Whole watershed hydrological dynamic regulation and control system based on SWAT model

Abstract

The invention discloses a whole-basin hydrological dynamic regulation and control system based on an SWAT model, and relates to the technical field of hydrology and water resources, and the whole-basin hydrological dynamic regulation and control system comprises a data collection module which comprises a collection unit and a data preprocessing unit, the data preprocessing unit is used for carrying out cleaning, denoising and normalization processing on the collected topographic data, land data and meteorological data, and obtaining a data preprocessing value. According to the whole-watershed hydrological dynamic regulation and control system based on the SWAT model, topographic data, land data (including soil data and land utilization data) and meteorological data in a whole watershed are comprehensively acquired through the data acquisition module, and rich basic information is provided for hydrological dynamic regulation and control. The influence of various factors on the hydrological process can be considered more comprehensively, and the accuracy of hydrological simulation and regulation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrology and water resources, and specifically to a whole-basin hydrological dynamic regulation system based on the SWAT model. Background Art

[0002] In today's society, the whole-basin hydrological dynamic regulation is crucial for the rational utilization of water resources, ecological environment protection, and the sustainable development of the economy and society. However, there are a series of challenges in the whole-basin hydrological dynamic regulation at present.

[0003] On the one hand, the existing hydrological regulation systems have limitations in data collection. Traditional data collection methods often focus on single-type data, such as topographic data or meteorological data, and insufficient attention is paid to the comprehensive collection of land data. Among them, soil data plays a key role in understanding the infiltration, storage, and loss of water in the soil, and land use data directly affects the water resource demand and hydrological response in different regions of the basin. The lack of comprehensive collection of these data makes it impossible to accurately grasp the complex influencing factors of the whole-basin hydrological process.

[0004] On the other hand, the quality of the collected data is uneven. There may be problems such as duplicate measurement points, outliers, and noise interference in the data. If these problems are not addressed, they will seriously affect the accuracy and reliability of subsequent hydrological models. At present, there is a lack of efficient and systematic data cleaning, denoising, and normalization methods, resulting in the difficulty of directly applying the data to accurate hydrological simulation and regulation decision-making.

[0005] In addition, the accuracy of existing hydrological models needs to be improved in the whole-basin application. Due to incomplete and inaccurate data, the models may not accurately reflect the actual hydrological situation of the whole basin. Especially under complex terrain, diverse land use, and variable meteorological conditions, there may be a large deviation between the simulation results of the models and the actual situation, making it difficult to meet the scientific and accurate requirements of hydrological dynamic regulation.

[0006] At the same time, after the implementation of the regulation strategy, there is a lack of an effective feedback mechanism to evaluate the regulation effect and verify the accuracy of the model, making it difficult to timely adjust and optimize the regulation strategy, which affects the scientificity and effectiveness of the whole-basin hydrological dynamic regulation. Summary of the Invention

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: A whole-basin hydrological dynamic regulation system based on the SWAT model, including a data collection module for collecting topographic data, land data, and meteorological data within the whole basin;

[0008] Among them, the data acquisition module includes a collection unit and a data preprocessing unit. The data preprocessing unit is used to clean, denoise, and normalize the collected terrain data, land data, and meteorological data, and obtain data preprocessing values.

[0009] The data acquisition module comprehensively collects terrain data, land data (including soil data and land use data), and meteorological data within the entire basin, providing rich basic information for hydrological dynamic regulation. It can more comprehensively consider the impacts of various factors on the hydrological process and improve the accuracy of hydrological simulation and regulation.

[0010] The model operation module, with the SWAT model built-in, uses the data preprocessing values obtained by the data acquisition module to simulate the hydrological process and obtain the hydrological results of water balance and runoff process.

[0011] The feedback module feeds back the actual effects after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification.

[0012] The feedback module feeds back the actual effects after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification. The regulation decision-making module formulates corresponding regulation strategies according to the model operation results and the preset basin management objectives, forming a closed-loop system, continuously optimizing the hydrological dynamic regulation decision of the entire basin, and improving the scientificity and sustainability of water resources management.

