A dynamic hydrological coupling data analysis method and system for complex watersheds

Abstract

The present invention relates to the technical field of hydrological data analysis, and in particular to a method and system for dynamic hydrological coupling data analysis of a complex watershed. The method comprises the following steps: obtaining historical meteorological data, historical hydrological data and historical remote sensing data and performing hydrological cycle simulation analysis to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model; performing watershed gridding processing on the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model to generate a hydrological cycle grid model; obtaining measured meteorological data and measured hydrological data and performing time-space simulation division and hydrological time-space correlation analysis to obtain the time-space correlation correlation relationship between hydrological changes in each watershed sub-division; performing watershed time-space coupling early warning processing on the hydrological cycle grid model to generate a hydrological change time-space coupling early warning response result corresponding to the complex watershed. The present invention can accurately analyze and predict hydrological changes and their mutual coupling relationships in complex watersheds.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrological data analysis, and in particular to a method and system for analyzing dynamic hydrological coupling data of a complex watershed. Background Art

[0002] Complex river basins usually have diverse geographical environments, climate characteristics and hydrological conditions, and changes in hydrological processes are affected by a combination of multiple factors. Therefore, how to accurately and in real time analyze the hydrological dynamics in complex river basins has become a key issue in water resources management and disaster prevention and control. At the same time, by integrating multi-source data (such as remote sensing data, meteorological data, field hydrological observation data, etc.) and introducing advanced spatiotemporal data mining technology, the dynamic coupling relationship between hydrological elements can be accurately captured. In this way, through modeling and prediction methods based on machine learning and deep learning, it is possible to analyze hydrological changes in complex river basins in real time and accurately, and optimize water resources scheduling and disaster prediction. However, traditional hydrological analysis methods mostly rely on physical models or statistical models, which are mainly used to simulate the relationship between hydrological elements such as precipitation, runoff, evaporation and factors such as basin topography and land use. Common hydrological models such as the hydrological cycle model and precipitation-runoff model use certain mathematical formulas and experimental data to infer the basin's hydrological process. Although these methods can simulate the basin's hydrological behavior to a certain extent, the existing single model often cannot meet the needs of multi-source data processing and dynamic changes, and thus cannot fully consider the dynamic coupling relationship between various types of data, making it difficult to provide timely warnings before disasters occur. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a dynamic hydrological coupling data analysis method and system for a complex watershed to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a dynamic hydrological coupling data analysis method for a complex watershed includes the following steps:

[0005] Step S1: acquiring historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and performing hydrological cycle simulation analysis on the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed;

[0006] Step S2: Gridding the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed to generate a hydrological cycle gridding model corresponding to each watershed sub-division;

[0007] Step S3: obtaining measured meteorological data and measured hydrological data corresponding to the complex watershed, and performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; performing hydrological spatiotemporal correlation analysis on the corresponding hydrological cycle grid model based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, and obtaining the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division;

[0008] Step S4: Based on the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, the hydrological cycle grid model corresponding to each basin sub-division is processed for spatiotemporal coupling early warning of the basin, so as to generate a spatiotemporal coupling early warning response result of hydrological changes corresponding to the complex basin.

[0009] Further, step S1 includes the following steps:

[0010] Step S11: obtaining historical meteorological data corresponding to the complex watershed, including precipitation, temperature, humidity and wind speed;

[0011] Step S12: Obtaining historical hydrological data corresponding to the complex watershed, including flow, runoff depth, and groundwater level;

[0012] Step S13: Obtain historical remote sensing data corresponding to the complex watershed, including surface humidity and vegetation coverage obtained by satellites or drones;

[0013] Step S14: obtaining land use type, topography and soil geomorphology data corresponding to the complex watershed, and performing three-dimensional spatial modeling of the complex watershed based on the land use type, topography and soil geomorphology data corresponding to the complex watershed, so as to generate a three-dimensional spatial model of the complex watershed terrain;

[0014] Step S15: Perform hydrological cycle simulation analysis on the three-dimensional spatial model of complex basin terrain based on historical meteorological data, historical hydrological data and historical remote sensing data to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0015] Further, step S15 includes the following steps:

[0016] Step S151: spatially extend and calibrate the historical meteorological data according to the geographical location information of the meteorological stations corresponding to the complex watershed and in combination with the Kriging interpolation method, so as to spatially extend the precipitation, temperature, humidity and wind speed recorded by each meteorological station to cover the entire complex watershed, thereby obtaining the historical meteorological spatial extension data;

[0017] Step S152: Obtain the river direction and watershed watershed corresponding to the complex watershed through the three-dimensional spatial model of the complex watershed terrain, and use linear interpolation to perform time series alignment and registration of the flow, runoff depth and groundwater level in the historical hydrological data based on the river direction and watershed watershed watershed to obtain historical hydrological time series registration data;

[0018] Step S153: Obtain the shooting time and spatial resolution corresponding to the satellite or the UAV, and perform spatiotemporal calibration processing on the surface humidity and vegetation coverage in the historical remote sensing data using bilinear interpolation and resampling technology based on the shooting time and spatial resolution to obtain historical remote sensing spatiotemporal calibration data;

[0019] Step S154: performing frequency domain component conversion on the corresponding precipitation, temperature, humidity and wind speed in the historical meteorological spatial extension data to obtain historical meteorological change data corresponding to different frequency components, including precipitation, temperature, humidity and wind speed changes corresponding to high-frequency and low-frequency components; performing fluctuation feature analysis on the historical hydrological time series registration data based on the historical meteorological change data corresponding to different frequency components to obtain fluctuation features between meteorological changes and hydrology corresponding to each frequency component;

[0020] Step S155: Based on the corresponding surface humidity and vegetation coverage in the historical remote sensing spatiotemporal calibration data, the historical hydrological time series registration data is analyzed for potential impact characteristics, and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are obtained; the fluctuation characteristics between the corresponding meteorological changes and hydrology under each frequency component and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are integrated to obtain a complex basin meteorological-remote sensing hydrological feature set;

[0021] Step S156: Based on the complex basin meteorological-remote sensing hydrological feature set, a hydrological cycle simulation analysis is performed on the three-dimensional spatial model of the complex basin terrain to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0022] Further, step S156 includes the following steps:

[0023] The three-dimensional spatial model of complex basin terrain is imported into the terrain analysis software based on finite difference, so as to use the terrain analysis software to simulate the distribution of solar radiation in the complex basin and combine it with the corresponding temperature in the historical meteorological data to calculate the heat balance corresponding to different slope aspects and slope areas, and obtain the balance influence parameters of terrain on heat redistribution;

[0024] By combining the principles of hydrogeomorphology and obtaining runoff depth and groundwater level changes from historical hydrological data, the corresponding gully density and water system branching ratio in complex watersheds are analyzed;

[0025] Obtain the soil texture and permeability characteristics corresponding to the complex watershed, and calculate the soil permeability distribution of the three-dimensional spatial model of the complex watershed terrain based on the soil texture and permeability characteristics corresponding to the complex watershed, so as to obtain the spatial distribution of the soil permeability coefficient corresponding to the complex watershed;

[0026] The topographic and geomorphic parameters of the balance of topography on heat redistribution, the gully density corresponding to the complex watershed, the water system branching ratio and the spatial distribution of soil permeability coefficient are integrated to obtain the topographic and geomorphic parameter set of the complex watershed.

[0027] Based on the complex basin meteorological-remote sensing hydrological feature set and the complex basin topographic and geomorphological parameter set, the hydrological cycle simulation analysis of the complex basin terrain three-dimensional spatial model is carried out to generate the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0028] Furthermore, the hydrological cycle simulation analysis of the three-dimensional spatial model of complex basin terrain based on the complex basin meteorological-remote sensing hydrological feature set and the complex basin terrain and geomorphic parameter set includes the following steps:

[0029] Obtain the time period through historical meteorological data The corresponding precipitation , and based on the period The corresponding precipitation The vegetation canopy interception model is constructed for the complex watershed meteorological-remote sensing hydrological feature set to generate the vegetation canopy interception model corresponding to the complex watershed ,in Indicates during the period The corresponding vegetation canopy interception, represents the potential influence coefficient between surface moisture and hydrology, represents the potential influence coefficient between vegetation coverage and hydrology, Indicates the index corresponding to the historical meteorological data, where 1 represents precipitation, 2 represents temperature, 3 represents humidity, and 4 represents wind speed. For the high frequency components The fluctuation characteristics between historical meteorological data and hydrology, For the low frequency component Fluctuation characteristics between historical meteorological data and hydrology;

[0030] Based on the period The corresponding precipitation The precipitation input of the vegetation canopy interception model corresponding to the complex watershed is calculated to obtain the actual precipitation input corresponding to the complex watershed. ;

[0031] Based on the corresponding terrain balance influence parameters on heat redistribution in the complex basin terrain parameter set, the potential evaporation calculation formula is used to calculate the basin evaporation of the complex basin terrain three-dimensional spatial model to obtain the corresponding potential evaporation of the complex basin. ;

[0032] Based on the corresponding gully density, water system branching ratio and soil permeability coefficient spatial distribution in the complex basin terrain parameter set, the soil permeability calculation is performed on the corresponding soil terrain in the three-dimensional spatial model of the complex basin terrain to obtain the corresponding soil permeability of the complex basin. ,in Indicates during the period The corresponding soil permeability coefficient is Indicates during the period The corresponding soil moisture content is Indicates during the period The corresponding soil topography water potential, represents the gully density corresponding to the complex watershed, Indicates the branching ratio of the water system corresponding to the complex watershed;

[0033] The surface runoff output corresponding to the complex basin is calculated based on the actual precipitation input, potential evaporation and soil infiltration corresponding to the complex basin and combined with the water balance principle to obtain the surface runoff output corresponding to the complex basin. ;

[0034] Based on the actual precipitation input, potential evaporation, soil infiltration and surface runoff output corresponding to the complex watershed, a hydrological cycle simulation analysis is carried out on the three-dimensional spatial model of the complex watershed terrain to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed.

[0035] Furthermore, the potential evaporation calculation formula is specifically as follows:

[0036] ;

[0037] ;

[0038] ;

[0039] ;

[0040] In the formula, is the potential evaporation corresponding to the complex basin, is the slope of the saturated water vapor pressure curve, For the period The corresponding solar simulated net radiation is For the period The corresponding soil heat flux is is the parameter affecting the balance of topography on heat redistribution, For the period The corresponding soil temperature is For the period The corresponding wind speed is For the period The corresponding saturated water vapor pressure is For the period The actual water vapor pressure corresponding to is an exponential function, For the period The corresponding relative humidity.

