A progressive decoupling method, system, device and medium for generating a watershed hydrology and water quality model pedigree

Abstract

The application discloses a kind of watershed hydrology water quality model generation progressive decoupling method, system, equipment and medium, the method is first in pre-constructed watershed hydrology water quality model (parent model) Positioning target area's most downstream sub catchment, then by dynamic topological tracking method, the sub catchment of upstream sub catchment that exists hydraulic connection with most downstream sub catchment is identified, and the topological correlation sub catchment set is obtained;Then the parameters of each sub catchment in the set are extracted, including model parameters, boundary conditions, initial conditions and parent model general configuration parameters;Finally, according to the extracted information, the sub model is constructed, and the consistency of the model results is verified;When the research requirement involves more fine scale, the above decoupling process is iteratively executed with the above sub model as a new parent model, until the final scale requirement is met.The application significantly improves the accuracy and efficiency of the spatial scale decoupling of the watershed hydrology water quality model, and is suitable for large-scale watershed fine management and research.

Description

Technical Field

[0001] The present invention relates to the field of basin hydrological and water quality model calculation, and in particular to a progressive decoupling method, system, equipment and medium for generation of basin hydrological and water quality model lineages. Background Art

[0002] The computational complexity of watershed hydrological and water quality models has long severely constrained the efficiency and accuracy of simulations. Watershed hydrological and water quality processes encompass hydrological processes such as precipitation, evaporation, runoff, and infiltration, as well as water quality processes such as the migration, transformation, and degradation of various pollutants. These processes are intertwined and influence each other, forming an intricate system. To simulate this complex system as accurately as possible, the watershed is typically divided into a large number of computational units. This division is primarily intended to capture the spatial differences between different regions within the basin, such as the impact of factors such as topography, soil type, and land use patterns on hydrological and water quality processes. However, when the watershed is divided into a large number of computational units, the overall computational workload increases exponentially, as each unit must independently perform complex hydrological and water quality calculations. This consumes massive amounts of computing resources, making it difficult even for high-performance computers to cope with the workload. Simulation time is also significantly extended, significantly slowing research progress. Moreover, the complex calculation process and significantly extended simulation time make model debugging, error detection and correction extremely difficult, making it difficult to ensure the accuracy and reliability of the simulation. The entire research process becomes extremely time-consuming and labor-intensive, seriously affecting the in-depth development of watershed management and research. Summary of the Invention

[0003] Purpose of the invention: The first purpose of the present invention is to provide a progressive decoupling method for generating a lineage of watershed hydrological and water quality models with low dependence on computing resources and high simulation efficiency; the second purpose of the present invention is to provide a progressive decoupling system for generating a lineage of watershed hydrological and water quality models; the third purpose of the present invention is to provide a progressive decoupling device for generating a lineage of watershed hydrological and water quality models; the fourth purpose of the present invention is to provide a computer-readable storage medium.

[0004] Technical solution: The present invention provides a progressive decoupling method for generation of a watershed hydrological and water quality model lineage, comprising:

[0005] S1: Obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model;

[0006] S2: Locate the most downstream subcatchment corresponding to the target area in the parent model as the starting node of the target area extraction process;

[0007] S3: Based on the river network topology in the parent model, a dynamic topology tracking method is used to identify all upstream subcatchments that are hydraulically connected to the start node, and a set of topologically connected subcatchments is obtained.

[0008] S4: extracting the model parameter set corresponding to each sub-catchment in the topologically associated sub-catchment set;

[0009] S5: Extract boundary conditions related to the target area;

[0010] S6: Extract the initial conditions of the target area;

[0011] S7: Extract common configuration parameters of the parent model;

[0012] S8: construct a sub-model using the information extracted in steps S4 to S7, and verify the consistency of its model results;

[0013] S9: When there is a need to extract a smaller-scale local watershed model in the target area, the sub-model constructed in step S8 is used as a new parent model, and steps S2 to S8 are executed repeatedly until all application requirements for the target area extraction are met.

[0014] Furthermore, in step S2, the most downstream sub-catchment corresponding to the target area is located by automatically locating the most downstream sub-catchment corresponding to the target area using the river network topology structure or manually selecting the most downstream sub-catchment corresponding to the target area.

[0015] Furthermore, step S3 includes:

[0016] S301: Initialize a set containing only the starting node;

[0017] S302: According to the river network topology of the starting node in the parent model, obtain the first-level upstream sub-catchment area that has a hydraulic connection relationship with the starting node, and add the first-level upstream sub-catchment area to the set;

[0018] S303: taking the newly added upstream sub-catchment area in step S302 as a new starting node;

[0019] S304: cyclically executing steps S302 to S303 until the top of the sub-catchment without upstream is tracked;

[0020] In each loop, it is determined whether the upstream sub-catchment is already in the set. If so, it is discarded; if not, it is added to the set. Finally, the complete set of topologically associated sub-catchments is output.

[0021] Furthermore, the model parameter set in step S4 includes sub-catchment related parameters, sub-catchment parameter group related parameters, sub-river channel related parameters corresponding to the sub-catchment, and sub-river channel parameter group related parameters.

[0022] Furthermore, the boundary conditions described in step S5 include meteorological driving input, point source discharge input, and river diversion or pumping input. The boundary condition extraction method is based on a topologically associated sub-catchment set, combined with the correspondence between the sub-catchment and the meteorological station preset in the basin hydrological and water quality model, and includes point source discharge and river pumping within the range of the topologically associated sub-catchment set.

[0023] Furthermore, the initial conditions in step S6 include a cold start state and a hot start state, wherein the cold start state corresponds to the initial parameter settings in the parent model master control file, and the hot start state corresponds to the hot start initial condition file of the parent model.