[0013] The regulation decision-making module formulates corresponding hydrological dynamic regulation strategies according to the results of the model operation module and the preset basin management objectives.

[0014] Preferably, the collection unit includes terrain data collection, land data collection, and meteorological data collection.

[0015] Among them, the terrain data collection uses the global positioning system and total station to measure the terrain of the entire basin, and combines satellite images to identify and analyze the terrain of a large-scale basin.

[0016] The land data collection includes soil data collection and land use data collection.

[0017] The meteorological data collection sets corresponding meteorological monitoring stations at the sampling points, and the meteorological monitoring stations real-time monitor meteorological elements such as temperature, humidity, precipitation, wind direction, and wind speed.

[0018] Preferably, the soil data collection selects sampling points within the entire basin for soil sample collection.

[0019] The land use data collection utilizes satellite remote sensing imaging technology to classify and identify land use conditions, classify land use types, and conduct comparative analysis of satellite images from different periods to monitor changes in land use.

[0020] Preferably, the sampling points are:

[0021] The basin terrain is divided into several areas using lidar, and the terrain data, soil data, land use data, etc. are superimposed and analyzed using a geographic information system to obtain virtual sampling beacons. The virtual sampling beacons are then field-tested to determine the sampling points.

[0022] Preferably, the data preprocessing unit includes data cleaning, data denoising and data normalization processing;

[0023] Wherein, the data cleaning includes terrain data cleaning, land data cleaning and meteorological data cleaning;

[0024] The terrain data cleaning is used to remove duplicate measurement points and process outliers by standard deviation method to obtain primary terrain data;

[0025] The land data cleaning is used to remove abnormal land samples and classify different land use types to obtain primary land data;

[0026] The meteorological data cleaning is used to remove abnormal values caused by sensor failure, data transmission errors or extreme weather events, and ensure the consistency of meteorological data in time and space to obtain primary meteorological data.

[0027] The data preprocessing unit cleans, denoises, and normalizes the collected data, effectively removing duplicate data, outliers, and noise, improving data quality and usability. The processed data can be better applied to the model operation module of the built-in SWAT model, improving the accuracy of hydrological simulation.

[0028] Preferably, the data denoising includes terrain data denoising, land data denoising and meteorological data denoising;

[0029] The terrain data denoising removes random noise in the terrain main sentence by digital filtering, retains the main features of the terrain, and obtains the final terrain data;

[0030] The land data denoising reduces random fluctuations of the land data by using data smoothing technology and image enhancement technology to obtain the final land data;

[0031] The meteorological data denoising removes abnormal values of meteorological data through time series analysis, and obtains final meteorological data by fusing data from multiple meteorological sensors.

[0032] Preferably, the final terrain data, final land data, and final meteorological data are normalized to obtain a terrain data value T, a soil data value S, a land use data value L, and a meteorological data value M.

[0033] Preferably, the specific expression of the terrain data value T is:

[0034] T = ω h T h + ω s T s ;

[0035] where ω h is the elevation normalization weight value, ω s is the slope normalization weight value, and ω h + ω s = 1, T h is the elevation normalization value, and T s is the slope normalization value.

[0036] Preferably, the specific expression of T h is:

[0037]

[0038] where H is the target elevation value, the maximum value of the elevation data is H max , and the minimum value of the elevation data is H min ;

[0039] The specific expression of T s is:

[0040]

[0041] where S is the target slope value, S max is the maximum value of the slope data, and S min is the minimum value of the slope data.

[0042] Preferably, a data preprocessing value P is obtained based on the terrain data value T, the soil data value S, the land use data value L, and the meteorological data value M;

[0043] The specific expression of the data preprocessing value P is:

[0044] P = aT + bS + cL + dM;

[0045] The a is the terrain data weight, b is the soil data weight, c is the land use data weight, d is the meteorological data weight, and a + b + c + d = 1 is satisfied.