[0041] Further, step S2 includes the following steps:

[0042] Step S21: Obtain high-resolution terrain data, land use type maps, and river system distribution data corresponding to complex watersheds;

[0043] Step S22: performing type area terrain fluctuation analysis on the high-resolution terrain data corresponding to the complex watershed based on the land use type map corresponding to the complex watershed, and obtaining the terrain fluctuation change rate corresponding to different land use type areas in the complex watershed;

[0044] Step S23: Based on the land use type map corresponding to the complex watershed, the river system distribution data corresponding to the complex watershed is evaluated and analyzed for the water system confluence density, so as to obtain the river system confluence density corresponding to the different land use type areas in the complex watershed;

[0045] Step S24: basin grid division planning is performed according to the terrain undulation change rate and river system confluence density corresponding to different land use type areas in the complex basin. If the terrain undulation change rate and the river system confluence density are both greater than or equal to the preset threshold, the basin grid division standard of the corresponding land use type area is determined to be 0.5x0.5 square kilometers; if the terrain undulation change rate and the river system confluence density are both less than the preset threshold, the basin grid division standard of the corresponding land use type area is determined to be 2x2 square kilometers, otherwise it is determined to be 1x1 square kilometers, so as to obtain the complex basin adaptive grid division standard;

[0046] Step S25: Based on the complex watershed adaptive grid division standard, the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed is gridded to generate a hydrological cycle grid model corresponding to each watershed sub-division.

[0047] Further, step S3 includes the following steps:

[0048] Step S31: Acquire measured meteorological data and measured hydrological data corresponding to the complex watershed;

[0049] Step S32: performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step;

[0050] Step S33: performing Z-score standardization on different vector elements in the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, to obtain the hydrological standardized characteristic vector corresponding to each watershed sub-division at each simulation time step;

[0051] Step S34: Perform fluctuation mode statistics calculation on the hydrological standardized characteristic vectors corresponding to each basin sub-division at each simulation time step, and obtain the fluctuation mode set of the hydrological characteristic vectors corresponding to each basin sub-division at different time scales, including the instantaneous frequency and fluctuation amplitude corresponding to each hydrological characteristic vector; perform similarity matching calculation on the fluctuation mode set of the hydrological characteristic vectors corresponding to each basin sub-division at different time scales using a similarity measurement algorithm based on dynamic time warping, so as to flexibly match the fluctuation mode sequence of each basin sub-division on the time axis, calculate the similarity between each basin sub-division, and obtain the similarity of hydrological changes between each basin sub-division;

[0052] Step S35: each basin sub-division is regarded as a graph node, and the similarity of hydrological changes between each basin sub-division is used as the weight of the edge to construct a complex basin hydrological change conduction path diagram; based on the complex basin hydrological change conduction path diagram, a hydrological spatiotemporal correlation analysis is performed on the hydrological cycle grid model corresponding to each basin sub-division using a causal inference-based association analysis, so as to determine the causal sequence of hydrological changes between each basin sub-division by considering the influence of the terrain, soil and vegetation factors corresponding to each basin sub-division on hydrological conduction, and obtain the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, including the corresponding spatiotemporal correlation relationship between the increase in precipitation and runoff in the upstream sub-division and the increase in water level and flow in the downstream sub-division.

[0053] Further, step S4 includes the following steps:

[0054] Step S41: constructing a hydrological diffusion evolution situation change model corresponding to each basin sub-division according to the spatiotemporal correlation relationship of hydrological changes between each basin sub-division;

[0055] Step S42: Based on the hydrological diffusion evolution trend change model corresponding to each river basin sub-division, the hydrological cycle grid model corresponding to each river basin sub-division is processed for river basin time-space coupling early warning, so as to set dynamic early warning thresholds considering the topography, land use changes and meteorological changes corresponding to each river basin sub-division of the complex river basin, and compare and judge between the hydrological diffusion evolution changes of each river basin sub-division and the dynamic early warning threshold, so as to generate the hydrological change time-space coupling early warning response result corresponding to the complex river basin.

[0056] Furthermore, the present invention also provides a complex watershed dynamic hydrological coupling data analysis system, which is used to execute the complex watershed dynamic hydrological coupling data analysis method as described above. The complex watershed dynamic hydrological coupling data analysis system includes:

[0057] The complex watershed hydrological cycle simulation module is used to obtain the historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and to simulate and analyze the hydrological cycle of the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed;

[0058] The watershed grid processing module is used to perform watershed grid processing on the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed, so as to generate the hydrological cycle grid model corresponding to each watershed sub-division;

[0059] The complex watershed hydrological spatiotemporal association module is used to obtain the measured meteorological data and measured hydrological data corresponding to the complex watershed, and perform spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, the corresponding hydrological cycle grid model is subjected to hydrological spatiotemporal association analysis, so as to obtain the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division;

[0060] The watershed spatiotemporal coupling warning module is used to perform watershed spatiotemporal coupling warning processing on the hydrological cycle grid model corresponding to each watershed sub-division based on the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division, so as to generate spatiotemporal coupling warning response results of hydrological changes corresponding to complex watersheds.

[0061] Beneficial effects of the present invention:

[0062] 1. The dynamic hydrological coupling data analysis method for complex river basins proposed in the present invention has the beneficial effect of collecting historical meteorological data, historical hydrological data and historical remote sensing data of complex river basins, so as to fully understand the hydrological conditions at different time and space scales in the river basin. These data sources provide information about precipitation, temperature, humidity, wind speed, surface evaporation, soil moisture, groundwater level and other information. These factors are key variables affecting the hydrological process. Based on these data, the hydrological cycle simulation analysis is carried out using a hydrological model, which can accurately depict the interaction between hydrological processes such as precipitation, evaporation, infiltration and runoff in complex river basins. Through these simulations, a reasonable hydrological cycle simulation model can be constructed, which not only helps to reveal the mechanism of water cycle in the river basin, but also provides a scientific basis for subsequent hydrological change analysis, river basin water resources management and disaster warning. Through this simulation model, the changing trend of hydrological processes under different meteorological conditions and human activities can be further derived, thereby providing important decision-making support for water resources scheduling, ecological protection and disaster prevention and control in the river basin. Secondly, by gridding the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to a complex watershed, the complex watershed can be divided into multiple sub-divisions, and a hydrological cycle grid model can be established for each sub-division, which can efficiently reflect the spatiotemporal distribution characteristics of the hydrological process in space. Gridding can localize the analysis of the hydrological change process within the watershed, avoid over-simplification in large-scale simulations, and make the hydrological characteristics and changes of each sub-division more accurate. Such zoning and gridding models not only improve the resolution of the model, but also can perform personalized simulations according to the geographical, climatic, soil and other characteristics of different regions, thereby effectively capturing the spatial heterogeneity of the hydrological process. The gridded model can reflect changes in precipitation, evaporation, infiltration, etc. in local areas, and supports efficient calculation and analysis. It is suitable for hydrological simulation and disaster warning in large-scale watersheds, and provides a powerful tool for spatiotemporal dynamic analysis of watershed hydrological models.Then, by obtaining the measured meteorological data and hydrological data corresponding to the complex basin and dividing these data into time and space simulation, it is possible to achieve a detailed analysis of the hydrological changes of each basin sub-division at different time steps. The measured data provides more accurate hydrological change information than the simulated data. Combined with the time and space simulation division, it can reveal the dynamic characteristics of the basin hydrological changes, such as seasonality and periodic fluctuations. In this process, by extracting the characteristic vector of hydrological changes, it can provide the necessary input for the subsequent time and space correlation analysis to ensure that the time and space correlation of the hydrological model is truly reflected. The time and space correlation analysis helps to discover the mutual influence and propagation laws of hydrological changes between different regions within the basin, such as how precipitation changes in a certain area affect runoff changes in neighboring areas. It can meet the needs of multi-source data processing and dynamic changes, thereby revealing the dynamic coupling correlation and timing laws between various types of basin hydrological data. Through this analysis, the key areas and sensitive periods of hydrological changes in the basin can be identified, thereby providing accurate information support for subsequent water resources management and flood warning. Finally, by conducting spatiotemporal coupling early warning processing on the hydrological cycle grid model corresponding to each sub-division of the basin based on the spatiotemporal correlation relationship of hydrological changes between each sub-division of the basin, coupling analysis can be performed on the basis of spatiotemporal correlation, so as to more accurately predict the hydrological response between sub-divisions within the basin and identify potential hydrological crises, such as the impact of upstream precipitation on downstream runoff, or how the water level change in a certain division is transmitted to adjacent areas. The coupled early warning system can issue hydrological change early warning information in advance based on the combination of historical data and real-time data to reduce the impact of natural disasters. In this way, through the generated spatiotemporal coupling early warning response results of hydrological changes, relevant departments can take timely measures, such as adjusting reservoir water storage, implementing flood control projects, and initiating emergency responses, so as to be able to issue early warnings before hydrological disasters occur, which is conducive to the sustainable development and early warning response work of complex basins.

[0063] 2. The dynamic hydrological coupling data analysis system for complex river basins proposed in the present invention is generally composed of a complex river basin hydrological cycle simulation module, a river basin grid processing module, a complex river basin hydrological spatiotemporal association module, and a river basin spatiotemporal coupling early warning module. It can implement the dynamic hydrological coupling data analysis method for any complex river basin described in the present invention, and is used to combine the operations between computer programs running on each module to implement the dynamic hydrological coupling data analysis method for complex river basins. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient dynamic hydrological coupling data analysis process for complex river basins, thereby simplifying the operating procedures of the dynamic hydrological coupling data analysis system for complex river basins. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] 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:

[0065] Figure 1 It is a schematic diagram of the steps of the dynamic hydrological coupling data analysis method for complex watersheds of the present invention;

[0066] Figure 2 for Figure 1 Detailed step flow chart of step S1 in FIG. DETAILED DESCRIPTION

[0067] The technical method of the present invention is described clearly and completely below 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.

[0068] To achieve this, please refer to Figure 1 to Figure 2 The present invention provides a method for analyzing dynamic hydrological coupling data of a complex watershed, the method comprising the following steps:

[0069] Step S1: acquiring historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and performing hydrological cycle simulation analysis on the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed;

[0070] Step S2: Gridding the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed to generate a hydrological cycle gridding model corresponding to each watershed sub-division;

[0071] Step S3: obtaining measured meteorological data and measured hydrological data corresponding to the complex watershed, and performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; performing hydrological spatiotemporal correlation analysis on the corresponding hydrological cycle grid model based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, and obtaining the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division;

[0072] Step S4: Based on the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, the hydrological cycle grid model corresponding to each basin sub-division is processed for spatiotemporal coupling early warning of the basin, so as to generate a spatiotemporal coupling early warning response result of hydrological changes corresponding to the complex basin.

[0073] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a schematic diagram of the steps of the dynamic hydrological coupling data analysis method for a complex watershed according to the present invention. In this example, the dynamic hydrological coupling data analysis method for a complex watershed includes the following steps:

[0074] Step S1: acquiring historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and performing hydrological cycle simulation analysis on the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed;

[0075] In an embodiment of the present invention, historical meteorological data, historical hydrological data and historical remote sensing data of a complex watershed are obtained through multiple data sources. Meteorological data include but are not limited to temperature, precipitation, wind speed, air pressure, humidity and other information, which are usually extracted from meteorological stations, satellite data or remote sensing images; hydrological data covers indicators such as flow rate, river water level, precipitation runoff and other indicators of the watershed, which can be obtained through hydrological monitoring stations, flow measuring instruments and other equipment; remote sensing data are obtained through satellite remote sensing technology, covering land use, vegetation cover, soil moisture and other information. Based on these historical data, using hydrological Circulation models (such as precipitation-evaporation-infiltration-runoff models) are used to simulate and analyze complex watersheds. In this process, physical models (such as the SWAT model or HEC-HMS model in the hydrological model) or data-driven methods (such as machine learning models) are used to model the hydrological processes in the watershed, thereby generating a hydrological cycle model between precipitation, evaporation, infiltration and runoff. This model is based on many years of historical data and comprehensively considers factors such as climate change, topography, soil, and vegetation, so that it can accurately simulate the hydrological processes of the watershed and ultimately generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed.