[0024] Furthermore, in step S8, a quantitative error analysis method is used to verify the consistency of the model results, and the quantitative error analysis method uses mean square error (MSE) or root mean square error (RMSE);

[0025] When the mean square error (MSE) is used, the square of the difference between the simulated values ​​of each sub-catchment of the parent model and the child model at each moment is calculated, and the square of the difference between each sub-catchment and the result calculated at each moment is summed. The formula is expressed as:

[0026] ;

[0027] Among them, A(i,t) represents the calculation result of the parent model i sub-catchment at time t, and B(i,t) represents the calculation result of the child model i sub-catchment at time t;

[0028] Based on the number of subcatchments and the total number of time steps, the sum of the squares of the differences between the simulated values ​​of each subcatchment of the parent model and the child model at each moment is averaged. The formula is:

[0029] ;

[0030] Where I is the number of subcatchments and T is the total number of time steps;

[0031] When the MSE of the flow simulation is less than the first set percentage of the square of the corresponding average flow, and the MSE of the water quality concentration simulation is less than the second set percentage of the square of the corresponding average concentration, it is considered that the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful;

[0032] When the root mean square error (RMSE) is used, the RMSE is further calculated based on the MSE:

[0033] ;

[0034] When the RMSE of the flow simulation is less than the first set percentage of the corresponding average flow, and the RMSE of the water quality concentration simulation is less than the second set percentage of the corresponding average concentration, it is considered that the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful.

[0035] Based on the same inventive concept, the present invention provides a progressive decoupling system for generation of a watershed hydrological and water quality model lineage, comprising:

[0036] The model acquisition module is used to obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model;

[0037] The starting node positioning module is used to locate the most downstream sub-catchment area corresponding to the target area in the parent model as the starting node of the target area extraction process;

[0038] The dynamic topology tracking module is used to identify all upstream sub-catchments that are hydraulically connected to the starting node based on the river network topology in the parent model through dynamic topology tracking methods, and obtain a set of topologically connected sub-catchments;

[0039] A model parameter set extraction module is used to extract the model parameter set corresponding to each sub-catchment in the topologically associated sub-catchment set;

[0040] Boundary condition extraction module, used to extract boundary conditions related to the target area;

[0041] An initial condition extraction module is used to extract the initial conditions of the target area;

[0042] Common configuration parameter extraction module, used to extract common configuration parameters of the parent model;

[0043] The sub-model generation module is used to construct a sub-model based on the information extracted by the model parameter set extraction module, the boundary condition extraction module, the initial condition extraction module and the general configuration parameter extraction module, and to verify the consistency of its model results;

[0044] The loop module is used to use the sub-model constructed by the sub-model generation module as the new parent model when there is a demand for extracting a smaller-scale local watershed model in the target area, and to cyclically run the starting node positioning module, dynamic topology tracking module, model parameter set extraction module, boundary condition extraction module, initial condition extraction module, general configuration parameter extraction module and sub-model generation module until all application requirements for target area extraction are met.

[0045] Based on the same inventive concept, the present invention provides a progressive decoupling device for generating a lineage of watershed hydrological and water quality models, comprising a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the progressive decoupling device implements the steps of the above-mentioned progressive decoupling method.

[0046] Based on the same inventive concept, a computer-readable storage medium of the present invention stores a computer program thereon, and when the program is executed by a processor, the steps of the above-mentioned progressive decoupling method are implemented.

[0047] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0048] The present invention decouples the parent basin model. Its essence is to disassemble a large basin into multiple independent sub-basins. By performing hydrological and water quality simulations of the sub-basin models instead of the parent basin model, it facilitates the rapid implementation of localized refined simulation, analysis, and verification of complex basins, reduces simulation time and computing resource consumption, and accelerates the research, calibration, and optimization of basin models. When conducting targeted research on local spatial regions, it is possible to track and search based on a simple downstream target sub-catchment area through the topological structure established by the basin model, and quickly identify its upstream sub-catchment area. This is accurate and efficient, significantly improving the efficiency of model spatial decoupling.

[0049] This invention enables progressive multi-level model decoupling and expansion, forming a dynamically hierarchical model pedigree. This step-by-step modeling strategy enables progressively refined modeling from the basin scale to smaller regional scales. This progressive multi-level model decoupling and expansion allows for the rapid generation of basin hydrological and water quality model pedigrees based on the existing parent basin model, enabling studies of sub-basins at finer scales, such as hydrological and water quality simulations of grandchild models.

[0050] This invention not only innovates the computational paradigm of traditional watershed simulation, but also opens up a new path for the refined management of complex watersheds. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flowchart of a progressive decoupling method for generation of a watershed hydrological and water quality model lineage disclosed in an embodiment of the present invention;

[0052] Figure 2 This is a diagram of the sub-catchment areas and sub-river channels of the parent model in an embodiment of the present invention (the target area is in the red area);

[0053] Figure 3 1. It is a sub-catchment area and sub-river channel map of the sub-model in an embodiment of the present invention;

[0054] Figure 4This is a schematic diagram of a progressive decoupling system structure for generation of a watershed hydrological and water quality model lineage disclosed in an embodiment of the present invention;

[0055] Figure 5 It is a schematic diagram of the structure of a progressive decoupling device for lineage generation of a watershed hydrological and water quality model disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It will be understood by those skilled in the art that the purposes and advantages that can be achieved by the present invention are not limited to the specific description of the above beneficial effects, and the above and other purposes that can be achieved by the present invention will be more clearly understood based on the following detailed description.

[0057] It should be understood by those skilled in the art that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether hardware or software is used depends on the specific application and design and tree conditions of the technical solution. Professionals and technicians may use different methods to implement the functions described for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0058] References to "embodiments" in this disclosure mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the disclosure. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0059] Example 1: Please refer to Figure 1 , Figure 1 This is a flowchart of a progressive decoupling method for generating a lineage of a watershed hydrological and water quality model disclosed in an embodiment of the present invention. The progressive decoupling method for generating a lineage of a watershed hydrological and water quality model may include the following operations:

[0060] S1: Obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model.