[0046] Using the preprocessed data for hydrological process simulation to obtain water balance hydrological results and runoff process hydrological results can more accurately reflect the actual hydrological situation of the entire basin, providing a reliable basis for formulating scientific and reasonable hydrological dynamic regulation strategies and improving the accuracy and effectiveness of hydrological regulation in the entire basin.

[0047] The present invention provides a whole-basin hydrological dynamic regulation system based on the SWAT model, which has the following beneficial effects:

[0048] First, the whole-basin hydrological dynamic regulation system based on the SWAT model comprehensively collects topographic data, land data (including soil data and land use data), and meteorological data within the whole basin through the data acquisition module of this patent, providing rich basic information for hydrological dynamic regulation. It can consider various factors affecting the hydrological process more comprehensively and improve the accuracy of hydrological simulation and regulation.

[0049] Second, the whole-basin hydrological dynamic regulation system based on the SWAT model cleans, denoises, and normalizes the collected data through the data preprocessing unit, effectively removing duplicate data, outliers, and noise, and improving the quality and usability of the data. The processed data can be better applied to the model operation module with the built-in SWAT model to improve the accuracy of hydrological simulation.

[0050] Third, the whole-basin hydrological dynamic regulation system based on the SWAT model uses the preprocessed data for hydrological process simulation to obtain water balance hydrological results and runoff process hydrological results, which can more accurately reflect the actual hydrological situation of the entire basin, providing a reliable basis for formulating scientific and reasonable hydrological dynamic regulation strategies and improving the accuracy and effectiveness of hydrological regulation in the entire basin.

[0051] Fourth, the whole-basin hydrological dynamic regulation system based on the SWAT model feeds back the actual effects after the implementation of the regulation strategy to the data acquisition module and the model operation module through the feedback module for model calibration and verification. The regulation decision-making module formulates corresponding regulation strategies according to the model operation results and the preset basin management objectives, forming a closed-loop system to continuously optimize the whole-basin hydrological dynamic regulation decision-making and improve the scientificity and sustainability of water resource management. Specific implementation manner

[0052] The present invention will be further described in detail below in conjunction with specific embodiments. The embodiments of the present invention are given for purposes of illustration and description, and are not exhaustive or limit the present invention to the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles of the present invention and its practical applications, and to enable those of ordinary skill in the art to understand the present invention and design various embodiments with various modifications suitable for specific purposes.

[0053] First embodiment, the present invention provides a technical solution: a whole-basin hydrological dynamic regulation system based on the SWAT model, including a data acquisition module for collecting topographic data, land data, and meteorological data within the whole basin;

[0054] Among them, the data acquisition module includes an acquisition unit and a data preprocessing unit, and the data preprocessing unit is used to clean, denoise, and normalize the collected topographic data, land data, and meteorological data, and obtain data preprocessing values;

[0055] By comprehensively collecting topographic data, land data (including soil data and land use data), and meteorological data within the whole basin through the data acquisition module, rich basic information is provided for hydrological dynamic regulation. It can more comprehensively consider the influence of various factors on the hydrological process and improve the accuracy of hydrological simulation and regulation.

[0056] A model operation module, with the SWAT model built-in, uses the data preprocessing values obtained by the data acquisition module to simulate the hydrological process and obtain water balance hydrological results and runoff process hydrological results;

[0057] A feedback module that feeds back the actual effect after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification;

[0058] The feedback module feeds back the actual effect after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification. The regulation decision-making module formulates corresponding regulation strategies according to the model operation results and the preset basin management objectives, forming a closed-loop system, continuously optimizing the whole-basin hydrological dynamic regulation decision-making, and improving the scientificity and sustainability of water resource management.

[0059] A regulation decision-making module that formulates corresponding hydrological dynamic regulation strategies according to the results of the model operation module and the preset basin management objectives.

