A method for evaluating nitrogen interception capacity of rural rivers in plain river network areas

Abstract

The present invention relates to a method for assessing the nitrogen interception capacity of rural rivers in plain river networks. To address the unclear nitrogen interception capacity of rural rivers in plain river networks, a river nitrogen cycle model (River-N) was developed that incorporates aquatic plants and biogeochemical cycles. Coupled with the existing EFDC (Effluent Three-Dimensional Hydrodynamic Model) and the NDP (Polder Nitrogen Cycle Model), the model simulates the input, output, migration, and transformation of three forms of nitrogen (particulate nitrogen, ammonia nitrogen, and nitrate nitrogen) in rural rivers, exploring the source-sink balance of nitrogen and quantitatively assessing the nitrogen interception capacity of rural rivers in plain river networks. This method integrates simulation techniques for river network hydrodynamics, biogeochemical cycles, polder hydrology, and nitrogen loss, fully accounting for the unique characteristics of slow flow and widespread aquatic plants in rural rivers in plain river networks. This method addresses the challenge of accurately estimating nitrogen interception in rural rivers in plain river networks, providing technical support for the treatment and management of nitrogen pollution in rural rivers in these regions.

Description

Technical Field

[0001] The present invention belongs to the technical field of water environment health assessment, and specifically relates to a method for evaluating the nitrogen interception capacity of plain rural rivers by combining a multi-scale model. Background Art

[0002] Plain river network areas are widely distributed in the middle and lower reaches of rivers around the world, such as the Yangtze River, the Mekong River, and most parts of the Netherlands. They are characterized by flat terrain, crisscrossing rivers, highly developed river networks, widespread polder areas, and significant impacts from human activities. Currently, a large number of studies are dedicated to exploring patterns of nitrogen reduction in regional water bodies. Among them, rural rivers are considered to be the "capillaries" of plain river network areas and have significant nitrogen interception potential. However, the intensity of human activities around rural rivers in plain river network areas is high, and there are many sources of nitrogen (drainage of farmland in polder areas, water changes in surrounding fish ponds, influx of peripheral rivers, etc.). The migration and transformation process is complex, making it difficult to accurately assess nitrogen interception capacity. This is a difficult problem that needs to be urgently solved in the practice of nitrogen pollution prevention and control.

[0003] Hydrodynamic-water quality models (MIKE11, EFDC, etc.) can systematically simulate the migration and transformation of river nitrogen and are currently an important method for assessing the nitrogen interception capacity of rivers. However, these methods lack consideration of macrophyte components and cannot account for the biogeochemical cycles of different forms of nitrogen under the action of macrophytes. Therefore, they are not suitable for rural rivers in plain river networks with dense macrophytes, and new technical methods are urgently needed. Summary of the Invention

[0004] The purpose of the present invention is to fill the gap in the existing technology and develop a river nitrogen cycle model (River-N) that covers aquatic plants and biogeochemical cycles. It couples the existing three-dimensional hydrodynamic model of the river network (EFDC) and the polder nitrogen cycle model (NDP) to finely simulate the source and sink, consumption and retention of nitrogen, and form a nitrogen interception capacity assessment method suitable for rural rivers in plain river network areas.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for evaluating the nitrogen interception capacity of rural rivers in plain river networks, comprising:

[0007] Based on the three-dimensional hydrodynamic model (EFDC), the water exchange between rural rivers and peripheral rivers in the plain river network area is simulated, that is, the water input and output between rural rivers and peripheral rivers in the plain river network area;

[0008] The polder nitrogen cycle model (NDP) simulates the water and nitrogen exchange flux between rural rivers in plain river networks and polder areas, namely the impact of polder irrigation, flood drainage, and culvert water diversion on river nitrogen cycle processes. The nitrogen mentioned includes particulate nitrogen, ammonia nitrogen, and nitrate nitrogen.

[0009] Establish a river nitrogen cycle model (River-N) that includes aquatic plants and biogeochemical cycles. The governing equations of the river nitrogen cycle model include the aquatic plant growth and destruction processes.

[0010] Based on the simulation results of the three-dimensional hydrodynamic model and the polder nitrogen cycle model, the boundary conditions of the river (such as the confluence of the main river channel, the material exchange between the polder and the river, etc.) were determined and input into the river nitrogen cycle model to simulate the daily dynamic changes of nitrogen in rural rivers in the plain river network area and evaluate the nitrogen interception capacity of rural rivers in the plain river network area.

