Drainage basin sediment transport prediction method fusing sub-rainfall spatial differentiation information

Abstract

The invention provides a drainage basin sediment transport prediction method, device and equipment fusing sub-rainfall spatial differentiation information and a storage medium. The method comprises the following steps: establishing a plurality of sub-rainfall spatial differentiation characterization indexes based on multi-dimensional features; constructing underlying surface feature indexes corresponding to the rainfall core area based on the sub-rainfall and the underlying surface features; screening out the sub-rainfall spatial differentiation characterization index through the correlation between the sub-rainfall spatial differentiation characterization index and the drainage basin sediment transport modulus as well as between the underlying surface characteristic index and the drainage basin sediment transport modulus, and obtaining a high-correlation characterization index; converting the high-correlation characterization indexes into mutually independent principal components by adopting a principal component analysis method, and determining the index with the highest explanatory variable in the plurality of principal components as a dominant sub-rainfall spatial differentiation index; taking the dominant sub-rainfall spatial differentiation index as an independent variable, taking a basin sub-rainfall sediment transport modulus as a dependent variable, and constructing a basin sediment transport prediction model fused with sub-rainfall spatial differentiation information through multiple regression analysis; and the accuracy and comprehensiveness of river basin sediment transport prediction are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of engineering sediment technology, and in particular to a basin sediment transport prediction method, device, equipment and storage medium integrating sub-rainfall spatial differentiation information. Background Art

[0002] A watershed is the fundamental unit for runoff generation and sediment transport, as well as comprehensive management. Accurately understanding the intensity and distribution of erosion and sediment production in a watershed is a key prerequisite for scientifically deploying soil and water conservation measures and promoting optimal management of soil and water resources. Rainfall is the fundamental driving force behind erosion and sediment production in a watershed. Elucidating the response of watershed sediment transport to changes in rainfall characteristics can provide important insights for ecological management practices, including soil and water conservation.

[0003] At the slope scale, soil erosion is closely related to rainfall characteristics such as rainfall amount, duration, intensity, erosivity, and preceding rainfall. In contrast, erosion and sediment yield at the watershed scale is more complex and nonlinear. Consequently, the relationship between watershed erosion and sediment yield and several characteristic parameters of a single rainfall event differs significantly from that at the slope scale. Scholars have attributed the dominant rainfall factors affecting watershed erosion and sediment yield to rainfall type, amount, maximum rainfall intensity, duration, and their combination, and have constructed statistical models of watershed sediment transport based on these factors. Most studies believe that short-duration, high-intensity rainfall primarily drives watershed erosion and sediment yield, and that the relationship between watershed erosion and sediment yield and rainfall is dependent on rainfall type. Furthermore, some studies have found that even when rainfall events with similar rainfall-related characteristic variables across the watershed surface, significant differences in erosion and sediment yield can still occur within the watershed, attributing this to the impact of spatial heterogeneity in single rainfall events on erosion and sediment yield. Overall, the spatial heterogeneity of rainfall events in number, duration, and intensity within a watershed leads to significant spatial variation in runoff and erosion and sediment yield, resulting in varying sediment transport intensities within the watershed. This finding not only reveals the key role of spatial rainfall variation in watershed erosion and sediment yield, but also suggests that focusing solely on areal rainfall characteristics in studies of the relationship between rainfall events and watershed erosion and sediment yield will fail to reflect the mechanisms of watershed erosion and sediment yield, thereby reducing the accuracy and rationality of relevant predictions. To this end, many studies have classified rainfall events based on their spatial distribution within the watershed, thereby exploring the relationship between different rainfall types and erosion and sediment yield. For example, using the K-means clustering method, rainfall events were classified into four spatial patterns based on areal rainfall, rainfall coefficient of variation, and maximum rainfall over a period of time. These studies found that rainfall events with similar areal rainfall but different spatial distribution and variability exhibited significantly different erosion and sediment yield intensities. Heavy rainfall events with weak variability were more likely to result in more severe erosion and sediment yield.

[0004] Current research on the mechanisms by which spatial variability in rainfall events influences watershed erosion and sediment production has largely focused on point or area rainfall variables, ignoring the spatial variability of rainfall. This limitation makes it difficult to accurately interpret the mechanisms of watershed sediment production and transport, significantly limiting the accuracy of predictions. Summary of the Invention

[0005] The present invention provides a basin sediment transport prediction method, device, equipment and storage medium that integrates information on the spatial differentiation of rainfall events, so as to address the defect of the existing technology that ignores the heterogeneity of rainfall in spatial distribution, improve the accuracy of sediment transport forecast at the basin scale, and provide a more accurate scientific basis for the prevention and control of rainstorm erosion disasters in the basin.