[0076] Step S2: Gridding the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed to generate a hydrological cycle gridding model corresponding to each watershed sub-division;

[0077] In an embodiment of the present invention, a complex watershed is divided into a plurality of smaller sub-divisions by spatially decomposing a previously generated precipitation-evaporation-infiltration-runoff hydrological cycle model. In this process, a geographic information system (GIS) tool is used for spatial data processing, and the watershed is divided according to different geographical units (such as watershed sub-divisions, administrative divisions, etc.). The hydrological cycle model of each sub-division is gridded. In specific implementation, a gridding algorithm (such as rasterization, vectorization conversion, etc.) is used to convert each watershed sub-division into a raster form to form a hydrological grid model. Each grid corresponds to a set of parameters of the hydrological cycle model, such as precipitation, evaporation, infiltration, etc. The spatial distribution of hydrological data is achieved through spatial interpolation technology (such as Kriging interpolation or nearest neighbor interpolation). In this process, the terrain information, land use type, and surface conditions in the remote sensing data are used to further optimize the accuracy and applicability of the gridded model, and finally a hydrological cycle gridded model corresponding to each watershed sub-division is generated.

[0078] Step S3: obtaining measured meteorological data and measured hydrological data corresponding to the complex watershed, and performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; performing hydrological spatiotemporal correlation analysis on the corresponding hydrological cycle grid model based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, and obtaining the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division;

[0079] In an embodiment of the present invention, by obtaining the measured meteorological data and hydrological data of the basin, performing spatiotemporal simulation division, and extracting the hydrological change characteristic vector, firstly, the measured meteorological data and hydrological data are obtained, and the spatiotemporal consistency of the data is ensured, that is, the meteorological data and the hydrological data are ensured to be from the same time and space scales. Then, the meteorological and hydrological data of each time step are processed using a time series analysis method (such as sliding average, seasonal decomposition), divided into different time periods (such as years, seasons, months, days, etc.), and a hydrological change characteristic vector is constructed. For example, at each time step, the precipitation, evaporation, soil moisture and other indicators of each basin sub-division are extracted. The hydrological characteristic vector at that moment is composed. Then, the spatiotemporal analysis methods (such as dynamic time warping and correlation analysis) are used to conduct correlation analysis on the hydrological characteristics between different watershed sub-divisions, and to explore the spatiotemporal correlation between different sub-divisions. Specifically, the Pearson correlation coefficient between the hydrological characteristic vectors of different regions can be calculated or more complex machine learning methods (such as cluster analysis and principal component analysis) can be used to analyze whether the hydrological changes of each sub-division at different time steps have significant spatial correlation, thereby identifying potential spatiotemporal correlation patterns and finally obtaining the spatiotemporal correlation relationship between the hydrological changes of each watershed sub-division.

[0080] Step S4: Based on the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, the hydrological cycle grid model corresponding to each basin sub-division is processed for spatiotemporal coupling early warning of the basin, so as to generate a spatiotemporal coupling early warning response result of hydrological changes corresponding to the complex basin.

[0081] In an embodiment of the present invention, the spatiotemporal coupling early warning processing of the watershed is performed by using the spatiotemporal correlation results of the hydrological changes in the watershed sub-divisions obtained previously. First, the spatiotemporal correlation results are used to construct a coupling relationship model between watersheds. This process analyzes the spatiotemporal variation laws of different watershed sub-divisions to evaluate whether the hydrological changes therein have an impact on other areas. For example, multiple regression analysis, collaborative filtering or causal inference models are used to capture the hydrological mutual influence mechanism between different sub-divisions. On this basis, an early warning model of spatiotemporal coupling of watersheds is established, and abnormal changes in hydrological status are judged by setting thresholds. For example, when the precipitation in a certain sub-division increases significantly, it will affect the runoff in the downstream area. At this time, the hydrological change trend of the downstream area can be predicted according to the model, and an early warning can be issued in advance. The early warning model will consider the hydrological response time, change rate and other factors of each watershed sub-division, perform real-time monitoring and dynamic adjustment, and generate a spatiotemporal coupling early warning response result of hydrological changes in a complex watershed. This early warning response result can be provided to the watershed manager for decision support, such as early deployment of water conservancy projects, adjustment of reservoir storage, etc., and finally generate a spatiotemporal coupling early warning response result of hydrological changes corresponding to the complex watershed.

[0082] Further, as an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0083] Step S11: obtaining historical meteorological data corresponding to the complex watershed, including precipitation, temperature, humidity and wind speed;

[0084] In an embodiment of the present invention, by determining the geographical scope and study period of a complex watershed, historical meteorological data in the watershed are obtained using meteorological satellite data and ground-based meteorological station data. Meteorological data are usually obtained through the National Meteorological Administration, local meteorological stations, global meteorological data platforms or meteorological satellites. For precipitation, daily precipitation data within the watershed can be extracted from meteorological stations and satellite meteorological data (such as TRMM, GPM, etc.), or an inversion algorithm can be used to calculate precipitation within the watershed. Temperature, humidity and wind speed can be obtained through a network of ground-based meteorological stations, or reconstructed through satellite remote sensing data (such as MODIS or ERA5 climate data sets). In particular, the acquisition of humidity and wind speed requires data supplementation through reanalysis products of high-resolution meteorological models or regional climate models. All these data are extracted and integrated according to the watershed scope through a GIS system, and data quality control and missing value filling are performed to ensure the integrity and accuracy of the data, and ultimately historical meteorological data corresponding to the complex watershed are obtained.

[0085] Step S12: Obtaining historical hydrological data corresponding to the complex watershed, including flow, runoff depth, and groundwater level;

[0086] In an embodiment of the present invention, by obtaining hydrological observation data in the basin, mainly including parameters such as flow rate, runoff depth and groundwater level, the flow data is generally obtained through hydrological stations in the basin, and on-site observations are carried out using instruments such as water flow meters and flowmeters, while referring to historical flow data released by major hydrological monitoring websites and basin management departments; the runoff depth is usually obtained by inverting remote sensing image data or calculating through long-term monitoring data of groundwater level observation points; in terms of groundwater level monitoring, groundwater level measurement wells and hydrological and meteorological stations provide reliable data sources, all hydrological data need to be quality controlled and time-space matched by hydrological analysis software (such as HEC-HMS or SWAT model), different types of hydrological data are combined and input into the hydrological model to obtain more accurate basin hydrological characteristics, and finally obtain historical hydrological data corresponding to complex basins.

[0087] Step S13: Obtain historical remote sensing data corresponding to the complex watershed, including surface humidity and vegetation coverage obtained by satellites or drones;

[0088] In an embodiment of the present invention, the surface humidity and vegetation coverage in the watershed are obtained by using satellite remote sensing data. First, by using NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) or ESA's Sentinel-1, Sentinel-2 satellite images, the surface humidity is inverted and calculated using reflectivity, temperature and other information. By analyzing remote sensing images at different time points, the humidity changes in different areas of the watershed can be obtained. The vegetation coverage is estimated by NDVI (Normalized Difference Vegetation Index) images. The NDVI value reflects the growth of vegetation and is usually calculated through optical satellite images (such as MODIS or Landsat series). This data is helpful for further analysis of vegetation water utilization and land surface evaporation. All remote sensing data are preprocessed, corrected, fused, and merged in time and space through remote sensing data processing software (such as ENVI or QGIS), and finally the historical remote sensing data corresponding to the complex watershed is obtained.

[0089] Step S14: obtaining land use type, topography and soil geomorphology data corresponding to the complex watershed, and performing three-dimensional spatial modeling of the complex watershed based on the land use type, topography and soil geomorphology data corresponding to the complex watershed, so as to generate a three-dimensional spatial model of the complex watershed terrain;

[0090] In an embodiment of the present invention, by collecting land use type, terrain and soil geomorphology data in the basin, the land use type data can be obtained through local or national land resource management departments, or extracted using a global land cover classification data set (such as GLC2000 or MODIS land cover data), and the terrain data is usually obtained through a digital elevation model (DEM). Commonly used DEM data sources include SRTM, ASTER or LiDAR scanning data. Soil geomorphology data needs to refer to a soil survey report, or be obtained using a global soil data set (such as ISRIC's soil information database). Based on these data, professional GIS modeling tools (such as ArcGIS or QGIS) can be used for spatial analysis and processing to obtain a three-dimensional spatial model of a complex basin. The model takes into account the geographical landforms, soil types and land use distribution of the basin. The terrain data and soil types are converted into a spatial model with physical properties through three-dimensional modeling software (such as AutoCAD Civil 3D or SketchUp), and finally a three-dimensional spatial model of the complex basin terrain is generated by modeling.

[0091] Step S15: Perform hydrological cycle simulation analysis on the three-dimensional spatial model of complex basin terrain based on historical meteorological data, historical hydrological data and historical remote sensing data to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0092] In an embodiment of the present invention, by using the above-mentioned historical meteorological data, hydrological data, remote sensing data and terrain three-dimensional model, a hydrological cycle simulation is performed, so as to construct a precipitation-evaporation-infiltration-runoff (hydrological cycle) model based on the physical processes of precipitation, evaporation, infiltration and runoff by using hydrological simulation software, such as HEC-HMS, SWAT or MIKE SHE. In the model, precipitation is used as a meteorological input, and the runoff depth and the flow of surface water are affected by the distribution and intensity of precipitation in the basin. The evaporation and potential evaporation can be calculated based on the historical temperature, humidity and wind speed data, and the evaporation process is adjusted in combination with the surface humidity, vegetation coverage and soil properties. The infiltration process considers the influence of soil permeability and vegetation coverage on water infiltration. After all parameters are input into the hydrological model, the model performs spatiotemporal coupling calculation to generate dynamic simulation results of the hydrological cycle. These simulation results can reflect the hydrological process and water resource changes in the basin under different meteorological and hydrological conditions, and finally generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to a complex basin.

[0093] Further, step S15 includes the following steps:

[0094] Step S151: spatially extend and calibrate the historical meteorological data according to the geographical location information of the meteorological stations corresponding to the complex watershed and in combination with the Kriging interpolation method, so as to spatially extend the precipitation, temperature, humidity and wind speed recorded by each meteorological station to cover the entire complex watershed, thereby obtaining the historical meteorological spatial extension data;

[0095] In an embodiment of the present invention, the geographical location information of all meteorological stations in a complex river basin is collected, and spatial extension calibration is performed in combination with the historical meteorological data of these meteorological stations. Specifically, the historical data such as precipitation, temperature, humidity and wind speed of each meteorological station are associated with the precise geographical coordinates of the meteorological station using a geographic information system (GIS). Then, the meteorological data are spatially expanded using the Kriging interpolation method. Kriging interpolation is a statistical interpolation method based on spatial autocorrelation, which can predict meteorological data at unknown locations based on measurement data at known stations. Through this method, spatial speculation of meteorological data at any location within a complex river basin can be achieved, and historical meteorological spatial extension data covering the entire river basin can be obtained, ensuring that the meteorological data can accurately reflect the meteorological conditions of each region in the river basin, and finally obtaining historical meteorological spatial extension data.

