soil attribute data; According to the nitrogen emission load data corresponding to each sub-basin and the total nitrogen emission load data calculation algorithm, the initial water body non-point source total nitrogen annual emission load data corresponding to each sub-basin is obtained, wherein the total nitrogen emission load data calculation algorithm is: NPS_TN=orgN surf +NO 3surf +NO 3lat,ly +NO 3perc,ly Where, NPS_TN is the annual discharge load data of total nitrogen from non-point sources in the initial water body, orgN surf The organic nitrogen emission load data, NO 3surf The nitrate discharge load data for surface runoff, NO 3lat,ly The sidestream nitrate discharge loading data, NO 3perc,ly The groundwater nitrate discharge load data; According to the hydrological data corresponding to each sub-basin, the annual total nitrogen emission load data of the initial water body non-point source and the soil nitrous oxide emission load calculation algorithm, the soil nitrous oxide emission load data corresponding to each sub-basin is obtained, wherein the soil nitrous oxide emission load calculation algorithm is: N2O soil =-6.519+1.075×SN+0.246×T soil (z,d n )+0.12×SW t In the formula, N2O soil The soil nitrous oxide emission load data; According to the soil nitrous oxide emission load data corresponding to each sub-basin, the hydrological response unit corresponding to the sub-basin and the nitrous oxide emission load calculation algorithm, the initial nitrous oxide emission load data corresponding to each sub-basin is obtained, wherein the nitrous oxide emission load calculation algorithm is: In the formula, N2O SUB,i is the soil nitrous oxide emission load data corresponding to the i-th sub-basin; i is the sub-basin number; k is the hydrological response unit number; N2O HRU,k is the nitrous oxide emission load data of the kth hydrological response unit; A HRU,k is the area of ​​the kth hydrological response unit; A SUB,i is the area of ​​the ith sub-basin; Obtain several watershed nitrogen emission reduction control schemes, and obtain the optimized water body non-point source total nitrogen annual emission load data and optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes according to the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin; According to the optimized annual total nitrogen emission load data of non-point sources in water bodies and the optimized nitrous oxide emission load data, a fuzzy nitrogen emission reduction optimization configuration model is constructed, wherein the fuzzy nitrogen emission reduction optimization configuration model includes a cost-effectiveness objective function, an initial water body non-point source total nitrogen emission load improvement rate constraint and an initial nitrous oxide emission load improvement rate constraint, wherein the cost-effectiveness objective function is: Where max_f is the cost-effectiveness data corresponding to the various basin nitrogen emission reduction control schemes, i is the sub-basin number, i = 1, 2, ..., m, j is the BMPS type, j = 1, 2, ..., n, N i,0 is the initial water body non-point source total nitrogen annual discharge load data of the ith sub-basin, N i is the optimized annual total nitrogen discharge load data of non-point sources in water bodies of the ith sub-basin, X i,j is the first decision variable, B i,j is the second decision variable, which indicates the implementation scale of the j-th basin nitrogen emission reduction control scheme in the i-th sub-basin; U j represents the unit cost of the j-th basin nitrogen emission reduction control scheme; The initial water body non-point source total nitrogen emission load improvement rate constraint condition is: Where Cr is the fuzzy credibility programming function, N0 is the sum of the initial annual total nitrogen discharge load data of non-point sources in each sub-basin, is the first triangular fuzzy number associated with the total nitrogen discharge load data from non-point sources in water bodies, σ N Respectively The upper bound and median of , λ is the confidence level parameter; The initial nitrous oxide emission load improvement rate constraint is: In the formula, K i (X i,j ,B i,j ) is the optimized nitrous oxide emission load data of the ith sub-basin, K0 is the sum of the initial nitrous oxide emission load data of each sub-basin, The second triangular fuzzy number associated with the nitrous oxide emission load data, σ K Respectively The upper bound and median of ; The fuzzy nitrogen emission reduction optimization configuration model is converted into a deterministic model as the final nitrogen emission reduction optimization configuration model, wherein the final nitrogen emission reduction optimization configuration model includes a second cost-effectiveness objective function, an optimization constraint on the improvement rate of the total nitrogen emission load of non-point sources in water bodies, and an optimization constraint on the improvement rate of the nitrous oxide emission load, wherein the optimization constraint on the improvement rate of the total nitrogen emission load of non-point sources in water bodies is: The constraint condition for optimizing the improvement rate of nitrous oxide emission load is: According to the final nitrogen emission reduction optimization configuration model, a nitrogen emission reduction control plan for the target watershed is obtained, and nitrogen emission reduction control is performed on the watershed river network in the target area according to the nitrogen emission reduction control plan for the target watershed.

2. The method for optimizing nitrogen emission reduction in a watershed according to claim 1, characterized in that: Also includes the steps: Obtain the observed values ​​of the hydrological data and the nitrogen emission load data, and verify the hydrological model using a verification algorithm according to the hydrological data, the nitrogen emission load data and the corresponding simulation values ​​output by the hydrological model of the target area, and obtain the verified hydrological model, wherein the verification algorithm is: In the formula, E NS is the efficiency coefficient; t is the unit time, T is the time length; O t is the corresponding observation value at time t, P t is the simulated value of the hydrological data and nitrogen emission load data output by the hydrological model corresponding to the tth moment; is the average value of the observed values; R 2 is the coefficient of certainty; is the average value of the simulation values.

3. An optimization device applied to the basin nitrogen emission reduction optimization method according to any one of claims 1 to 2, characterized in that: include: A data acquisition module is used to acquire spatial data and attribute data of a target area, wherein the spatial data includes elevation data, land use data, soil distribution data and soil slope data, and the attribute data includes meteorological attribute data and soil attribute data; the elevation data is a digital elevation model, which represents the digital elevation information of the ground terrain; the land use data reflects the division of land use types; the soil distribution data refers to the distribution of soil types; the meteorological attribute data is a set of data reflecting the weather; and the soil attribute data is a set of data reflecting the properties of the soil; A hydrological model construction module, for constructing a river network of the target area based on the elevation data, dividing the river network into a plurality of sub-basins, dividing the sub-basins into a plurality of hydrological response units according to the land use data, soil distribution and soil slope data corresponding to each sub-basin, and constructing a hydrological model associated with the target area, wherein the hydrological model is a SWAT model, and is used to simulate the spatiotemporal distribution of nitrogen pollution in the target area; A first emission load data calculation module is used to input the meteorological attribute data and soil attribute data into a hydrological model, and obtain the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin output by the hydrological model; The second emission load data calculation module is used to obtain several kinds of watershed nitrogen emission reduction control schemes, and obtain the optimized water body non-point source total nitrogen annual emission load data and optimized nitrous oxide emission load data corresponding to each sub-basin under various watershed nitrogen emission reduction control schemes according to the initial water body non-point source total nitrogen annual emission load data and initial nitrous oxide emission load data corresponding to each sub-basin; The optimization module is used to construct a nitrogen emission reduction optimization configuration model based on the optimized annual non-point source total nitrogen emission load data of the water body and the optimized nitrous oxide emission load data, and obtain the target basin nitrogen emission reduction control plan from the various basin nitrogen emission reduction control plans based on the nitrogen emission reduction optimization configuration model.

4. A computer device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the method for optimizing nitrogen emission reduction in a watershed as described in any one of claims 1 to 2 are implemented.

5. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for optimizing nitrogen emission reduction in a watershed according to the resource management method based on a neural network model as described in any one of claims 1 to 2 are implemented.

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