A method and system for analyzing hydrological regime changes for hydrological engineering

Abstract

The present invention relates to the field of hydrological monitoring technology, and in particular to a method and system for analyzing hydrological situation changes for hydrological engineering. The method comprises the following steps: acquiring remote sensing data of a hydrological monitoring area, and analyzing river morphology changes based on the remote sensing data of the hydrological monitoring area, thereby obtaining river morphology change data; acquiring hydrological equipment measurement information data, and extracting water body section features and water flow velocity features based on the hydrological equipment measurement information data, thereby obtaining water body section data and water flow velocity data; analyzing water flow rate based on the water body section data and water flow velocity data, thereby obtaining water flow rate data; classifying section orientations based on the hydrological equipment measurement information data, thereby obtaining left section hydrological equipment measurement information data and right section hydrological equipment measurement information data. The present invention completes the hydrological situation prediction task based on hydrological monitoring technology.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrological monitoring, and in particular to a method and system for analyzing hydrological situation changes used in hydrological engineering. Background Art

[0002] Traditional hydrological situation analysis methods mostly rely on experience and simple statistical models, which are difficult to adapt to complex hydrological environmental changes. The spatial and temporal resolution of monitoring equipment is usually low, making it difficult to achieve real-time monitoring and comprehensive coverage of hydrological elements. When processing large-scale hydrological data, there is insufficient computing power, and there are obstacles to integrating ground monitoring data with remote sensing data, which limits the comprehensive analysis of hydrological situations and makes it difficult to provide multi-dimensional information support. As the amount of data increases, traditional systems experience processing delays or crashes, and are unable to complete the analysis and prediction of hydrological situations in a timely manner. Due to the lack of real-time monitoring and dynamic update mechanisms, timely and effective warnings and response measures cannot be provided when extreme events occur. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a method and system for analyzing hydrological situation changes in hydrological engineering to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a hydrological regime change analysis method for hydrological engineering includes the following steps:

[0005] Step S1: acquiring remote sensing data of the hydrological monitoring area, and performing river morphology change analysis based on the remote sensing data of the hydrological monitoring area, thereby obtaining river morphology change data;

[0006] Step S2: obtaining the measurement information data of the hydrological equipment, and performing water body section feature extraction and water flow velocity feature extraction according to the measurement information data of the hydrological equipment, thereby obtaining water body section data and water flow velocity data; performing water flow analysis according to the water body section data and water flow velocity data, thereby obtaining water flow data;

[0007] Step S3: classifying the section orientation according to the hydrological equipment measurement information data, thereby obtaining the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; performing section morphology analysis according to the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data, thereby obtaining section morphology data; constructing a hydrodynamic model according to the section morphology data, thereby obtaining hydrodynamic model data;

[0008] Step S4: Calculate the velocity relationship line according to the water body section data and the water flow data, so as to obtain the velocity relationship line data; dynamically correct the velocity relationship line data according to the river channel morphology change data and the section morphology data, so as to obtain the velocity relationship line dynamic correction data;

[0009] Step S5: Perform hydrological situation prediction based on the hydrodynamic model data and the dynamic correction data of the velocity relationship line, thereby obtaining hydrological situation prediction data, and uploading it to the hydrological engineering management platform to execute the hydrological situation prediction task.

[0010] The river data obtained by remote sensing technology in the present invention can cover a large area, provide high-resolution terrain information, help identify and analyze the morphological changes of the river, remote sensing data can be quickly updated, timely reflect the changes of the river in different time periods, support dynamic monitoring, and provide scientific basis for water resource management, ecological restoration and flood control planning, and improve the accuracy of decision-making. Through real-time measurement of hydrological equipment, water body section characteristics and flow rate data can be accurately obtained, the reliability of data can be enhanced, and flow analysis can be performed by integrating water body section and flow rate data, which is helpful to deeply understand the dynamics of water flow and provide support for water resource allocation and flood warning. Through cross-section orientation classification, hydrological data are divided into left section and right section, which is convenient for systematic analysis and enhances the effectiveness of data processing. A hydrodynamic model is constructed based on cross-section morphological data to provide a simulation basis for subsequent hydrological situation prediction and improve the scientificity and reliability of prediction. Through dynamic correction of flow rate relationship line, it can adapt to the changes in river morphology, improve the accuracy of flow rate prediction, and enhance the adaptability of the model. This correction mechanism helps to timely reflect the changes in hydrological situation and provide the latest water flow state information for management departments. Comprehensive hydrodynamic model data and flow velocity relationship line dynamic correction data can be used to achieve comprehensive hydrological situation prediction, provide a scientific basis for management departments, upload the predicted data to the hydrological engineering management platform, promote real-time information sharing, and improve the collaborative work efficiency of management departments at all levels. Through real-time monitoring and dynamic updates, it can issue early warnings in time when extreme weather events occur, thereby enhancing flood control and disaster resistance capabilities.

[0011] Optionally, step S1 specifically includes:

[0012] Step S11: acquiring remote sensing data of the hydrological monitoring area, and dividing the band types according to the remote sensing data of the hydrological monitoring area, thereby obtaining green band data and near infrared band data;

[0013] Step S12: performing band reflectance statistics according to the green band data and the near-infrared band data, so as to obtain high-reflectance green band data and low-reflectance near-infrared band data;

[0014] Step S13: Calculating the water body remote sensing index according to the high reflectivity green band data and the low reflectivity near infrared band data, thereby obtaining the water body remote sensing index data;

[0015] Step S14: extracting river channel area features from the remote sensing data of the hydrological monitoring area according to the water body remote sensing index data, thereby obtaining river channel area data;

[0016] Step S15: Perform river channel morphology change analysis based on the river channel area data to obtain river channel morphology change data.

[0017] The band data obtained by the present invention through remote sensing technology can cover a large area, quickly collect hydrological information, and is particularly suitable for monitoring difficult-to-reach areas. The band is subdivided into a green band and a near-infrared band, which helps to analyze the water body and its surrounding environment in a targeted manner, and improves the professionalism and applicability of the data. The reflectivity statistics of the green band and the near-infrared band are helpful to quantify the characteristics of the water body and provide reference indicators for the health status of the water body. The data of the high-reflectivity green band and the low-reflectivity near-infrared band can provide a more accurate basis for subsequent analysis and improve the credibility of the data. By calculating the water body remote sensing index, it is possible to effectively distinguish between water bodies and other surface materials, improve the accuracy of water body extraction, and the water body remote sensing index provides an important indicator for water body changes, pollution monitoring and ecological assessment, and helps to achieve real-time environmental monitoring. Extracting river area features based on the water body remote sensing index helps to identify important parameters such as the spatial characteristics, width, and depth of the river, laying the foundation for further analysis. By extracting river area data, remote sensing information can be combined with ground data to solve the shortcomings of traditional methods in data integration. By analyzing the changes in river morphology, we can timely identify the evolution trend of the river and support the formulation of river management and flood control measures. The river morphology change data provides a scientific basis for water resources management, helps to evaluate the response of the river to climate change, and enhance disaster prevention and mitigation capabilities.

[0018] Optionally, step S15 is specifically:

[0019] Step S151: Generate remote sensing point cloud according to the river area data, so as to obtain the river area point cloud data;

[0020] Step S152: constructing a river digital elevation model according to the river area point cloud data, thereby obtaining a river digital elevation model;

[0021] Step S153: extracting riverbed elevation features according to the river channel digital elevation model, thereby obtaining riverbed elevation data;

[0022] Step S154: Calculating the riverbed slope according to the riverbed elevation data, thereby obtaining riverbed slope data;

[0023] Step S155: performing slope change analysis according to the riverbed slope data, thereby obtaining riverbed slope increase data and riverbed slope decrease data;

[0024] Step S156: classifying the river channel area data into river channel morphology according to the riverbed slope increase data and the riverbed slope decrease data, thereby obtaining river channel erosion area data and river channel deposition area data;

[0025] Step S157: Performing river channel morphology change regional integration based on the river channel erosion area data and the river channel deposition area data, thereby obtaining river channel morphology change data.

[0026] The present invention can obtain high-precision three-dimensional terrain information by generating point cloud data of the river area, improve the ability to identify river characteristics, and the point cloud data can cover a large area, providing comprehensive basic data for subsequent analysis. The river digital elevation model (DEM) provides a three-dimensional representation of the river terrain, which helps to more intuitively understand the river morphology and its changes. Through the digital elevation model, various terrain analyses can be quickly performed to reduce the complexity of manual processing. Extracting riverbed elevation data from the digital elevation model can more accurately reflect the real situation of the riverbed, laying the foundation for subsequent analysis. The acquisition of riverbed elevation characteristics helps to evaluate the ecological and environmental changes of the river and support the formulation of ecological protection measures. By calculating the slope of the riverbed, important information about the direction, velocity and hydrodynamics of the water flow can be provided, and the understanding of the behavior of the river can be enhanced. The slope data provides a scientific basis for the design of river engineering and governance measures, and helps to optimize water resource management. By analyzing the increase and decrease of the slope, the erosion and sedimentation of the riverbed can be identified, which helps to monitor the stability of the river. The slope change analysis can provide early warning for changes in the hydrological situation and support the early formulation of disaster prevention and mitigation measures. Classifying river erosion and sedimentation areas based on slope data can clarify the characteristics of different areas and help targeted governance. The results of river morphology classification provide an important basis for ecological management and protection measures and promote the sustainable use of water resources. Integrating data on erosion and sedimentation areas can comprehensively evaluate changes in river morphology and provide scientific support for policy making. Through continuous integration of morphological change data, it is helpful to establish a long-term river monitoring system and improve the ability to respond to changes in hydrological conditions.

[0027] Optionally, step S2 specifically includes:

[0028] Step S21: obtaining hydrological equipment measurement information data, and performing water body section feature extraction and water flow velocity feature extraction according to the hydrological equipment measurement information data, thereby obtaining water body section data and water flow velocity data;

[0029] Step S22: extracting cross-sectional width features and cross-sectional depth features according to the water body cross-sectional data, thereby obtaining cross-sectional width data and cross-sectional depth data;

[0030] Step S23: Calculating the cross-sectional area of ​​the water body according to the cross-sectional width data and the cross-sectional depth data, thereby obtaining the cross-sectional area data of the water body;

[0031] Step S24: analyzing the distribution of water bodies and sand according to the remote sensing data of the hydrological monitoring area, thereby obtaining water body and sand distribution data;

[0032] Step S25: Calculate the roughness coefficient of sand according to the water body sand distribution data, so as to obtain the water body sand roughness coefficient data;

[0033] Step S26: drawing a water flow velocity distribution map according to the water body sand roughness coefficient data and the water flow velocity data, thereby obtaining a water flow velocity distribution map;

[0034] Step S27: Calculate the water flow rate according to the water flow velocity distribution diagram and the water body cross-sectional area data, so as to obtain the water flow rate data.

