Progressive decoupling method, system, equipment and medium for watershed hydrology and water quality model lineage generation

Abstract

The invention discloses a progressive decoupling method, a progressive decoupling system, progressive decoupling equipment and a progressive decoupling medium for lineage generation of a watershed hydrology and water quality model. The method comprises the following steps: firstly, positioning a most downstream sub catchment area of a target area in a pre-constructed watershed hydrology and water quality model (a parent model); then, through a dynamic topology tracking method, an upstream sub catchment area which has a hydraulic communication relation with the most downstream sub catchment area is identified, and a topological correlation sub catchment area set is obtained; performing parameter extraction on each sub catchment area in the set, wherein the parameter extraction comprises model parameters, boundary conditions, initial conditions and general configuration parameters of a parent model; and finally, constructing a sub-model according to the extracted information, and carrying out consistency verification on a model result of the sub-model. And when the research demand relates to a finer scale, iteratively executing the decoupling process by taking the sub-model as a new parent model until the final scale requirement is met. According to the method, the spatial scale decoupling precision and efficiency of the watershed hydrology and water quality model are remarkably improved, and the method 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 calculations, and particularly to a progressive decoupling method, system, device and medium for generating a lineage of basin hydrological and water quality models. Background Art

[0002] The computational complexity of basin hydrological and water quality models has long severely restricted the efficiency and accuracy of simulation work. Basin hydrological and water quality processes include hydrological processes such as precipitation, evaporation, runoff, infiltration, etc., as well as water quality processes such as the migration, transformation, and degradation of various pollutants. These processes are intertwined and interact with each other, forming an intricate system. In order to simulate this complex system as accurately as possible, the basin is usually finely divided into a large number of computational units. The original intention of this division is to capture the spatial differences in different regions within the basin, such as the influence of factors such as terrain undulation, soil type, and land use pattern on hydrological and water quality processes. However, when the basin is finely divided into a large number of computational units, since each computational unit has to independently perform complex hydrological and water quality calculations, the overall computational amount increases exponentially. This results in the consumption of a large amount of computational resources, making it difficult for even high-performance computers to handle easily. At the same time, the simulation time is greatly extended, and the research progress is severely slowed down. Moreover, the complex calculation process and significantly extended simulation time make it extremely difficult to debug the model, troubleshoot errors, and make corrections, making it difficult to ensure the accuracy and reliability of the simulation. The entire research process becomes extremely time-consuming and laborious, seriously affecting the in-depth development of basin management and research. Summary of the Invention

[0003] Object of the Invention: The first object of the present invention is to provide a progressive decoupling method for generating a lineage of basin hydrological and water quality models with low computational resource dependence and high simulation efficiency; the second object of the present invention is to provide a progressive decoupling system for generating a lineage of basin hydrological and water quality models; the third object of the present invention is to provide a progressive decoupling device for generating a lineage of basin hydrological and water quality models; the fourth object of the present invention is to provide a computer-readable storage medium.

[0004] Technical Solution: A progressive decoupling method for generating a lineage of basin hydrological and water quality models according to the present invention includes: S1: Obtain a pre-constructed and calibrated basin hydrological and water quality model as an 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; S3: Based on the river network topological structure in the parent model, identify all upstream sub-catchments that have a hydraulic connection relationship with the starting node through a dynamic topological tracking method to obtain a set of topologically associated sub-catchments; S4: Extract the set of model parameters corresponding to each sub-catchment in the set of topologically associated sub-catchments; S5: Extract the boundary conditions related to the target area; S6: Extract the initial conditions of the target area; S7: Extract the general configuration parameters of the parent model; S8: Use the information extracted in steps S4 to S7 to construct a sub-model and perform consistency verification on its model results; S9: When there is a need to extract a smaller-scale local watershed model for the target area, use the sub-model constructed in step S8 as the new parent model, and loop through steps S2 to S8 until all application requirements for the target area extraction are met.

[0005] Further, in step S2, to locate the most downstream sub-catchment corresponding to the target area, the method of automatically locating the most downstream sub-catchment corresponding to the target area using the river network topological structure or the method of manually selecting the most downstream sub-catchment corresponding to the target area is adopted.

[0006] Further, step S3 includes: S301: Initialize a set containing only the starting node; S302: According to the river network topological structure of the starting node in the parent model, obtain the first-level upstream sub-catchments that have a hydraulic connection relationship with the starting node, and add the first-level upstream sub-catchments to the set; S303: Use the newly added upstream sub-catchment in step S302 as the new starting node; S304: Loop through steps S302 to S303 until the top without upstream sub-catchments is traced; In each loop, determine whether the upstream sub-catchment is already in the set. If it is, discard it; if not, add it to the set. Finally, output the complete set of topologically associated sub-catchments.

[0007] Further, the model parameter set in step S4 includes sub-catchment-related parameters, sub-catchment parameter group-related parameters, sub-channel-related parameters corresponding to the sub-catchment, and sub-channel parameter group-related parameters.

[0008] Further, the boundary conditions in step S5 include meteorological driving input, point source emission input, and river channel water diversion or pumping input. The boundary condition extraction method is based on the set of topologically associated sub-catchments, combined with the preset correspondence between sub-catchments and weather stations in the watershed hydrological and water quality model, and includes point source emissions and river channel pumping within the range of the set of topologically associated sub-catchments.

[0009] Further, the initial conditions in step S6 include cold start state and hot start state, where the cold start state corresponds to the initial parameter settings in the main control file of the parent model, and the hot start state corresponds to the hot start initial condition file of the parent model.