[0061] The pre-construction method of the watershed hydrological and water quality model is an existing technology. The construction process mainly includes the following parts:

[0062] (1) Construction of hydrological response units

[0063] The elevation DEM (Digital Elevation Model) data is converted into slope spatial vector data, and the acquired land use type data, soil data, and slope spatial vector data are fused to construct a hydrological response unit.

[0064] (2) Sub-catchment construction

[0065] Using elevation DEM data, the SWAT (Soil and Water Assessment Tool) model automatically generates subcatchments and subchannels. Manual modifications are performed to address any inappropriate boundaries or subchannels that do not meet application requirements due to algorithm limitations, data errors, or application requirements. Ultimately, subcatchments and subchannels are determined to be realistic and meet simulation requirements. Subcatchments and subchannels are uniquely coded and have a one-to-one correspondence. Each subchannel has a unique downstream, forming a river network topology from upstream to downstream.

[0066] A subcatchment is a small physical unit bounded by certain topographic features. Each subcatchment corresponds to a sub-river channel. This sub-river channel receives the water and load from the corresponding subcatchment's land-based inflow, as well as water and load from upstream sources, pumping input from the river channel, and point sources. It can also serve as a source for irrigation and pump water to other sub-rivers or outside the basin. The outflow and load from a sub-river channel flows into its downstream sub-river channel, serving as upstream inflow and load for that sub-river channel.

[0067] like Figure 2 As shown, the parent model obtained in this embodiment is divided into 209 sub-catchments (due to image size limitations, not all numbers are shown).

[0068] (3) Generation of other files

[0069] Prepare files for meteorological driving inputs, point source discharge inputs, and river diversion or pumping inputs.

[0070] (IV) Model parameter configuration

[0071] Localize the model, set the model parameters, and adjust and determine the final model parameters based on parameter calibration and model verification.

[0072] (V) Setting the model initial conditions

[0073] Set the model cold start initial parameters and generate the model hot start initial condition file.

[0074] S2: Locate the most downstream subcatchment corresponding to the target area in the parent model as the starting node of the target area extraction process.

[0075] The parent model contains several sub-basins, and the target area is any of these sub-basins, selected based on research needs. The most downstream sub-catchment is generally automatically located based on the river network topology. For ease of operation, it can also be manually selected.

[0076] like Figure 2 As shown, in this embodiment, the red range is used as the target area, and its most downstream sub-catchment area is coded as 65.

[0077] S3: Based on the river network topology in the parent model, a dynamic topology tracking method is used to identify all upstream sub-catchments that are hydraulically connected to the starting node, and a set of topologically connected sub-catchments is obtained.

[0078] The dynamic topology tracing method starts from a starting node and tracks upstream along the river, progressively identifying all upstream subcatchments that are hydraulically connected to the starting node. Redundant identification must be avoided during the tracing process. Furthermore, to ensure the integrity of the set of topologically connected subcatchments, this embodiment also includes special water intake routes, such as irrigation diversions and river pumping, within the tracking and identification scope.

[0079] The dynamic topology tracking method specifically includes the following steps:

[0080] S301: Initialize a set containing only the starting node.

[0081] S302: According to the river network topology of the starting node in the parent model, the first-level upstream sub-catchment area that has a hydraulic connectivity relationship with the starting node is obtained, and the first-level upstream sub-catchment area is added to the set.

[0082] S303: Use the upstream sub-catchment area newly added in step S302 as a new starting node.

[0083] S304: Steps S302 to S303 are executed in a loop until the top of the sub-catchment without upstream is traced.

[0084] In each loop, it is determined whether the upstream subcatchment is already in the set. If so, it is discarded; if not, it is added to the set. Finally, the complete set of topologically related subcatchments is output.

[0085] This dynamic topology tracing method performs step-by-step upstream tracing and can quickly determine the set of topologically related sub-catchments while avoiding redundancy and omission.

[0086] like Figure 3As shown in the figure, in this embodiment, all upstream sub-catchments of sub-catchment 65 are coded as 41, 42, 45, 48, 54, 57, 60, 61, 106, 107, 112, 119, 123, 136, 137, 146, 154, 172, 176, 179, 182, 183, 204, and 205. Based on the river network topology in the parent model, considering the irrigation water sources and river pumping sources involved in the sub-catchments found by upstream tracing, this embodiment only includes the river pumping source sub-catchment, coded as 42.

[0087] S4: Extract the model parameter set corresponding to each sub-catchment in the topologically associated sub-catchment set.

[0088] The watershed hydrological and water quality model is in text form, and all parameters are placed in different cards and different texts. Some parameter settings are set directly according to the sub-catchment area, some are set directly according to the hydrological response unit, some are set according to the sub-basin parameter group and the hydrological response unit, and some are set according to the sub-river channel parameter group and the hydrological response unit.

[0089] According to the sub-catchment settings, the parameters corresponding to the topologically associated sub-catchment set can be directly extracted; according to the hydrological response unit settings, all parameters can be directly extracted; according to the sub-basin parameter group and the hydrological response unit settings, it is necessary to determine the corresponding sub-catchment parameter group based on the topologically associated sub-catchment set, and extract based on the sub-catchment parameter group; according to the sub-channel parameter group and the hydrological response unit settings, it is necessary to determine the corresponding sub-channel parameter group based on the topologically associated sub-catchment set, and extract based on the sub-channel parameter group.

[0090] The model parameter set includes sub-catchment related parameters, sub-catchment parameter group related parameters, sub-catchment corresponding sub-channel related parameters and sub-channel parameter group related parameters.