[0096] Step S152: Obtain the river direction and watershed watershed corresponding to the complex watershed through the three-dimensional spatial model of the complex watershed terrain, and use linear interpolation to perform time series alignment and registration of the flow, runoff depth and groundwater level in the historical hydrological data based on the river direction and watershed watershed watershed to obtain historical hydrological time series registration data;

[0097] In an embodiment of the present invention, a three-dimensional spatial terrain model of a complex watershed (usually based on a digital elevation model DEM) is used to extract the river direction and watershed line of the watershed. The river grid and the main flow direction of the water flow in the watershed are identified through terrain analysis tools, and the position of the watershed line is determined. Based on the river direction and watershed in the watershed, a linear interpolation method is used to perform time series alignment and registration of historical hydrological data (such as flow, runoff depth, groundwater level, etc.). Linear interpolation adjusts the time step of the historical hydrological data by performing interpolation calculations between adjacent time series data points, so that the hydrological data of different time periods correspond to the river direction and the watershed position. This step ensures that the hydrological data is consistent with the hydrological conditions and spatiotemporal distribution of the watershed, thereby providing a reliable historical data basis for further analysis of hydrological changes, and ultimately obtaining historical hydrological time series registration data.

[0098] Step S153: Obtain the shooting time and spatial resolution corresponding to the satellite or the UAV, and perform spatiotemporal calibration processing on the surface humidity and vegetation coverage in the historical remote sensing data using bilinear interpolation and resampling technology based on the shooting time and spatial resolution to obtain historical remote sensing spatiotemporal calibration data;

[0099] In an embodiment of the present invention, remote sensing data taken by a satellite or an unmanned aerial vehicle is obtained, specifically including the shooting time and spatial resolution. According to the shooting time and spatial resolution of the remote sensing image, bilinear interpolation and resampling technology are used to perform spatiotemporal calibration on the surface moisture and vegetation coverage in the remote sensing data. Bilinear interpolation is a commonly used two-dimensional data interpolation method. The spatial resolution of the data is adjusted by calculating the weighted average of adjacent pixels. The resampling technology is used to change the spatial resolution of the remote sensing data so that it can match the required analysis scale. Through these two methods, the spatiotemporal information of historical remote sensing data can be adjusted to a unified standard, so that the surface moisture and vegetation coverage data can be analyzed at the same time and space scales, and finally the historical remote sensing spatiotemporal calibration data is obtained.

[0100] Step S154: performing frequency domain component conversion on the corresponding precipitation, temperature, humidity and wind speed in the historical meteorological spatial extension data to obtain historical meteorological change data corresponding to different frequency components, including precipitation, temperature, humidity and wind speed changes corresponding to high-frequency and low-frequency components; performing fluctuation feature analysis on the historical hydrological time series registration data based on the historical meteorological change data corresponding to different frequency components to obtain fluctuation features between meteorological changes and hydrology corresponding to each frequency component;

[0101] In an embodiment of the present invention, by performing frequency domain component conversion on the previously obtained historical meteorological spatial extension data, in order to analyze the changes in meteorological data under different frequency components, Fourier transform or wavelet transform is used to convert the time series data into the frequency domain. Fourier transform can convert meteorological data in the time domain (such as precipitation, temperature, humidity, wind speed) into components of different frequencies, wherein high-frequency components represent short-term fluctuations and low-frequency components represent long-term trends. By analyzing the fluctuations of historical meteorological data at different frequencies, the periodic characteristics and trend changes of meteorological changes can be revealed. Based on these frequency component data, the fluctuation characteristics of the historical hydrological time series registration data are further analyzed. By comparing the fluctuation characteristics of meteorological changes and hydrological changes at different frequencies, the relationship between meteorology and hydrology can be identified, such as the impact of precipitation changes on flow or groundwater level, and finally the fluctuation characteristics between meteorological changes and hydrology corresponding to each frequency component are obtained.

[0102] Step S155: Based on the corresponding surface humidity and vegetation coverage in the historical remote sensing spatiotemporal calibration data, the historical hydrological time series registration data is analyzed for potential impact characteristics, and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are obtained; the fluctuation characteristics between the corresponding meteorological changes and hydrology under each frequency component and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are integrated to obtain a complex basin meteorological-remote sensing hydrological feature set;

[0103] In an embodiment of the present invention, a potential impact feature analysis is performed based on the surface humidity and vegetation coverage in the previously obtained historical remote sensing spatiotemporal calibration data to reveal the relationship between these remote sensing variables and hydrological data. First, a statistical analysis method (such as correlation analysis, regression analysis, etc.) is used to quantify the potential impact between surface humidity, vegetation coverage and historical hydrological time series registration data (such as flow, runoff depth, groundwater level, etc.). Through these analyses, the impact of remote sensing indicators such as surface humidity and vegetation coverage on the hydrological cycle at different time scales and spatial scales can be identified. For example, surface humidity may affect the permeability characteristics of soil moisture, while vegetation coverage may affect evaporation and soil moisture retention capacity. The meteorological changes and hydrological fluctuation characteristics under each frequency component and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are integrated to form a complex basin meteorological-remote sensing hydrological feature set. This feature set provides multi-dimensional and multi-level input data for the subsequent establishment of a hydrological model, and finally a complex basin meteorological-remote sensing hydrological feature set is obtained.

[0104] Step S156: Based on the complex basin meteorological-remote sensing hydrological feature set, a hydrological cycle simulation analysis is performed on the three-dimensional spatial model of the complex basin terrain to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0105] In an embodiment of the present invention, a hydrological cycle simulation analysis is performed on a three-dimensional spatial terrain model of a complex watershed based on a previously obtained meteorological-remote sensing hydrological feature set of the complex watershed. First, meteorological data, remote sensing data and hydrological data are combined to perform hydrological cycle simulation using a physically based hydrological model (such as a SWAT model, a MIKE model, etc.). During the simulation process, input data including precipitation, evaporation, soil permeability characteristics, flow and groundwater level are used to determine the path and distribution of water flow according to the three-dimensional terrain model (DEM) of the watershed. The simulation will involve processes such as precipitation, evaporation, infiltration and runoff. The simulation results provide a set of dynamic, spatiotemporal simulation models for the hydrological cycle process of the watershed. Through this model, the hydrological response of the watershed under different meteorological and remote sensing conditions can be evaluated, the changing trend and distribution characteristics of water resources can be analyzed, and finally a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed can be simulated and generated.

[0106] Further, step S156 includes the following steps:

[0107] The three-dimensional spatial model of complex basin terrain is imported into the terrain analysis software based on finite difference, so as to use the terrain analysis software to simulate the distribution of solar radiation in the complex basin and combine it with the corresponding temperature in the historical meteorological data to calculate the heat balance corresponding to different slope aspects and slope areas, and obtain the balance influence parameters of terrain on heat redistribution;

[0108] In an embodiment of the present invention, when a three-dimensional terrain model of a complex watershed is imported into a terrain analysis software based on finite differences, a high-precision digital terrain model (DTM) of the watershed is first obtained, and a refined three-dimensional terrain model is generated using LiDAR technology or satellite remote sensing data. This model should be able to accurately express the terrain changes in the watershed, including ridges, valleys, slopes and other features. Then, using specialized terrain analysis software, such as ArcGIS or Surfer, these three-dimensional terrain data are imported into the system for processing. In this process, the system first grids the terrain data and calculates the slope and slope direction of each grid cell. Then, using the solar radiation model, by analyzing the sunlight exposure of terrain units with different slopes and aspects, combined with the temperature records in the historical meteorological data, the solar radiation of each area in the basin is simulated. In this step, it is necessary to introduce a radiation transfer model (such as the SHADOW model), combine the historical temperature data with the slope and aspect information of the terrain, and calculate the heat balance of each terrain unit. The calculation of the heat balance includes factors such as absorbed solar radiation, scattering, ground reflection and heat transfer. The generated heat balance parameters are used to reflect the influence of the terrain on the heat distribution, and finally the balance influence parameters of the terrain on the heat redistribution are obtained.

[0109] Preferably, the corresponding gully density and water system branching ratio in the complex watershed are analyzed by combining the hydrogeomorphology principle and obtaining the runoff depth and groundwater level change from the historical hydrological data;

[0110] In an embodiment of the present invention, based on the principle of hydrogeomorphology, the runoff depth of a complex watershed is analyzed using historical hydrological data. By collecting hydrological data such as precipitation, evaporation, and runoff from multiple monitoring points in the watershed and performing time series analysis, the hydrological change trend in the watershed under different seasons and climatic conditions is determined. Then, the gully density and water system branching ratio information of the watershed are combined to quantitatively analyze the hydrological and geomorphological characteristics. The gully density refers to the total length of the gullies per unit area, which reflects the soil erosion and distribution characteristics of surface water flow in the watershed. The water system branching ratio is a parameter for measuring the complexity of the branches of the river system in the watershed. Through the corresponding runoff depth and groundwater level changes in the historical hydrological data, the GIS (geographic information system) tool is used to perform spatial analysis of the hydrological characteristics in the watershed, and then the gully density and water system branching ratio of the watershed are calculated, and finally the corresponding gully density and water system branching ratio in the complex watershed are obtained.

[0111] Preferably, the soil texture and permeability characteristics corresponding to the complex watershed are obtained, and the soil permeability distribution of the three-dimensional spatial model of the complex watershed terrain is estimated according to the soil texture and permeability characteristics corresponding to the complex watershed, so as to obtain the spatial distribution of the soil permeability coefficient corresponding to the complex watershed;

[0112] In an embodiment of the present invention, when obtaining the soil texture and permeability characteristics of a complex watershed, soil survey and sampling are first required. Common sampling methods include ground sampling and drilling sampling. Soil samples from different sections of the watershed are subjected to laboratory analysis to determine the physical and chemical properties of the soil, such as particle size distribution, porosity, soil density, permeability coefficient, etc. Then, the soil permeability coefficient of different areas of the watershed is calculated by using a soil permeability model (such as the Richards equation) in combination with the soil texture characteristics of the watershed. The spatial distribution of the soil permeability coefficient can be spatially analyzed by an interpolation algorithm (such as the Kriging method) to obtain an accurate permeability coefficient distribution map. In specific operations, professional soil data analysis software (such as Hydrus) is used to model the soil permeability process, and the software is combined with meteorological data (such as precipitation and temperature) in the watershed for verification and calibration. By this method, the spatial distribution of the soil permeability coefficient in a complex watershed can be obtained, and finally the spatial distribution of the soil permeability coefficient corresponding to the complex watershed can be obtained.