[0010] Further, in step S8, a quantitative error analysis method is adopted to verify the consistency of the model results. The quantitative error analysis method adopts the mean square error MSE or the root mean square error RMSE; When using the mean square error MSE, calculate the square of the difference between the simulation values of each sub-watershed of the parent model and the child model at each moment, and sum the squares of the differences calculated for each sub-watershed and each moment. The formula is expressed as: ; Among them, A(i,t) represents the calculation result of the i-th sub-watershed of the parent model at the t-th moment, and B(i,t) represents the calculation result of the i-th sub-watershed of the child model at the t-th moment; According to the number of sub-watersheds and the total number of time steps, average the sum of the squares of the differences between the simulation values of each sub-watershed of the parent model and the child model at each moment. The formula is expressed as: ; Among them, I is the number of sub-watersheds, 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 requirement is met, the two models are highly consistent, and the decoupling is successful; When using the root mean square error RMSE, on the basis of calculating the MSE, further calculate the RMSE: ; 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 requirement is met, the two models are highly consistent, and the decoupling is successful.

[0011] Based on the same inventive concept, a progressive decoupling system for generating a lineage of a watershed hydrological and water quality model of the present invention includes: A model acquisition module, configured to acquire a pre-constructed and calibrated watershed hydrological and water quality model as an initial parent model; A starting node positioning module, configured to locate the most downstream sub-watershed corresponding to the target area in the parent model as the starting node of the target area extraction process; A dynamic topology tracking module, configured to identify all upstream sub-watersheds having a hydraulic connection relationship with the starting node based on the river network topology structure in the parent model, and obtain a set of topologically associated sub-watersheds; A model parameter set extraction module, configured to extract the model parameter sets corresponding to each sub-watershed in the set of topologically associated sub-watersheds; Boundary condition extraction module, configured to extract boundary conditions related to a target area; Initial condition extraction module, configured to extract initial conditions of the target area; General configuration parameter extraction module, configured to extract general configuration parameters of the parent model; Sub-model generation module, configured 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 perform consistency verification on the model results; Loop module, when there is a need to extract a smaller-scale local watershed model for the target area, uses the sub-model constructed by the sub-model generation module as the new parent model, and loops through the starting node positioning module, the dynamic topology tracking module, the model parameter set extraction module, the boundary condition extraction module, the initial condition extraction module, the general configuration parameter extraction module, and the sub-model generation module until all application requirements for the target area extraction are met.

[0012] Based on the same inventive concept, a progressive decoupling device for generating a lineage of a watershed hydrological and water quality model according to the present invention includes a processor and a memory, where computer instructions are stored in the memory, and the processor is configured 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.

[0013] Based on the same inventive concept, a computer-readable storage medium according to the present invention stores a computer program, and when the program is executed by a processor, it implements the steps of the above-mentioned progressive decoupling method.

[0014] Advantageous effects: Compared with the prior art, the present invention has the following remarkable advantages: The present invention decouples the parent watershed model, and its essence is to disassemble a large watershed into multiple independent sub-watersheds. By carrying out hydrological and water quality simulations of the sub-watershed models to replace the operation of the parent watershed model, it is convenient to quickly carry out local refined simulations, analyses, and verifications on complex watersheds, reduce the consumption of simulation time and computing resources, and accelerate the research, calibration, and optimization processes of the watershed model. When conducting targeted research on a local spatial area, it is possible to quickly identify its upstream sub-catchments through the topological structure established by the watershed model based on the selection of a simple downstream target sub-catchment, which is accurate, efficient, and significantly improves the model spatial decoupling efficiency.

[0015] The present invention can achieve progressive multi-level model decoupling and expansion, forming a dynamic hierarchical model pedigree. Through this step-by-step refinement modeling strategy, progressive fine modeling from the basin scale to smaller regional scales can be realized. This progressive multi-level model decoupling and expansion can rapidly generate the lineage of basin hydrological and water quality models based on the existing parent basin model, enabling research on sub-basins at finer scales, such as conducting hydrological and water quality simulations of grandson models.

[0016] The present invention not only revolutionizes the computational paradigm of traditional basin simulation but also opens up a new path for the refined management of complex basins. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic flowchart of a progressive decoupling method for generating the lineage of a basin hydrological and water quality model disclosed in an embodiment of the present invention; Figure 2 It is a diagram of the sub-catchments and sub-channels of the parent model in an embodiment of the present invention (the target area is within the red range); Figure 3 It is a diagram of the sub-catchments and sub-channels of the sub-model in an embodiment of the present invention; Figure 4 It is a schematic structural diagram of a progressive decoupling system for generating the lineage of a basin hydrological and water quality model disclosed in an embodiment of the present invention; Figure 5 It is a schematic structural diagram of a progressive decoupling device for generating the lineage of a basin hydrological and water quality model disclosed in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. Those skilled in the art will understand that the objectives and advantages that can be achieved by the present invention are not limited to the specific beneficial effects described above, and the above and other objectives that the present invention can achieve will be more clearly understood from the following detailed description.

[0019] Those of ordinary skill in the art should understand that the various exemplary components, systems, and methods described in connection with the embodiments disclosed in the present invention can be implemented in hardware, software, or a combination of both. Specifically, whether to execute in a hardware or software manner depends on the specific application and design and tree conditions of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0020] As used herein, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of the present invention. The phrase may not necessarily refer to the same embodiment when it appears in various places in the specification, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0021] Embodiment 1: Please refer to Figure 1 , Figure 1 which is a schematic 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: S1: Obtain a pre-constructed and calibrated watershed hydrological and water quality model as an initial parent model.