[0011] The method of the present invention, based on the three-dimensional hydrodynamic model, simulates the water exchange between rural rivers and peripheral rivers in the plain river network area. The specific process includes:

[0012] Collect meteorological and hydrological monitoring data, including meteorological data such as daily data on solar radiation and rainfall, and hydrological data such as daily data on river water levels;

[0013] Sorting out the complex river network in the plain river area, designing the generalized model of river grids and cross sections, that is, determining the size and shape of the grid unit, which serves as the smallest basic calculation unit in the three-dimensional hydrodynamic model;

[0014] Clarify the type and input mode of the model boundary conditions, input the collected time series monitoring data, and test and select the spatial resolution and time step that are suitable for the model;

[0015] Design simulation scenarios of typical meteorological and hydrological conditions, simulate the water flow direction of grid cells, and calculate the water exchange between rivers and surrounding river networks.

[0016] The simulation of water exchange and nitrogen exchange flux between rural rivers and polder areas in plain river networks based on the NDP polder area nitrogen cycle model includes:

[0017] Based on the Nitrogen Development Platform (NDP) model of the polder area, a parameterized representation method for artificially controlled hydrological processes in the polder area was designed to simulate and depict the unique characteristics of the hydrological-nitrogen cycle in the polder area, including the migration and transformation of nitrogen in the "four waters" (atmospheric water, surface water, soil water, and groundwater), drainage by sluice pumps, and nitrogen interception in ditches and ponds under hydrological drive.

[0018] Quantitatively evaluate the water and nitrogen exchange flux between the polder area and the river, including the amount of water pumped for irrigation, flood drainage, and culvert water diversion in the polder area, and determine the amount of nitrogen exchange brought about by the above water exchange.

[0019] The polder area described in the present invention refers to a relatively closed artificial water collection unit formed by embankment and reclamation in the flood-prone areas of the plains in the downstream of the basin, that is, a fragmented basin in the plain river network area. It is widely distributed in the coastal areas along the Yangtze River, Mekong River, Rhine River, Danube River, Mississippi River and other major rivers in the world, among which the plain river network area of ​​Taihu Lake Basin is particularly widely distributed; nitrogen includes three forms of nitrogen (particulate nitrogen, ammonia nitrogen, and nitrate nitrogen), and total nitrogen is the sum of the concentrations of the three forms of nitrogen, and the concentration unit is mg / L.

[0020] Due to the widespread distribution of large aquatic plants in plain rural rivers, the key processes affecting river nitrogen interception are identified. Therefore, the present invention focuses on the role of large aquatic plants in river nitrogen interception and designs a river nitrogen cycle model (River-N) covering aquatic plants and biogeochemical cycles. It quantitatively simulates multi-scale processes such as river hydrodynamics, nitrogen exchange between the water-soil and water-air interface, nitrogen biogeochemical processes, and the growth and death of large aquatic plants. The above processes cover the key processes of river nitrogen interception; the nitrogen exchange between the water-soil and water-air interface includes the release of nitrogen to the overlying water body caused by the concentration difference between the bottom sediment and the interstitial water, the resuspension of particulate nitrogen caused by water disturbance, and the natural sedimentation of particulate nitrogen; the nitrogen biogeochemical process includes the conversion between different forms of nitrogen such as nitrification and denitrification, as well as the nitrogen absorption of aquatic plants. Compared with the mainstream river model (MIKE21, etc.), the river nitrogen cycle model of the present invention increases the generalization of the impact of aquatic plants on the river nitrogen cycle, including: aquatic plant growth and disappearance processes, etc., and improves the applicability of the model in rivers with widespread distribution of large aquatic plants.

[0021] This model (River-N) primarily describes the migration and transformation of three forms of nitrogen. Nitrate nitrogen sources primarily include nitrification in water bodies and atmospheric deposition. Ammonia nitrogen sources primarily include atmospheric deposition, sediment release, plant decay, and mineralization. Particulate nitrogen sources primarily include atmospheric deposition, plant decay, assimilation, and resuspension of particulate nitrogen in sediments.

[0022] The nitrogen interception capacity of rural rivers in plain river network areas mentioned in the present invention refers to the nitrogen retention flux of the river, including natural sedimentation, denitrification, aquatic plant absorption, etc.