[0035] The present invention can obtain high-quality water body section and flow velocity characteristic data through real-time measurement of hydrological equipment, laying a solid foundation for subsequent analysis. The acquisition of real-time data helps to capture the changes in hydrological elements and support timely water resources management and emergency response. Extracting cross-sectional width and depth characteristics helps to fully understand the morphological characteristics of the water body and provide necessary parameters for water flow behavior analysis. The integration of width and depth characteristics quantifies the geometric characteristics of the water body and helps to improve the accuracy of the model. The cross-sectional area of ​​the water body is an important parameter for water flow analysis, which helps further flow calculation and hydrodynamic research. Accurate cross-sectional area calculation provides necessary input for hydrodynamic models and improves the reliability of flow and flow velocity prediction. Analyzing the sand distribution of the water body can reveal the characteristics of the riverbed, support the assessment of ecological and environmental changes, and help protect aquatic ecosystems. Sand distribution data provides a scientific basis for river management, shoreline management, and optimal utilization of water resources. Calculating the sand roughness coefficient helps to understand the interaction between water flow and riverbed, and provides important parameters for velocity and flow models. The change of the roughness coefficient reflects the dynamic characteristics of the riverbed and helps to formulate corresponding ecological management measures. The flow velocity distribution map provides an intuitive display of water flow behavior, which helps to better understand the spatial variation characteristics of water flow. The flow velocity distribution map provides important visual information support for water resource management, flood warning and ecological restoration. Water flow data is the core indicator of hydrological analysis, providing a scientific basis for water resource allocation, flood prevention and disaster relief, and ecological management. By combining flow calculation with real-time data, the response speed and accuracy of the hydrological monitoring system can be improved.

[0036] Optionally, step S24 is specifically:

[0037] Step S241: extracting pixel spectrum features of the hydrological monitoring area according to the remote sensing data of the hydrological monitoring area, thereby obtaining pixel spectrum data of the hydrological monitoring area;

[0038] Step S242: Calculating vegetation index according to the pixel spectrum of the hydrological monitoring area, thereby obtaining vegetation index data;

[0039] Step S243: dividing the remote sensing data of the hydrological monitoring area into sand distribution according to the vegetation index data and the river area data, thereby obtaining sand distribution data;

[0040] Step S244: obtaining ground data of sand particle size;

[0041] Step S245: Calculating the sand particle size distribution according to the sand distribution data and the ground-collected sand particle size data, thereby obtaining the sand particle size distribution data;

[0042] Step S246: performing water body sand distribution analysis on the river area data according to the sand particle size distribution data, thereby obtaining water body sand distribution data.

[0043] By extracting pixel spectral features, the present invention can fully understand the spectral characteristics of the hydrological monitoring area and provide basic data for subsequent analysis. The spectral features help to distinguish different types of land objects and improve the ability to identify water and soil characteristics. The vegetation index can reflect the vegetation growth status, provide important indicators of ecological environment changes, support ecological protection and restoration strategies, and quickly calculate the vegetation index to achieve real-time monitoring of the ecological status of the hydrological monitoring area and help evaluate the impact of human activities. According to the vegetation index and river area data, the sand distribution can be divided to quantify the sand characteristics of different regions and provide data support for land management. The sand distribution data can be used to evaluate the soil stability of the hydrological monitoring area and help formulate flood control and ecological restoration measures. Through the actual collection of sand particle size data, important ground truth data can be provided for remote sensing analysis to enhance the accuracy of the model. The data collected on the ground supplements the deficiencies of remote sensing data and improves the comprehensiveness of the overall analysis. Calculating the sand particle size distribution can reveal the changes in soil physical properties and provide basic data for fluid dynamics research. By analyzing the distribution of sand and soil in water bodies, we can fully understand the sedimentation characteristics and water quality conditions of the water bodies, and provide important information for water resource management. The sand and soil distribution data in water bodies can help to realize the dynamic monitoring and change analysis of hydrological elements and enhance the early warning capabilities for extreme events.

[0044] Optionally, step S246 is specifically:

[0045] Perform sand particle size statistics according to the sand particle size distribution data, so as to obtain coarse sand particle size distribution data and fine sand particle size distribution data;

[0046] Performing sand transport simulation on the coarse sand particle size distribution data and the fine sand particle size distribution data according to the water flow velocity data, thereby obtaining sand transport data;

[0047] Conduct sand deposition analysis based on sand transport data to obtain sand deposition data;

[0048] Perform sand suspension analysis based on sand transport data to obtain sand suspension data;

[0049] The sand particle size distribution curve is drawn according to the sand deposition data and the sand suspension data, thereby obtaining the sand particle size distribution curve data;

[0050] The flow velocity analysis and sand density calculation are performed according to the sand particle size distribution curve data, so as to obtain the sand particle size distribution flow velocity curve and sand density data;

[0051] Water-soil-sand distribution analysis is performed based on the sand particle size distribution velocity curve and sand density data to obtain water body sand distribution data.

[0052] The present invention can better understand the characteristics of sand and soil by counting the particle sizes of coarse sand and fine sand, provide key data for subsequent research on soil erosion and sediment transportation, classify sand and soil of different particle sizes, and help formulate targeted land management and ecological restoration strategies. The simulation of sand and soil transportation based on water flow velocity data can reveal the transportation characteristics of sand and soil under different flow conditions, help predict the impact of water flow on river morphology, and the simulation results provide a scientific basis for river management, shoreline protection and water resource allocation, and help formulate reasonable prevention and control measures. By analyzing sand and soil deposition data, the distribution and characteristics of river sediments can be understood, providing a basis for river management and ecological restoration. Sedimentation analysis helps to judge the impact of sand and soil on aquatic ecology and promote the protection of biodiversity. The analysis of sand and soil suspension can reveal the concentration and distribution of suspended matter in water bodies, provide data support for water quality monitoring and pollution control, and the dynamic changes of suspended matter are closely related to water quality, which helps to evaluate the impact of human activities and natural factors on the water ecological environment. By drawing the sand particle size distribution curve, the proportional relationship of different particle sizes can be intuitively displayed, which is convenient for analysis and comparison. The curve data provides a clear diagram for scientific research exchanges and promotes cooperation and communication between different disciplines. Combining flow velocity and sand density data, we can deeply understand the dynamic behavior of sand in water bodies and provide a basis for the study of water flow and soil interaction. The analysis of flow velocity and density is helpful for sand management under different hydrological conditions and improving the efficiency of water resource utilization. Through the comprehensive analysis of sand distribution data in water bodies, the sediment characteristics of water bodies and their impact on the ecological environment can be comprehensively evaluated. Real-time sand distribution monitoring helps to identify potential risks of soil erosion in advance and provide support for emergency management.

[0053] Optionally, step S3 specifically includes:

[0054] Step S31: classifying the section orientation according to the hydrological equipment measurement information data, thereby obtaining the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data;

[0055] Step S32: performing left section morphology analysis according to the left section hydrological equipment measurement information data, thereby obtaining left section morphology data;

[0056] Step S33: performing right section morphology analysis according to the right section hydrological equipment measurement information data, thereby obtaining right section morphology data;

[0057] Step S34: performing cross-sectional morphology integration according to the left cross-sectional morphology data and the right cross-sectional morphology data, thereby obtaining cross-sectional morphology data;

[0058] Step S35: constructing a hydrodynamic model according to the cross-sectional morphology data, thereby obtaining hydrodynamic model data.

[0059] The present invention obtains the measurement information of the left section and the right section by classification, which is helpful to organize and manage hydrological data, improve the accuracy and efficiency of subsequent analysis, and can provide an independent analysis basis for different cross-sectional characteristics, so as to facilitate the comparison of the hydrological characteristics and changes of the left and right banks. An in-depth morphological analysis of the left section is carried out to provide specific morphological characteristic data, which is helpful to understand the shore characteristics and their impact on the water flow. Through the morphological characteristics of the left bank, it is helpful to assess the impact of environmental changes on the shore ecology and structure, and provide data support for management. Similar to the left section analysis, the morphological data of the right section can be used to compare the different characteristics of the left and right banks, revealing their similarities and differences in hydrological characteristics, providing the necessary morphological parameters for understanding the overall water flow behavior, and facilitating the construction and verification of subsequent models. The left and right section data are integrated to form complete cross-sectional morphological data, which provides a comprehensive perspective for the analysis of the overall river morphology. The integrated data can be used for more complex hydrological models to improve the depth and breadth of the analysis. The hydrodynamic model constructed based on the integrated cross-sectional morphological data can simulate the behavior of water flow and its impact on river channel morphology, providing an important basis for water resources management. The hydrodynamic model provides scientific support for hydrological situation forecasting, helps make flood control, irrigation and other water management decisions, and enhances the ability to respond to extreme weather.

[0060] Optionally, step S32 is specifically:

[0061] Step S321: Perform hydrological period statistics based on the hydrological equipment measurement information data of the left section, thereby obtaining the equipment measurement information data of the left section during the dry season and the equipment measurement information data of the left section during the flood season;

[0062] Step S322: extracting the features of the left section of the stone bank according to the remote sensing data of the hydrological monitoring area, thereby obtaining the left end face stone bank data;

[0063] Step S323: analyzing the water flow friction force of the equipment measured in the dry season of the left section according to the stone bank of the left section, thereby obtaining the water flow friction force data of the left section in the dry season;

[0064] Step S324: simulating the water flow of the equipment measurement information data of the left section during the flood period according to the left end face stone bank, so as to obtain the water flow data of the left section during the flood period;

[0065] Step S325: performing a masonry stone hardness analysis based on the left end face masonry stone bank data, thereby obtaining masonry stone hardness data;

[0066] Step S326: performing concentrated flow analysis on the water flow data of the left section during the flood period according to the hardness data of the masonry stones, thereby obtaining concentrated flow data of the water flow of the left section during the flood period;

[0067] Step S327: analyzing the water flow velocity according to the concentrated flow data of the left section during the flood season and the water flow friction data of the left section during the dry season, thereby obtaining the water flow velocity data of the left section;

[0068] Step S328: performing sediment transport analysis on the left section of the stone bank according to the water flow velocity data of the left section, thereby obtaining sediment transport data of the left section;

[0069] Step S329: Perform a left section stone bank morphology analysis on the left section stone bank data according to the left section sediment transport data, thereby obtaining the left section morphology data.