[0113] Preferably, the topographic and geomorphic parameters of the balance influence parameters of the terrain on heat redistribution, the gully density corresponding to the complex watershed, the water system branching ratio and the spatial distribution of the soil permeability coefficient are integrated to obtain a set of topographic and geomorphic parameters of the complex watershed;

[0114] In an embodiment of the present invention, various parameters obtained from the previous analysis are effectively summarized and spatially compared. Specifically, the spatial distribution layers of terrain heat balance parameters, gully density, water system branch ratio and soil permeability coefficient are first superimposed in the GIS software, and spatial interpolation and registration are performed to ensure that each data set is correctly aligned in the same coordinate system. Then, through statistical analysis and data weighted fusion, the heat impact, gully characteristics, water system branches and soil permeability characteristics of different terrain units are comprehensively analyzed to obtain the comprehensive terrain and geomorphic parameters of each terrain unit. This parameter set can be further optimized through multivariate regression analysis or machine learning models to improve the accuracy and rationality of the integration results, and finally a complex basin terrain and geomorphic parameter set is obtained.

[0115] Preferably, a hydrological cycle simulation analysis is performed on the three-dimensional spatial model of complex basin terrain based on the complex basin meteorological-remote sensing hydrological feature set and the complex basin topographic and geomorphological parameter set to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0116] In an embodiment of the present invention, when simulating and analyzing the hydrological cycle of a complex watershed by using a meteorological-remote sensing hydrological feature set and a topographic and geomorphic parameter set based on a complex watershed, it is first necessary to sort out historical meteorological data (including precipitation, temperature, wind speed, etc.) and remote sensing data (such as NDVI, land use change, etc.) to form a meteorological-remote sensing hydrological feature set. Then, in combination with the topographic and geomorphic parameter set, the precipitation, evaporation, infiltration and runoff processes of the watershed are simulated through a hydrological model (such as a SWAT model or a MIKE model). In this process, the finite difference method is used to discretize the three-dimensional spatial model in the complex watershed. , calculate the hydrological cycle process within each grid unit. During the simulation process, it is necessary to consider various hydrological processes such as the spatial distribution of precipitation, evaporation loss, surface water infiltration, and groundwater flow, and combine the influence of factors such as soil permeability, vegetation coverage, and surface roughness on water flow to generate a complete precipitation-evaporation-infiltration-runoff hydrological cycle model. The results of the model can further analyze the spatial distribution of precipitation, evaporation loss, surface water infiltration, and groundwater flow in the basin, help predict the potential impact of future climate change on the hydrological cycle, and finally generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to a complex basin.

[0117] Furthermore, the hydrological cycle simulation analysis of the three-dimensional spatial model of complex basin terrain based on the complex basin meteorological-remote sensing hydrological feature set and the complex basin terrain and geomorphic parameter set includes the following steps:

[0118] Obtain the time period through historical meteorological data The corresponding precipitation , and based on the period The corresponding precipitation The vegetation canopy interception model is constructed for the complex watershed meteorological-remote sensing hydrological feature set to generate the vegetation canopy interception model corresponding to the complex watershed ,in Indicates during the period The corresponding vegetation canopy interception, represents the potential influence coefficient between surface moisture and hydrology, represents the potential influence coefficient between vegetation coverage and hydrology, Indicates the index corresponding to the historical meteorological data, where 1 represents precipitation, 2 represents temperature, 3 represents humidity, and 4 represents wind speed. For the high frequency components The fluctuation characteristics between historical meteorological data and hydrology, For the low frequency component Fluctuation characteristics between historical meteorological data and hydrology;

[0119] In the embodiment of the present invention, the time period is obtained by historical meteorological data. The corresponding precipitation , and based on this, a vegetation canopy interception model for complex watersheds was constructed The process first requires obtaining a historical meteorological data set for many years, covering parameters such as precipitation, temperature, humidity, and wind speed, and dividing these data into different time periods. After collecting the precipitation data in the basin, statistical methods are used to process it to ensure data quality, and the precipitation is adjusted using the known vegetation coverage and basin characteristics, and according to the given vegetation canopy interception formula: ,in, and They represent the potential influence coefficients between surface humidity and hydrology, and between vegetation coverage and hydrology, respectively. and Respectively represent the fluctuation characteristics between historical meteorological data such as precipitation, temperature, humidity and wind speed and hydrology. In this formula, and The signal analysis of high-frequency and low-frequency components can reveal the relationship between meteorological factors and hydrological processes. By Fourier transform or wavelet transform of meteorological data, the high-frequency and low-frequency fluctuation characteristics in each time period are obtained, so as to establish the dynamic coupling relationship between meteorological data and hydrological factors through analysis, and use this formula to calculate the dynamic coupling relationship between meteorological data and hydrological factors in each time period. The vegetation canopy interception amount within the basin is calculated, and finally a vegetation canopy interception model corresponding to the complex watershed is constructed.

[0120] Preferably, based on the time period The corresponding precipitation The precipitation input of the vegetation canopy interception model corresponding to the complex watershed is calculated to obtain the actual precipitation input corresponding to the complex watershed. ;

[0121] In the embodiment of the present invention, by The amount of precipitation in , calculate the actual precipitation input for a complex watershed, which first relies on the previously calculated vegetation canopy interception , and the precipitation input is calculated using the following formula: In actual operation, we first need to obtain accurate precipitation data and ensure that the data source is reliable, such as precipitation records from weather stations or satellite remote sensing data. Then, we need to analyze factors such as the topography and vegetation coverage of the basin to determine the interception amount of vegetation canopy. This value is usually obtained through remote sensing technology or ground observation data. The actual precipitation input is obtained by subtracting the vegetation canopy interception. , which characterizes the amount of water that actually enters the soil or runoff system, and ultimately the actual precipitation input corresponding to the complex watershed is obtained.

[0122] Preferably, the basin evaporation is calculated based on the balance influence parameters of the terrain on heat redistribution corresponding to the complex basin terrain parameter set using the potential evaporation calculation formula for the complex basin terrain three-dimensional spatial model to obtain the potential evaporation corresponding to the complex basin. ;

[0123] In the embodiment of the present invention, a suitable potential evaporation calculation formula is formed by combining the slope of the saturated water vapor pressure curve, the simulated solar net radiation, the soil heat flux, the balance influence parameter of the terrain on the heat redistribution, the soil temperature, the wind speed, the saturated water vapor pressure, the actual water vapor pressure, the relative humidity and related parameters to calculate the watershed evaporation of the complex basin terrain three-dimensional spatial model, so as to quantitatively estimate the potential evaporation in the period, and finally obtain the potential evaporation corresponding to the complex basin .

[0124] Preferably, the soil infiltration calculation is performed on the corresponding soil terrain in the three-dimensional spatial model of the complex basin terrain based on the corresponding gully density, water system branching ratio and soil permeability coefficient spatial distribution in the complex basin terrain parameter set to obtain the corresponding soil permeability of the complex basin. ,in Indicates during the period The corresponding soil permeability coefficient is Indicates during the period The corresponding soil moisture content is Indicates during the period The corresponding soil topography water potential, represents the gully density corresponding to the complex watershed, Indicates the branching ratio of the water system corresponding to the complex watershed;

[0125] In the embodiment of the present invention, the soil permeability of the basin is simulated by utilizing the topographic parameter set of the complex basin, including spatial distribution information such as gully density, water system branching ratio, and soil permeability coefficient. Specifically, the calculation of soil permeability depends on the following formula: ,in, Indicates during the period The corresponding soil permeability coefficient is Indicates during the period The corresponding soil moisture content is Indicates during the period The corresponding soil topography water potential, represents the gully density corresponding to the complex watershed, Indicates the branching ratio of the water system corresponding to the complex watershed. Based on the terrain information, the soil moisture content change rate of the watershed is first calculated. and the rate of change of soil water potential Then, combined with the gully density and water system branching ratio of the basin, the soil infiltration is finally calculated. This step usually relies on numerical simulation methods and soil physical models. The soil moisture is simulated through the soil moisture dynamic model (such as the Richards equation) to finally obtain the soil infiltration corresponding to the complex watershed.

[0126] Preferably, the surface runoff output corresponding to the complex basin is calculated based on the actual precipitation input, potential evaporation and soil infiltration corresponding to the complex basin and combined with the water balance principle to obtain the surface runoff output corresponding to the complex basin. ;

[0127] In the embodiment of the present invention, according to the actual precipitation input In(t) and potential evaporation of the complex basin, and soil infiltration , combining the water balance principle to calculate the surface runoff output The water balance formula is: Specifically, firstly, according to the actual precipitation input In(t) and potential evaporation calculated above, and soil infiltration , these hydrological elements are substituted into the formula for calculation to obtain the surface runoff output. In this process, accurate hydrological and meteorological data are required to ensure the accuracy of the calculation results. At the same time, it is also necessary to make adjustments based on the specific characteristics of the basin, such as land use type, slope, etc., in order to more accurately reflect the runoff characteristics of different areas in the basin, and finally obtain the surface runoff output corresponding to the complex basin.

[0128] Preferably, a hydrological cycle simulation analysis is performed on the three-dimensional spatial model of the complex basin terrain based on the actual precipitation input, potential evaporation, soil infiltration and surface runoff output corresponding to the complex basin, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

[0129] In the embodiment of the present invention, based on the actual precipitation input obtained in the previous step Potential evaporation , soil infiltration and surface runoff output , use the hydrological cycle model to simulate and analyze the hydrological process of a complex watershed. The goal of this step is to generate a complete hydrological cycle model of precipitation-evaporation-infiltration-runoff. Numerical simulation methods (such as hydrological models SWAT or MIKE) are usually used for simulation. By establishing a hydrological model of the watershed, the hydrological response of the watershed under different meteorological conditions and land use patterns can be predicted, and hydrological processes on different time scales can be simulated, such as flow changes, soil moisture dynamics, runoff fluctuations, etc. Finally, the coupled simulation generates a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed.

[0130] Furthermore, the potential evaporation calculation formula is specifically as follows:

[0131] ;

[0132] ;

[0133] ;

[0134] ;

[0135] In the formula, is the potential evaporation corresponding to the complex basin, is the slope of the saturated water vapor pressure curve, For the period The corresponding solar simulated net radiation is For the period The corresponding soil heat flux is is the parameter affecting the balance of topography on heat redistribution, For the period The corresponding soil temperature is For the period The corresponding wind speed is For the period The corresponding saturated water vapor pressure is For the period The actual water vapor pressure corresponding to is an exponential function, For the period The corresponding relative humidity.