[0060] The acquisition unit includes topographic data acquisition, land data acquisition, and meteorological data acquisition;

[0061] Among them, for the topographic data collection, the global positioning system and total station are used to measure the topography of the entire basin, and satellite images are combined to identify and analyze the topography of a large-scale basin;

[0062] The land data collection includes soil data collection and land use data collection;

[0063] For the meteorological data collection, corresponding meteorological monitoring stations are set at the sampling points, and the meteorological monitoring stations monitor meteorological elements such as temperature, humidity, precipitation, wind direction, and wind speed in real time.

[0064] For the soil data collection, sampling points are selected within the entire basin for soil sample collection;

[0065] For the land use data collection, satellite remote sensing image technology is used to classify and identify the land use situation, classify the land use types, and conduct comparative analysis on satellite images of different periods to monitor the changes in land use.

[0066] The specific sampling points are as follows:

[0067] The topography of the basin is divided into several regions by lidar, and using geographic information system, topographic data, soil data, land use data, etc. are superimposed and analyzed to obtain virtual sampling beacons, and on-site detection is carried out on the virtual sampling beacons to determine the sampling points.

[0068] The data preprocessing unit includes data cleaning, data denoising, and data normalization processing;

[0069] Among them, the data cleaning includes topographic data cleaning, land data cleaning, and meteorological data cleaning;

[0070] The topographic data cleaning is used to remove duplicate measurement points and process outliers by the standard deviation method to obtain primary topographic data;

[0071] The land data cleaning is used to remove abnormal land sample comparisons and classify different land use types to obtain primary land data;

[0072] The meteorological data cleaning is used to remove outliers caused by sensor failures, data transmission errors, or extreme weather events, and ensure the consistency of meteorological data in time and space to obtain primary meteorological data.

[0073] The data preprocessing unit performs cleaning, denoising, and normalization processing on the collected data, effectively removing duplicate data, outliers, and noise, improving the quality and usability of the data. The processed data can be better applied to the model operation module of the built-in SWAT model to improve the accuracy of hydrological simulation.

[0074] The data denoising includes terrain data denoising, land data denoising, and meteorological data denoising;

[0075] Among them, the terrain data denoising removes random noise in the terrain main sentence through digital filtering, retains the main terrain features, and obtains the final terrain data;

[0076] The land data denoising reduces the random fluctuations of the land data through data smoothing technology and image enhancement technology to obtain the final land data;

[0077] The meteorological data denoising clears the outliers of the meteorological data through time series analysis and fuses the data from multiple meteorological sensors to obtain the final meteorological data.

[0078] The final terrain data, final land data, and final meteorological data are normalized to obtain the terrain data value T, soil data value S, land use data value L, and meteorological data value M.

[0079] The specific expression of the terrain data value T is:

[0080] T = ω h T h + ω s T s ;

[0081] Among them, ω h is the elevation normalization weight value, ω s is the slope normalization weight value, and ω h + ω s = 1, ω h = 0.2, ω s = 0.8, T h is the elevation normalization value, T s is the slope normalization value.

[0082] The specific expression of the said T h is:

[0083]

[0084] Among them, H is the target elevation value, the maximum value of the elevation data is H max , and the minimum value of the elevation data is H min ;

[0085] The specific expression of the said T s is:

[0086]

[0087] Among them, S is the target slope value, S max is the maximum value of the slope data, S minis the minimum value of the slope data.

[0088] Based on the terrain data value T, soil data value S, land use data value L, and meteorological data value M, a data preprocessing value P is obtained;

[0089] The specific expression of the data preprocessing value P is:

[0090] P = aT + bS + cL + dM;

[0091] Where a is the terrain data weight, b is the soil data weight, c is the land use data weight, and d is the meteorological data weight, and a = 0.15, b = 0.34, c = 0.12, d = 0.39.

[0092] Using the preprocessed data for hydrological process simulation to obtain water balance hydrological results and runoff process hydrological results can more accurately reflect the actual hydrological situation of the entire basin. It provides a reliable basis for formulating scientific and reasonable hydrological dynamic regulation strategies and improves the accuracy and effectiveness of the entire basin's hydrological regulation.