[0022] The method for pre-constructing a watershed hydrological and water quality model is a prior art. The construction process mainly includes the following parts: (I) Construction of hydrological response units Convert elevation DEM (Digital Elevation Model) data into slope spatial vector data, and fuse the obtained land use type data, soil data, and slope spatial vector data to construct hydrological response units.

[0023] (II) Construction of sub-watersheds Use elevation DEM data to initially automatically generate sub-watersheds and sub-channels in the SWAT (Soil and Water Assessment Tool) model, and manually modify the parts where the division boundaries or sub-channels are unreasonable or do not meet the application requirements due to algorithm limitations, data errors, or application requirements during automatic division to determine the final sub-watersheds and sub-channels that conform to the actual situation and meet the simulation requirements. The sub-watersheds and sub-channels have unique and one-to-one corresponding codes. Each sub-channel has a unique downstream, and a river network topological structure is formed from upstream to downstream.

[0024] A sub-watershed is a small natural geographical unit enclosed by certain topographic features. Each sub-watershed corresponds to a sub-channel. The sub-channel receives the water volume and load from the land area of the corresponding sub-watershed, as well as the water volume and load from its upstream, channel pumping input, point source input, etc., and can be used as an irrigation water source for water intake and irrigation, or as a pumping water source to pump water to other sub-channels or outside the watershed. The water volume and load flowing out of the sub-channel enter its downstream sub-channel as the upstream water and load of its downstream sub-channel.

[0025] Such as Figure 2As shown, the parent model obtained in this embodiment divides into 209 sub-watersheds (due to image size limitations, not all numbers are shown).

[0026] (III) Generation of Other Documents Produce meteorological driving input, point source emission input, and river diversion or pumping input files.

[0027] (IV) Model Parameter Configuration Perform local expression on the model, set model parameters, and adjust and determine the final model parameters according to the parameter calibration and model verification situations.

[0028] (V) Setting of Model Initial Conditions Set the initial parameters for the cold start of the model and generate the initial condition file for the hot start of the model.

[0029] S2: Locate the most downstream sub-watershed corresponding to the target area in the parent model as the starting node for the target area extraction process.

[0030] The parent model contains several sub-basins, and the target area is any one of these sub-basins, selected according to research needs. The most downstream sub-watershed is generally automatically located through the river network topology structure. For the convenience of operation, the most downstream sub-watershed can also be selected manually.

[0031] As Figure 2 shown, in this embodiment, the red range is used as the target area, and the code of its most downstream sub-watershed is 65.

[0032] S3: Based on the river network topology structure in the parent model, identify all upstream sub-watersheds that have a hydraulic connection relationship with the starting node through the dynamic topology tracing method to obtain the set of topologically associated sub-watersheds.

[0033] The dynamic topology tracing method starts from the starting node, traces upstream along the river, and gradually identifies all upstream sub-watersheds that have a hydraulic connection relationship with the starting node. Redundant and repeated identifications need to be avoided during the tracing process. In addition, in order to ensure the integrity of the set of topologically associated sub-watersheds, this embodiment also includes special water intake paths such as irrigation water diversion and river pumping into the tracing and identification scope.

[0034] The dynamic topology tracing method specifically includes the following steps: S301: Initialize the set that only contains the starting node.

[0035] S302: According to the river network topology structure of the starting node in the parent model, obtain the first-level upstream sub-watersheds that have a hydraulic connection relationship with this starting node, and add the first-level upstream sub-watersheds to the set.

[0036] S303: Use the newly added upstream sub - catchment in step S302 as the new starting node.

[0037] S304: Loop through steps S302 to S303 until the top of the sub - catchment with no upstream sub - catchment is reached.

[0038] During each loop, determine whether the upstream sub - catchment is already in the set. If it is, discard it; if not, add it to the set. Finally, output the complete set of topologically associated sub - catchments.

[0039] This dynamic topology tracking method performs step - by - step upstream tracking, which can quickly determine the set of topologically associated sub - catchments while avoiding redundancy and omission.

[0040] As Figure 3 shown, in this embodiment, the codes of all upstream sub - catchments of sub - catchment No. 65 are 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. According to the river network topology structure in the parent model, considering the sub - catchments related to the irrigation water intake sources and river channel pumping sources involved in the upstream - traced sub - catchments, in this embodiment, there is only a sub - catchment related to the river channel pumping source, with the code 42.

[0041] S4: Extract the set of model parameters corresponding to each sub - catchment in the set of topologically associated sub - catchments.

[0042] The basin hydrological and water quality model is in text form, and all parameters are placed in different cards and different texts. Some parameter settings are directly based on sub - catchments, some are directly based on hydrological response units, some are based on sub - basin parameter groups and hydrological response units, and some are based on sub - river - channel parameter groups and hydrological response units.

[0043] For those set according to sub - catchments, directly extract the parameters corresponding to the set of topologically associated sub - catchments; for those set according to hydrological response units, directly extract all parameters; for those set according to sub - basin parameter groups and hydrological response units, it is necessary to determine the corresponding sub - catchment parameter groups according to the set of topologically associated sub - catchments and extract according to the sub - catchment parameter groups; for those set according to sub - river - channel parameter groups and hydrological response units, it is necessary to determine the corresponding sub - river - channel parameter groups according to the set of topologically associated sub - catchments and extract according to the sub - river - channel parameter groups.

[0044] The set of model parameters includes sub - catchment - related parameters, sub - catchment parameter - group - related parameters, sub - catchment - corresponding sub - river - channel - related parameters, and sub - river - channel parameter - group - related parameters.