[0070] The present invention obtains hydrological characteristic data of different periods by statistically analyzing the equipment measurement information in the dry season and flood season, laying the foundation for subsequent analysis, accurately grasping the changes in the hydrological cycle, and helping to formulate reasonable water resources management and disaster prevention plans. Extracting the characteristic data of the stacked stone bank is helpful to analyze its impact on the water flow and river channel morphology, providing a basis for protective measures, and understanding the characteristics of the shore can promote the assessment and protection of the ecological environment. Through friction analysis, the behavioral characteristics of the water flow in the dry season are obtained, which helps to understand the impact of the shore on the water flow, provide important parameters for the design and maintenance of hydrological facilities, and improve the safety of the project. The flow simulation of the water flow during the flood season can predict potential risks and help formulate emergency plans. The simulation results can be used to dynamically adjust the water management strategy and improve the ability to cope with floods. Hardness data provides a scientific basis for the use of stacked stones, ensures the stability of the protective structure, provides guidance for future construction and maintenance, and ensures the rationality and feasibility of the design. Analyzing the concentrated flow of water flow during the flood season helps to understand the impact of water flow on the shore and the bottom bed, provides a basis for the assessment of local erosion and sedimentation risks, and helps to take preventive measures in advance. Flow velocity data provides a clear picture of the changes in water flow at different stages, enhances the understanding of hydrodynamics, and can be used to formulate watershed management and flood control strategies and improve the efficiency of water resource utilization. By analyzing the transport of sediments, it is helpful to understand the impact of water flow on riverbed morphology and ecological environment, identify sedimentation areas, and contribute to ecological protection and river restoration. Through the morphological analysis of the stone bank, a comprehensive understanding of the overall river morphology is provided, providing a basis for subsequent management, providing data support for improving and enhancing embankment design, and promoting the sustainable development of the water environment.

[0071] Optionally, step S33 is specifically:

[0072] Step S331: performing hydrological period statistics of the right section according to the hydrological equipment measurement information data of the right section, thereby obtaining the equipment measurement information data of the right section during the dry season and the equipment measurement information data of the right section during the flood season;

[0073] Step S332: extracting the features of the right section waterweed floodplain according to the remote sensing data of the hydrological monitoring area, thereby obtaining the right section waterweed floodplain data;

[0074] Step S333: analyzing the flow resistance of the equipment measurement information data of the right section during the dry season according to the water grass floodplain data of the right section, thereby obtaining the flow resistance data of the right section;

[0075] Step S334: local waterlogging simulation is performed on the waterweed floodplain data of the right section according to the water resistance data of the right section, so as to obtain the local waterlogging data of the waterweed floodplain of the right section;

[0076] Step S335: performing sediment settlement analysis on the equipment measurement information data of the right section during the flood period according to the water grass floodplain data of the right section, thereby obtaining sediment settlement data;

[0077] Step S336: extracting the location feature of the right section water grass floodplain according to the right section water grass floodplain data, thereby obtaining the location data of the right section water grass floodplain;

[0078] Step S337: performing riverbed uplift analysis on the waterweed floodplain position data of the right section according to the sediment settlement data, thereby obtaining riverbed uplift data;

[0079] Step S338: Integrate the cross-sectional morphology based on the riverbed uplift data and the local waterlogging data of the right cross-sectional waterweed, so as to obtain the right cross-sectional morphology data.

[0080] The present invention provides a basis for subsequent analysis by obtaining measurement data of the dry season and flood season of the right section, enhances the understanding of hydrological changes, clarifies the characteristics of the hydrological cycle, and helps to optimize water resource management strategies and flood response measures. Extracting characteristic data of waterweed floodplains can enhance the understanding of the ecological environment, help protect and restore aquatic ecosystems, provide a scientific basis for the protection and management of waterweed floodplains, and promote ecological balance. By analyzing the flow resistance during the dry season, we can understand the impact of waterweed on water flow, provide data support for water flow dynamics research, provide optimization measures for river management, reduce water flow resistance, and improve water flow efficiency. Simulating local waterlogging can predict waterlogging problems that occur under specific conditions, help formulate response plans, provide references for the design of related water conservancy facilities, and ensure their effectiveness under extreme conditions. Through sediment deposition data, the impact of waterweed floodplains on the sedimentation process is analyzed to help understand the interaction between ecology and hydrology, provide dynamic data of sedimentation conditions for watershed management, and optimize sediment management strategies. Extracting floodplain location feature data can enhance the spatial understanding of regional hydrological characteristics, help planning and management, and provide location data support for the protection and rational use of waterweed floodplains. Through the analysis of riverbed uplift, we can understand the impact of sediments on riverbed morphology, provide reference for river channel stability, provide data support for river channel maintenance and improvement measures, and enhance the ability of rivers to resist natural disasters. Integrate right-section morphological data to fully reflect hydrological characteristics and their changes, provide basic data for the design and optimization of water conservancy projects, provide a scientific basis for river channel management, and enhance the ability to respond to hydrological changes.

[0081] Optionally, the present specification also provides a hydrological regime change analysis method and system for hydrological engineering, which are used to execute the hydrological regime change analysis method for hydrological engineering as described above. The hydrological regime prediction system for the hydrological engineering includes:

[0082] River morphology analysis module: used to obtain remote sensing data of the hydrological monitoring area, and analyze the river morphology changes based on the remote sensing data of the hydrological monitoring area, so as to obtain river morphology change data;

[0083] Water flow analysis module: used to obtain the measurement information data of hydrological equipment, and extract the water body section characteristics and water flow velocity characteristics according to the measurement information data of hydrological equipment, so as to obtain the water body section data and water flow velocity data; perform water flow analysis according to the water body section data and water flow velocity data, so as to obtain the water flow data;

[0084] Section morphology analysis module: used to classify section orientation according to the hydrological equipment measurement information data, so as to obtain the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; to perform section morphology analysis according to the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data, so as to obtain section morphology data; to construct a hydrodynamic model according to the section morphology data, so as to obtain hydrodynamic model data;

[0085] Flow velocity relationship line correction module: used to calculate the flow velocity relationship line according to the water body section data and the water flow data, so as to obtain the flow velocity relationship line data; dynamically correct the flow velocity relationship line data according to the river channel morphology change data and the section morphology data, so as to obtain the dynamic correction data of the flow velocity relationship line;

[0086] Hydrological situation prediction module: used to predict the hydrological situation based on the hydrodynamic model data and the dynamic correction data of the velocity relationship line, so as to obtain the hydrological situation prediction data and upload it to the hydrological engineering management platform to perform the hydrological situation prediction task.

[0087] The hydrological situation change analysis system for hydrological engineering of the present invention can implement any hydrological situation change analysis method for hydrological engineering of the present invention, and is used to combine the operation and signal transmission medium between various modules to complete the hydrological situation change analysis method for hydrological engineering. The internal modules of the system cooperate with each other to complete the hydrological situation prediction task. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0089] Figure 1 A schematic diagram of the steps of the hydrological regime change analysis method for hydrological engineering according to the present invention;

[0090] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0091] Figure 3 Detailed step flow diagram of step S15 in the present invention;

[0092] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0093] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0094] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0095] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0096] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for analyzing hydrological regime changes for hydrological engineering, the method comprising the following steps:

[0097] Step S1: acquiring remote sensing data of the hydrological monitoring area, and performing river morphology change analysis based on the remote sensing data of the hydrological monitoring area, thereby obtaining river morphology change data;

[0098] In this embodiment, high-resolution satellite images are used to obtain remote sensing data of the hydrological monitoring area, and Sentinel satellites are selected for data acquisition. The remote sensing data is preprocessed by image processing software, image enhancement and classification algorithms are applied to ensure data quality. Subsequently, the river area is extracted using water body indexes (such as NDWI), the river boundary of each phase is calculated, and then its morphological changes are analyzed. The morphological change data is obtained by calculating indicators such as river width, curvature and area to form time series data, and then the changing trend of the river is visually displayed.

[0099] Step S2: obtaining the measurement information data of the hydrological equipment, and performing water body section feature extraction and water flow velocity feature extraction according to the measurement information data of the hydrological equipment, thereby obtaining water body section data and water flow velocity data; performing water flow analysis according to the water body section data and water flow velocity data, thereby obtaining water flow data;

[0100] In this embodiment, real-time measurement data of hydrological equipment is collected, including information such as water level, flow rate and water temperature. Through hydrological sensors, water body cross-sectional characteristics, such as cross-sectional width and depth data, are obtained in real time. A flow velocity sensor is used to record water flow velocity data, which is transmitted to the data processing system in real time by the data acquisition unit inside the device. The cross-sectional data and flow velocity data are integrated to calculate the water flow rate, and the formula is flow rate (Q) = cross-sectional area (A) × flow rate (V). This step obtains specific water flow data through flow analysis, providing a basis for subsequent analysis.

[0101] Step S3: classifying the section orientation according to the hydrological equipment measurement information data, thereby obtaining the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; performing section morphology analysis according to the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data, thereby obtaining section morphology data; constructing a hydrodynamic model according to the section morphology data, thereby obtaining hydrodynamic model data;

[0102] In this embodiment, the cross section is oriented and classified, and the measurement points are divided into left cross section and right cross section by coordinate system using GIS software, and relevant data are extracted respectively. For the data of left cross section and right cross section, geometric analysis technology is used to analyze the cross section morphology, and the shape characteristics of the cross section, such as width, depth and slope angle, are calculated. These cross section morphology data provide the necessary basic parameters for constructing the hydrodynamic model, and the corresponding formula, such as the Bernoulli equation in fluid mechanics, is used to form the hydrodynamic model data.