[0093] The second embodiment, based on the first embodiment, a data acquisition module is used to collect terrain data, land data, and meteorological data within the entire basin;

[0094] Among them, the data acquisition module includes an acquisition unit and a data preprocessing unit. The data preprocessing unit is used to clean, denoise, and normalize the collected terrain data, land data, and meteorological data, and obtain a data preprocessing value;

[0095] By comprehensively collecting terrain data, land data (including soil data and land use data), and meteorological data within the entire basin through the data acquisition module, it provides rich basic information for hydrological dynamic regulation. It can more comprehensively consider the influence of various factors on the hydrological process and improve the accuracy of hydrological simulation and regulation.

[0096] The model operation module, with the SWAT model built-in, uses the data preprocessing value obtained by the data acquisition module to perform hydrological process simulation to obtain water balance hydrological results and runoff process hydrological results;

[0097] The feedback module feeds back the actual effect after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification;

[0098] The feedback module feeds back the actual effect after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification. The regulation decision-making module formulates corresponding regulation strategies based on the model operation results and the preset basin management objectives, forming a closed-loop system that continuously optimizes the entire basin's hydrological dynamic regulation decision-making and improves the scientificity and sustainability of water resource management.

[0099] The regulation decision-making module formulates corresponding hydrological dynamic regulation strategies according to the results of the model operation module and the preset watershed management objectives.

[0100] The acquisition unit includes terrain data acquisition, land data acquisition, and meteorological data acquisition;

[0101] Among them, the terrain data acquisition uses the global positioning system and total station to measure the terrain of the entire watershed, and combines satellite images to identify and analyze the terrain of the large-scale watershed;

[0102] The land data acquisition includes soil data acquisition and land use data acquisition;

[0103] The meteorological data acquisition sets corresponding meteorological monitoring stations at the sampling points, and the meteorological monitoring stations real-time monitor meteorological elements such as temperature, humidity, precipitation, wind direction, and wind speed.

[0104] The soil data acquisition selects sampling points within the entire watershed for soil sample collection;

[0105] The land use data acquisition uses satellite remote sensing image technology to classify and identify land use conditions, classifies land use types, and conducts comparative analysis on satellite images of different periods to monitor land use changes.

[0106] The sampling points are specifically:

[0107] The terrain of the watershed is divided into several regions by lidar, and the terrain data, soil data, land use data, etc. are superimposed and analyzed using a geographic information system to obtain virtual sampling beacons, and the virtual sampling beacons are field-tested to determine the sampling points.

[0108] The data preprocessing unit includes data cleaning, data denoising, and data normalization processing;

[0109] Among them, the data cleaning includes terrain data cleaning, land data cleaning, and meteorological data cleaning;

[0110] The terrain data cleaning is used to remove duplicate measurement points and process outliers by the standard deviation method to obtain primary terrain data;

[0111] The land data cleaning is used to compare and remove abnormal land samples and classify different land use types to obtain primary land data;

[0112] The meteorological data cleaning is used to remove outliers caused by sensor failures, data transmission errors, or extreme weather events, and to ensure the consistency of meteorological data in time and space, obtaining primary meteorological data.

[0113] The data preprocessing unit performs cleaning, denoising, and normalization on the collected data, effectively removing duplicate data, outliers, and noise, improving the quality and usability of the data. The processed data can be better applied to the model operation module with the built-in SWAT model, improving the accuracy of hydrological simulation.

[0114] The data denoising includes terrain data denoising, land data denoising, and meteorological data denoising;

[0115] Among them, the terrain data denoising removes random noise in the terrain main sentence through digital filtering, retains the main terrain features, and obtains the final terrain data;

[0116] The land data denoising reduces the random fluctuations of land data through data smoothing technology and image enhancement technology, obtaining the final land data;

[0117] The meteorological data denoising clears the outliers of meteorological data through time series analysis and fuses the data from multiple meteorological sensors to obtain the final meteorological data.

[0118] The final terrain data, final land data, and final meteorological data are normalized to obtain the terrain data value T, soil data value S, land use data value L, and meteorological data value M.