[0045] The parameters related to sub-catchments include the parameters of the sub-catchment's own attributes, the related settings of the hydrological response unit, the grouping settings of the sub-catchments (the main control file specifies the group to which the sub-catchment belongs, and the parameters are set according to the group, rather than according to the sub-catchment, so the corresponding group needs to be found to extract the parameters), the parameters related to the irrigation water intake mode, the parameters related to the surface pollutant accumulation mode, and the parameters of the advanced function module. Among them, the parameters related to the irrigation water intake mode are used to simulate the irrigation process of the basin plots, the parameters related to the surface pollutant accumulation mode are used to simulate the surface pollutant accumulation process of the basin, and the parameters of the advanced function module include the parameters related to the adjustment of groundwater outflow and the hydrological and water quality parameters related to storage and detention.

[0046] The parameters related to the sub-catchment parameter group include hydrological parameters and water quality parameters.

[0047] The parameters related to the sub-channel corresponding to the sub-catchment include the parameters of the channel's own attributes, the settings of the topological connection relationship, and the grouping settings (the main control file specifies the group to which the sub-channel belongs, and the parameters are set according to the group, rather than according to the sub-channel, so the corresponding group needs to be found to extract the parameters).

[0048] The parameters related to the sub-channel parameter group include hydrological parameters and water quality parameters.

[0049] Finally, through the hydrological response unification interface, the set of model parameters of each sub-catchment extracted is added to the sub-model input file.

[0050] In this embodiment, the input file for the irrigation water intake mode is irr.inp; the input file for the surface pollution accumulation mode is acc.inp; the input file for the parameters of the advanced function module is adv.inp; other parameters are in the same input file, called the model main control file, and the main control file is IWS.inp.

[0051] S5: Extract the boundary conditions related to the target area.

[0052] The boundary conditions include meteorological driving input, point source emission input, and river diversion or pumping input.

[0053] The boundary condition extraction method is based on the set of topologically associated sub-catchments, combined with the preset correspondence between the sub-catchment and the meteorological station in the basin hydrological and water quality model, and includes point source emissions and river pumping within the range of the set of topologically associated sub-catchments.

[0054] In this embodiment, the meteorological driving input involves the meteorological data.air format files and the parameter settings of the meteorological condition-related cards in the main control file IWS.inp. The meteorological data.air format files are 3.air, 4.air, 6.air, and the meteorological condition-related cards in the main control file IWS.inp are C10, C15, C20, C30, and C60.

[0055] The point source emission input involves the point source data in the.inp format file, the point source attenuation setting in the.inp format file, and the parameter settings of the relevant cards for point source input in the main control.inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the main control file is IWS.inp, and the relevant cards for point source input in the main control file IWS.inp are C31, C420, C425, and C660.

[0056] The river diversion or pumping input involves the point source data related to river pumping in the.inp format file, the point source attenuation setting in the.inp format file, and the parameter settings of the relevant cards for river pumping in the main control.inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the main control file is IWS.inp, and the relevant cards for river pumping in the main control file IWS.inp are C31, C420, C430, and C660.

[0057] S6: Extract the initial conditions of the target area.

[0058] The initial conditions include the cold start state and the hot start state. The cold start state corresponds to the initial parameter settings in the main control file of the parent model, and all the parameters of the relevant cold start settings can be extracted.

[0059] The hot start state corresponds to the hot start initial condition file of the parent model. The hot start state parameters are set in the separately generated hot start file, which are divided into sub - catchments, sub - rivers, point sources, and river pumping. For extracting these corresponding parameters, the hot start parameters of the corresponding sub - catchments and sub - rivers need to be extracted according to the previously generated topological associated sub - catchment set, and the hot start parameters of the corresponding point sources and river pumping are extracted according to the point source emission input and the river diversion or pumping input, and a new hot start file is regenerated.

[0060] In order to maintain the same initial state for the subsequent generated sub - model and the parent model in the same - area simulation, the initial state of the sub - basins that need to be extracted in the parent model can be completely retained, so that the extracted sub - model can start the simulation from the same initial state as the relevant spatial area of the parent model.

[0061] S7: Extract the general configuration parameters of the parent model.

[0062] The general configuration parameters include the start - stop state, the simulation time step, the simulation and output time intervals, the output variable settings, and the output file settings.

[0063] The general configuration parameters of the parent model are used to configure the sub - model in step S8, which helps to maintain the integrity of the sub - model and its consistency with the parent model.

[0064] S8: Construct a sub-model using the information extracted in steps S4 to S7 and perform consistency verification on its model results.

[0065] Adopt a quantitative error analysis method to compare and evaluate the simulation results of the parent model and the sub-model in each sub-watershed at each time period. The quantitative error analysis method includes mean square error MSE, root mean square error RMSE, and mean absolute error MAE.

[0066] Taking the mean square error MSE as an example, if the MSE value is within the acceptable range, it is determined that the simulation results of the sub-model are highly consistent with the parent model, thereby confirming that the sub-domain extraction is successful and the model decoupling is effective. Specifically: Calculate the square of the difference between the simulated values of the parent model and the sub-model at each moment in each sub-watershed, and sum the squares of the differences calculated for each sub-watershed and each moment. The formula is expressed as: ; Among them, A(i,t) represents the calculation result of the parent model at the i-th sub-watershed at the t-th moment, and B(i,t) represents the calculation result of the sub-model at the i-th sub-watershed at the t-th moment.

[0067] According to the number of sub-watersheds and the total number of time steps, average the sum of the squares of the differences between the simulated values of the parent model and the sub-model at each moment in each sub-watershed. The formula is expressed as: ; Among them, I is the number of sub-watersheds, and T is the total number of time steps.