[0023] As a preferred implementation method of a scheme, the control equation describing the growth and decay process of aquatic plants is as follows:

[0024] BSH T =BSH T-ΔT +((1-K STR )k SHOOTGrow f Uptake f PLT -K SHOOTDec f SHOOTDecT )BSH T

[0025] BRO T =BRO T-ΔT +K STR K SHOOTGrow f Uptake f PLT BSH T -K ROOTDec f ROOTDecT BRO T

[0026]

[0027]

[0028]

[0029]

[0030] Where T represents the time, ΔT represents the time step, BSH T represents the aboveground biomass of aquatic plants, K STR Indicates the proportion of aquatic plants transferred from the ground to the root system, k SHOOTGrow represents the maximum growth rate of the aboveground part of aquatic plants under optimal conditions, f Uptake represents the nitrogen limitation of aquatic plants, f PLT Indicates the temperature limit for aquatic plant growth, K SHOOTDec represents the maximum growth rate of the aboveground part of aquatic plants under optimal conditions, f SHOOTDecT Indicates the temperature limit for the decay of the above-ground parts of aquatic plants, BRO T Indicates the biomass of underground parts of aquatic plants, KH Uptake The half-saturation constant of nitrogen absorption by aquatic plants, K ROOTDec represents the metabolic rate of the root system at the reference temperature, f ROOTDecT Indicates the temperature limit for root decay of aquatic plants, NH T Indicates the concentration of ammonia nitrogen in surface water, NO T represents the concentration of nitrate nitrogen in surface water, θ PL Indicates the effect of temperature on the growth of aquatic plants. represents the surface water temperature, T PL1 、T PL2 represents the lower and upper limits of the optimal temperature for aquatic plant growth, θ SHOOTDec Indicates the effect of temperature on the metabolic rate of the aboveground parts of aquatic plants. represents the daily average water temperature, θ ROOTDec Represents the effect of temperature on the metabolic rate of aquatic plant roots.

[0031] As a preferred implementation scheme, the horizontal coordinate reference of the three-dimensional hydrodynamic model is rectangular coordinates or orthogonal curvilinear coordinates, and the space is discretized using staggered grids. The time integral adopts the second-order precision finite difference method combined with the internal and external mode splitting technology, that is, the internal module of shear stress or oblique pressure and the external model of free surface gravity wave or normal pressure are quickly calculated separately; the external module adopts a semi-implicit calculation method, which allows a larger time step and can adopt an adaptive time step mode. The internal module adopts an implicit format of vertical diffusion, and the dry-wet grid technology is adopted in the floodplain area.

[0032] The meteorological monitoring data refers to indicators such as daily rainfall, daily average temperature, daily maximum temperature, daily minimum temperature, and daily average humidity; the hydrological monitoring data refers to water level; and the water quality monitoring data refers to indicators such as total nitrogen, particulate nitrogen, ammonia nitrogen, and nitrate nitrogen.

[0033] As a preferred implementation scheme, the method also includes verifying the model based on measured meteorological, hydrological and water quality monitoring data, calibrating and calibrating model parameters, and improving the model simulation accuracy.

[0034] Furthermore, the model verification adopts the global sensitivity analysis method MOAT (Morris one at a time) to identify the key parameters of the model, construct an intelligent optimization model of the model parameters (genetic algorithm combined with super Latin square sampling), obtain the optimal parameter set of the model, and improve the model simulation accuracy.

[0035] Furthermore, based on the measured meteorological, hydrological, and water quality monitoring data, the simulated values ​​and measured values ​​of indicators such as total nitrogen, particulate nitrogen, ammonia nitrogen, and nitrate nitrogen were compared, and the Nash efficiency coefficient (Nash-Sutcliffe efficiency) was used to quantitatively evaluate the simulation effect of the model; the meteorological monitoring data referred to indicators such as daily rainfall, daily average temperature, daily maximum temperature, daily minimum temperature, and daily average humidity; the hydrological monitoring data referred to water level; and the water quality monitoring data referred to indicators such as total nitrogen, particulate nitrogen, ammonia nitrogen, and nitrate nitrogen.

[0036] As a preferred implementation scheme, the nitrogen interception capacity of rural rivers in plain river network areas is evaluated based on the nitrogen retention flux of rivers.

[0037] Furthermore, the nitrogen retention flux of the river includes quantified fluxes of natural sedimentation of particulate nitrogen, denitrification, anaerobic ammonium oxidation, and aquatic plant absorption processes.

[0038] This study integrates simulation technologies for river network hydrodynamics, biogeochemical cycles, polder hydrology, and nitrogen loss. By developing a river nitrogen cycle model (River-N) that encompasses aquatic plants and biogeochemical cycles, coupled with the existing three-dimensional river network hydrodynamic model (EFDC) and polder nitrogen cycle model (NDP), it simulates the input, output, and migration and transformation processes of three forms of nitrogen (particulate nitrogen, ammonia nitrogen, and nitrate nitrogen) in rural rivers, explores the source-sink balance of nitrogen, and quantitatively assesses the nitrogen interception capacity of rural rivers in plain river networks. The mechanism and method of this study will provide key technical support for the treatment and management of nitrogen pollution in rural rivers, which are widely distributed in the middle and lower reaches of plain river networks.