[0006] The present invention provides a basin sediment transport prediction method integrating sub-rainfall spatial differentiation information, comprising the following steps.

[0007] Based on multi-dimensional characteristics, multiple indicators representing the spatial differentiation of rainfall are established; the multi-dimensional characteristics include the degree of spatial variability of rainfall and the characteristics of rainfall in the core area of the basin; Based on the rainfall and underlying surface characteristics, the underlying surface characteristic index corresponding to the rainfall core area is constructed; Through the correlation between the spatial differentiation characterization index of rainfall and the watershed sediment transport modulus, as well as the correlation between the underlying surface characteristic index and the watershed sediment transport modulus, the spatial differentiation characterization index of rainfall whose correlation with the watershed sediment transport exceeds the correlation threshold is screened out, and the high correlation characterization index is obtained; The principal component analysis method was used to convert the highly correlated characterization indicators into independent principal components, and the indicator with the highest explanatory variable among multiple principal components was determined as the dominant secondary rainfall spatial differentiation indicator of the basin sediment transport modulus. Taking the dominant secondary rainfall spatial differentiation index as the independent variable and the basin secondary rainfall sediment transport modulus as the dependent variable, a basin sediment transport prediction model integrating the secondary rainfall spatial differentiation information was constructed through multiple regression analysis, and the basin sediment transport was predicted using the basin sediment transport prediction model.

[0008] According to the present invention, a basin sediment transport prediction method integrating spatial differentiation information of rainfall events is provided, the method further comprising: Calculate the rainfall variables of multiple rain gauges in the basin during a runoff rainfall event; the rainfall variables include: rainfall amount, rainfall duration, and rainfall intensity; The control area of each rain gauge was obtained using the Thiessen polygon method; The rainfall threshold is determined, and the rain gauges whose rainfall variable values are greater than the rainfall threshold are determined as the selected rain gauges, and the control areas of the selected rain gauges are determined as the rainfall core areas of the basin.

[0009] According to a watershed sediment transport prediction method that integrates secondary rainfall spatial differentiation information provided by the present invention, the secondary rainfall spatial differentiation characterization index includes a relative rainfall variable value in the watershed rainfall core area, and multiple secondary rainfall spatial differentiation characterization indexes are established based on multi-dimensional characteristics, including: establishing a relative rainfall variable value in the watershed rainfall core area based on the multi-dimensional characteristics; establishing the relative rainfall variable value in the watershed rainfall core area based on the multi-dimensional characteristics is achieved by the following formula: Among them, SCR is the ratio of the surface rainfall variable value in the core area of the basin to the average rainfall index value of the entire basin; HCA is the average rainfall variable value in the core area of the basin; is the area average of a rainfall variable in the basin.

[0010] According to a watershed sediment transport prediction method that integrates sub-rainfall spatial differentiation information provided by the present invention, the sub-rainfall spatial differentiation characterization index includes a sediment connectivity index value of the watershed rainfall core area. Multiple sub-rainfall spatial differentiation characterization indexes are established based on multi-dimensional characteristics, including: establishing a sediment connectivity index value of the watershed rainfall core area based on the multi-dimensional characteristics; establishing the sediment connectivity index value of the watershed rainfall core area based on the multi-dimensional characteristics is achieved by the following formula:

[0011] IC is the sediment connectivity index, which ranges from [-∞, +∞]. The larger the value, the better the sediment connectivity and the stronger the sediment production and transport capacity. D up 、 D dn represent the upslope and downslope components respectively; W i For the i The weight factor of each grid cell is assigned using the C factor of RUSLE, which mainly reflects the influence of vegetation cover; S i For the i The slope of the grid unit (m / m); A is the i The upslope catchment area of each grid cell (m 2 ); d i For the i Length of the confluence path from each grid cell to the nearest river channel or sedimentation area (m); For the i The average upslope weight factor of each grid cell; For the i The average upslope slope of each grid cell (m / m).