[0068] When the MSE of flow simulation is less than 5% of the square of the corresponding average flow, and the MSE of water quality concentration simulation is less than 10% of the square of the corresponding average concentration, it is considered that the accuracy requirement is met, the two models are highly consistent, and the decoupling is successful.

[0069] If the root mean square error RMSE is used, on the basis of calculating the MSE, further calculate the RMSE: ; When the RMSE of flow simulation is less than 5% of the corresponding average flow, and the RMSE of water quality concentration simulation is less than 10% of the corresponding average concentration, it is considered that the accuracy requirement is met, the two models are highly consistent, and the decoupling is successful. RMSE is closely related to MSE, but the unit of RMSE is the same as the original data, which is easier to interpret.

[0070] The mean absolute error MAE and the mean square error MSE can both be used to measure the error between the predicted value and the actual value, but MAE uses the absolute value instead of the square error and is not sensitive to outliers. Therefore, the present invention uses the mean square error MSE or the root mean square error RMSE.

[0071] In this embodiment, all the extracted files are stored in a new path (i.e., the folder of the sub-model), and the corresponding file path in the master control file is updated to generate a new executable sub-model in which the simulation results of each sub-catchment are consistent with the model results of the sub-catchment corresponding to the parent model.

[0072] The sub-model contains the main control file main.inp, the meteorological data placement folder AIR and the auxiliary input file placement 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.

[0073] 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.

[0074] The present invention can realize progressive multi-level model decoupling and expansion, forming a dynamic hierarchical model pedigree. Through this step-by-step modeling strategy, progressive fine modeling from the basin scale to a smaller regional scale can be realized, and the consistency of parameter inheritance and the isomorphic unity of the simulation environment can be maintained between models at each level. This progressive multi-level model decoupling and expansion can quickly generate a basin hydrological and water quality model pedigree based on the existing parent basin model, and realize the study of a finer-scale sub-basin, such as conducting hydrological and water quality simulation of a grandchild model.

[0075] Example 2: Please refer to Figure 4 , Figure 4 It is a schematic diagram of the structure of a progressive decoupling system for generating a lineage of a watershed hydrological and water quality model disclosed in an embodiment of the present invention. The progressive decoupling system for generating a lineage of a watershed hydrological and water quality model 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.

[0076] The model acquisition module is used to obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model.

[0077] The pre-construction method of the watershed hydrological and water quality model is an existing technology, and the construction process mainly includes the following parts: 1.1 Construction of hydrological response unit Convert the elevation DEM (Digital Elevation Model) data into slope spatial vector data, and based on the obtained land use type data, soil data, and slope spatial vector data, perform fusion to construct hydrological response units.

[0078] (2) Sub-watershed construction Use the elevation DEM data to initially and automatically generate sub-watersheds and sub-channels in the SWAT (Soil and Water Assessment Tool) model, and manually modify the parts where the division boundaries or sub-channels are unreasonable and do not meet the application requirements due to algorithm limitations, data errors, or application requirements during automatic division, so as to determine the final sub-watersheds and sub-channels that conform to the actual situation and meet the simulation requirements, where the sub-watersheds and sub-channels have unique codes and are in one-to-one correspondence. Each sub-channel has a unique downstream, and a river network topological structure is formed from upstream to downstream.

[0079] A sub-watershed is a small natural geographical unit surrounded by certain topographic features. Each sub-watershed corresponds to a sub-channel. The sub-channel undertakes the water volume and load of the land area water inflow of the corresponding sub-watershed, as well as the water volume and load of the upstream, channel pumping input, point source input, etc., and can be used as an irrigation water source for water intake irrigation, as a pumping water source to pump water to other sub-channels or outside the basin. The water volume and load flowing out of the sub-channel enter its downstream sub-channel and serve as the upstream water and load of its downstream sub-channel.

[0080] As Figure 2 shown, the parent model obtained in this embodiment divides 209 sub-watersheds (due to image size limitations, not all numbers are shown).

[0081] (3) Generation of other files Produce meteorological driving input, point source emission input, and river channel water diversion or pumping input files.

[0082] (4) Model parameter configuration Perform local expression on the model, set model parameters, and adjust and determine the final model parameters according to the parameter calibration and model verification situations.

[0083] (5) Model initial condition setting Set the initial parameters for model cold start and generate the initial condition file for model warm start.

[0084] The starting node positioning module is used to locate the most downstream sub-watershed corresponding to the target area in the parent model as the starting node of the target area extraction process.

[0085] The parent model contains several sub - basins, and the target area is any one of these sub - basins, which is selected according to research needs. The most downstream sub - catchment is generally automatically located through the river network topology structure. For the convenience of operation, the most downstream sub - catchment can also be selected manually.

[0086] As Figure 2 shown, in this embodiment, the red area is used as the target area, and the code of its most downstream sub - catchment is 65.

[0087] The dynamic topology tracking module is used to identify all upstream sub - catchments that have a hydraulic connection relationship with the starting node based on the river network topology structure in the parent model, and obtain the set of topologically associated sub - catchments.

[0088] The dynamic topology tracking method starts from the starting node, traces upstream along the river course, and gradually identifies all upstream sub - catchments that have a hydraulic connection relationship with the starting node. Redundant and repeated identifications need to be avoided during the tracking process. In addition, in order to ensure the integrity of the set of topologically associated sub - catchments, this embodiment also includes special water - taking paths such as irrigation water diversion and river pumping into the tracking and identification scope.

[0089] The dynamic topology tracking method specifically includes the following steps: S301: Initialize a set that only contains the starting node.

[0090] S302: According to the river network topology structure of the starting node in the parent model, obtain the first - level upstream sub - catchments that have a hydraulic connection relationship with this starting node, and add the first - level upstream sub - catchments to the set.