[0103] Step S4: Calculate the velocity relationship line according to the water body section data and the water flow data, so as to obtain the velocity relationship line data; dynamically correct the velocity relationship line data according to the river channel morphology change data and the section morphology data, so as to obtain the velocity relationship line dynamic correction data;

[0104] In this embodiment, the velocity relationship line is calculated using water body cross-sectional data and flow data, and the flow data and cross-sectional area are subjected to correlation analysis, and the relationship formula between velocity and flow is obtained through regression analysis. Dynamic correction is performed on the river channel morphology change data and cross-sectional morphology data, and the velocity relationship line is optimized using methods such as Kalman filtering. This process ensures that the velocity relationship line obtained can reflect the real-time hydrological state, thereby improving the accuracy of subsequent predictions.

[0105] Step S5: Perform hydrological situation prediction based on the hydrodynamic model data and the dynamic correction data of the velocity relationship line, thereby obtaining hydrological situation prediction data, and uploading it to the hydrological engineering management platform to execute the hydrological situation prediction task.

[0106] In this embodiment, hydrological situation prediction is performed based on the hydrodynamic model data and the dynamically corrected velocity relationship line, and a prediction model is formed by using statistical analysis methods, such as time series analysis, combined with historical hydrological data and real-time monitoring data. The obtained prediction results are uploaded to the hydrological engineering management platform, and a database management system is used to ensure real-time updating and queryability of the data. The platform provides support for the monitoring and analysis of hydrological situations, thereby effectively guiding water resources management and flood control decisions. Through this system, the hydrological situation prediction data formed can provide a scientific basis for relevant departments to ensure the ability to respond to sudden hydrological events.

[0107] Optionally, step S1 specifically includes:

[0108] Step S11: acquiring remote sensing data of the hydrological monitoring area, and dividing the band types according to the remote sensing data of the hydrological monitoring area, thereby obtaining green band data and near infrared band data;

[0109] In this embodiment, remote sensing data of the hydrological monitoring area is obtained, and high-resolution satellite images are used, such as Sentinel-2 remote sensing images are selected for data collection. After the data is acquired, the image is preprocessed by remote sensing image processing software (such as ENVI or ERDAS IMAGINE), including steps such as noise removal and geometric correction. The image data is divided into different bands using band division technology, and the green band (such as a wavelength of 490 nm) and near-infrared band (such as a wavelength of 850 nm) data are extracted. This process stores the results as two sets of data sets for subsequent analysis.

[0110] Step S12: performing band reflectance statistics according to the green band data and the near-infrared band data, so as to obtain high-reflectance green band data and low-reflectance near-infrared band data;

[0111] In this embodiment, reflectivity statistical analysis is performed based on the acquired green band data and near-infrared band data. The band reflectivity value of each pixel is calculated by using remote sensing analysis software, and the reflectivity value is associated with the band data. A reflectivity threshold is set, and pixels with a reflectivity greater than a certain standard value are classified as high-reflectivity green band data, and vice versa as low-reflectivity near-infrared band data. This statistical result will provide basic data support for the subsequent calculation of water body remote sensing indexes to ensure the accuracy of the analysis.

[0112] Step S13: Calculating the water body remote sensing index according to the high reflectivity green band data and the low reflectivity near infrared band data, thereby obtaining the water body remote sensing index data;

[0113] In this embodiment, the water body remote sensing index is calculated based on the high reflectivity green band data and the low reflectivity near infrared band data. The commonly used water body index formula, such as the normalized water index (NDWI), is used, and the calculation method is: NDWI = (green band - near infrared band) / (green band + near infrared band). Enter the corresponding band data in the remote sensing software, and the program automatically calculates the water body index value of each pixel. By setting the NDWI threshold, the water body area is distinguished from the non-water body area, and the water body remote sensing index data is generated, which lays the foundation for subsequent feature extraction.

[0114] Step S14: extracting river channel area features from the remote sensing data of the hydrological monitoring area according to the water body remote sensing index data, thereby obtaining river channel area data;

[0115] In this embodiment, the remote sensing data of the hydrological monitoring area is used to extract river channel regional features based on the water body remote sensing index data. GIS software (such as ArcGIS or QGIS) is used to combine the water body remote sensing index with the regional terrain data to identify river channel features. The water body extraction tool is used to extract the water body area by setting a threshold to form river channel regional data. This process generates detailed river channel regional data by analyzing the geometric shape, area and boundary characteristics of the river channel, providing a data basis for subsequent river channel morphological change analysis.

[0116] Step S15: Perform river channel morphology change analysis based on the river channel area data to obtain river channel morphology change data.

[0117] In this embodiment, the river morphology change analysis is performed based on the acquired river area data, and the morphological indicators of the river area are calculated using spatial analysis tools, including parameters such as river width, flow velocity, and river curvature. The change amount and change rate are calculated by comparing the historical river data with the current data. The river morphology change data is visualized using visualization tools to form charts and maps to intuitively display the change trend of the river. This analysis provides a scientific basis for monitoring and evaluating changes in the hydrological situation, which is helpful for subsequent water resources management and flood control decisions.

[0118] Optionally, step S15 is specifically:

[0119] Step S151: Generate remote sensing point cloud according to the river area data, so as to obtain the river area point cloud data;

[0120] In this embodiment, remote sensing point cloud generation is based on the acquired river area data, and is processed using high-resolution remote sensing images or laser radar (LiDAR) data. During the processing, point cloud software (such as LAStools or CloudCompare) is used for data preprocessing, including noise removal and ground classification. By setting a height threshold (such as 1.5 meters), the ground point cloud is extracted to ensure coverage of the river area. Finally, the generated river area point cloud data contains a large number of three-dimensional coordinate points, representing the spatial characteristics of the river, and providing a basis for the subsequent construction of a digital elevation model.

[0121] Step S152: constructing a river digital elevation model according to the river area point cloud data, thereby obtaining a river digital elevation model;

[0122] In this embodiment, a river digital elevation model (DEM) is constructed based on the generated river area point cloud data. The point cloud data is processed using an interpolation algorithm (such as inverse distance weighted or Kriging interpolation) to generate an elevation model. The grid size is set to 1 meter to ensure the spatial resolution of the elevation data. A continuous river elevation surface is obtained by weighted averaging the elevation data in each grid. The constructed river digital elevation model should have high precision so as to reflect the slight changes in the riverbed and provide accurate data for the subsequent riverbed elevation feature extraction.

[0123] Step S153: extracting riverbed elevation features according to the river channel digital elevation model, thereby obtaining riverbed elevation data;

[0124] In this embodiment, riverbed elevation feature extraction is performed based on the obtained river channel digital elevation model. GIS software (such as ArcGIS or QGIS) is used to calculate the elevation features of the riverbed using elevation data. The specific operation includes applying terrain analysis tools, extracting elevation values, and generating elevation feature maps. Thresholds (such as points where the riverbed elevation is lower than the water surface height) are set to classify riverbed features, thereby identifying specific elevation data of the riverbed, forming a detailed riverbed elevation map, and providing necessary input data for slope calculation.

[0125] Step S154: Calculating the riverbed slope according to the riverbed elevation data, thereby obtaining riverbed slope data;

[0126] In this embodiment, the riverbed slope calculation is performed based on the extracted riverbed elevation data. The slope analysis tool in the GIS software is used to input the riverbed elevation data and generate a slope map. During the calculation process, the slope calculation formula is used to analyze the elevation difference between adjacent pixels and calculate the slope value. The pixel size of the slope calculation is set to 1 meter to ensure accuracy. The generated slope data can clearly show the steepness and change trend of the riverbed, providing basic data support for subsequent slope change analysis.

[0127] Step S155: performing slope change analysis according to the riverbed slope data, thereby obtaining riverbed slope increase data and riverbed slope decrease data;

[0128] In this embodiment, the slope change analysis is performed based on the obtained riverbed slope data. The historical slope data and the current slope data are compared using GIS software to calculate the increase or decrease of the slope. In the specific implementation, the time interval and change threshold (such as the area where the slope change is greater than 5%) are set for statistics to generate a slope change map. By analyzing the slope increase data and decrease data, a detailed slope change analysis result is formed, which provides the necessary basis for the subsequent river morphology classification.

[0129] Step S156: classifying the river channel area data into river channel morphology according to the riverbed slope increase data and the riverbed slope decrease data, thereby obtaining river channel erosion area data and river channel deposition area data;

[0130] In this embodiment, the river channel area data is classified into river channel morphology according to the riverbed slope increase data and slope decrease data. GIS software is used to integrate and classify data and analyze the slope change characteristics in the river channel area. By setting classification standards (such as slope increase greater than 5% is defined as erosion area, and slope decrease greater than 5% is defined as deposition area), a spatial distribution map of river channel erosion area and deposition area is generated. The accuracy and reliability of the classification results are ensured to provide support for subsequent analysis and decision-making.

[0131] Step S157: Performing river channel morphology change regional integration based on the river channel erosion area data and the river channel deposition area data, thereby obtaining river channel morphology change data.

[0132] In this embodiment, the river morphology change area is integrated based on the river erosion area data and the river deposition area data. GIS software is used to perform overlay analysis on the classified areas to generate river morphology change data. Using spatial analysis tools, the erosion area and the deposition area are spatially matched to generate a comprehensive layer of river morphology change. By statistically analyzing the area and proportion of the changed area, the degree of river morphology change is evaluated to provide a decision-making basis for hydrological engineering management.

[0133] Optionally, step S2 specifically includes:

[0134] Step S21: obtaining hydrological equipment measurement information data, and performing water body section feature extraction and water flow velocity feature extraction according to the hydrological equipment measurement information data, thereby obtaining water body section data and water flow velocity data;

[0135] In this embodiment, the process of obtaining the measurement information data of the hydrological equipment is carried out through the hydrological measuring equipment (such as current meter, depth meter) deployed in the river. First, real-time data within a certain time range is collected, including water level, flow rate and other hydrological characteristics. Through the data recording device, the hydrological data of each minute is read and recorded in the database. Subsequently, the data is sorted and cleaned using data processing software (such as MATLAB or Excel) to remove outliers and ensure the validity of the data. Then, the water body section feature is extracted based on the measurement information data of the hydrological equipment, and the water depth and flow rate of each measuring point are calculated using the cross-section method, and finally the water body section data and water flow velocity data are generated to provide a basis for subsequent analysis.