[0119] The specific expression of the terrain data value T is:

[0120] T = ω h T h + ω s T s ;

[0121] Among them, ω h is the elevation normalization weight value, ω s is the slope normalization weight value, and ω h + ω s = 1, ω h = 0.25, ω s = 0.75, T h is the elevation normalization value, T s is the slope normalization value.

[0122] The specific expression of the said T h is:

[0123]

[0124] Among them, H is the target elevation value, and the maximum value of the elevation data is H max , and the minimum value of the elevation data is H min ;

[0125] The specific expression of the said T s is as follows:

[0126]

[0127] Among them, S is the target slope value, S max is the maximum value of the slope data, and S min is the minimum value of the slope data.

[0128] According to the terrain data value T, soil data value S, land use data value L, and meteorological data value M, a data preprocessing value P is obtained;

[0129] The specific expression of the said data preprocessing value P is as follows:

[0130] P = aT + bS + cL + dM;

[0131] The said a is the terrain data weight, b is the soil data weight, c is the land use data weight, and d is the meteorological data weight, where a = 0.15, b = 0.15, c = 0.5, and d = 0.2.

[0132] Using the preprocessed data for hydrological process simulation to obtain water balance hydrological results and runoff process hydrological results can more accurately reflect the actual hydrological situation of the entire basin. It provides a reliable basis for formulating scientific and reasonable hydrological dynamic regulation strategies and improves the accuracy and effectiveness of the hydrological regulation of the entire basin.

[0133] The third embodiment, based on the first and second embodiments, a data acquisition module is used to acquire terrain data, land data, and meteorological data within the entire basin;

[0134] Among them, the said data acquisition module includes an acquisition unit and a data preprocessing unit, and this data preprocessing unit is used to clean, denoise, and normalize the acquired terrain data, land data, and meteorological data, and obtain a data preprocessing value;

[0135] By comprehensively acquiring terrain data, land data (including soil data and land use data), and meteorological data within the entire basin through the data acquisition module, it provides rich basic information for hydrological dynamic regulation, can more comprehensively consider the influence of various factors on the hydrological process, and improves the accuracy of hydrological simulation and regulation.

[0136] A model operation module, with the SWAT model built-in, uses the data preprocessing value obtained by the said data acquisition module to perform hydrological process simulation to obtain water balance hydrological results and runoff process hydrological results;

[0137] A feedback module that feeds back the actual effect after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification;

[0138] The feedback module feeds back the actual effect after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification. The regulation decision-making module formulates corresponding regulation strategies according to the model operation results and the preset watershed management objectives, forming a closed-loop system that continuously optimizes the hydrological dynamic regulation decision-making of the entire watershed and improves the scientificity and sustainability of water resources management.

[0139] A regulation decision-making module that formulates corresponding hydrological dynamic regulation strategies according to the results of the model operation module and the preset watershed management objectives.

[0140] The acquisition unit includes terrain data acquisition, land data acquisition, and meteorological data acquisition;

[0141] Among them, the terrain data acquisition uses the global positioning system and total station to measure the terrain of the entire watershed, and combines satellite images to identify and analyze the terrain of the large-scale watershed;

[0142] The land data acquisition includes soil data acquisition and land use data acquisition;

[0143] The meteorological data acquisition sets corresponding meteorological monitoring stations at the sampling points, and the meteorological monitoring stations continuously monitor meteorological elements such as air temperature, humidity, precipitation, wind direction, and wind speed.

[0144] The soil data acquisition selects sampling points within the entire watershed for soil sample collection;

[0145] The land use data acquisition uses satellite remote sensing image technology to classify and identify land use conditions, classifies land use types, and conducts comparative analysis of satellite images in different periods to monitor land use changes.

[0146] The specific sampling points are as follows:

[0147] The watershed terrain is divided into several regions by lidar, and the terrain data, soil data, land use data, etc. are superimposed and analyzed using geographic information system to obtain virtual sampling beacons, and on-site detection is carried out on the virtual sampling beacons to determine the sampling points.