[0091] S303: Take the newly added upstream sub - catchment in step S302 as the new starting node.

[0092] S304: Loop and execute steps S302 to S303 until the top without upstream sub - catchments is reached.

[0093] During each loop, judge whether the upstream sub - catchment is already in the set. If it is, discard it; if not, add it to the set. Finally, output the complete set of topologically associated sub - catchments.

[0094] This dynamic topology tracking method performs step - by - step upstream tracking, which can quickly determine the set of topologically associated sub - catchments and avoid redundancy and omission at the same time.

[0095] As Figure 3As shown in the figure, in this embodiment, all the upstream sub - catchments of the 65th sub - catchment 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. According to the river network topology structure in the parent model, considering the irrigation water intake sources and the sub - catchments related to the river channel pumping sources involved in the upstream - traced sub - catchments, in this embodiment, there is only a sub - catchment related to the river channel pumping source, coded as 42.

[0096] The model parameter set extraction module is used to extract the model parameter sets corresponding to each sub - catchment in the set of topologically associated sub - catchments.

[0097] The basin hydrological and water quality model is in text form, and all parameters are placed in different cards and different texts. Some parameter settings are directly based on sub - catchments, some are directly based on hydrological response units, some are based on sub - basin parameter groups and hydrological response units, and some are based on sub - river - channel parameter groups and hydrological response units.

[0098] For those set according to sub - catchments, directly extract the parameters corresponding to the set of topologically associated sub - catchments; for those set according to hydrological response units, directly extract all parameters; for those set according to sub - basin parameter groups and hydrological response units, it is necessary to determine the corresponding sub - catchment parameter groups according to the set of topologically associated sub - catchments and extract according to the sub - catchment parameter groups; for those set according to sub - river - channel parameter groups and hydrological response units, it is necessary to determine the corresponding sub - river - channel parameter groups according to the set of topologically associated sub - catchments and extract according to the sub - river - channel parameter groups.

[0099] The model parameter set includes sub - catchment - related parameters, sub - catchment parameter group - related parameters, sub - catchment - corresponding sub - river - channel - related parameters, and sub - river - channel parameter group - related parameters.

[0100] The sub - catchment - related parameters include sub - catchment self - attribute parameters, hydrological response unit - related setting parameters, sub - catchment grouping setting parameters (the main control file specifies the group to which the sub - catchment belongs, and the parameters are set according to the group rather than the sub - catchment, so the corresponding group needs to be found to extract the parameters), 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 in the basin, and the advanced function module parameters include groundwater outflow adjustment - related parameters and storage - related hydrological and water quality parameters.

[0101] The sub - catchment parameter group - related parameters include hydrological parameters and water quality parameters.

[0102] The parameters related to the sub-channel corresponding to the sub-watershed include the parameters of the channel's own attributes, the parameters for setting the topological connection relationship, and the parameters for grouping settings (the main control file specifies the group to which the sub-channel belongs, and the parameters are set according to the group, rather than according to the sub-channel. Therefore, the corresponding group needs to be found to extract the parameters).

[0103] The parameters related to the sub-channel parameter group include hydrological parameters and water quality parameters.

[0104] Finally, through the hydrological response unification interface, the set of model parameters of each sub-watershed extracted is added to the sub-model input file.

[0105] In this embodiment, the input file for the irrigation water intake mode is irr.inp; the input file for the surface pollution accumulation mode is acc.inp; the input file for the parameters of the advanced function module is adv.inp; other parameters are in the same input file, called the model main control file, and the main control file is IWS.inp.

[0106] The boundary condition extraction module is used to extract the boundary conditions related to the target area.

[0107] The boundary conditions include meteorological driving input, point source emission input, and river channel water diversion or pumping input.

[0108] The boundary condition extraction method is based on the set of topologically associated sub-watersheds, combined with the corresponding relationship between the sub-watersheds and meteorological stations preset in the basin hydrological and water quality model, and includes point source emissions and river channel pumping within the range of the set of topologically associated sub-watersheds.

[0109] In this embodiment, the meteorological driving input involves the meteorological data.air format files and the parameter settings of the meteorological condition-related cards in the main control file IWS.inp. The meteorological data.air format files are 3.air, 4.air, and 6.air, and the meteorological condition-related cards in the main control file IWS.inp are C10, C15, C20, C30, and C60.

[0110] The point source emission input involves the point source data.inp format file, the point source attenuation setting.inp format file, and the parameter settings of the point source input-related cards in the main.inp format file. The point source data file is point.inp, the point source attenuation setting file is psdecay.inp, the main control file is IWS.inp, and the point source input-related cards in the main control file IWS.inp are C31, C420, C425, and C660.

[0111] River diversion or pumping input involves the setting parameters of the river pumping - related cards in the river pumping - related point - source data.inp file, the point - source decay setting.inp file, and the main control.inp file. The point - source data file is point.inp, the point - source decay setting file is psdecay.inp, the main control file is IWS.inp, and the river - pumping - related cards in the main control file IWS.inp are C31, C420, C430, and C660.

[0112] Initial condition extraction module, used to extract the initial conditions of the target area.

[0113] The initial conditions include cold - start state and hot - start state. Among them, the cold - start state corresponds to the initial parameter settings in the main control file of the parent model, and extracting the parameters of all cold - start - related settings is sufficient.