[0012] The present invention also provides a basin sediment transport prediction device integrating spatial differentiation information of rainfall events, comprising the following modules: The characterization index establishment module is used to establish multiple rainfall spatial differentiation characterization indicators based on multi-dimensional characteristics; wherein the multi-dimensional characteristics include the degree of rainfall spatial variability and rainfall characteristics in the core area of the basin; The underlying surface characteristic index construction module is used to construct the underlying surface characteristic index corresponding to the rainfall core area based on the rainfall and underlying surface characteristics; A correlation determination module is used to screen out the sub-rainfall spatial differentiation characterization indicators whose correlation with the basin sediment transport modulus exceeds the correlation threshold through the correlation between the sub-rainfall spatial differentiation characterization indicators and the basin sediment transport modulus, as well as the correlation between the underlying surface characteristic indicators and the basin sediment transport modulus, to obtain high-correlation characterization indicators; The module for determining the dominant secondary rainfall spatial differentiation index is used to convert highly correlated characterization indicators into mutually independent principal components using the principal component analysis method, and to determine the index with the highest explanatory variable among multiple principal components as the dominant secondary rainfall spatial differentiation index of the basin sediment transport modulus; The basin sediment transport prediction model construction module is used to take the dominant secondary rainfall spatial differentiation index as the independent variable and the basin secondary rainfall sediment transport modulus as the dependent variable. Through multiple regression analysis, a basin sediment transport prediction model integrating the secondary rainfall spatial differentiation information is constructed, and the basin sediment transport is predicted through the basin sediment transport prediction model.

[0013] According to the present invention, a basin sediment transport prediction device integrating spatial differentiation information of rainfall events is provided, wherein the device further comprises: The basin rainfall core area determination module is used to calculate the rainfall variables of multiple rain gauges in the basin during a secondary runoff rainfall event; the rainfall variables include rainfall amount, rainfall duration, and rainfall intensity; the control area of each rain gauge is obtained using the Thiessen polygon method; the rainfall threshold is determined, and the rain gauges whose rainfall variable values are greater than the rainfall threshold are determined as selected rain gauges, and the control areas of the selected rain gauges are determined as the basin rainfall core area.

[0014] According to the present invention, a watershed sediment transport prediction device that integrates secondary rainfall spatial differentiation information is provided, wherein the secondary rainfall spatial differentiation characterization index includes a relative rainfall variable value in the watershed rainfall core area, and a characterization index establishment module is used to establish the relative rainfall variable value in the watershed rainfall core area based on multi-dimensional characteristics. Establishing the relative rainfall variable value in the watershed rainfall core area based on the multi-dimensional characteristics is achieved by the following formula: Among them, SCR is the ratio of the surface rainfall variable value in the core area of the basin to the average rainfall index value of the entire basin; HCA is the average rainfall variable value in the core area of the basin; is the area average of a rainfall variable in the basin.

[0015] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for predicting watershed sediment transport by integrating spatial differentiation information of secondary rainfall as described above is implemented.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for predicting watershed sediment transport by integrating spatial differentiation information of rainfall events as described above is implemented.

[0017] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned methods for predicting watershed sediment transport by integrating spatial differentiation information of secondary rainfall.

[0018] The method, device, equipment and storage medium for predicting watershed sediment transport by integrating sub-rainfall spatial differentiation information provided by the present invention establish multiple sub-rainfall spatial differentiation characterization indicators based on multi-dimensional features; construct underlying surface characteristic indicators corresponding to the rainfall core area based on sub-rainfall and underlying surface characteristics; through the correlation between sub-rainfall spatial differentiation characterization indicators and watershed sediment transport modulus and the correlation between underlying surface characteristic indicators and watershed sediment transport modulus, sub-rainfall spatial differentiation characterization indicators whose correlation with watershed sediment transport exceeds a correlation threshold are screened out to obtain highly correlated characterization indicators; principal component analysis is used to classify highly correlated characterization indicators The data were converted into independent principal components, and the indicator with the highest explanatory variable among the multiple principal components was identified as the dominant secondary rainfall spatial differentiation indicator of the basin sediment transport modulus. Using the dominant secondary rainfall spatial differentiation indicator as the independent variable and the basin secondary rainfall sediment transport modulus as the dependent variable, a basin sediment transport prediction model incorporating secondary rainfall spatial differentiation information was constructed through multiple regression analysis. Basin sediment transport was then predicted using this model. A series of indices representing secondary rainfall spatial differentiation were innovatively constructed based on multiple dimensions, including the degree of spatial variability of secondary rainfall in the basin, rainfall characteristics in the rainfall core area, and underlying surface characteristics in the rainfall core area. These indices can comprehensively and effectively reflect the primary influencing mechanisms of secondary rainfall spatial differentiation on basin sediment production and transport, providing a solid foundation for the construction of subsequent sediment transport forecast models and effectively improving the accuracy and comprehensiveness of basin sediment transport predictions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1It is a flow chart of the basin sediment transport prediction method integrating the spatial differentiation information of rainfall events provided by the present invention.

[0021] Figure 2 This is the research basin location provided by the present invention.