[0136] The present invention obtains a potential evaporation calculation formula by using a specific mathematical model and verifying it, which is used to calculate the evaporation of a complex basin terrain three-dimensional spatial model. The formula fully considers the potential evaporation corresponding to the complex basin. , the slope of the saturated water vapor pressure curve , time period The corresponding solar simulated net radiation , in the period The corresponding soil heat flux , the balance parameters of topography on heat redistribution , in the period The corresponding soil temperature , in the period Corresponding wind speed , in the period The corresponding saturated water vapor pressure , in the period The actual water vapor pressure , exponential function , in the period The relative humidity , where by combining in the time period The corresponding soil temperature , exponential function and related parameters constitute a The corresponding saturated water vapor pressure Functional relationship , and by combining the The corresponding saturated water vapor pressure And during the period The relative humidity It constitutes a period of time The actual water vapor pressure Functional relationship , and also by combining The corresponding saturated water vapor pressure And during the period The corresponding soil temperature It constitutes a saturated water vapor pressure curve slope Functional relationship , according to the potential evaporation corresponding to the complex basin The correlation between the above parameters constitutes a functional relationship This formula can realize the basin evaporation calculation process for the three-dimensional spatial model of complex basin terrain. At the same time, the potential evaporation calculation formula is used to describe the measurement of the maximum evaporation occurring on the water surface under specific meteorological conditions. It is usually estimated based on meteorological data (such as temperature, humidity, wind speed, radiation, etc.). Net radiation is the radiation energy received by the surface and is one of the driving factors of evaporation. The stronger the solar radiation, the greater the evaporation potential of the surface; soil heat flux represents the heat transferred from the surface to the soil, which affects the evaporation of water on the soil surface. When the soil temperature is high, the evaporation rate will also increase; air temperature affects the saturated water vapor pressure, which in turn determines the evaporation capacity of the air. Higher temperatures usually mean stronger evaporation capacity; wind speed directly affects the rate of water vapor exchange between the air and the ground. Higher wind speeds will accelerate the evaporation process; relative humidity determines the water vapor concentration in the air. The lower the relative humidity, the stronger the evaporation capacity. In addition, the potential evaporation quantified by this calculation formula provides an important benchmark to help water resource managers understand the evaporation losses that occur in specific areas under specific climatic conditions. By comparing with the actual evaporation, the effective utilization of water resources can be further analyzed, thereby improving the accuracy and applicability of the potential evaporation calculation formula.

[0137] Further, step S2 includes the following steps:

[0138] Step S21: Obtain high-resolution terrain data, land use type maps, and river system distribution data corresponding to complex watersheds;

[0139] In an embodiment of the present invention, high-resolution terrain data of a complex watershed area is obtained, which can be obtained through remote sensing technology, such as using laser radar (LiDAR) technology to obtain three-dimensional terrain data, or using global or local high-resolution digital elevation models (DEMs) such as ASTER GDEM and SRTM. These terrain data can reflect the elevation changes of the watershed, covering the terrain features such as the slope and undulation of the watershed. Next, a land use type map of the watershed is obtained, which can usually be analyzed through a land use classification map or remote sensing image data. Common remote sensing image classification techniques include supervised classification methods such as support vector machines (SVM) and random forests (RF), or unsupervised classification techniques such as K-means clustering (K-means). Finally, it is necessary to obtain river system distribution data, which can be generated through a hydrological model or an existing water system map of the watershed, or extracted through remote sensing images and GIS data processing. All these data are integrated and processed through a geographic information system (GIS) platform to ensure that the acquired data can accurately cover all geographical and hydrological features of the complex watershed, and finally obtain high-resolution terrain data, land use type maps, and river system distribution data corresponding to the complex watershed.

[0140] Step S22: performing type area terrain fluctuation analysis on the high-resolution terrain data corresponding to the complex watershed based on the land use type map corresponding to the complex watershed, and obtaining the terrain fluctuation change rate corresponding to different land use type areas in the complex watershed;

[0141] In an embodiment of the present invention, by spatially aligning a land use type map of a complex watershed with high-resolution terrain data, regions of different land use types are divided, and for each land use type region, the terrain undulation change rate is calculated. Specifically, the terrain undulation change rate can be calculated by terrain indices (such as slope, curvature, terrain profile, etc.), which are usually obtained by DEM data analysis. For example, the slope analysis tool in the GIS platform can be used to calculate the slope change of each region, or the terrain undulation index (such as terrain undulation, terrain profile change) can be used to evaluate the terrain undulation change of the region. For each region, the standard deviation or change rate of its terrain undulation change is calculated to reflect the complexity of the terrain of the region. Different land use type regions will present different terrain undulation characteristics. For example, urbanized areas usually have relatively flat terrain, while farmland, forest and other areas have large undulation differences. Finally, the terrain undulation change rate corresponding to different land use type regions in the complex watershed is obtained.

[0142] Step S23: Based on the land use type map corresponding to the complex watershed, the river system distribution data corresponding to the complex watershed is evaluated and analyzed for the water system confluence density, so as to obtain the river system confluence density corresponding to the different land use type areas in the complex watershed;

[0143] In an embodiment of the present invention, by evaluating the density of river water system confluence in different land use type areas within a watershed, first, combining the river water system distribution data and the land use type map within the watershed, an overlay analysis is performed through a GIS platform. For each land use type area, the main rivers, tributaries and water systems are identified, and the density of water system confluence is calculated. The water system density can be achieved by calculating the river length per unit area. For different types of land use areas within the watershed, such as cities, farmlands, forests, wetlands, etc., the respective water system densities can be calculated separately. Furthermore, a comprehensive evaluation can be performed based on the watershed area of ​​the watershed water system, the confluence characteristics of the rivers, and the precipitation and runoff conditions in the watershed. If the water system distribution is relatively dense, it means that the water system confluence density in the area is relatively high, otherwise it is relatively low. Finally, the river water system confluence density corresponding to different land use type areas in a complex watershed is obtained.

[0144] Step S24: basin grid division planning is performed according to the terrain undulation change rate and river system confluence density corresponding to different land use type areas in the complex basin. If the terrain undulation change rate and the river system confluence density are both greater than or equal to the preset threshold, the basin grid division standard of the corresponding land use type area is determined to be 0.5x0.5 square kilometers; if the terrain undulation change rate and the river system confluence density are both less than the preset threshold, the basin grid division standard of the corresponding land use type area is determined to be 2x2 square kilometers, otherwise it is determined to be 1x1 square kilometers, so as to obtain the complex basin adaptive grid division standard;

[0145] In an embodiment of the present invention, the terrain undulation change rate and the water system confluence density are used as key factors to formulate the watershed grid division standard based on the previous analysis results. Specifically, if the terrain undulation change rate and the water system confluence density of a certain area are greater than or equal to the preset threshold value (for example, the undulation change rate is greater than 5% and the water system density is greater than 0.5 km / km2), the watershed grid division standard of the area is set to 0.5x0.5 km2. This division is suitable for areas with more complex terrain and dense water systems to ensure that various factors can be considered more finely in the hydrological model; if both are less than the preset threshold value, the watershed grid division standard is set to 2x2 km2, which is suitable for areas with flat terrain and sparse water system distribution; and for areas between the two, the watershed grid division standard of 1x1 km2 is adopted. Through this adaptive grid division method, the resolution of the grid can be flexibly adjusted according to the specific characteristics of the watershed, the adaptability and accuracy of the model can be improved, and finally an adaptive grid division standard for complex watersheds is obtained.

[0146] Step S25: Based on the complex watershed adaptive grid division standard, the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed is gridded to generate a hydrological cycle grid model corresponding to each watershed sub-division.

[0147] In an embodiment of the present invention, by utilizing the previously determined adaptive grid division standard, the basin is divided into multiple sub-areas, and these sub-areas will be further processed as the basic units of the hydrological model. For each sub-area, a precipitation-evaporation-infiltration-runoff (hydrological cycle) simulation model is established. This model takes into account multiple hydrological processes such as precipitation, evaporation, soil infiltration, and runoff. By simulating the hydrological processes of different sub-areas in the basin, the hydrological changes in different areas are predicted. In specific operations, the meteorological data (such as precipitation, temperature, etc.) in each grid are first extracted, and then the hydrological processes in each grid are calculated. For smaller grids (such as 0.5x0.5 square kilometers), high-precision simulation can be performed using finer-grained meteorological data and hydrological processes; and for larger grids (such as 2x2 square kilometers), regional averaging can be adopted for simplification. Through this basin gridding processing, a hydrological cycle gridding model corresponding to each basin sub-division is finally generated.

[0148] Further, step S3 includes the following steps:

[0149] Step S31: Acquire measured meteorological data and measured hydrological data corresponding to the complex watershed;

[0150] In an embodiment of the present invention, measured meteorological and hydrological data in a complex river basin are obtained from relevant data sources such as meteorological stations and hydrological monitoring stations. Meteorological data generally include but are not limited to precipitation, temperature, relative humidity, wind speed, solar radiation and other elements. These data should have high timeliness and spatial coverage, and can reflect the meteorological changes in the river basin at different time and space positions; hydrological data include but are not limited to hydrological indicators such as water level, flow, runoff, evaporation, etc. These data should be collected in real time through multiple hydrological monitoring stations in the river basin to ensure that all sub-divisions of the river basin are covered, and the temporal and spatial resolution of the data should meet the needs of subsequent simulation analysis. Common acquisition methods include remote sensing data, meteorological and hydrological monitoring station data, historical meteorological data databases, etc., to ensure that seasonal changes and long-term trends can be identified, and finally the measured meteorological data and measured hydrological data corresponding to the complex river basin are obtained.

[0151] Step S32: performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step;

[0152] In the embodiment of the present invention, the acquired meteorological data and hydrological data are divided into time and space. The meteorological data and hydrological data are usually time series data. The basin needs to be divided into multiple sub-divisions according to the topography, climate distribution and hydrological characteristics of the basin for more accurate spatial analysis. In this process, the geographic information system (GIS) technology is used to divide the complex basin into spaces, and the corresponding meteorological data and hydrological data are matched to each sub-division according to the geographical characteristics, climate conditions and hydrological background of different sub-divisions. For each sub-division, a suitable time step (such as hours, days, months, etc.) is selected. ) to carry out spatiotemporal simulation to ensure that the time scale of simulation can cover different hydrological phenomena and changes, and by using time series analysis methods, such as autoregressive model (AR) or moving average model (MA), preprocessing and trend decomposition of time series data are carried out to extract the hydrological change characteristic vector of each sub-division at each simulation time step. The characteristic vector usually contains the change of multiple hydrological indicators, such as the increase and decrease trend of water level and flow, which can reflect the core characteristics of the hydrological change of the basin sub-division at this time step, and finally the hydrological change characteristic vector corresponding to each basin sub-division at each simulation time step is obtained.

[0153] Step S33: performing Z-score standardization on different vector elements in the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, to obtain the hydrological standardized characteristic vector corresponding to each watershed sub-division at each simulation time step;

[0154] In an embodiment of the present invention, the hydrological change characteristic vectors of each watershed sub-division at each simulation time step are standardized. In order to eliminate the dimensional differences of different hydrological characteristics and their influence on subsequent analysis, the Z-score standardization method is used to standardize the hydrological characteristics of each sub-division. Specifically, the Z-score standardization process is to calculate the mean and standard deviation of each element in the characteristic vector, and then convert it using the following formula: Z=(X-μ) / σ, where X is the original value of a hydrological characteristic, μ is the mean of the characteristic, and σ is the standard deviation of the characteristic. The standardized value indicates the degree of deviation of the characteristic from its mean, which can effectively eliminate the influence of the dimensions between different hydrological characteristics, ensure that the data has a unified scale and standard, and avoid some characteristics affecting the subsequent fluctuation mode calculation due to excessively large or small dimensions, and finally obtain the hydrological standardized characteristic vector corresponding to each watershed sub-division at each simulation time step.