[0039] The beneficial effects of the present invention are: (1) providing a quantitative means for calculating the nitrogen source-sink law of plain rural rivers, providing technical support for identifying key nitrogen sources in rivers; (2) providing a quantitative method for nitrogen interception law of plain rural rivers, which is conducive to accurately identifying the main controlling factors of nitrogen interception in rivers; (3) providing a prediction of future changes in the nitrogen interception capacity of plain rural rivers, which can predict the changes in nitrogen interception capacity under different engineering schemes and support the optimization of nitrogen pollution prevention and control schemes. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flow chart of the method of the present invention is shown.

[0041] Figure 2 Shown is the location of Jiangjiahe and surrounding land use.

[0042] Figure 3 The water exchange between Jiangjia River and surrounding rivers (with and without dredging conditions) simulated by the 3D hydrodynamic model of the river network (EFDC) is shown.

[0043] Figure 4 The concentration changes of particulate nitrogen, ammonia nitrogen and nitrate nitrogen in Jiangjia River simulated by the river nitrogen cycle model (River-N) are shown (with and without dredging conditions).

[0044] Figure 5 The nitrogen source and sink characteristics of Jiangjia River under no dredging conditions (2020-2021) are shown.

[0045] Figure 6 The total nitrogen concentration changes in Jiangjia River (with and without dredging) simulated by the River Nitrogen Cycle Model (River-N) are shown.

[0046] Figure 7 The nitrogen source and sink characteristics of Jiangjia River under dredging conditions (2020-2021) are shown. DETAILED DESCRIPTION

[0047] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings and specific implementation methods.

[0048] Example 1

[0049] Example 1 Taking the calculation of nitrogen interception capacity in Jiangjiahe (Zhuzhen Town, Liyang City, Jiangsu Province) as an example, the method of the present invention is further explained.

[0050] This example uses the constructed river nitrogen cycle model (River-N) as a basis to conduct river meteorological, hydrological, and water quality monitoring (2020-2021). It simulates the input, output, and migration and transformation processes of the three forms of nitrogen in rivers, calculates nitrogen migration and transformation, input and output, and evaluates the nitrogen interception capacity of rivers. The dynamic nitrogen simulation of rural rivers in plain river networks is carried out in four steps:

[0051] (1) Jiangjiahe meteorological, hydrological and water quality monitoring

[0052] Jiangjia River is located in the western part of Taihu Lake Basin, a typical plain river network area in southeastern China. It is about 1130m long, with an average river width of about 24m and an average water depth of about 1.5m. It is a typical rural small river ( Figure 2 ). In this embodiment, the data used to build the evaluation model mainly include meteorological, water quality and water level data from 2020 to 2021. The meteorological data comes from the measured data in the Jianwei residential area near Jiangjiahe, including air pressure, precipitation, and temperature. The water quality data comes from the water quality monitoring of Jiangjiahe, surrounding rivers and fish ponds in the polder area. The monitoring indicators include total nitrogen (TN), ammonia nitrogen (NH4 + ) and nitrate (NO x ), particulate nitrogen (PN). The monitoring frequency is 1-2 months / time and is used for model verification.

[0053] (2) Calculation of water exchange between Jiangjia River and surrounding river networks

[0054] Given the flat terrain and complex water system of the Jiangjia River, a high spatial resolution grid was required to accurately simulate the movement of water flow between grid cells, as well as its channeling and rising processes. The computational domain of the Jiangjia River was gridded using a square grid with a 10m grid size for the hydrodynamic reaction units.

[0055] The EFDC model was used to simulate the hydrodynamic conditions of Jiangjia River and calculate the water exchange between Jiangjia River and surrounding river networks. The measured water level and precipitation data of Jiangjia River and surrounding rivers were input into the EFDC model with a simulation step of one day. The simulation results were processed to determine the daily input and output water volume between Jiangjia River and surrounding rivers in 2020-2021 ( Figure 3 ).

[0056] (3) Simulation of nitrogen source-sink balance process in Jiangjiahe

[0057] The nitrogen source-sink balance of Jiangjia River is influenced by both human activities in the surrounding polders and water exchange with surrounding rivers. Therefore, this example uses the River Nitrogen Cycle Model (River-N) to couple the River Network Three-Dimensional Hydrodynamic Model (EFDC) with the Polder Nitrogen Cycle Model (NDP) to simulate the nitrogen source-sink balance process in Jiangjia River. The NDP model is a model constructed in the applicant's previously published article, see "Towards the development of a modeling framework to track nitrogen export from lowland artificial watersheds (polders)."