[0091] The sub-catchment related parameters include the sub-catchment attribute parameters, hydrological response unit related setting parameters, sub-catchment group setting parameters (the master control file specifies the group to which the sub-catchment belongs, and the parameters are set according to the group, not the sub-catchment. Therefore, the corresponding group must be found before the parameters can be extracted), irrigation water intake mode related parameters, surface pollutant accumulation mode related parameters and advanced function module parameters. Among them, the irrigation water intake mode related parameters are used to simulate the irrigation process of the basin plots, the surface pollutant accumulation mode related parameters are used to simulate the surface pollutant accumulation process of the basin, and the advanced function module parameters include groundwater outflow adjustment related parameters and storage-related hydrological and water quality parameters.

[0092] The relevant parameters of the sub-catchment parameter group include hydrological parameters and water quality parameters.

[0093] The parameters related to the sub-channels of the sub-catchment area include the channel's own attribute parameters, topological connection relationship setting parameters, and group setting parameters (the master control file specifies the group to which the sub-channel belongs, and the parameters are set according to the group, not the sub-channel. Therefore, the parameters can only be extracted after finding the corresponding group).

[0094] Parameters related to the sub-channel parameter group, including hydrological parameters and water quality parameters.

[0095] Finally, the extracted model parameter sets of each sub-catchment are added to the sub-model input file through the unified hydrological response interface.

[0096] In this embodiment, the input file for the irrigation water intake model is irr.inp; the input file for the surface pollution accumulation model is acc.inp; the input file for the advanced function module parameters is adv.inp; other parameters are all in the same input file, called the model master file, which is IWS.inp.

[0097] S5: Extract boundary conditions related to the target area.

[0098] Boundary conditions include meteorological driving input, point source discharge input, and river diversion or pumping input.

[0099] The boundary condition extraction method is based on a set of topologically connected subcatchments, combined with the correspondence between subcatchments and meteorological stations preset in the basin hydrological and water quality model, and includes point source discharges and river pumping within the set of topologically connected subcatchments.

[0100] In this embodiment, the weather drive input involves the weather data .air format file and the weather condition related card parameter settings in the master control file IWS.inp. The weather data .air format files are 3.air, 4.air, and 6.air, and the weather condition related cards in the master control file IWS.inp are C10, C15, C20, C30, and C60.

[0101] Point source emission input involves the point source data .inp format file, the point source attenuation setting .inp format file and the point source input related card setting parameters in the master control .inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the master control file is IWS.inp, and the point source input related cards in the master control file IWS.inp are C31, C420, C425 and C660.

[0102] River water diversion or pumping input involves the river pumping-related point source data .inp format file, point source attenuation setting .inp format file and river pumping-related card setting parameters in the master control .inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the master control file is IWS.inp, and the river pumping-related cards in the master control file IWS.inp are C31, C420, C430 and C660.

[0103] S6: Extract the initial conditions of the target area.

[0104] The initial conditions include cold start state and hot start state. The cold start state corresponds to the initial parameter settings in the parent model master control file. All parameters related to the cold start settings can be extracted.

[0105] The hot start state corresponds to the parent model's hot start initial condition file. Hot start state parameters are set in a separately generated hot start file and are divided into subcatchments, sub-channels, point sources, and channel pumping. Extracting these parameters requires extracting the corresponding subcatchments and sub-channel hot start parameters based on the previously generated topologically associated subcatchments. Extracting the corresponding point source and channel pumping hot start parameters based on the point source discharge input and channel diversion or pumping input requires regenerating a new hot start file.

[0106] In order to keep the initial state of the subsequently generated sub-model consistent with that of the parent model in the same area simulation, the initial state of the sub-basin to be extracted in the parent model can be completely retained, so that the extracted sub-model can start simulation from the same initial state as the relevant spatial area of ​​the parent model.

[0107] S7: Extract common configuration parameters of the parent model.

[0108] Common configuration parameters include start and stop status, simulation time step, simulation and output time interval, output variable settings and output file settings.

[0109] The common configuration parameters of the parent model are used to configure the child model in step S8, which helps to maintain the integrity of the child model and its consistency with the parent model.

[0110] S8: Build a sub-model using the information extracted from steps S4 to S7, and verify the consistency of its model results.

[0111] Quantitative error analysis methods, including mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), were used to compare and evaluate the simulation results of the parent model and the child model for each sub-catchment at each time period.

[0112] Taking the mean square error (MSE) as an example, if the MSE value is within an acceptable range, the simulation results of the sub-model are determined to be highly consistent with the parent model, thus confirming that the sub-domain extraction is successful and the model decoupling is effective. Specifically:

[0113] Calculate the square of the difference between the simulated values ​​of each sub-catchment of the parent model and the child model at each moment, and sum the square of the difference between each sub-catchment and the result calculated at each moment. The formula is expressed as:

[0114] ;

[0115] Among them, A(i,t) represents the calculation result of the i-th sub-catchment of the parent model at the t-th time, and B(i,t) represents the calculation result of the i-th sub-catchment of the child model at the t-th time.

[0116] Based on the number of subcatchments and the total number of time steps, the sum of the squares of the differences between the simulated values ​​of each subcatchment of the parent model and the child model at each moment is averaged. The formula is:

[0117] ;

[0118] Where I is the number of subcatchments and T is the total number of time steps.

[0119] When the MSE of the flow simulation is less than 5% of the square of the corresponding average flow, and the MSE of the water quality concentration simulation is less than 10% of the square of the corresponding average concentration, it is considered that the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful.

[0120] If the root mean square error (RMSE) is used, then the RMSE is further calculated based on the MSE:

[0121] ;

[0122] When the RMSE of the flow simulation is less than 5% of the corresponding average flow, and the RMSE of the water concentration simulation is less than 10% of the corresponding average concentration, the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful. RMSE is closely related to MSE, but the units of RMSE are consistent with the original data, making it easier to interpret.