[0136] Step S22: extracting cross-sectional width features and cross-sectional depth features according to the water body cross-sectional data, thereby obtaining cross-sectional width data and cross-sectional depth data;

[0137] In this embodiment, based on the acquired water body cross-section data, cross-section width feature extraction and cross-section depth feature extraction are performed. Using hydrological survey data, the cross-section width is first measured by setting calibration rods on both sides of the cross-section to ensure that the measurement accuracy is within 0.1 meters. Then, by collecting depth data at different positions on the cross-section, the depth of each measuring point is calculated to obtain cross-section depth data. The entire process can be visualized using GIS tools to more intuitively display the cross-section width and depth. Finally, the width and depth data are stored in the database to provide parameter support for subsequent water body cross-sectional area calculations.

[0138] Step S23: Calculating the cross-sectional area of ​​the water body according to the cross-sectional width data and the cross-sectional depth data, thereby obtaining the cross-sectional area data of the water body;

[0139] In this embodiment, the cross-sectional area of ​​the water body is calculated based on the extracted cross-sectional width data and cross-sectional depth data. The shore area is calculated using a triangular cross-section, that is, area = width × depth / 2; the middle area is calculated using a trapezoidal cross-section, that is, area = the sum of the depths of adjacent measuring points × width / 2. For the width and depth values ​​of each measuring point, it is necessary to ensure that the values ​​are valid to avoid the influence of extreme values. To improve the accuracy of the calculation, a threshold value can be set (such as the width and depth should both be greater than 0), and the areas of each measuring point can be accumulated to obtain the total cross-sectional area data of the water body. This data provides the basis for subsequent flow calculations.

[0140] Step S24: analyzing the distribution of water bodies and sand according to the remote sensing data of the hydrological monitoring area, thereby obtaining water body and sand distribution data;

[0141] In this embodiment, the distribution analysis of sand in the water body is performed based on the remote sensing data of the hydrological monitoring area. Remote sensing images (such as satellite images) are used to perform analysis using image processing software (such as ENVI or ArcGIS). First, the sand characteristics of the water body are extracted through band combination and NDVI (normalized difference vegetation index) calculation. Then, a classification algorithm (such as maximum likelihood classification or support vector machine) is used to analyze the distribution of sand in the water body. By setting the classification accuracy requirement (such as 85%), the validity and accuracy of the sand distribution data are ensured, and finally a sand distribution map is generated.

[0142] Step S25: Calculate the sand roughness coefficient according to the water body sand distribution data, so as to obtain the water body sand roughness coefficient data;

[0143] In this embodiment, the sand roughness coefficient is calculated based on the sand distribution data of the water body. The known sand types and their corresponding roughness coefficients (such as the roughness values ​​in the Manning formula) are used, combined with the sand distribution data of the previous step, to analyze the roughness of each area. The sand area is divided into different categories, and the roughness value of each category is set according to the specific situation (for example, fine sand is 0.02, coarse sand is 0.03). Finally, the calculation results are sorted and output as sand roughness coefficient data to support the drawing of the water flow velocity distribution map.

[0144] Step S26: drawing a water flow velocity distribution map according to the water body sand roughness coefficient data and the water flow velocity data, thereby obtaining a water flow velocity distribution map;

[0145] In this embodiment, the roughness coefficient data of the water body sand and the water flow velocity data are used to draw the water flow velocity distribution map. The velocity data is combined with the roughness coefficient, and the velocity distribution is calculated by a fluid mechanics formula (such as the Darcy-Weisbach formula). Spatial analysis is performed using GIS software (such as ArcGIS), and the velocity data is mapped to the river area to form a velocity distribution map. In this process, a classification standard (such as 0-1 m / s, 1-2 m / s, etc.) is set to visualize the velocity and ensure that the generated velocity distribution map is intuitive and easy to read.

[0146] Step S27: Calculate the water flow rate according to the water flow velocity distribution diagram and the water body cross-sectional area data, so as to obtain the water flow rate data.

[0147] In this embodiment, the water flow rate is calculated based on the water flow velocity distribution map and the water body cross-sectional area data. The water flow rate calculation formula is flow rate = cross-sectional area × flow rate. The flow rate values ​​of each area in the flow velocity distribution map are combined with the corresponding cross-sectional area to calculate the flow rate area by area. Ensure that the flow velocity and cross-sectional area of ​​each area are the latest data, set thresholds (such as the flow velocity should be greater than 0), and filter invalid areas. Summarize the flow data of all areas to obtain the overall water flow data, which provides an important reference for the analysis of hydrological situation changes.

[0148] Optionally, step S24 is specifically:

[0149] Step S241: extracting pixel spectrum features of the hydrological monitoring area according to the remote sensing data of the hydrological monitoring area, thereby obtaining pixel spectrum data of the hydrological monitoring area;

[0150] In this embodiment, pixel spectral feature extraction is performed based on remote sensing data of the hydrological monitoring area, and multispectral data of the area is obtained using high-resolution remote sensing images (such as Landsat or Sentinel satellite images). Spectral analysis software (such as ENVI) is used to process the original image and perform atmospheric correction to ensure the accuracy of the data. By analyzing the spectral reflectance of each pixel, spectral features of different bands (such as visible light, near infrared, etc.) are extracted. The generated spectral data includes reflectance values ​​within the wavelength range, which lay the foundation for subsequent vegetation index calculation and sand distribution analysis.

[0151] Step S242: Calculating vegetation index according to the pixel spectrum of the hydrological monitoring area, thereby obtaining vegetation index data;

[0152] In this embodiment, the vegetation index is calculated based on the extracted pixel spectral data of the hydrological monitoring area, and a common vegetation index calculation formula, such as NDVI (normalized difference vegetation index) is used. The NDVI calculation formula is NDVI = (NIR - R) / (NIR + R), where NIR represents the near-infrared band reflectance and R represents the red light band reflectance. The NDVI is calculated pixel by pixel through the corresponding band reflectance values ​​in the spectral data, and the generated vegetation index data is used to evaluate the vegetation coverage in the area and further provide a basis for the division of sand distribution.

[0153] Step S243: dividing the remote sensing data of the hydrological monitoring area into sand distribution according to the vegetation index data and the river area data, thereby obtaining sand distribution data;

[0154] In this embodiment, the remote sensing data of the hydrological monitoring area is divided into sand distribution according to the vegetation index data and the river area data. First, the vegetation index is combined with the spatial distribution information of the river area, and the classification of the sand area is realized by setting a threshold (such as NDVI less than 0.2 can be considered as bare soil or sand area). GIS software (such as ArcGIS) is used for spatial analysis, and a sand distribution map is generated through regional division, and sand distribution data is extracted. This data not only provides the location of the sand area, but also provides a basis for subsequent particle size distribution calculations.

[0155] Step S244: obtaining ground data of sand particle size;

[0156] In this embodiment, the process of obtaining the ground data of sand particle size needs to collect soil samples in the sand distribution area. Soil samples are randomly selected at different locations by field collection equipment (such as soil sampler) to ensure the representativeness of the samples. Each sample needs to be analyzed for particle size, and the sand is classified by particle size by sieving method and laser particle size analyzer, and the particle size distribution of each sample is recorded. The obtained particle size data will be used for the subsequent calculation of sand particle size distribution.

[0157] Step S245: Calculating the sand particle size distribution according to the sand distribution data and the ground-collected sand particle size data, thereby obtaining the sand particle size distribution data;

[0158] In this embodiment, the sand particle size distribution is calculated based on the sand distribution data and the ground-collected sand particle size data. The particle size data obtained in the previous step is combined with the remote sensing analysis results, and the sand particle size is regionally estimated using a spatial interpolation method (such as Kriging interpolation). By setting a particle size classification standard (such as 0.05mm-0.1mm, 0.1mm-0.5mm, etc.), the particle size data in the sand area is classified and summarized, and the sand particle size distribution data finally generated provides a basis for sand property analysis.

[0159] Step S246: performing water body sand distribution analysis on the river area data according to the sand particle size distribution data, thereby obtaining water body sand distribution data.

[0160] In this embodiment, the sand distribution in the water body is analyzed based on the sand particle size distribution data of the river area data. First, the sand particle size distribution data is mapped to the river area using GIS tools, and a comprehensive analysis is performed in combination with the hydrological monitoring data. The impact of sand on water flow is evaluated by calculating the distribution characteristics of sand at different particle sizes. The analysis may include calculating the suspension ratio and sedimentation characteristics of sand in flowing water, and finally generating water body sand distribution data. These data will provide important information for subsequent analysis of hydrological changes.

[0161] Optionally, step S246 is specifically:

[0162] Perform sand particle size statistics according to the sand particle size distribution data, so as to obtain coarse sand particle size distribution data and fine sand particle size distribution data;

[0163] In this embodiment, the sand particle size statistics are performed based on the sand particle size distribution data. By grouping the acquired particle size data, the particle size range is first set, for example, a particle size less than 0.25 mm is defined as fine sand, and a particle size greater than 0.25 mm but less than 2.0 mm is defined as coarse sand. The particle size data is subjected to frequency analysis using statistical analysis software (such as Excel or R), and the number of samples in each particle size group and its proportion of the total samples are calculated, thereby generating coarse sand particle size distribution data and fine sand particle size distribution data. This process provides the basic characteristics of different particle size distributions of sand, which is convenient for subsequent transportation simulation.

[0164] Performing sand transport simulation on the coarse sand particle size distribution data and the fine sand particle size distribution data according to the water flow velocity data, thereby obtaining sand transport data;

[0165] In this embodiment, sand transport simulation is performed on the coarse sand particle size distribution data and the fine sand particle size distribution data according to the water flow velocity data. First, an appropriate sand transport model is selected, such as the Chezy or Manning formula. A velocity threshold is set, and 0.3 m / s is usually used as the critical velocity for sand transport. Using the velocity data and particle size distribution, a formula is used to calculate the sand transport capacity at different flow rates to generate sand transport data. This process provides the dynamic changes of sand under the action of water flow, which helps to understand the movement characteristics of sand.

[0166] Conduct sand deposition analysis based on sand transport data to obtain sand deposition data;

[0167] In this embodiment, sand deposition analysis is performed based on sand transport data. First, the area for deposition analysis is determined and the calculation standard of the deposition rate is set. Usually, the deposition rate corresponding to the particle size at a flow rate of 0.1-0.3m / s is selected for analysis. Using the deposition model, the deposition amount at different locations is calculated by comparing the flow rate and the amount of sand transported, and sand deposition data is generated. This analysis helps evaluate the deposition behavior of sand under different water flow conditions and provides a basis for subsequent hydrological situation analysis.