[0148] The data preprocessing unit includes data cleaning, data denoising, and data normalization processing;

[0149] Among them, the data cleaning includes terrain data cleaning, land data cleaning, and meteorological data cleaning;

[0150] The terrain data cleaning is used to remove duplicate measurement points and process outliers by standard deviation method to obtain primary terrain data;

[0151] The land data cleaning is used to remove abnormal land samples and classify different land use types to obtain primary land data;

[0152] The meteorological data cleaning is used to remove abnormal values caused by sensor failure, data transmission errors or extreme weather events, and ensure the consistency of meteorological data in time and space to obtain primary meteorological data.

[0153] The data preprocessing unit cleans, denoises, and normalizes the collected data, effectively removing duplicate data, outliers, and noise, improving data quality and usability. The processed data can be better applied to the model operation module of the built-in SWAT model, improving the accuracy of hydrological simulation.

[0154] The data denoising includes terrain data denoising, land data denoising and meteorological data denoising;

[0155] The terrain data denoising removes random noise in the terrain main sentence by digital filtering, retains the main features of the terrain, and obtains the final terrain data;

[0156] The land data denoising reduces random fluctuations of the land data by using data smoothing technology and image enhancement technology to obtain the final land data;

[0157] The meteorological data denoising removes abnormal values of meteorological data through time series analysis, and obtains final meteorological data by fusing data from multiple meteorological sensors.

[0158] The final terrain data, final land data and final meteorological data are normalized to obtain terrain data value T, soil data value S, land use data value L and meteorological data value M.

[0159] The specific expression of the terrain data value T is:

[0160] T=ω h T h +ω s T s ;

[0161] Among them, ω h is the normalized weight value of elevation, ω s is the slope normalized weight value, and ω h +ω s =1,ω h =0.34,ω s =0.66, Th is the elevation normalization value, T s is the slope normalization value.

[0162] The specific expression of the said T h is as follows:

[0163]

[0164] [[ID=)14]]where H is the target elevation value, the maximum value of the elevation data is H max , and the minimum value of the elevation data is H min ;

[0165] The specific expression of the said T s is as follows:

[0166]

[0167] where S is the target slope value, S max is the maximum value of the slope data, S min is the minimum value of the slope data.

[0168] Based on the terrain data value T, soil data value S, land use data value L, and meteorological data value M, the data preprocessing value P is obtained;

[0169] The specific expression of the said data preprocessing value P is:

[0170] P = aT + bS + cL + dM;

[0171] The said a is the terrain data weight, b is the soil data weight, c is the land use data weight, d is the meteorological data weight, where a = 0.12, b = 0.18, c = 0.36, d = 0.34.

[0172] Using the preprocessed data for hydrological process simulation to obtain the water balance hydrological result and runoff process hydrological result can more accurately reflect the actual hydrological situation of the whole basin. It provides a reliable basis for formulating scientific and reasonable hydrological dynamic regulation strategies and improves the accuracy and effectiveness of the whole basin hydrological regulation.

[0173] Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art and related fields without creative work shall fall within the protection scope of the present invention. The structures, devices, and operation methods not specifically described and explained in the present invention, unless otherwise specified and limited, are implemented according to the conventional means in the art.

Claims

1. A whole-basin hydrological dynamic regulation system based on the SWAT model, characterized in that, Including: A data acquisition module, which is used to acquire topographic data, land data and meteorological data within the entire basin; Among them, the data acquisition module includes an acquisition unit and a data preprocessing unit. The data preprocessing unit is used to clean, denoise and normalize the acquired topographic data, land data and meteorological data, and obtain data preprocessing values; A model operation module, with the SWAT model built in, uses the data preprocessing values obtained by the data acquisition module to simulate the hydrological process, and obtains the hydrological results of water balance and the hydrological results of runoff process; A feedback module, which feeds back the actual effects after the implementation of the regulation strategy to the data acquisition module and the model operation module for model calibration and verification; A regulation decision-making module, which formulates corresponding hydrological dynamic regulation strategies according to the results of the model operation module and the preset basin management objectives.