[0123] Both mean absolute error (MAE) and mean square error (MSE) can be used to measure the error between the predicted value and the actual value. However, MAE uses absolute values ​​rather than squared errors and is less sensitive to outliers. Therefore, the present invention uses mean square error (MSE) or root mean square error (RMSE).

[0124] In this embodiment, all extracted files are stored in a new path (i.e., the folder of the sub-model), and the corresponding file paths in the master control file are updated to generate a new sub-model that can be run and in which the simulation results of each sub-catchment are consistent with the model results of the corresponding sub-catchment of the parent model.

[0125] The sub-model contains the main control file main.inp, the meteorological data folder AIR, and the auxiliary input file folder INP. The AIR folder contains three meteorological data files 3.air, 4.air, and 6.air. The INP folder contains the initial condition hot start file init.inp, the point source data file point.inp, the point source attenuation setting file psdecay.inp, the irrigation water intake mode input file irr.inp, the surface pollution accumulation mode input file acc.inp, and the advanced function module parameter input file adv.inp.

[0126] S9: When there is a need to extract a smaller-scale local watershed model in the target area, the sub-model constructed in step S8 is used as a new parent model, and steps S2 to S8 are executed repeatedly until all application requirements for the target area extraction are met.

[0127] This invention enables progressive multi-level model decoupling and expansion, forming a dynamically hierarchical model pedigree. This step-by-step modeling strategy enables progressively finer modeling from the watershed scale to smaller regional scales, while maintaining consistent parameter inheritance and homogeneous simulation environments across each model level. This progressive multi-level model decoupling and expansion enables rapid generation of a watershed hydrological and water quality model pedigree based on the existing parent watershed model, enabling research on finer-scale sub-watersheds, such as hydrological and water quality simulations of grandchild models.

[0128] Example 2: Please refer to Figure 4 , Figure 4 This is a schematic diagram of the structure of a progressive decoupling system for generating a lineage of watershed hydrological and water quality models disclosed in an embodiment of the present invention. The progressive decoupling system for generating a lineage of watershed hydrological and water quality models includes a model acquisition module, a starting node positioning module, a dynamic topology tracking module, a model parameter set extraction module, a boundary condition extraction module, an initial condition extraction module, a general configuration parameter extraction module, a sub-model generation module and a loop module.

[0129] The model acquisition module is used to obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model.

[0130] The pre-construction method of the watershed hydrological and water quality model is an existing technology. The construction process mainly includes the following parts:

[0131] (1) Construction of hydrological response units

[0132] The elevation DEM (Digital Elevation Model) data is converted into slope spatial vector data, and the acquired land use type data, soil data, and slope spatial vector data are fused to construct a hydrological response unit.

[0133] (2) Sub-catchment construction

[0134] Using elevation DEM data, the SWAT (Soil and Water Assessment Tool) model automatically generates subcatchments and subchannels. Manual modifications are performed to address any inappropriate boundaries or subchannels that do not meet application requirements due to algorithm limitations, data errors, or application requirements. Ultimately, subcatchments and subchannels are determined to be realistic and meet simulation requirements. Subcatchments and subchannels are uniquely coded and have a one-to-one correspondence. Each subchannel has a unique downstream, forming a river network topology from upstream to downstream.

[0135] A subcatchment is a small physical unit bounded by certain topographic features. Each subcatchment corresponds to a sub-river channel. This sub-river channel receives the water and load from the corresponding subcatchment's land-based inflow, as well as water and load from upstream sources, pumping input from the river channel, and point sources. It can also serve as a source for irrigation and pump water to other sub-rivers or outside the basin. The outflow and load from a sub-river channel flows into its downstream sub-river channel, serving as upstream inflow and load for that sub-river channel.

[0136] like Figure 2 As shown, the parent model obtained in this embodiment is divided into 209 sub-catchments (due to image size limitations, not all numbers are shown).

[0137] (3) Generation of other files

[0138] Prepare files for meteorological driving inputs, point source discharge inputs, and river diversion or pumping inputs.

[0139] (IV) Model parameter configuration

[0140] Localize the model, set the model parameters, and adjust and determine the final model parameters based on parameter calibration and model verification.

[0141] (V) Setting the model initial conditions

[0142] Set the model cold start initial parameters and generate the model hot start initial condition file.

[0143] The starting node positioning module is used to locate the most downstream sub-catchment area corresponding to the target area in the parent model as the starting node of the target area extraction process.

[0144] The parent model contains several sub-basins, and the target area is any of these sub-basins, selected based on research needs. The most downstream sub-catchment is generally automatically located based on the river network topology. For ease of operation, it can also be manually selected.

[0145] like Figure 2 As shown, in this embodiment, the red range is used as the target area, and its most downstream sub-catchment area is coded as 65.

[0146] The dynamic topology tracking module is used to identify all upstream sub-catchments that have hydraulic connectivity with the starting node based on the river network topology in the parent model through the dynamic topology tracking method, and obtain a set of topologically associated sub-catchments.

[0147] The dynamic topology tracing method starts from a starting node and tracks upstream along the river, progressively identifying all upstream subcatchments that are hydraulically connected to the starting node. Redundant identification must be avoided during the tracing process. Furthermore, to ensure the integrity of the set of topologically connected subcatchments, this embodiment also includes special water intake routes, such as irrigation diversions and river pumping, within the tracking and identification scope.

[0148] The dynamic topology tracking method specifically includes the following steps:

[0149] S301: Initialize a set containing only the starting node.

[0150] S302: According to the river network topology of the starting node in the parent model, the first-level upstream sub-catchment area that has a hydraulic connectivity relationship with the starting node is obtained, and the first-level upstream sub-catchment area is added to the set.