[0058] The River Nitrogen Cycle Model (River-N) describes the migration and transformation of three forms of nitrogen. Nitrate nitrogen sources primarily include nitrification and atmospheric deposition in water bodies. Ammonia nitrogen sources primarily include atmospheric deposition, sediment release, plant decay, and mineralization. Particulate nitrogen sources primarily include atmospheric deposition, plant decay, assimilation, and resuspension of particulate nitrogen in sediments. Furthermore, denitrification, anaerobic ammonium oxidation, and plant uptake consume both nitrate and ammonia nitrogen. The governing equations include:

[0059] ①Total nitrogen;

[0060] ΔTN T =ΔPN T +ΔNH T +ΔNO T

[0061] ② Aquatic plant growth, that is, this application design introduces the control equation describing the growth and disappearance process of aquatic plants;

[0062] BSH T =BSH T-ΔT +((1-K STR )k SHOOTGrow f Uptake f PLT -K SHOOTDec f SHOOTDecT )BSH T

[0063] BRO T =BRO T-ΔT +K STR K SHOOTGrow f Uptake f PLT BSH T -K ROOTDec f ROOTDecT BRO T

[0064]

[0065]

[0066]

[0067]

[0068] ③ Particulate nitrogen;

[0069]

[0070] ④ Ammonia nitrogen;

[0071]

[0072] ⑤ Nitrate nitrogen;

[0073]

[0074] In the formula, T represents the time, ΔT represents the model running time step, TN T Indicates the total nitrogen concentration in water, PN T Indicates the concentration of particulate nitrogen in water, NO T Indicates the nitrate nitrogen concentration in water, NH T Indicates the ammonia nitrogen concentration in water. represents the concentration of particulate nitrogen resuspension, represents the ammonia nitrogen assimilation concentration, represents the nitrate assimilation concentration, Indicates the concentration of particulate nitrogen in plant decay, represents the concentration of atmospheric deposition particulate nitrogen, Indicates the concentration of particulate nitrogen deposited in water bodies; Indicates the ammonia nitrogen concentration caused by nitrification, Indicates the concentration of ammonia nitrogen absorbed by plants, Nitrate assimilation ammonia nitrogen concentration, Indicates the anaerobic ammonium oxidation ammonia nitrogen concentration, represents the nitrate nitrogen concentration due to denitrification, represents the atmospheric deposition ammonia nitrogen concentration, Indicates the concentration of ammonia nitrogen in plant decay; represents the atmospheric deposition nitrate nitrogen concentration, Indicates the concentration of nitrate nitrogen absorbed by plants, Indicates the anaerobic ammonium oxidation nitrate concentration.

[0075] The River Nitrogen Cycle Model (River-N) uses the output of the EFDC and NDP models as data drivers to simulate nitrogen concentrations in the Jiangjia River, influenced by the combined effects of water-nitrogen exchange with surrounding rivers and within the polder area. The resulting nitrogen concentrations are fed into the River Nitrogen Cycle Model (River-N), which characterizes the transformation and migration of nitrogen through various biogeochemical processes and calculates the fluxes of each process, ultimately simulating the nitrogen source-sink balance in the Jiangjia River.

[0076] The measured water level, water quality, and meteorological data of Jiangjiahe River and the dike area were input into a river nitrogen cycle model (River-N) with a simulation step of daily. Then, the global parameter sensitivity analysis method (MOAT) was used to identify the 10 more sensitive parameters in the river nitrogen cycle model (River-N). These 10 parameters were assigned reasonable parameter ranges. A genetic algorithm was used in combination with super Latin square sampling experiments to optimize the simulation accuracy of the mechanism model.

[0077] (4) Evaluation of nitrogen interception capacity of Jiangjiahe River

[0078] Step (2) of this embodiment determines the daily exchange water volume between Jiangjia River and surrounding rivers in 2020-2021 ( Figure 3 ), based on the nitrogen flux of each biogeochemical process established in step (3) of this embodiment, the nitrogen source, sink, consumption and retention flux of the biogeochemical process of Jiangjia River were statistically determined, and the nitrogen interception capacity of Jiangjia River was analyzed ( Figure 5 ).

[0079] Example 2

[0080] Example 2 takes the evaluation of the impact of sediment dredging on nitrogen interception capacity in Jiangjia River (Zhuzhen Town, Liyang City, Jiangsu Province) as an example to further illustrate the method of the present invention.