2. The full-basin hydrological dynamic regulation system based on the SWAT model according to claim 1, wherein: The acquisition unit includes topographic data acquisition, land data acquisition and meteorological data acquisition; Among them, the topographic data acquisition uses the global positioning system and total station to measure the topography of the entire basin, and combines satellite images to identify and analyze the topography of a large range of basins; The land data acquisition includes soil data acquisition and land use data acquisition; For the meteorological data acquisition, corresponding meteorological monitoring stations are set at the sampling points, and the meteorological monitoring stations monitor meteorological elements such as temperature, humidity, precipitation, wind direction and wind speed in real time.

3. A whole-basin hydrological dynamic regulation system based on the SWAT model according to claim 3, characterized in that, The soil data acquisition selects sampling points within the entire basin to collect soil samples; The land use data acquisition uses satellite remote sensing image technology to classify and identify land use conditions, classifies land use types, and conducts comparative analysis on satellite images in different periods to monitor changes in land use.

4. A whole-basin hydrological dynamic regulation system based on the SWAT model according to claim 4, characterized in that: The sampling points are specifically: Using lidar to divide the basin topography into several regions, using geographic information system to perform overlay analysis on topographic data, soil data, land use data, etc., obtaining virtual sampling beacons, and conducting field detection on the virtual sampling beacons to determine sampling points.

5. The full-basin hydrological dynamic regulation system based on the SWAT model according to claim 1, characterized in that: The data preprocessing unit includes data cleaning, data denoising and data normalization processing; Among them, the data cleaning includes topographic data cleaning, land data cleaning and meteorological data cleaning; The topographic data cleaning is used to remove duplicate measurement points and process outliers by the standard deviation method to obtain primary topographic data; The land data cleaning is used to compare and remove abnormal land samples and classify different land use types to obtain primary land data; The meteorological data cleaning is used to remove outliers caused by sensor failures, data transmission errors or extreme weather events, and ensure the consistency of meteorological data in time and space to obtain primary meteorological data.

6. The full-basin hydrological dynamic regulation system based on the SWAT model according to claim 5, wherein: The data denoising includes topographic data denoising, land data denoising and meteorological data denoising; Among them, the topographic data denoising removes random noise in the topographic main sentence through digital filtering, retains the main topographic features, and obtains the final topographic data; The land data denoising reduces the random fluctuations of land data through data smoothing technology and image enhancement technology to obtain the final land data; The denoising of the meteorological data clears the outliers of the meteorological data through time series analysis, and fuses the data of multiple meteorological sensors to obtain the final meteorological data.

7. A whole-basin hydrological dynamic regulation system based on the SWAT model according to claim 6, characterized in that: The final terrain data, final land data, and final meteorological data are normalized to obtain the terrain data value T, soil data value S, land use data value L, and meteorological data value M.

8. A whole-basin hydrological dynamic regulation system based on the SWAT model according to claim 7, characterized in that: The specific expression of the terrain data value T is: T = ω h T h + ω s T s ; Among them, ω h is the elevation normalization weight value, ω s is the slope normalization weight value, and ω h + ω s = 1, T h is the elevation normalization value, T s is the slope normalization value.

9. The whole-basin hydrological dynamic regulation system based on the SWAT model according to claim 8, characterized in that: The said T h has the following specific expression: Among them, H is the target elevation value, and the maximum value of the elevation data is H max , and the minimum value of the elevation data is H min ; The said T s has the specific expression as follows: Among them, S is the target slope value, S max is the maximum value of the slope data, S min is the minimum value of the slope data.

10. A whole-basin hydrological dynamic regulation system based on the SWAT model according to claim 9, characterized in that: Based on the terrain data value T, soil data value S, land use data value L, and meteorological data value M, the data preprocessing value P is obtained; The specific expression of the data preprocessing value P is: P = aT + bS + cL + dM; Where a is the terrain data weight, b is the soil data weight, c is the land use data weight, d is the meteorological data weight, and a + b + c + d = 1.

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