[0151] S303: Use the upstream sub-catchment area newly added in step S302 as a new starting node.

[0152] S304: Steps S302 to S303 are executed in a loop until the top of the sub-catchment without upstream is traced.

[0153] In each loop, it is determined whether the upstream subcatchment is already in the set. If so, it is discarded; if not, it is added to the set. Finally, the complete set of topologically related subcatchments is output.

[0154] This dynamic topology tracing method performs step-by-step upstream tracing and can quickly determine the set of topologically related sub-catchments while avoiding redundancy and omission.

[0155] like Figure 3As shown in the figure, in this embodiment, all upstream sub-catchments of sub-catchment 65 are coded as 41, 42, 45, 48, 54, 57, 60, 61, 106, 107, 112, 119, 123, 136, 137, 146, 154, 172, 176, 179, 182, 183, 204, and 205. Based on the river network topology in the parent model, considering the irrigation water sources and river pumping sources involved in the sub-catchments found by upstream tracing, this embodiment only includes the river pumping source sub-catchment, coded as 42.

[0156] The model parameter set extraction module is used to extract the model parameter set corresponding to each sub-catchment in the topologically associated sub-catchment set.

[0157] The watershed hydrological and water quality model is in text form, and all parameters are placed in different cards and different texts. Some parameter settings are set directly according to the sub-catchment area, some are set directly according to the hydrological response unit, some are set according to the sub-basin parameter group and the hydrological response unit, and some are set according to the sub-river channel parameter group and the hydrological response unit.

[0158] According to the sub-catchment settings, the parameters corresponding to the topologically associated sub-catchment set can be directly extracted; according to the hydrological response unit settings, all parameters can be directly extracted; according to the sub-basin parameter group and the hydrological response unit settings, it is necessary to determine the corresponding sub-catchment parameter group based on the topologically associated sub-catchment set, and extract based on the sub-catchment parameter group; according to the sub-channel parameter group and the hydrological response unit settings, it is necessary to determine the corresponding sub-channel parameter group based on the topologically associated sub-catchment set, and extract based on the sub-channel parameter group.

[0159] The model parameter set includes sub-catchment related parameters, sub-catchment parameter group related parameters, sub-catchment corresponding sub-channel related parameters and sub-channel parameter group related parameters.

[0160] The sub-catchment related parameters include the sub-catchment attribute parameters, hydrological response unit related setting parameters, sub-catchment group setting parameters (the master control file specifies the group to which the sub-catchment belongs, and the parameters are set according to the group, not the sub-catchment. Therefore, the corresponding group must be found before the parameters can be extracted), irrigation water intake mode related parameters, surface pollutant accumulation mode related parameters and advanced function module parameters. Among them, the irrigation water intake mode related parameters are used to simulate the irrigation process of the basin plots, the surface pollutant accumulation mode related parameters are used to simulate the surface pollutant accumulation process of the basin, and the advanced function module parameters include groundwater outflow adjustment related parameters and storage-related hydrological and water quality parameters.

[0161] The relevant parameters of the sub-catchment parameter group include hydrological parameters and water quality parameters.

[0162] The parameters related to the sub-channels of the sub-catchment area include the channel's own attribute parameters, topological connection relationship setting parameters, and group setting parameters (the master control file specifies the group to which the sub-channel belongs, and the parameters are set according to the group, not the sub-channel. Therefore, the parameters can only be extracted after finding the corresponding group).

[0163] Parameters related to the sub-channel parameter group, including hydrological parameters and water quality parameters.

[0164] Finally, the extracted model parameter sets of each sub-catchment are added to the sub-model input file through the unified hydrological response interface.

[0165] In this embodiment, the input file for the irrigation water intake model is irr.inp; the input file for the surface pollution accumulation model is acc.inp; the input file for the advanced function module parameters is adv.inp; other parameters are all in the same input file, called the model master file, which is IWS.inp.

[0166] The boundary condition extraction module is used to extract the boundary conditions related to the target area.

[0167] Boundary conditions include meteorological driving input, point source discharge input, and river diversion or pumping input.

[0168] The boundary condition extraction method is based on a set of topologically connected subcatchments, combined with the correspondence between subcatchments and meteorological stations preset in the basin hydrological and water quality model, and includes point source discharges and river pumping within the set of topologically connected subcatchments.

[0169] In this embodiment, the weather drive input involves the weather data .air format file and the weather condition related card parameter settings in the master control file IWS.inp. The weather data .air format files are 3.air, 4.air, and 6.air, and the weather condition related cards in the master control file IWS.inp are C10, C15, C20, C30, and C60.

[0170] Point source emission input involves the point source data .inp format file, the point source attenuation setting .inp format file and the point source input related card setting parameters in the master control .inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the master control file is IWS.inp, and the point source input related cards in the master control file IWS.inp are C31, C420, C425 and C660.

[0171] River water diversion or pumping input involves the river pumping-related point source data .inp format file, point source attenuation setting .inp format file and river pumping-related card setting parameters in the master control .inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the master control file is IWS.inp, and the river pumping-related cards in the master control file IWS.inp are C31, C420, C430 and C660.

[0172] The initial condition extraction module is used to extract the initial conditions of the target area.

[0173] The initial conditions include cold start state and hot start state. The cold start state corresponds to the initial parameter settings in the parent model master control file. All parameters related to the cold start settings can be extracted.

[0174] The hot start state corresponds to the parent model's hot start initial condition file. Hot start state parameters are set in a separately generated hot start file and are divided into subcatchments, sub-channels, point sources, and channel pumping. Extracting these parameters requires extracting the corresponding subcatchments and sub-channel hot start parameters based on the previously generated topologically associated subcatchments. Extracting the corresponding point source and channel pumping hot start parameters based on the point source discharge input and channel diversion or pumping input requires regenerating a new hot start file.