[0168] Perform sand suspension analysis based on sand transport data to obtain sand suspension data;

[0169] In this embodiment, the sand suspension analysis is performed based on the sand transport data. First, the suspension threshold is set. Usually, particles with a diameter of more than 0.2 mm are considered suspended particles. The concentration of sand with different particle sizes suspended in flowing water is calculated by using the flow velocity data, combined with the particle diameter and fluid density, and using the Stokes law or a similar suspension calculation model. The resulting sand suspension data provides important information for subsequent sand deposition and flow velocity analysis.

[0170] The sand particle size distribution curve is drawn according to the sand deposition data and the sand suspension data, thereby obtaining the sand particle size distribution curve data;

[0171] In this embodiment, the sand particle size distribution curve is drawn based on the sand deposition data and the sand suspension data. First, the different particle size data obtained in the deposition and suspension analysis are collected. The sand particle size is used as the X-axis, and the deposition amount and suspension amount are used as the Y-axis. The curve is fitted through statistical software (such as MATLAB or Python) to generate a particle size distribution curve. This curve intuitively shows the deposition and suspension characteristics of sand with different particle sizes, providing a graphical data display for subsequent analysis.

[0172] The flow velocity analysis and sand density calculation are performed according to the sand particle size distribution curve data, so as to obtain the sand particle size distribution flow velocity curve and sand density data;

[0173] In this embodiment, flow velocity analysis and sand density calculation are performed based on the sand particle size distribution curve data. First, the amount of deposited and suspended sand in different particle size ranges is extracted from the particle size distribution curve. Combined with fluid mechanics theory, the sand flow behavior at different flow rates is calculated. At the same time, based on the flow velocity and particle size distribution data, the sand density is calculated using a formula, which can usually be used: density = mass / volume. The sand particle size distribution flow velocity curve and sand density data obtained lay the foundation for water, soil and sand distribution analysis.

[0174] Water-soil-sand distribution analysis is performed based on the sand particle size distribution velocity curve and sand density data to obtain water body sand distribution data.

[0175] In this embodiment, water-soil sand distribution analysis is performed based on the velocity curve of sand particle size distribution and sand density data, and the velocity curve is combined with the density data to evaluate the behavior of sand under different flow rates and density conditions. The fluid dynamics model is used to determine the distribution pattern of sand in the water body by analyzing the distribution characteristics of sand particles in the water body. The resulting water body sand distribution data provides an important reference for hydrological engineering management and water resources management, ensuring that the dynamic changes of sand can be taken into account when making decisions.

[0176] Optionally, step S3 specifically includes:

[0177] Step S31: classifying the section orientation according to the hydrological equipment measurement information data, thereby obtaining the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data;

[0178] In this embodiment, the cross-section orientation is classified according to the hydrological equipment measurement information data, and the data from the hydrological measurement equipment, including water level, flow rate, flow rate and other information, are collected. These data are usually obtained by an automatic hydrological monitoring system (such as a water level sensor, a flow meter). The measurement data are classified by location to determine the measurement data of the left bank and the right bank. The left bank data is generally located on the left side of the river flow, while the right bank data is located on the right side. Using a geographic information system (GIS) tool, these data are spatially marked and classified to obtain clear left section hydrological equipment measurement information data and right section hydrological equipment measurement information data.

[0179] Step S32: performing left section morphology analysis according to the left section hydrological equipment measurement information data, thereby obtaining left section morphology data;

[0180] In this embodiment, the left section morphology analysis is performed based on the measurement information data of the hydrological equipment of the left section. This step first uses the water level and flow rate information in the measurement data to extract the geometric shape characteristics of the section. Using numerical calculation methods, based on the acquired water depth data, by setting a suitable grid size, the left section is divided into several small units, and the cross-sectional area and average water depth of each unit are calculated. Combined with existing terrain data (such as digital elevation model), the cross-sectional morphological characteristics of the left bank are analyzed, including the width, depth, slope, etc. of the section. Finally, the left section morphological data is formed, laying the foundation for subsequent model construction.

[0181] Step S33: performing right section morphology analysis according to the right section hydrological equipment measurement information data, thereby obtaining right section morphology data;

[0182] In this embodiment, the right section morphology analysis is performed based on the measurement information data of the right section hydrological equipment. First, the water level and flow rate data of the right bank are also extracted. The same numerical calculation method is used to divide the right section into several small units, calculate the cross-sectional area and water depth of each unit, and comprehensively consider the terrain data. By analyzing these characteristics, the key parameters such as the width, depth, and slope of the right bank section are determined. The obtained right section morphology data and the left section morphology data together provide necessary information for subsequent section integration.

[0183] Step S34: performing cross-sectional morphology integration according to the left cross-sectional morphology data and the right cross-sectional morphology data, thereby obtaining cross-sectional morphology data;

[0184] In this embodiment, the cross-sectional morphology is integrated based on the left cross-sectional morphology data and the right cross-sectional morphology data. First, the morphology data of the cross-sections on both sides are compared, and the data of the left cross-section and the right cross-section are spatially integrated using a mathematical model (such as an interpolation method). By calculating the mean of the cross-sectional width and depth, as well as the water depth change at the corresponding position, a complete cross-sectional morphology feature is formed. The key parameters in the integration process include the coordinates of the cross-sectional position and the measured depth. The integrated data provides a basis for the overall morphological characteristics of the river channel.

[0185] Step S35: constructing a hydrodynamic model according to the cross-sectional morphology data, thereby obtaining hydrodynamic model data.

[0186] In this embodiment, a hydrodynamic model is constructed based on the cross-sectional morphology data. First, a suitable hydrodynamic model is selected, such as a fluid dynamics model (for example, the Navier-Stokes equations of fluid mechanics) or an empirical formula (such as the Manning formula). The integrated cross-sectional morphology data, including the width, depth, slope and water flow information of the cross section, are input into the model for calculation. The model parameters are set, including fluid density, dynamic viscosity and friction coefficient, etc. The model parameters can be adjusted according to local hydrological characteristics and historical data. The hydrodynamic model data finally generated is used to analyze the flow behavior and its impact on the river morphology, and provide support for the prediction of changes in the hydrological situation.

[0187] Optionally, step S32 is specifically:

[0188] Step S321: Perform hydrological period statistics based on the hydrological equipment measurement information data of the left section, thereby obtaining the equipment measurement information data of the left section during the dry season and the equipment measurement information data of the left section during the flood season;

[0189] In this embodiment, hydrological cycle statistics are performed based on the measurement information data of the hydrological equipment in the left section. The water level and flow data of the left section in different time periods are collected. These data are usually collected by automatic monitoring equipment and include daily, monthly and seasonal records. The collected data are analyzed using statistical analysis software to calculate the equipment measurement information data during the dry season (such as when the flow rate is less than a specific threshold, such as 5 m³ / s) and the flood season (when the flow rate is greater than a specific threshold, such as 50 m³ / s). By visualizing the distribution and changes of the hydrological cycle, the measurement information data of the dry season and flood season of the left section are obtained to facilitate subsequent analysis.

[0190] Step S322: extracting the features of the left section of the stone bank according to the remote sensing data of the hydrological monitoring area, thereby obtaining the left end face stone bank data;

[0191] In this embodiment, the feature extraction of the left section stone bank is performed based on the remote sensing data of the hydrological monitoring area. First, the acquired remote sensing image is processed, and the characteristic information of the stone bank is extracted using spectral analysis. Select appropriate bands (such as red and near-infrared bands) for analysis, and apply classification algorithms (such as support vector machines) to distinguish the stacked stones. The coverage area and distribution characteristics of the stacked stones are extracted to form the left section stone bank data, including the size, shape and distribution of the stones on the shore, for subsequent friction analysis.

[0192] Step S323: analyzing the water flow friction force of the equipment measured in the dry season of the left section according to the stone bank of the left section, thereby obtaining the water flow friction force data of the left section in the dry season;

[0193] In this embodiment, the water flow friction force analysis is performed on the left section dry season equipment measurement information data according to the left section stacked stone bank. The flow velocity and flow rate data of the left section during the dry season are combined with the characteristics of the stacked stone bank (such as stone size and arrangement) for calculation. According to the friction formula (such as the Manning formula), the corresponding parameters (such as water flow velocity and roughness coefficient of the stacked stone bank) are input to calculate the friction force of the fluid on the stacked stone bank, and the left section dry season water flow friction force data is formed to analyze its influence on the water flow.

[0194] Step S324: simulating the water flow of the equipment measurement information data of the left section during the flood period according to the left end face stone bank, so as to obtain the water flow data of the left section during the flood period;

[0195] In this embodiment, water flow simulation is performed on the left section flood period equipment measurement information data according to the left section stone bank. The water flow velocity and water level data during the flood period are obtained, and a fluid dynamics simulation method (such as CFD simulation) is selected in combination with the characteristics of the stone bank. The parameters input to the model include flow velocity, flow rate and characteristics of the stone bank, and the flow of water on the stone bank is simulated to generate water flow data to help understand the dynamic behavior of water flow during the flood period.

[0196] Step S325: performing a masonry stone hardness analysis based on the left end face masonry stone bank data, thereby obtaining masonry stone hardness data;

[0197] In this embodiment, the hardness analysis of the stacked stone is performed based on the data of the stacked stone bank on the left end. The hardness information of the stacked stone material is collected, and the hardness value of each stacked stone is obtained by sampling on site and performing a standard hardness test (such as a Mohs hardness test). Combined with remote sensing data and ground surveys, the spatial distribution analysis of the hardness data is performed to form the stacked stone hardness data, which provides a basis for evaluating the stability of the shoreline.

[0198] Step S326: performing concentrated flow analysis on the water flow data of the left section during the flood period according to the hardness data of the masonry stones, thereby obtaining concentrated flow data of the water flow of the left section during the flood period;

[0199] In this embodiment, the water flow concentrated flow analysis is performed on the water flow data of the left section during the flood period according to the hardness data of the masonry stones. The concentrated flow of water on the surface of stones with different hardness is analyzed by combining the results of the flow simulation with the hardness information of the masonry stones and applying the principles of fluid mechanics. A hardness threshold is set, such as stones with a hardness greater than a specific value, to evaluate their impact on the direction and velocity of the water flow, and to form the concentrated flow data of the water flow in the left section during the flood period.