[0155] Step S34: Perform fluctuation mode statistics calculation on the hydrological standardized characteristic vectors corresponding to each basin sub-division at each simulation time step, and obtain the fluctuation mode set of the hydrological characteristic vectors corresponding to each basin sub-division at different time scales, including the instantaneous frequency and fluctuation amplitude corresponding to each hydrological characteristic vector; perform similarity matching calculation on the fluctuation mode set of the hydrological characteristic vectors corresponding to each basin sub-division at different time scales using a similarity measurement algorithm based on dynamic time warping, so as to flexibly match the fluctuation mode sequence of each basin sub-division on the time axis, calculate the similarity between each basin sub-division, and obtain the similarity of hydrological changes between each basin sub-division;

[0156] In an embodiment of the present invention, a fluctuation mode analysis is performed on the hydrological standardized characteristic vectors of each watershed sub-division at each simulation time step. The fluctuation mode analysis aims to identify the periodic fluctuation characteristics in hydrological changes and their performance at different time scales. First, the frequency distribution and amplitude characteristics of each hydrological characteristic vector are analyzed using methods such as wavelet transform or Hilbert transform. Through frequency domain analysis, different frequency modes in hydrological changes, such as daily fluctuations, seasonal changes, and abnormal fluctuations, can be identified. Then, the fluctuation mode set of each watershed sub-division at different time scales is calculated, wherein each mode contains the instantaneous frequency and fluctuation amplitude of the hydrological characteristic vector. In this step, the dynamic time warping (DTW) algorithm can be used for similarity matching to flexibly match the fluctuation mode sequence on the time axis to ensure that even if the time steps are different or the fluctuation forms vary, similarity modes can still be found between the sub-divisions, and finally the similarity of hydrological changes between the watershed sub-divisions is calculated.

[0157] Step S35: each basin sub-division is regarded as a graph node, and the similarity of hydrological changes between each basin sub-division is used as the weight of the edge to construct a complex basin hydrological change conduction path diagram; based on the complex basin hydrological change conduction path diagram, a hydrological spatiotemporal correlation analysis is performed on the hydrological cycle grid model corresponding to each basin sub-division using a causal inference-based association analysis, so as to determine the causal sequence of hydrological changes between each basin sub-division by considering the influence of the terrain, soil and vegetation factors corresponding to each basin sub-division on hydrological conduction, and obtain the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, including the corresponding spatiotemporal correlation relationship between the increase in precipitation and runoff in the upstream sub-division and the increase in water level and flow in the downstream sub-division.

[0158] In an embodiment of the present invention, each watershed sub-division is regarded as a node of a graph through a graph theory method, and the edge weight between each node represents the similarity of hydrological changes between watershed sub-divisions. The hydrological change similarity measure can be calculated by the similarity measure of the fluctuation mode obtained by previous quantification. For example, the dynamic time warping (DTW) algorithm is used to calculate the fluctuation mode similarity between each two sub-divisions to obtain a similarity matrix as the edge weight of the graph. Subsequently, the shortest path algorithm, community detection algorithm and other methods are used to analyze the conduction path of hydrological changes in the watershed. Based on the structure of the graph, it is possible to identify which sub-divisions have strong interdependence or conduction relationships in hydrological changes, thereby constructing a complex The transmission path diagram of hydrological changes in miscellaneous watersheds. Next, based on the causal inference method, considering factors such as topography, soil, and vegetation in the watershed, the causal relationship of hydrological changes between sub-divisions is analyzed. For example, if the precipitation in the upstream sub-division increases and leads to an increase in runoff, the causal relationship between the water level rise and the flow increase in the downstream sub-division can be inferred. The resulting spatiotemporal correlation relationship diagram of hydrological changes will help understand the mutual influence and transmission mechanism of hydrological changes between different sub-divisions, and ultimately the spatiotemporal correlation relationship of hydrological changes between sub-divisions of each basin is obtained, including the corresponding spatiotemporal correlation relationship between the increase in precipitation and runoff in the upstream sub-division and the rise in water level and flow in the downstream sub-division.

[0159] Further, step S4 includes the following steps:

[0160] Step S41: constructing a hydrological diffusion evolution situation change model corresponding to each basin sub-division according to the spatiotemporal correlation relationship of hydrological changes between each basin sub-division;

[0161] In an embodiment of the present invention, a hydrological diffusion evolution trend change model is constructed according to the spatiotemporal correlation of hydrological changes between each basin sub-division. To achieve this goal, a spatiotemporal statistical analysis method is used to analyze the hydrological characteristics of each basin sub-division, including multiple hydrological variables such as precipitation, runoff, evaporation, and soil moisture. First, the historical hydrological data and meteorological data of the basin sub-division are obtained, and the hydrological change pattern of the basin sub-division is extracted by time series analysis (such as autoregressive moving average model ARMA, long short-term memory network LSTM, etc.), and then a spatial interpolation algorithm (such as Kriging interpolation method, inverse distance weighted method IDW) is used to perform spatial correlation analysis on the hydrological data to reveal the hydrological change trends and mutual influences between different sub-divisions. A mathematical model based on the changes in hydrological parameters between basin sub-divisions is established, which can reflect the hydrological diffusion laws of each basin sub-division, and take time and space factors into consideration to generate a predictable hydrological trend evolution model, which can provide a quantitative description of the hydrological changes between different basin sub-divisions, and finally obtain the corresponding hydrological diffusion evolution trend change model between each basin sub-division.

[0162] Step S42: Based on the hydrological diffusion evolution trend change model corresponding to each river basin sub-division, the hydrological cycle grid model corresponding to each river basin sub-division is processed for river basin time-space coupling early warning, so as to set dynamic early warning thresholds considering the topography, land use changes and meteorological changes corresponding to each river basin sub-division of the complex river basin, and compare and judge between the hydrological diffusion evolution changes of each river basin sub-division and the dynamic early warning threshold, so as to generate the hydrological change time-space coupling early warning response result corresponding to the complex river basin.

[0163] In the embodiment of the present invention, a hydrological cycle grid model is further constructed based on the hydrological diffusion evolution trend change model of each basin sub-division, and the basin time-space coupling early warning processing is performed. First, according to the previously established hydrological diffusion model, the hydrological cycle of the complex basin is gridded, and the basin is divided into multiple grid units. Each grid unit represents a specific hydrological cycle area. In the grid model, the hydrological variables (such as precipitation, evaporation, flow, etc.) of each grid unit are dynamically calculated according to different time steps to form a hydrological cycle process based on time and space changes. Secondly, taking into account the topography, The impact of land use change and meteorological change on hydrological process requires setting dynamic warning thresholds for each grid unit. Topographic features can be obtained through digital elevation model (DEM), land use change can be identified through remote sensing image analysis technology, and meteorological change can be integrated through meteorological station data and numerical weather forecast model. This information will help determine the dynamic warning threshold of each grid unit. Usually, methods such as extreme value theory and risk assessment model are used to determine the range of threshold change. Next, the hydrological diffusion evolution model is used to simulate the hydrological change situation of each grid unit and compare it with the dynamic warning threshold. If the hydrological state of a grid unit exceeds the set threshold, the corresponding warning response is triggered. The warning response can be combined with historical hydrological event data through machine learning algorithms such as decision trees and support vector machines (SVM) to detect hydrological anomalies and generate warning information. Based on the warning analysis of spatiotemporal coupling, the spatiotemporal coupling warning response results of hydrological changes in complex basins are generated. The response results can timely predict the hydrological state of each sub-division in the basin, identify the corresponding flood risk areas, and finally generate the spatiotemporal coupling warning response results of hydrological changes corresponding to the complex basin.

[0164] Furthermore, the present invention also provides a complex watershed dynamic hydrological coupling data analysis system, which is used to execute the complex watershed dynamic hydrological coupling data analysis method as described above. The complex watershed dynamic hydrological coupling data analysis system includes:

[0165] The complex watershed hydrological cycle simulation module is used to obtain the historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and to simulate and analyze the hydrological cycle of the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed;

[0166] The watershed grid processing module is used to perform watershed grid processing on the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed, so as to generate the hydrological cycle grid model corresponding to each watershed sub-division;

[0167] The complex watershed hydrological spatiotemporal association module is used to obtain the measured meteorological data and measured hydrological data corresponding to the complex watershed, and perform spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, the corresponding hydrological cycle grid model is subjected to hydrological spatiotemporal association analysis, so as to obtain the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division;

[0168] The watershed spatiotemporal coupling warning module is used to perform watershed spatiotemporal coupling warning processing on the hydrological cycle grid model corresponding to each watershed sub-division based on the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division, so as to generate spatiotemporal coupling warning response results of hydrological changes corresponding to complex watersheds.

[0169] 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 dynamic hydrological coupling data analysis method for a complex watershed, characterized in that: The following steps are involved: Step S1: acquiring historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and performing hydrological cycle simulation analysis on the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed; Step S2: Gridding the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed to generate a hydrological cycle gridding model corresponding to each watershed sub-division; Wherein, step S2 comprises the following steps: Step S21: Obtain high-resolution terrain data, land use type maps, and river system distribution data corresponding to complex watersheds; Step S22: performing type area terrain fluctuation analysis on the high-resolution terrain data corresponding to the complex watershed based on the land use type map corresponding to the complex watershed, and obtaining the terrain fluctuation change rate corresponding to different land use type areas in the complex watershed; Step S23: Based on the land use type map corresponding to the complex watershed, the river system distribution data corresponding to the complex watershed is evaluated and analyzed for the water system confluence density, so as to obtain the river system confluence density corresponding to the different land use type areas in the complex watershed; Step S24: basin grid division planning is performed according to the terrain undulation change rate and river system confluence density corresponding to different land use type areas in the complex basin. If the terrain undulation change rate and the river system confluence density are both greater than or equal to the preset threshold, the basin grid division standard of the corresponding land use type area is determined to be 0.5x0.5 square kilometers; if the terrain undulation change rate and the river system confluence density are both less than the preset threshold, the basin grid division standard of the corresponding land use type area is determined to be 2x2 square kilometers, otherwise it is determined to be 1x1 square kilometers, so as to obtain the complex basin adaptive grid division standard; Step S25: gridding the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed based on the complex watershed adaptive grid division standard, thereby generating a hydrological cycle grid model corresponding to each watershed sub-division; Step S3: obtaining measured meteorological data and measured hydrological data corresponding to the complex watershed, and performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; performing hydrological spatiotemporal correlation analysis on the corresponding hydrological cycle grid model based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, and obtaining the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division; Wherein, step S3 comprises the following steps: Step S31: Acquire measured meteorological data and measured hydrological data corresponding to the complex watershed; Step S32: performing spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; Step S33: performing Z-score standardization on different vector elements in the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, to obtain the hydrological standardized characteristic vector corresponding to each watershed sub-division at each simulation time step; Step S34: Perform fluctuation mode statistics calculation on the hydrological standardized characteristic vectors corresponding to each basin sub-division at each simulation time step, and obtain the fluctuation mode set of the hydrological characteristic vectors corresponding to each basin sub-division at different time scales, including the instantaneous frequency and fluctuation amplitude corresponding to each hydrological characteristic vector; perform similarity matching calculation on the fluctuation mode set of the hydrological characteristic vectors corresponding to each basin sub-division at different time scales using a similarity measurement algorithm based on dynamic time warping, so as to flexibly match the fluctuation mode sequence of each basin sub-division on the time axis, calculate the similarity between each basin sub-division, and obtain the similarity of hydrological changes between each basin sub-division; Step S35: each basin sub-division is regarded as a graph node, and the similarity of hydrological changes between each basin sub-division is used as the weight of the edge to construct a complex basin hydrological change conduction path diagram; based on the complex basin hydrological change conduction path diagram, a hydrological spatiotemporal correlation analysis is performed on the hydrological cycle grid model corresponding to each basin sub-division using a causal inference-based association analysis, so as to determine the causal sequence of hydrological changes between each basin sub-division by considering the influence of the terrain, soil and vegetation factors corresponding to each basin sub-division on hydrological conduction, and obtain the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, including the spatiotemporal correlation relationship between the increase in precipitation and runoff in the upstream sub-division and the increase in water level and flow in the downstream sub-division; Step S4: Based on the spatiotemporal correlation relationship of hydrological changes between each basin sub-division, the hydrological cycle grid model corresponding to each basin sub-division is processed for spatiotemporal coupling early warning of the basin, so as to generate a spatiotemporal coupling early warning response result of hydrological changes corresponding to the complex basin.