[0175] In order to keep the initial state of the subsequently generated sub-model consistent with that of the parent model in the same area simulation, the initial state of the sub-basin to be extracted in the parent model can be completely retained, so that the extracted sub-model can start simulation from the same initial state as the relevant spatial area of ​​the parent model.

[0176] The common configuration parameter extraction module is used to extract the common configuration parameters of the parent model.

[0177] Common configuration parameters include start and stop status, simulation time step, simulation and output time interval, output variable settings and output file settings.

[0178] The common configuration parameters of the parent model are used to configure the child model, which helps maintain the integrity of the child model and its consistency with the parent model.

[0179] The sub-model generation module is used to construct a sub-model based on the information extracted by the model parameter set extraction module, the boundary condition extraction module, the initial condition extraction module and the general configuration parameter extraction module, and to verify the consistency of its model results.

[0180] Quantitative error analysis methods, including mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), were used to compare and evaluate the simulation results of the parent model and the child model for each sub-catchment at each time period.

[0181] Taking the mean square error (MSE) as an example, if the MSE value is within an acceptable range, the simulation results of the sub-model are determined to be highly consistent with the parent model, thus confirming that the sub-domain extraction is successful and the model decoupling is effective. Specifically:

[0182] Calculate the square of the difference between the simulated values ​​of each sub-catchment of the parent model and the child model at each moment, and sum the square of the difference between each sub-catchment and the result calculated at each moment. The formula is expressed as:

[0183] ;

[0184] Among them, A(i,t) represents the calculation result of the i-th sub-catchment of the parent model at the t-th time, and B(i,t) represents the calculation result of the i-th sub-catchment of the child model at the t-th time.

[0185] Based on the number of subcatchments and the total number of time steps, the sum of the squares of the differences between the simulated values ​​of each subcatchment of the parent model and the child model at each moment is averaged. The formula is:

[0186] ;

[0187] Where I is the number of subcatchments and T is the total number of time steps.

[0188] When the MSE of the flow simulation is less than 5% of the square of the corresponding average flow, and the MSE of the water quality concentration simulation is less than 10% of the square of the corresponding average concentration, it is considered that the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful.

[0189] If the root mean square error (RMSE) is used, then the RMSE is further calculated based on the MSE:

[0190] ;

[0191] When the RMSE of the flow simulation is less than 5% of the corresponding average flow, and the RMSE of the water concentration simulation is less than 10% of the corresponding average concentration, the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful. RMSE is closely related to MSE, but the units of RMSE are consistent with the original data, making it easier to interpret.

[0192] Both mean absolute error (MAE) and mean square error (MSE) can be used to measure the error between the predicted value and the actual value. However, MAE uses absolute values ​​rather than squared errors and is less sensitive to outliers. Therefore, the present invention uses mean square error (MSE) or root mean square error (RMSE).

[0193] In this embodiment, all extracted files are stored in a new path (i.e., the folder of the sub-model), and the corresponding file paths in the master control file are updated to generate a new sub-model that can be run and in which the simulation results of each sub-catchment are consistent with the model results of the corresponding sub-catchment of the parent model.

[0194] The sub-model contains the main control file main.inp, the meteorological data folder AIR, and the auxiliary input file folder INP. The AIR folder contains three meteorological data files 3.air, 4.air, and 6.air. The INP folder contains the initial condition hot start file init.inp, the point source data file point.inp, the point source attenuation setting file psdecay.inp, the irrigation water intake mode input file irr.inp, the surface pollution accumulation mode input file acc.inp, and the advanced function module parameter input file adv.inp.

[0195] The loop module is used to use the sub-model constructed by the sub-model generation module as the new parent model when there is a demand for extracting a smaller-scale local watershed model in the target area, and to cyclically run the starting node positioning module, dynamic topology tracking module, model parameter set extraction module, boundary condition extraction module, initial condition extraction module, general configuration parameter extraction module and sub-model generation module until all application requirements for target area extraction are met.

[0196] Example 3: Please refer to Figure 5 , Figure 5 This is a schematic structural diagram of a progressive decoupling device for generating a lineage of a watershed hydrological and water quality model disclosed in an embodiment of the present invention. The device may include a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the progressive decoupling device implements the steps of the progressive decoupling method described in the above embodiment 1 and can achieve consistent technical effects.

[0197] The memory may include computer-readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory. The device may further include other removable / non-removable, volatile / non-volatile computer-system storage media. By way of example only, the memory may be used to read and write to non-removable, non-volatile magnetic media (commonly referred to as a "hard drive"). A program / utility having a set (at least one) of program modules may be stored, for example, in the memory. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. The program modules generally perform the functions and / or methods described in the embodiments of the present invention.

[0198] The processor executes various functional applications and data processing by running the programs stored in the memory, for example, implementing the progressive decoupling method provided in Example 1 of the present invention.

[0199] Example 4: The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the progressive decoupling method described in the above-mentioned Example 1 are implemented and the same technical effect can be achieved.

[0200] The computer storage media of the embodiments of the present invention may employ any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0201] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0202] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0203] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0204] Of course, the computer-executable instructions of a storage medium provided by an embodiment of the present invention are not limited to the above method operations, but can also execute related operations in the method provided by any embodiment of the present invention.