[0114] The hot - start state corresponds to the hot - start initial condition file of the parent model. The hot - start state parameters are set in the separately generated hot - start file, which are divided into sub - catchments, sub - rivers, point sources, and river pumping. For these corresponding parameters extraction, it is necessary to extract the corresponding sub - catchment and sub - river hot - start parameters according to the previously generated topological association sub - catchment set, and extract the corresponding point - source and river - pumping hot - start parameters according to the point - source discharge input and river diversion or pumping input, and then regenerate a new hot - start file.

[0115] In order to maintain the same initial state of the subsequent generated sub - model and the parent model in the same - area simulation, the initial state of the sub - catchments that need to be extracted in the parent model can be completely retained, so that the extracted sub - model can start the simulation from the same initial state as the relevant spatial area of the parent model.

[0116] General configuration parameter extraction module, used to extract the general configuration parameters of the parent model.

[0117] The general configuration parameters include start - stop state, simulation time step, simulation and output time intervals, output variable settings, and output file settings.

[0118] The general configuration parameters of the parent model are used to configure the sub - model, which helps to maintain the integrity of the sub - model and its consistency with the parent model.

[0119] Sub - model generation module, used to construct a sub - model according to the information extracted by the model parameter set extraction module, boundary condition extraction module, initial condition extraction module, and general configuration parameter extraction module, and perform consistency verification on its model results.

[0120] Adopt a quantitative error analysis method to compare and evaluate the simulation results of the parent model and the sub - model in each sub - catchment at each time period. The quantitative error analysis methods include mean square error MSE, root mean square error RMSE, and mean absolute error MAE.

[0121] Taking the mean squared error (MSE) as an example, if the MSE value is within an acceptable range, it is determined that the simulation results of the sub-model are highly consistent with those of the parent model, thereby confirming that the sub-domain extraction is successful and the model decoupling is effective. Specifically: Calculate the square of the difference between the simulated values of each sub-watershed of the parent model and the sub-model at each moment, and sum the squares of the differences calculated for each sub-watershed and each moment. The formula is expressed as: ; where A(i,t) represents the calculation result of the i-th sub-watershed of the parent model at the t-th moment, and B(i,t) represents the calculation result of the i-th sub-watershed of the sub-model at the t-th moment.

[0122] According to the number of sub-watersheds and the total number of time steps, average the sum of the squares of the differences between the simulated values of each sub-watershed of the parent model and the sub-model at each moment. The formula is expressed as: ; where I is the number of sub-watersheds and T is the total number of time steps.

[0123] 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 requirement is met, the two models are highly consistent, and the decoupling is successful.

[0124] If the root mean squared error (RMSE) is used, based on the calculation of MSE, further calculate RMSE: ; When the RMSE of the flow simulation is less than 5% of the corresponding average flow, and the RMSE of the water quality concentration simulation is less than 10% of the corresponding average concentration, it is considered that the accuracy requirement is met, the two models are highly consistent, and the decoupling is successful. RMSE is closely related to MSE, but the unit of RMSE is the same as the original data, making it easier to interpret.

[0125] The mean absolute error (MAE) and the mean squared error (MSE) can both be used to measure the error between the predicted value and the actual value. However, MAE uses the absolute value instead of the squared error and is not sensitive to outliers. Therefore, this invention uses the mean squared error (MSE) or the root mean squared error (RMSE).

[0126] In this embodiment, all the extracted files are stored in a new path (i.e., the folder of the sub-model), and the file corresponding paths in the main control file are updated to generate a new sub-model that can run, and the simulation results of each sub-watershed are consistent with the model results of the corresponding sub-watershed of the parent model.

[0127] The sub-model includes the main control file main.inp, the meteorological data placement folder AIR, and the auxiliary input file placement 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 decay 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.

[0128] The loop module is used to, when there is a need to extract a smaller-scale local watershed model in the target area, take the sub-model constructed by the sub-model generation module as the new parent model, and loop through the starting node positioning module, the dynamic topology tracking module, the model parameter set extraction module, the boundary condition extraction module, the initial condition extraction module, the general configuration parameter extraction module, and the sub-model generation module until all application requirements for the target area extraction are met.

[0129] Embodiment 3: Please refer to Figure 5 , Figure 5 FIG. is a schematic structural diagram of a progressive decoupling device for generating a watershed hydrological and water quality model lineage disclosed in an embodiment of the present invention. The device may include a processor and a memory. Computer instructions are stored in the memory, and the processor is configured 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 Embodiment 1 above and can achieve consistent technical effects.

[0130] The memory may include a computer system readable medium 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 non-removable, non-volatile magnetic media (commonly referred to as a "hard disk drive"). A program / utility having a set (at least one) of program modules may be stored in the memory, such as an operating system, one or more application programs, other program modules, and program data. Each of these examples or some combination thereof may include an implementation of a network environment. The program modules generally execute the functions and / or methods described in the embodiments of the present invention.

[0131] The processor executes various functional applications and data processing by running the programs stored in the memory, such as implementing the progressive decoupling method provided in Embodiment 1 of the present invention.

[0132] Example 4: The embodiments of the present invention further provide 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 Embodiment 1 are implemented, and the same technical effects can be achieved.

[0133] The computer storage medium of the embodiments of the present invention may adopt 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 of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection with 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.

[0134] The computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0135] The program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination of the above.

[0136] Computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed 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 through 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., by connecting through the Internet using an Internet service provider).

[0137] 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, and may also execute related operations in the methods provided by any embodiment of the present invention.