2. The dynamic hydrological coupling data analysis method for a complex watershed according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: obtaining historical meteorological data corresponding to the complex watershed, including precipitation, temperature, humidity and wind speed; Step S12: Obtaining historical hydrological data corresponding to the complex watershed, including flow, runoff depth, and groundwater level; Step S13: Obtain historical remote sensing data corresponding to the complex watershed, including surface humidity and vegetation coverage obtained by satellites or drones; Step S14: obtaining land use type, topography and soil geomorphology data corresponding to the complex watershed, and performing three-dimensional spatial modeling of the complex watershed based on the land use type, topography and soil geomorphology data corresponding to the complex watershed, so as to generate a three-dimensional spatial model of the complex watershed terrain; Step S15: Perform hydrological cycle simulation analysis on the three-dimensional spatial model of complex basin terrain based on historical meteorological data, historical hydrological data and historical remote sensing data to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

3. The dynamic hydrological coupling data analysis method for complex watersheds according to claim 2 is characterized in that: Step S15 includes the following steps: Step S151: spatially extend and calibrate the historical meteorological data according to the geographical location information of the meteorological stations corresponding to the complex watershed and in combination with the Kriging interpolation method, so as to spatially extend the precipitation, temperature, humidity and wind speed recorded by each meteorological station to cover the entire complex watershed, thereby obtaining the historical meteorological spatial extension data; Step S152: Obtain the river direction and watershed watershed corresponding to the complex watershed through the three-dimensional spatial model of the complex watershed terrain, and use linear interpolation to perform time series alignment and registration of the flow, runoff depth and groundwater level in the historical hydrological data based on the river direction and watershed watershed watershed to obtain historical hydrological time series registration data; Step S153: Obtain the shooting time and spatial resolution corresponding to the satellite or the UAV, and perform spatiotemporal calibration processing on the surface humidity and vegetation coverage in the historical remote sensing data using bilinear interpolation and resampling technology based on the shooting time and spatial resolution to obtain historical remote sensing spatiotemporal calibration data; Step S154: performing frequency domain component conversion on the corresponding precipitation, temperature, humidity and wind speed in the historical meteorological spatial extension data to obtain historical meteorological change data corresponding to different frequency components, including precipitation, temperature, humidity and wind speed changes corresponding to high-frequency and low-frequency components; performing fluctuation feature analysis on the historical hydrological time series registration data based on the historical meteorological change data corresponding to different frequency components to obtain fluctuation features between meteorological changes and hydrology corresponding to each frequency component; Step S155: Based on the corresponding surface humidity and vegetation coverage in the historical remote sensing spatiotemporal calibration data, the historical hydrological time series registration data is analyzed for potential impact characteristics, and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are obtained; the fluctuation characteristics between the corresponding meteorological changes and hydrology under each frequency component and the potential impact characteristics between surface humidity and vegetation coverage and hydrology are integrated to obtain a complex basin meteorological-remote sensing hydrological feature set; Step S156: Based on the complex basin meteorological-remote sensing hydrological feature set, a hydrological cycle simulation analysis is performed on the three-dimensional spatial model of the complex basin terrain to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

4. The dynamic hydrological coupling data analysis method for complex watersheds according to claim 3 is characterized in that: Step S156 includes the following steps: The three-dimensional spatial model of complex basin terrain is imported into the terrain analysis software based on finite difference, so as to use the terrain analysis software to simulate the distribution of solar radiation in the complex basin and combine it with the corresponding temperature in the historical meteorological data to calculate the heat balance corresponding to different slope aspects and slope areas, and obtain the balance influence parameters of terrain on heat redistribution; By combining the principles of hydrogeomorphology and obtaining runoff depth and groundwater level changes from historical hydrological data, the corresponding gully density and water system branching ratio in complex watersheds are analyzed; Obtain the soil texture and permeability characteristics corresponding to the complex watershed, and calculate the soil permeability distribution of the three-dimensional spatial model of the complex watershed terrain based on the soil texture and permeability characteristics corresponding to the complex watershed, so as to obtain the spatial distribution of the soil permeability coefficient corresponding to the complex watershed; The topographic and geomorphic parameters of the balance of topography on heat redistribution, the gully density corresponding to the complex watershed, the water system branching ratio and the spatial distribution of soil permeability coefficient are integrated to obtain the topographic and geomorphic parameter set of the complex watershed. Based on the complex basin meteorological-remote sensing hydrological feature set and the complex basin topographic and geomorphological parameter set, the hydrological cycle simulation analysis is carried out on the three-dimensional spatial model of the complex basin terrain to generate the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex basin.

5. The dynamic hydrological coupling data analysis method for complex watersheds according to claim 4 is characterized in that: The hydrological cycle simulation analysis of the complex basin terrain three-dimensional spatial model based on the complex basin meteorological-remote sensing hydrological feature set and the complex basin terrain and geomorphological parameter set comprises the following steps: Obtain the time period through historical meteorological data The corresponding precipitation , and based on the period The corresponding precipitation The vegetation canopy interception model is constructed for the complex watershed meteorological-remote sensing hydrological feature set to generate the vegetation canopy interception model corresponding to the complex watershed ,in Indicates during the period The corresponding vegetation canopy interception, represents the potential influence coefficient between surface moisture and hydrology, represents the potential influence coefficient between vegetation coverage and hydrology, Indicates the index corresponding to the historical meteorological data, where 1 represents precipitation, 2 represents temperature, 3 represents humidity, and 4 represents wind speed. For the high frequency components The fluctuation characteristics between historical meteorological data and hydrology, For the low frequency component Fluctuation characteristics between historical meteorological data and hydrology; Based on the period The corresponding precipitation The precipitation input of the vegetation canopy interception model corresponding to the complex watershed is calculated to obtain the actual precipitation input corresponding to the complex watershed. ; Based on the corresponding terrain balance influence parameters on heat redistribution in the complex basin terrain parameter set, the potential evaporation calculation formula is used to calculate the basin evaporation of the complex basin terrain three-dimensional spatial model to obtain the corresponding potential evaporation of the complex basin. ; Based on the corresponding gully density, water system branching ratio and soil permeability coefficient spatial distribution in the complex basin terrain parameter set, the soil permeability calculation is performed on the corresponding soil terrain in the three-dimensional spatial model of the complex basin terrain to obtain the corresponding soil permeability of the complex basin. ,in Indicates during the period The corresponding soil permeability coefficient is Indicates during the period The corresponding soil moisture content is Indicates during the period The corresponding soil topography water potential, represents the gully density corresponding to the complex watershed, Indicates the branching ratio of the water system corresponding to the complex watershed; The surface runoff output corresponding to the complex basin is calculated based on the actual precipitation input, potential evaporation and soil infiltration corresponding to the complex basin and combined with the water balance principle to obtain the surface runoff output corresponding to the complex basin. ; Based on the actual precipitation input, potential evaporation, soil infiltration and surface runoff output corresponding to the complex watershed, a hydrological cycle simulation analysis is carried out on the three-dimensional spatial model of the complex watershed terrain to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed.

6. The dynamic hydrological coupling data analysis method for complex watersheds according to claim 5 is characterized in that: The potential evaporation calculation formula is specifically: ； ； ； ； In the formula, is the potential evaporation corresponding to the complex basin, is the slope of the saturated water vapor pressure curve, For the period The corresponding solar simulated net radiation is For the period The corresponding soil heat flux is is the parameter affecting the balance of topography on heat redistribution, For the period The corresponding soil temperature is For the period The corresponding wind speed is For the period The corresponding saturated water vapor pressure is For the period The actual water vapor pressure corresponding to is an exponential function, For the period The corresponding relative humidity.

7. The dynamic hydrological coupling data analysis method for complex watersheds according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: constructing a hydrological diffusion evolution situation change model corresponding to each basin sub-division according to the spatiotemporal correlation relationship of hydrological changes between each basin sub-division; Step S42: Based on the hydrological diffusion evolution trend change model corresponding to each river basin sub-division, the hydrological cycle grid model corresponding to each river basin sub-division is processed for river basin time-space coupling early warning, so as to set dynamic early warning thresholds considering the topography, land use changes and meteorological changes corresponding to each river basin sub-division of the complex river basin, and compare and judge between the hydrological diffusion evolution changes of each river basin sub-division and the dynamic early warning threshold, so as to generate the hydrological change time-space coupling early warning response result corresponding to the complex river basin.

8. A dynamic hydrological coupling data analysis system for complex watersheds, characterized in that: The method for analyzing the dynamic hydrological coupling data of a complex watershed according to claim 1 is used to perform the dynamic hydrological coupling data analysis system of the complex watershed, the dynamic hydrological coupling data analysis system of the complex watershed comprising: The complex watershed hydrological cycle simulation module is used to obtain the historical meteorological data, historical hydrological data and historical remote sensing data corresponding to the complex watershed, and to simulate and analyze the hydrological cycle of the complex watershed based on the historical meteorological data, historical hydrological data and historical remote sensing data, so as to generate a precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed; The watershed grid processing module is used to perform watershed grid processing on the precipitation-evaporation-infiltration-runoff hydrological cycle simulation model corresponding to the complex watershed, so as to generate the hydrological cycle grid model corresponding to each watershed sub-division; The complex watershed hydrological spatiotemporal association module is used to obtain the measured meteorological data and measured hydrological data corresponding to the complex watershed, and perform spatiotemporal simulation division on the measured meteorological data and measured hydrological data corresponding to the complex watershed, so as to obtain the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step; based on the hydrological change characteristic vector corresponding to each watershed sub-division at each simulation time step, the corresponding hydrological cycle grid model is subjected to hydrological spatiotemporal association analysis, so as to obtain the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division; The watershed spatiotemporal coupling warning module is used to perform watershed spatiotemporal coupling warning processing on the hydrological cycle grid model corresponding to each watershed sub-division based on the spatiotemporal correlation relationship of hydrological changes between each watershed sub-division, so as to generate spatiotemporal coupling warning response results of hydrological changes corresponding to complex watersheds.

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