[0200] Step S327: analyzing the water flow velocity according to the concentrated flow data of the left section during the flood season and the water flow friction data of the left section during the dry season, thereby obtaining the water flow velocity data of the left section;

[0201] In this embodiment, the water flow velocity analysis is performed based on the concentrated flow data of the left section during the flood period and the friction data of the water flow during the dry period. The flow data under two different states are combined and calculated using a hydrodynamic formula (such as the relationship between flow rate and flow velocity). By comparing the flow velocity changes during the flood period and the dry period, the dynamic change of the flow velocity is obtained, and the water flow velocity data of the left section is formed, which provides an important basis for water flow management.

[0202] Step S328: performing sediment transport analysis on the left section of the stone bank according to the water flow velocity data of the left section, thereby obtaining sediment transport data of the left section;

[0203] In this embodiment, the sediment transport analysis of the left section stone bank is performed based on the left section water flow velocity data. The kinetic energy and flow rate of the water flow are calculated based on the flow velocity data, and the sediment transport capacity under flow conditions is calculated using the sediment transport formula (such as the Einstein-Brown formula) in combination with the known sediment characteristics (such as particle size and density). The influence of the water flow on the stone bank is analyzed to form the sediment transport data of the left section, and the erosion and sedimentation of the bank are evaluated.

[0204] Step S329: Perform a left section stone bank morphology analysis on the left section stone bank data according to the left section sediment transport data, thereby obtaining the left section morphology data.

[0205] In this embodiment, the left section stone bank morphology analysis is performed on the left section stone bank data based on the left section sediment transport data. By analyzing the transport data, combined with the distribution and morphological characteristics of the stone bank, the impact of water flow on the shoreline morphology is evaluated. The numerical calculation method is used to analyze the shoreline changes under different water flow conditions, and finally the left section morphology data is formed to provide shoreline management and improvement solutions.

[0206] Optionally, step S33 is specifically:

[0207] Step S331: performing hydrological period statistics of the right section according to the hydrological equipment measurement information data of the right section, thereby obtaining the equipment measurement information data of the right section during the dry season and the equipment measurement information data of the right section during the flood season;

[0208] In this embodiment, the hydrological cycle statistics of the right section are performed based on the measurement information data of the hydrological equipment of the right section. The water level, flow and rainfall data of the right section under different seasons and climatic conditions are collected. These data are usually collected regularly by automatic hydrological monitoring instruments installed beside the river. These data are sorted and classified, and the measurement information during the dry season (for example, the flow is less than 5 m³ / s) and the flood season (the flow is higher than 50 m³ / s) is calculated using statistical analysis tools (such as Excel or R language), forming the equipment measurement information data of the right section during the dry season and the flood season, providing basic data for subsequent analysis.

[0209] Step S332: extracting the features of the right section waterweed floodplain according to the remote sensing data of the hydrological monitoring area, thereby obtaining the right section waterweed floodplain data;

[0210] In this embodiment, the features of the waterweed floodplain in the right section are extracted based on the remote sensing data of the hydrological monitoring area. The waterweed floodplain is classified using remote sensing images and image processing technology. A specific band (such as an infrared band) is selected to analyze the spectral characteristics of waterweed, and the waterweed is identified and segmented in combination with a vegetation index (such as NDVI). The distribution, coverage area and growth status of the waterweed floodplain are extracted to form the waterweed floodplain data of the right section. These data provide an important reference for subsequent analysis of water flow resistance and sediment settlement.

[0211] Step S333: analyzing the flow resistance of the equipment measurement information data of the right section during the dry season according to the water grass floodplain data of the right section, thereby obtaining the flow resistance data of the right section;

[0212] In this embodiment, the water flow resistance analysis is performed on the right section dry season equipment measurement information data based on the right section water grass flooding data. Combined with the water flow velocity, flow data, and the density and distribution of water grass, the hydraulic formula (such as the Manning formula) is used to calculate the water grass resistance to water flow. The input parameters include the water flow velocity (obtained from the equipment measurement data) and the roughness coefficient of the grass (determined through on-site investigation), and the right section water flow resistance data is calculated to evaluate the impact of water grass on water flow.

[0213] Step S334: local waterlogging simulation is performed on the waterweed floodplain data of the right section according to the water resistance data of the right section, so as to obtain the local waterlogging data of the waterweed floodplain of the right section;

[0214] In this embodiment, local waterlogging simulation is performed on the right section waterweed floodplain data according to the right section water flow resistance data. A simulation model of local waterlogging is established by combining the flow velocity and resistance data through the principle of water flow dynamics. An appropriate calculation method (such as the finite difference method) is selected, and the input parameters include the speed of the water flow, the resistance, and the coverage of the waterweed, and calculations are performed to obtain the waterlogging conditions under different conditions. Through the simulation results, the local waterlogging data of the right section waterweed floodplain is generated to help analyze the hydrological characteristics of the local area.

[0215] Step S335: performing sediment settlement analysis on the equipment measurement information data of the right section during the flood period according to the water grass floodplain data of the right section, thereby obtaining sediment settlement data;

[0216] In this embodiment, sediment settlement analysis is performed on the equipment measurement information data of the right section during the flood period according to the water grass floodplain data of the right section. Combined with the data of the flow rate and water velocity during the flood period, the sediment settlement formula (such as the Stokes formula) is used to calculate the sedimentation rate under specific conditions. The input parameters include water flow rate, sediment particle diameter (obtained by sampling), fluid viscosity, etc., and the sediment settlement under different water flow conditions is analyzed to form sediment settlement data, which provides a basis for the study of riverbed changes.

[0217] Step S336: extracting the location feature of the right section water grass floodplain according to the right section water grass floodplain data, thereby obtaining the location data of the right section water grass floodplain;

[0218] In this embodiment, the location feature of the right section water grass floodplain is extracted based on the water grass floodplain data of the right section. By analyzing the water grass distribution map, the spatial location feature is extracted using the Geographic Information System (GIS) technology. The specific coordinates and area of ​​the water grass floodplain and its distribution form on the right section are recorded to form the location data of the right section water grass floodplain. By analyzing the location features, the impact of water grass on water flow and its habitat characteristics can be further understood.

[0219] Step S337: performing riverbed uplift analysis on the waterweed floodplain position data of the right section according to the sediment settlement data, thereby obtaining riverbed uplift data;

[0220] In this embodiment, the riverbed uplift analysis is performed on the waterweed floodplain location data of the right section based on the sediment settlement data. The sedimentation rate data and the spatial distribution data of the waterweed floodplain are collected, and the riverbed uplift is analyzed by comparing the sediment distribution in different time periods using the riverbed deformation formula (such as the curvature method). The threshold of riverbed uplift (such as the uplift exceeding 10 cm) is set, the impact of waterweed is evaluated, riverbed uplift data is generated, and quantitative analysis results of riverbed changes are provided.

[0221] Step S338: Integrate the cross-sectional morphology based on the riverbed uplift data and the local waterlogging data of the right cross-sectional waterweed, so as to obtain the right cross-sectional morphology data.

[0222] In this embodiment, the cross-sectional morphology is integrated based on the riverbed uplift data and the waterweed flooding local waterlogging data of the right section. By analyzing the spatial distribution of riverbed uplift and local waterlogging, morphological integration is performed using 3D modeling software (such as AutoCAD or ArcGIS) to form comprehensive right section morphological data. Combining various types of data, the impact of hydrological changes on riverbed morphology is evaluated, providing an important basis for river management and improved design.

[0223] Optionally, the present specification also provides a hydrological regime change analysis method and system for hydrological engineering, which are used to execute the hydrological regime change analysis method for hydrological engineering as described above. The hydrological regime prediction system for the hydrological engineering includes:

[0224] River morphology analysis module: used to obtain remote sensing data of the hydrological monitoring area, and analyze the river morphology changes based on the remote sensing data of the hydrological monitoring area, so as to obtain river morphology change data;

[0225] Water flow analysis module: used to obtain the measurement information data of hydrological equipment, and extract the water body section characteristics and water flow velocity characteristics according to the measurement information data of hydrological equipment, so as to obtain the water body section data and water flow velocity data; perform water flow analysis according to the water body section data and water flow velocity data, so as to obtain the water flow data;

[0226] Section morphology analysis module: used to classify section orientation according to the hydrological equipment measurement information data, so as to obtain the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; to perform section morphology analysis according to the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data, so as to obtain section morphology data; to construct a hydrodynamic model according to the section morphology data, so as to obtain hydrodynamic model data;

[0227] Flow velocity relationship line correction module: used to calculate the flow velocity relationship line according to the water body section data and the water flow data, so as to obtain the flow velocity relationship line data; dynamically correct the flow velocity relationship line data according to the river channel morphology change data and the section morphology data, so as to obtain the dynamic correction data of the flow velocity relationship line;

[0228] Hydrological situation prediction module: used to predict the hydrological situation based on the hydrodynamic model data and the dynamic correction data of the velocity relationship line, so as to obtain the hydrological situation prediction data and upload it to the hydrological engineering management platform to perform the hydrological situation prediction task.

[0229] The hydrological situation change analysis system for hydrological engineering of the present invention can implement any hydrological situation change analysis method for hydrological engineering of the present invention, and is used to combine the operation and signal transmission medium between various modules to complete the hydrological situation change analysis method for hydrological engineering. The internal modules of the system cooperate with each other to complete the hydrological situation prediction task.

[0230] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0231] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for analyzing hydrological regime changes for hydrological engineering, characterized in that: The following steps are involved: Step S1: Acquire remote sensing data of the hydrological monitoring area, and perform river morphology change analysis based on the remote sensing data of the hydrological monitoring area, so as to obtain river morphology change data; Step S1 is specifically as follows: Step S11: acquiring remote sensing data of the hydrological monitoring area, and dividing the band types according to the remote sensing data of the hydrological monitoring area, thereby obtaining green band data and near infrared band data; Step S12: performing band reflectance statistics according to the green band data and the near-infrared band data, thereby obtaining high-reflectance green band data and low-reflectance near-infrared band data; Step S13: Calculating the water body remote sensing index based on the high reflectivity green band data and the low reflectivity near infrared band data, thereby obtaining the water body remote sensing index data; Step S14: extracting river channel area features from the remote sensing data of the hydrological monitoring area according to the water body remote sensing index data, thereby obtaining river channel area data; Step S15: analyzing the change of river channel morphology according to the river channel area data, thereby obtaining river channel morphology change data; Step S2: obtaining hydrological equipment measurement information data, and performing water body section feature extraction and water flow velocity feature extraction based on the hydrological equipment measurement information data, thereby obtaining water body section data and water flow velocity data; Perform water flow analysis based on water body cross-section data and water flow velocity data to obtain water flow data; Step S3: classifying the section orientation according to the hydrological equipment measurement information data, thereby obtaining the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; performing section morphology analysis according to the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data, thereby obtaining section morphology data; Constructing a hydrodynamic model based on the cross-sectional morphology data to obtain hydrodynamic model data; Step S4: Calculate the velocity relationship line according to the water body section data and the water flow data, so as to obtain the velocity relationship line data; dynamically correct the velocity relationship line data according to the river channel morphology change data and the section morphology data, so as to obtain the velocity relationship line dynamic correction data; Step S5: Perform hydrological situation prediction based on the hydrodynamic model data and the dynamic correction data of the velocity relationship line, thereby obtaining hydrological situation prediction data, and uploading it to the hydrological engineering management platform to execute the hydrological situation prediction task.