[0081] This example uses the constructed river nitrogen cycle model (River-N) as a basis to simulate the impact of sediment dredging on nitrogen migration and transformation, and evaluate the impact of sediment dredging on nitrogen interception capacity. The implementation is divided into four steps:

[0082] (1) Model generalization of Jiangjiahe sediment dredging

[0083] Taking the mud dredging project at the end of March 2020 as an example, the paper explains in detail how to use the model method of the present invention to evaluate the effect of improving or weakening the nitrogen source, sink, absorption and retention capacity of the river under dredging conditions.

[0084] The Taihu Lake Basin is a typical plain river network area in the Yangtze River Basin. Affected by human agricultural production and life activities, a large amount of nitrogen is transferred to the rivers, making rural rivers a key link in the regional nitrogen cycle. Due to the dense population and dense river network, the sources of these nitrogen are not only complex, but also widely distributed. The main sources are discharge from farmland in the embankment area, discharge from fish ponds, inflow from peripheral rivers, and atmospheric deposition. The discharge and transfer of nitrogen not only causes the deterioration of river water quality, but also eutrophication. Aquatic plants grow all over the river, leading to blockage of the river channel. The Jiangjia River channel is overgrown with aquatic plants ( Figure 2 In March 2020, Jiangjiahe River underwent sediment dredging.

[0085] Bottom sediment dredging has an important impact on the nitrogen cycle of rivers, which is mainly manifested in the reduction of aquatic organisms, the destruction of river aquatic habitats, and the reduction of nitrogen circulation rates in sediments, thereby changing the geobiochemical process of nitrogen, and thus affecting the change in nitrogen concentration in water bodies. However, the effect of dredging on river management is difficult to quantify and evaluate. The mechanism model method of the present invention can evaluate the effect of dredging on river management. By analyzing the role of rural small rivers in nitrogen sources, sinks, absorption and retention processes under dredging conditions, management decisions can be guided, and further nutrient loads can be absorbed to the maximum extent. The river nitrogen cycle model calculates the changes in the flux of each process by changing the parameters of the relevant biogeochemical processes, thereby realizing the simulation of the bottom sediment dredging effect. By monitoring water quality once every three days during the dredging period, verification of the bottom sediment dredging simulation is realized.

[0086] (2) Assessment of the impact of Jiangjiahe sediment dredging on nitrogen interception capacity

[0087] In order to understand in detail the impact of dredging on river nitrogen concentration, water quality monitoring frequency was once every three days during the dredging period and within two months after dredging (March 21 to June 25, 2020) to reflect the impact of dredging on the river nitrogen cycle. In the previous embodiment, the river nitrogen cycle model (River-N) of the present invention and its coupling with the existing river network three-dimensional hydrodynamic model (EFDC) and the polder nitrogen cycle model (NDP) were introduced in detail. The model method used in this embodiment is the same as that in the previous embodiment, but considering the impact of dredging projects on river hydrodynamics, large aquatic plants and water quality, this embodiment optimizes the release rate of nitrogen in the sediment, the adsorption rate of nitrogen by the sediment, the resuspension rate, the sedimentation rate, the denitrification rate and the nitrogen absorption capacity of large aquatic plants in the evaluation model. The optimization method is also completed using a genetic algorithm combined with a Latin hypercube sampling experiment.

[0088] Under dredging conditions, the simulation results of the three-dimensional hydrodynamic model of the river network ( Figure 3) shows that after dredging, the water exchange between Jiangjiahe and surrounding rivers increased significantly from June to October. In April 2020, immediately after dredging, the water exchange between Jiangjiahe and surrounding rivers fluctuated frequently, but overall the exchange volume was greater than in the absence of dredging. Considering that dredging removed both sediment and large aquatic plants from the Jiangjiahe River, the river's flowability increased, naturally leading to an increase in water exchange with surrounding rivers.

[0089] Under dredging conditions, the river nitrogen cycle model (River-N) was calibrated using the 2020 water quality data of Jiangjia River, and the 2021 water quality data was used to verify the model simulation effect. Figure 6 The simulation results show that the model has good simulation ability and can capture the variation characteristics of total nitrogen. The model can capture the fluctuation characteristics of pollutant concentrations. The fitting degree of total nitrogen in the validation period is relatively satisfactory (R 2 =0.58), higher than the 0.51 during the calibration period, which better captures the changing trend of pollutant concentrations. The PBIAS of TN during the validation period (-33.17%) was lower than that during the correction period (-34.39%). Therefore, the constructed rural river nitrogen cycle model has a good simulation level and can be used in the water quality simulation of Jiangjia River. The total nitrogen observation value on June 25, 2021, reached 13.16 mg / L, which is an outlier and is therefore not considered in the calculation of the goodness of fit.