[0022] Figure 3 It is a structural schematic diagram of a watershed sediment transport prediction device that integrates sub-rainfall spatial differentiation information provided by the present invention.

[0023] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0025] The following combination Figure 1-Figure 4 The present invention is described.

[0026] The present invention is mainly used to carry out basin erosion and sediment transport prediction at the sub-rainfall scale, and can provide an effective approach and theoretical support for improving the accuracy of basin-scale sediment production and transport forecasts. Figure 1 This is one of the flow charts of the basin sediment transport prediction method that integrates the spatial differentiation information of rainfall provided by the present invention. Figure 1 As shown, the method includes the following: Step 101: Establish multiple rainfall spatial differentiation characterization indicators based on multi-dimensional characteristics; wherein the multi-dimensional characteristics include the degree of rainfall spatial variability and rainfall characteristics in the core area of the basin.

[0027] Optionally, the present invention provides a method for predicting sediment transport in a watershed by integrating spatially varying information of rainfall events, further comprising: Calculate the rainfall variables of multiple rain gauges in the basin during a secondary runoff rainfall event; the rainfall variables include: rainfall amount, rainfall duration, and rainfall intensity.

[0028] The control area of each rain gauge was obtained using the Thiessen polygon method.

[0029] The rainfall threshold is determined, and the rain gauges whose rainfall variable values are greater than the rainfall threshold are determined as the selected rain gauges, and the control areas of the selected rain gauges are determined as the rainfall core areas of the basin.

[0030] In the above step 101, the embodiment of the present invention systematically screens and creates a series of sub-rainfall spatial differentiation characterization indicators based on the multi-dimensional sub-rainfall spatial differentiation characteristics; establishes a basin sediment transport forecasting method that reflects the sub-rainfall spatial differentiation characteristics, and verifies its rationality and reliability.

[0031] The rainfall core area of a watershed refers to the covered area within the watershed that is above a certain rainfall threshold.

[0032] The embodiment of the present invention systematically considers the spatial variability of secondary rainfall, rainfall core area, rainfall characteristics, the underlying surface of the rainfall core area, and other characteristics, systematically selects and establishes new secondary rainfall spatial differentiation characterization indicators, and preliminarily constructs a secondary rainfall spatial differentiation characterization indicator system (Table 1), thereby achieving a comprehensive and accurate characterization of the secondary rainfall spatial differentiation characteristics.

[0033] The degree of spatial variability of rainfall includes: basin surface rainfall dispersion coefficient, basin rainfall unevenness coefficient and basin spatial extreme rainfall ratio coefficient.

[0034] Basin rainfall dispersion coefficient C V It refers to the coefficient of deviation of sub-rainfall variables in the basin (including rainfall amount, rainfall duration, rainfall intensity, etc.).

[0035] The basin rainfall unevenness coefficient η refers to the ratio of the average value to the maximum value of the basin rainfall variable.

[0036] The basin spatial extreme rainfall ratio coefficient α refers to the ratio of the maximum to minimum rainfall variables in the basin.

[0037] The rainfall characteristics of the rainfall core area include the location of the rainfall center in the basin, the area ratio of the rainfall core area in the basin, the rainfall variable value in the rainfall core area of the basin, and the relative rainfall variable value in the rainfall core area of the basin.

[0038] Location of rainfall center in the basin C L Refers to the straight-line distance from the rainfall station to the basin outlet considering the rainfall weight. The proportion of the basin rainfall core area SCP refers to the proportion of the rainfall core area greater than a certain rainfall threshold to the basin area. The rainfall variable value H of the basin rainfall core area CA The relative rainfall variable value (CAR) in the core rainfall area of a basin refers to the ratio of the average rainfall index value in the core rainfall area to the rainfall index value in the entire basin.

[0039] The underlying surface characteristics of the rainfall core area include sediment connectivity in the rainfall core area, sediment connectivity IC in the rainfall core area CA Refers to the average sediment connectivity index IC value in the rainfall core area.

[0040] The calculation method of the characterization index of the spatial variability of rainfall in the basin is as follows: Basin rainfall dispersion coefficient C V (1) (2) Where: H i is the value of a rainfall variable at a rain gauge station in the basin, such as rainfall amount, rainfall duration, rainfall intensity, etc.; is the area average of a rainfall variable in the basin; n is the number of rainfall stations. C V The larger the value, the higher the degree of variability of the secondary rainfall in the basin; conversely, the more uniform the secondary rainfall distribution.