2. The hydrological regime change analysis method for hydrological engineering according to claim 1, characterized in that: Step S15 is specifically as follows: Step S151: Generate remote sensing point cloud according to the river area data, so as to obtain the river area point cloud data; Step S152: constructing a river digital elevation model according to the river area point cloud data, thereby obtaining a river digital elevation model; Step S153: extracting riverbed elevation features according to the river channel digital elevation model, thereby obtaining riverbed elevation data; Step S154: Calculating the riverbed slope according to the riverbed elevation data, thereby obtaining riverbed slope data; Step S155: performing slope change analysis according to the riverbed slope data, thereby obtaining riverbed slope increase data and riverbed slope decrease data; Step S156: classifying the river channel area data into river channel morphology according to the riverbed slope increase data and the riverbed slope decrease data, thereby obtaining river channel erosion area data and river channel deposition area data; Step S157: Performing river channel morphology change regional integration based on the river channel erosion area data and the river channel deposition area data, thereby obtaining river channel morphology change data.

3. The hydrological situation change analysis method for hydrological engineering according to claim 1 is characterized in that: Step S2 is specifically as follows: Step S21: obtaining hydrological equipment measurement information data, and performing water body section feature extraction and water flow velocity feature extraction according to the hydrological equipment measurement information data, thereby obtaining water body section data and water flow velocity data; Step S22: extracting cross-sectional width features and cross-sectional depth features according to the water body cross-sectional data, thereby obtaining cross-sectional width data and cross-sectional depth data; Step S23: Calculating the cross-sectional area of ​​the water body according to the cross-sectional width data and the cross-sectional depth data, thereby obtaining the cross-sectional area data of the water body; Step S24: analyzing the distribution of water bodies and sand according to the remote sensing data of the hydrological monitoring area, thereby obtaining water body and sand distribution data; Step S25: Calculate the sand roughness coefficient according to the water body sand distribution data, so as to obtain the water body sand roughness coefficient data; Step S26: drawing a water flow velocity distribution map according to the water body sand roughness coefficient data and the water flow velocity data, thereby obtaining a water flow velocity distribution map; Step S27: Calculate the water flow rate according to the water flow velocity distribution diagram and the water body cross-sectional area data, so as to obtain the water flow rate data.

4. The hydrological regime change analysis method for hydrological engineering according to claim 3 is characterized in that: Step S24 is specifically as follows: Step S241: extracting pixel spectrum features of the hydrological monitoring area according to the remote sensing data of the hydrological monitoring area, thereby obtaining pixel spectrum data of the hydrological monitoring area; Step S242: Calculating vegetation index according to the pixel spectrum of the hydrological monitoring area, thereby obtaining vegetation index data; Step S243: dividing the remote sensing data of the hydrological monitoring area into sand distribution according to the vegetation index data and the river area data, thereby obtaining sand distribution data; Step S244: obtaining ground data of sand particle size; Step S245: Calculating the sand particle size distribution according to the sand distribution data and the ground-collected sand particle size data, thereby obtaining the sand particle size distribution data; Step S246: performing water body sand distribution analysis on the river area data according to the sand particle size distribution data, thereby obtaining water body sand distribution data.

5. The hydrological regime change analysis method for hydrological engineering according to claim 4, characterized in that: Step S246 is specifically as follows: Perform sand particle size statistics according to the sand particle size distribution data, so as to obtain coarse sand particle size distribution data and fine sand particle size distribution data; Performing sand transport simulation on the coarse sand particle size distribution data and the fine sand particle size distribution data according to the water flow velocity data, thereby obtaining sand transport data; Conduct sand deposition analysis based on sand transport data to obtain sand deposition data; Perform sand suspension analysis based on sand transport data to obtain sand suspension data; The sand particle size distribution curve is drawn according to the sand deposition data and the sand suspension data, thereby obtaining the sand particle size distribution curve data; The flow velocity analysis and sand density calculation are performed according to the sand particle size distribution curve data, so as to obtain the sand particle size distribution flow velocity curve and sand density data; The water-soil-sand distribution analysis is performed based on the sand particle size distribution velocity curve and sand density data to obtain the water body sand distribution data.

6. The hydrological regime change analysis method for hydrological engineering according to claim 1, characterized in that: Step S3 is specifically as follows: Step S31: classifying the section orientation according to the hydrological equipment measurement information data, thereby obtaining the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; Step S32: performing left section morphology analysis according to the left section hydrological equipment measurement information data, thereby obtaining left section morphology data; Step S33: performing right section morphology analysis according to the right section hydrological equipment measurement information data, thereby obtaining right section morphology data; Step S34: performing cross-sectional morphology integration according to the left cross-sectional morphology data and the right cross-sectional morphology data, thereby obtaining cross-sectional morphology data; Step S35: constructing a hydrodynamic model according to the cross-sectional morphology data, thereby obtaining hydrodynamic model data.

7. The hydrological regime change analysis method for hydrological engineering according to claim 6, characterized in that: Step S32 is specifically as follows: Step S321: Perform hydrological period statistics based on the hydrological equipment measurement information data of the left section, thereby obtaining the equipment measurement information data of the left section during the dry season and the equipment measurement information data of the left section during the flood season; Step S322: extracting the features of the left cross-section stone bank according to the remote sensing data of the hydrological monitoring area, thereby obtaining the left end face stone bank data; Step S323: analyzing the water flow friction force of the equipment measured in the dry season of the left section according to the stone bank of the left section, thereby obtaining the water flow friction force data of the left section in the dry season; Step S324: simulating the water flow of the equipment measurement information data of the left section during the flood period according to the left end face stone bank, so as to obtain the water flow data of the left section during the flood period; Step S325: performing a masonry stone hardness analysis based on the left end face masonry stone bank data, thereby obtaining masonry stone hardness data; Step S326: performing concentrated flow analysis on the water flow data of the left section during the flood period according to the hardness data of the masonry stones, thereby obtaining concentrated flow data of the water flow of the left section during the flood period; Step S327: analyzing the water flow velocity according to the concentrated flow data of the left section during the flood season and the water flow friction data of the left section during the dry season, thereby obtaining the water flow velocity data of the left section; Step S328: performing sediment transport analysis on the left section of the stone bank according to the left section water flow velocity data, thereby obtaining the left section sediment transport data; Step S329: Perform a left section stone bank morphology analysis on the left section stone bank data according to the left section sediment transport data, thereby obtaining the left section morphology data.

8. The hydrological regime change analysis method for hydrological engineering according to claim 6, characterized in that: Step S33 is specifically as follows: Step S331: performing hydrological period statistics of the right section according to the hydrological equipment measurement information data of the right section, thereby obtaining the equipment measurement information data of the right section during the dry season and the equipment measurement information data of the right section during the flood season; Step S332: extracting the features of the right section waterweed floodplain according to the remote sensing data of the hydrological monitoring area, thereby obtaining the right section waterweed floodplain data; Step S333: analyzing the flow resistance of the equipment measurement information data of the right section during the dry season according to the water grass floodplain data of the right section, thereby obtaining the flow resistance data of the right section; Step S334: local waterlogging simulation is performed on the waterweed floodplain data of the right section according to the water resistance data of the right section, so as to obtain the local waterlogging data of the waterweed floodplain of the right section; Step S335: performing sediment settlement analysis on the equipment measurement information data of the right section during the flood period according to the water grass floodplain data of the right section, thereby obtaining sediment settlement data; Step S336: extracting the location feature of the right section water grass floodplain according to the right section water grass floodplain data, thereby obtaining the location data of the right section water grass floodplain; Step S337: performing riverbed uplift analysis on the waterweed floodplain position data of the right section according to the sediment settlement data, thereby obtaining riverbed uplift data; Step S338: Integrate the cross-sectional morphology based on the riverbed uplift data and the local waterlogging data of the right cross-sectional waterweed, so as to obtain the right cross-sectional morphology data.

9. A hydrological situation change analysis system for hydrological engineering, characterized in that: Used to execute the hydrological regime change analysis method for hydrological engineering as claimed in claim 1, the hydrological regime change analysis system for hydrological engineering comprises: River morphology analysis module: used to obtain remote sensing data of the hydrological monitoring area, and analyze the river morphology changes based on the remote sensing data of the hydrological monitoring area, so as to obtain river morphology change data; Water flow analysis module: used to obtain the measurement information data of hydrological equipment, and extract the water body section characteristics and water flow velocity characteristics according to the measurement information data of hydrological equipment, so as to obtain the water body section data and water flow velocity data; perform water flow analysis according to the water body section data and water flow velocity data, so as to obtain the water flow data; Section morphology analysis module: used to classify section orientation according to the hydrological equipment measurement information data, so as to obtain the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data; to perform section morphology analysis according to the left section hydrological equipment measurement information data and the right section hydrological equipment measurement information data, so as to obtain section morphology data; to construct a hydrodynamic model according to the section morphology data, so as to obtain hydrodynamic model data; Flow velocity relationship line correction module: used to calculate the flow velocity relationship line according to the water body section data and the water flow data, so as to obtain the flow velocity relationship line data; dynamically correct the flow velocity relationship line data according to the river channel morphology change data and the section morphology data, so as to obtain the dynamic correction data of the flow velocity relationship line; Hydrological situation prediction module: used to predict the hydrological situation based on the hydrodynamic model data and the dynamic correction data of the velocity relationship line, so as to obtain the hydrological situation prediction data and upload it to the hydrological engineering management platform to perform the hydrological situation prediction task.

Images