[0138] The specific embodiments described above have further elaborated on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A progressive decoupling method for generating a lineage of a watershed hydrological and water quality model, characterized in that, Including: S1: Obtain a pre-built and calibrated watershed hydrological and water quality model as the initial parent model; S2: Locate the most downstream sub-watershed corresponding to the target area in the parent model as the starting node for the target area extraction process; S3: Based on the river network topological structure in the parent model, identify all upstream sub-watersheds with a hydraulic connection relationship with the starting node through a dynamic topological tracing method to obtain a set of topologically associated sub-watersheds; S4: Extract the set of model parameters corresponding to each sub-watershed in the set of topologically associated sub-watersheds; S5: Extract the boundary conditions related to the target area; S6: Extract the initial conditions of the target area; S7: Extract the general configuration parameters of the parent model; S8: Use the information extracted in steps S4 to S7 to construct a sub-model and conduct consistency verification on its model results; S9: When there is a need to extract a smaller-scale local watershed model for the target area, use the sub-model constructed in step S8 as the new parent model, and loop through steps S2 to S8 until all application requirements for the target area extraction are met.

2. The progressive decoupling method generated based on the catchment hydrological and water quality model lineage according to claim 1, wherein In step S2, the method of locating the most downstream sub-watershed corresponding to the target area is to automatically locate the most downstream sub-watershed corresponding to the target area using the river network topological structure or to manually select the most downstream sub-watershed corresponding to the target area.

3. The progressive decoupling method generated according to the watershed hydrological water quality model lineage described in claim 1, characterized in that, Step S3 includes: S301: Initialize a set containing only the starting node; S302: According to the river network topological structure of the starting node in the parent model, obtain the first-level upstream sub-watersheds with a hydraulic connection relationship with the starting node and add the first-level upstream sub-watersheds to the set; S303: Use the newly added upstream sub-watersheds in step S302 as the new starting nodes; S304: Loop through steps S302 to S303 until the top end without upstream sub-watersheds is traced; In each loop process, determine whether the upstream sub-watersheds are already in the set. If so, discard them; if not, add them to the set. Finally, output the complete set of topologically associated sub-watersheds.

4. The progressive decoupling method generated according to the catchment hydrological and water quality model lineage described in claim 1, characterized in that The set of model parameters in step S4 includes sub-watershed-related parameters, sub-watershed parameter group-related parameters, sub-channel-related parameters corresponding to the sub-watershed, and sub-channel parameter group-related parameters.

5. The progressive decoupling method generated according to the watershed hydrological water quality model lineage described in claim 1, characterized in that The boundary conditions in step S5 include meteorological driving input, point source emission input, and river channel diversion or pumping input. The boundary condition extraction method is based on the set of topologically associated sub-watersheds, combined with the preset corresponding relationship between sub-watersheds and meteorological stations in the watershed hydrological and water quality model, and includes point source emissions and river channel pumping within the range of the set of topologically associated sub-watersheds.

6. The progressive decoupling method generated according to the watershed hydrological and water quality model lineage described in claim 1, characterized in that, The initial conditions in step S6 include cold start state and hot start state, where the cold start state corresponds to the initial parameter settings in the main control file of the parent model, and the hot start state corresponds to the hot start initial condition file of the parent model.

7. The progressive decoupling method generated according to the watershed hydrological and water quality model lineage described in claim 1, characterized in that, In step S8, a quantitative error analysis method is used for model result consistency verification, and the quantitative error analysis method uses the mean square error MSE or the root mean square error RMSE; When the mean squared error (MSE) is adopted, calculate the square of the difference between the simulated values of each sub-watershed of the parent model and the child model at each moment, and sum up the squares of the differences calculated for each sub-watershed and each moment. The formula is expressed as: ； Where, A(i,t) represents the calculation result of the i-th sub-watershed of the parent model at the t-th moment, and B(i,t) represents the calculation result of the i-th sub-watershed of the child model at the t-th moment; According to the number of sub-watersheds and the total number of time steps, average the sum of the squares of the differences between the simulated values of each sub-watershed of the parent model and the child model at each moment. The formula is expressed as: ； Where, I is the number of sub-watersheds, 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 requirement is met, the two models are highly consistent, and the decoupling is successful; When the root mean square error (RMSE) is adopted, then on the basis of calculating the MSE, further calculate the RMSE: ； 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 requirement is met, the two models are highly consistent, and the decoupling is successful.

8. A progressive decoupling system for generating a lineage of a basin hydrological and water quality model, characterized in that, Including: A model acquisition module, used to acquire a pre-constructed and calibrated watershed hydrological and water quality model as the initial parent model; A starting node positioning module, used to locate the most downstream sub-watershed corresponding to the target area in the parent model as the starting node of the target area extraction process; A dynamic topology tracking module, used to identify all upstream sub-watersheds that have a hydraulic connection relationship with the starting node based on the river network topology structure in the parent model, and obtain a set of topologically associated sub-watersheds; A model parameter set extraction module, used to extract the model parameter sets corresponding to each sub-watershed in the set of topologically associated sub-watersheds; A boundary condition extraction module, used to extract the boundary conditions related to the target area; An initial condition extraction module, used to extract the initial conditions of the target area; A general configuration parameter extraction module, used to extract the general configuration parameters of the parent model; A child model generation module, used to construct a child model according to 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 perform consistency verification on its model results; A loop module, used when there is a need to extract a smaller-scale local watershed model in the target area, take the child model constructed by the child model generation module as the new parent model, and loop through the starting node positioning module, the dynamic topology tracking module, the model parameter set extraction module, the boundary condition extraction module, the initial condition extraction module, the general configuration parameter extraction module, and the child model generation module until all application requirements for target area extraction are met.

9. A progressive decoupling device for generating a lineage of a watershed hydrological and water quality model, characterized in that, It includes a processor and a memory, and computer instructions are stored in the memory. The processor is configured 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 according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the steps of the progressive decoupling method according to any one of claims 1 to 7.

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