[0090] Under dredging conditions, the accuracy of the river nitrogen cycle model (River-N) meets the requirements. Through statistical analysis of the model under dredging conditions, we can understand in detail the role of rural small rivers in nitrogen sources, sinks, consumption and retention under dredging conditions. The statistical analysis of the model shows that ( Figure 7 ), inflow from surrounding rivers, drainage from the polder area, and sediment release are the primary nitrogen sources of the Jiangjia River, accounting for a combined 92.2% (51.9%), 28.5%, and 11.8%, respectively. Within the nitrogen sink structure, denitrification, drainage from surrounding rivers, and irrigation diversion from the polder area are the primary sources, accounting for a combined 87.9% (47.3%), 29.5%, and 11.1%, respectively. Affected by dredging, among nitrogen sources, sediment release and particulate nitrogen resuspension fluxes decreased by 29.48% and 87.93%, respectively, in 2021 compared to 2020. Among nitrogen sinks, particulate nitrogen deposition flux decreased by 15.34% in 2021 compared to 2020, while denitrification flux increased by 23% in 2021 compared to 2020. These differences suggest that dredging has enhanced sediment release, particulate nitrogen resuspension, and deposition, while weakening denitrification.

[0091] Comparing the simulation results of this embodiment with those of the model simulation results under the condition of no dredging in embodiment 1, it is found that the impact of dredging on the water quality of Jiangjia River is mainly reflected in the summer and autumn seasons (July to November) ( Figure 4). During the dredging period and the aquatic vegetation recovery period, the total nitrogen concentration under dredging conditions is generally greater than that under dredging conditions, especially in July and August, the concentration difference is greater. In the long term of dredging, from November 2020 to May 2021, the difference between the two scenarios is very small; as the water level rises, from June to October 2021, the concentration under the dredging scenario is significantly greater than that under the dredging scenario; from November to December, the water level drops, the difference in water exchange volume becomes smaller, and the concentration under dredging is slightly lower than that under dredging. The main reason for the peak difference from July to October may be that the concentration of the peripheral rivers during this period is greater than that of Jiangjiahe. After dredging, compared with other months, as much as 51.9% of the water flowed into Jiangjiahe from July to October ( Figure 3 ), plus the N concentration in the surrounding rivers is higher than that in Jiangjia River, causing more pollutants to enter the river and increase the concentration of pollutants. At the same time, through comparison, it was also found that the impact of dredging on pollutant concentrations is mainly reflected in the increase in the release rate of ammonia nitrogen in the sediment, the increase in the resuspension and sedimentation rate of particulate nitrogen, the decrease in plant absorption capacity, and the inhibition of denitrification. During the dredging period, the release rate of ammonia nitrogen was 3 times that before dredging, and the resuspension rate and sedimentation rate of particulate nitrogen were 233.3 times and 21.9 times that before dredging, respectively. This may be related to the strong disturbance of the water-soil interface caused by dredging. Denitrification, nitrification and assimilation are inhibited. On the one hand, it may be related to the destruction of the bacterial flora in the water environment by dredging, and on the other hand, it is related to the removal of aquatic plants; dredging has little effect on anaerobic ammonia oxidation. Overall, dredging increases the release of endogenous nitrogen, making the characteristics of the water-soil interface as a source more obvious. During the aquatic plant recovery period (May to August 2020), the ammonia nitrogen release rate, particulate nitrogen resuspension rate and sedimentation rate dropped significantly. With the recovery of aquatic vegetation, plant absorption, denitrification, nitrification and assimilation were significantly improved. The impact of dredging gradually weakened, nitrogen release decreased, and nitrogen absorption increased, making the characteristics of the water-soil interface as a sink more obvious.

[0092] Through statistical analysis of the model, it can be concluded that dredging can reduce the concentration of pollutants in the sediment, but it cannot significantly and continuously reduce the nitrogen content in the Jiangjia River water body. The influx of water from peripheral rivers into the Jiangjia River is the main factor affecting the concentration of pollutants in the Jiangjia River water body. The concentration of water from peripheral rivers is generally higher than that in the Jiangjia River. The large amount of water exchange causes the concentration of pollutants in the Jiangjia River water body to remain high. Compared with no dredging, more water from peripheral rivers flows into the Jiangjia River after dredging, causing more pollutants to enter the river and increase the concentration of pollutants. This is particularly obvious from July to October ( Figure 6 ).