[0205] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A progressive decoupling method for generation of a watershed hydrological and water quality model lineage, characterized in that: include: S1: Obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model; S2: Locate the most downstream sub-catchment corresponding to the target area in the parent model as the starting node of the target area extraction process; the parent model contains several sub-basins, and the target area is any one of these sub-basins; S3: Based on the river network topology in the parent model, a dynamic topology tracking method is used to identify all upstream subcatchments that are hydraulically connected to the start node, and a set of topologically connected subcatchments is obtained. Step S3 includes: S301: Initialize a set containing only the starting node; S302: According to the river network topology of the starting node in the parent model, obtain the first-level upstream sub-catchment area that has a hydraulic connection relationship with the starting node, and add the first-level upstream sub-catchment area to the set; S303: taking the newly added upstream sub-catchment area in step S302 as a new starting node; S304: cyclically executing steps S302 to S303 until the top of the sub-catchment without upstream is tracked; In each loop, it is determined whether the upstream sub-catchment is already in the set. If so, it is discarded; if not, it is added to the set. Finally, the complete set of topologically related sub-catchments is output. S4: extracting the model parameter set corresponding to each sub-catchment in the topologically associated sub-catchment set; S5: Extract boundary conditions related to the target area; S6: Extract the initial conditions of the target area; S7: Extract common configuration parameters of the parent model; S8: Using the information extracted from steps S4 to S7, a sub-model is constructed, and the consistency of the model results is verified using a quantitative error analysis method. When the accuracy requirements are met, the two models are considered to be highly consistent and the decoupling is successful; S9: When there is a need to extract a smaller-scale local watershed model in the target area, the sub-model constructed in step S8 is used as a new parent model, and steps S2 to S8 are executed repeatedly until all application requirements for the target area extraction are met.

2. The progressive decoupling method for generation of a watershed hydrological and water quality model lineage according to claim 1 is characterized in that: The positioning of the most downstream sub-catchment corresponding to the target area in step S2 is performed by automatically positioning the most downstream sub-catchment corresponding to the target area using the river network topology structure or manually selecting the most downstream sub-catchment corresponding to the target area.

3. The progressive decoupling method for generation of a watershed hydrological and water quality model lineage according to claim 1, characterized in that: The model parameter set in step S4 includes sub-catchment related parameters, sub-catchment parameter group related parameters, sub-river channel related parameters corresponding to the sub-catchment, and sub-river channel parameter group related parameters.

4. The progressive decoupling method for generation of a watershed hydrological and water quality model lineage according to claim 1, characterized in that: The boundary conditions described in step S5 include meteorological driving input, point source discharge input, and river diversion or pumping input. The boundary condition extraction method is based on the topologically associated sub-catchment set, combined with the corresponding relationship between the sub-catchment and the meteorological station preset in the basin hydrological and water quality model, and includes point source discharge and river pumping within the range of the topologically associated sub-catchment set.

5. The progressive decoupling method for generation of a watershed hydrological and water quality model lineage according to claim 1, characterized in that: The initial conditions in step S6 include a cold start state and a hot start state, wherein the cold start state corresponds to the initial parameter settings in the parent model master control file, and the hot start state corresponds to the hot start initial condition file of the parent model.

6. The progressive decoupling method for generation of a watershed hydrological and water quality model lineage according to claim 1, characterized in that: In step S8, the quantitative error analysis method adopts mean square error MSE or root mean square error RMSE; When the mean square error (MSE) is used, the square of the difference between the simulated values ​​of each sub-catchment of the parent model and the child model at each moment is calculated, and the square of the difference between each sub-catchment and the result calculated at each moment is summed. The formula is expressed as: ； Among them, A(i,t) represents the calculation result of the parent model i sub-catchment at time t, and B(i,t) represents the calculation result of the child model i sub-catchment at time t; Based on the number of subcatchments and the total number of time steps, the sum of the squares of the differences between the simulated values ​​of each subcatchment of the parent model and the child model at each moment is averaged. The formula is: ； Where I is the number of subcatchments and T is the total number of time steps; When the MSE of the flow simulation is less than the first set percentage of the square of the corresponding average flow, and the MSE of the water quality concentration simulation is less than the second set percentage of the square of the corresponding average concentration, it is considered that the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful; When the root mean square error (RMSE) is used, the RMSE is further calculated based on the MSE: ； When the RMSE of the flow simulation is less than the first set percentage of the corresponding average flow, and the RMSE of the water quality concentration simulation is less than the second set percentage of the corresponding average concentration, it is considered that the accuracy requirements are met, the two models are highly consistent, and the decoupling is successful.

7. A progressive decoupling system for generation of a watershed hydrological and water quality model lineage, used to implement the progressive decoupling method according to any one of claims 1 to 6, characterized in that: The progressive decoupling system comprises: The model acquisition module is used to obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model; The starting node positioning module is used to locate the most downstream sub-catchment area corresponding to the target area in the parent model as the starting node of the target area extraction process; The dynamic topology tracking module is used to identify all upstream sub-catchments that are hydraulically connected to the starting node based on the river network topology in the parent model through dynamic topology tracking methods, and obtain a set of topologically connected sub-catchments; A model parameter set extraction module is used to extract the model parameter set corresponding to each sub-catchment in the topologically associated sub-catchment set; Boundary condition extraction module, used to extract boundary conditions related to the target area; An initial condition extraction module is used to extract the initial conditions of the target area; Common configuration parameter extraction module, used to extract common configuration parameters of the parent model; The sub-model generation module is used to construct a sub-model based on the information extracted by the model parameter set extraction module, the boundary condition extraction module, the initial condition extraction module and the general configuration parameter extraction module, and to verify the consistency of its model results; The loop module is used to use the sub-model constructed by the sub-model generation module as the new parent model when there is a demand for extracting a smaller-scale local watershed model in the target area, and to cyclically run the starting node positioning module, dynamic topology tracking module, model parameter set extraction module, boundary condition extraction module, initial condition extraction module, general configuration parameter extraction module and sub-model generation module until all application requirements for target area extraction are met.

8. A progressive decoupling device for generation of a watershed hydrological and water quality model, characterized in that: It includes a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the progressive decoupling device implements the steps of the progressive decoupling method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the progressive decoupling method according to any one of claims 1 to 6.

Images