[0093] Under dredging conditions, Jiangjiahe's role as a nitrogen source is enhanced due to the greater water confluence of surrounding rivers. However, due to the enhanced hydrodynamics, the disappearance of large aquatic plants and the destruction of bacterial flora in the water body, Jiangjiahe's nitrogen absorption and retention effects are reduced. Therefore, the method of the present invention evaluates that Jiangjiahe's nitrogen interception capacity after dredging is limited, especially in 2021. As time goes by, the nitrogen reduction effect brought about by dredging becomes smaller and smaller.

Claims

1. A method for evaluating the nitrogen interception capacity of rural rivers in plain river networks, characterized in that: include: The water exchange between rural rivers and peripheral rivers in plain river network areas was simulated based on EFDC three-dimensional hydrodynamic model; Based on the NDP polder nitrogen cycle model, the water and nitrogen exchange flux between rural rivers and polders in plain river networks was simulated. The nitrogen exchange flux included particulate nitrogen, ammonia nitrogen and nitrate nitrogen. Establishing a River-N river nitrogen cycle model that covers aquatic plants and biogeochemical cycles, wherein the governing equations of the river nitrogen cycle model include the aquatic plant growth and destruction processes; Based on the simulation results of the EFDC three-dimensional hydrodynamic model and the NDP polder nitrogen cycle model, river boundary conditions were determined and input into the River-N river nitrogen cycle model to simulate the daily dynamic changes of nitrogen in rural rivers in plain river networks and evaluate the nitrogen interception capacity of rural rivers in plain river networks. The governing equation describing the growth and decay process of aquatic plants is as follows: ； ； ； ； ； ； Where T represents the time, ∆T represents the time step, represents the aboveground biomass of aquatic plants, Indicates the proportion of aquatic plants transferred from the ground to the root system, It represents the maximum growth rate of the aboveground part of aquatic plants under optimal conditions. represents the nitrogen limitation of aquatic plants, Indicates the temperature limit for the growth of aquatic plants, It represents the maximum growth rate of the aboveground part of aquatic plants under optimal conditions. Indicates the temperature limit for the decay of the above-ground parts of aquatic plants, represents the biomass of the underground part of aquatic plants, represents the half-saturation constant of nitrogen absorption by aquatic plants, represents the metabolic rate of the root system at the reference temperature, Indicates the temperature limit for root decay of aquatic plants, represents the ammonia nitrogen concentration in surface water, represents the concentration of nitrate nitrogen in surface water, Indicates the effect of temperature on the growth of aquatic plants. represents the surface water temperature, 、 Indicates the lower and upper limits of the optimal temperature for the growth of aquatic plants. Indicates the effect of temperature on the metabolic rate of the aboveground parts of aquatic plants. represents the daily average water temperature, Represents the effect of temperature on the metabolic rate of aquatic plant roots.

2. The method according to claim 1, characterized in that The three-dimensional hydrodynamic model uses grid cells based on water level to determine the direction of water flow and the three-dimensional hydrodynamic process.

3. The method according to claim 1, characterized in that The horizontal coordinate reference of the three-dimensional hydrodynamic model is rectangular coordinate or orthogonal curvilinear coordinate, the space is discretized by staggered grid, the time integration adopts the second-order precision finite difference method combined with the internal and external mode splitting technology, the external module adopts the semi-implicit calculation method, the internal module adopts the implicit format of vertical diffusion, and the dry-wet grid technology is used in the floodplain area.

4. The method according to claim 1, wherein It also includes model verification, calibration and verification of model parameters based on measured meteorological, hydrological and water quality monitoring data.

5. The method according to claim 4, characterized in that The model verification is as follows: using sensitivity analysis method to identify key parameters of the model, constructing an intelligent optimization model for model parameters, and obtaining the optimal parameter set of the model; comparing the simulated values ​​and measured values ​​of various nitrogen indicators, and using the Nash efficiency coefficient to quantitatively evaluate the simulation effect of the model.

6. The method according to claim 5, characterized in that The intelligent optimization is accomplished by using a genetic algorithm combined with a Latin hypercube sampling experiment.

7. The method according to claim 1, characterized in that Evaluation of nitrogen interception capacity of rural rivers in plain river network areas based on river nitrogen retention flux.

8. The method according to claim 7, characterized in that The nitrogen retention flux of the river includes the quantified flux of natural sedimentation of particulate nitrogen, denitrification, anaerobic ammonium oxidation, and aquatic plant absorption processes.

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