[0041] Basin rainfall unevenness coefficient η: (3) Where: is the area average of a rainfall variable in the basin; is the maximum value of a rainfall variable in the basin. The closer the η value is to 1, the more uniform the rainfall distribution in the basin is.

[0042] Basin spatial extreme rainfall ratio coefficient α: (4) Where: is the maximum value of a rainfall variable in the basin; is the minimum value of a rainfall variable in the basin. The closer the α value is to 1, the more uniform the rainfall distribution in the basin is.

[0043] Location of rainfall center in the basin C L : (5) Where: H i The meaning is the same as formula 2; For the i The straight-line distance from a rain gauge station to the basin outlet. C L The larger the value, the farther the rainfall center is from the basin outlet; conversely, the closer it is.

[0044] The proportion of the core rainfall area in the basin SCP: The rainfall core area refers to the area in the basin that is above a certain rainfall threshold during a rainfall event. The area ratio of the rainfall core area is the ratio of the area of the rainfall core area to the total area of the basin. The specific steps to determine the rainfall core area are as follows: 1) Calculate the rainfall of the basin under the runoff-producing rainfall event.n The first step is to determine the rainfall variables (rainfall, rainfall duration, and rainfall intensity) of each rain gauge; 2) use the Thiessen polygon method to obtain the control area of each rain gauge; 3) screen the rain gauges whose rainfall variable values are greater than the rainfall threshold, and use the control areas of these rain gauges as the "rainfall core area" of the basin under this rainfall event.

[0045] When determining the rainfall threshold in the rainfall core area, the main references are the average rainfall variable value of the basin, the median of the rainfall variable values of each rain gauge in the basin, and the following fixed rainfall thresholds: single rainfall ≥50 mm (heavy rain defined by meteorology), maximum 60-minute rainfall intensity ≥16 mm / h (heavy rain defined by meteorology), single rainfall ≥12 mm (erosive rainfall standard of the Loess Plateau), average rainfall intensity ≥2.4 mm / h (erosive average rainfall intensity standard of the Loess Plateau), maximum 30-minute rainfall intensity ≥15 mm / h (erosive maximum 30-minute rainfall intensity standard of the Loess Plateau), etc.

[0046] The average rainfall variable value H in the core rainfall area of the basin CA : According to the designated rainfall core area, the rainfall variable data of each rain gauge at each rainfall event were used to obtain the average rainfall variable value H in the rainfall core area of the basin based on GIS spatial analysis. CA .

[0047] Optionally, the sub-rainfall spatial differentiation characterization index includes a relative rainfall variable value in a core rainfall area of a watershed, and step 101 includes step A1: Step A1: Establish the relative rainfall variable value of the basin rainfall core area based on multi-dimensional characteristics.

[0048] The relative rainfall variable value of the basin rainfall core area based on multi-dimensional characteristics is established through the following formula: Among them, SCR is the ratio of the surface rainfall variable value in the core area of the basin to the average rainfall index value of the entire basin; HCA is the average rainfall variable value in the core area of the basin; is the area average of a rainfall variable in the basin.

[0049] Optionally, the sub-rainfall spatial differentiation characterization index includes a sediment connectivity index value of the basin rainfall core area, and step 101 includes step B1: establishing a sediment connectivity index value of the basin rainfall core area based on multi-dimensional features; The sediment connectivity index value of the basin rainfall core area is established based on multi-dimensional characteristics through the following formula:

[0050] IC is the sediment connectivity index, which ranges from [-∞, +∞]. The larger the value, the better the sediment connectivity and the stronger the sediment production and transport capacity. D up 、 D dn represent the upslope and downslope components respectively; W i For the i The weight factor of each grid cell is assigned using the C factor of RUSLE, which mainly reflects the influence of vegetation cover; S i For the i The slope of the grid unit (m / m); A is the i The upslope catchment area of each grid cell (m 2 ); d i For the i Length of the confluence path from each grid cell to the nearest river channel or sedimentation area (m); For the i The average upslope weight factor of each grid cell; For the i The average upslope slope of each grid cell (m / m).

[0051] In step B1 above, the sediment connectivity algorithm was used in ArcGIS software to extract terrain indicators such as slope, upper catchment area, and downslope catchment length based on the basin DEM. Combined with the basin land use data, the spatial analysis module was used to calculate the IC distribution of the basin. The IC of the rainfall event was calculated based on the rainfall core area of the rainfall event. CA .

[0052] Step 102: Construct underlying surface characteristic indices corresponding to the rainfall core area based on the rainfall events and underlying surface characteristics.

[0053] Step 103: Through the correlation between the sub-rainfall spatial differentiation characterization index and the watershed sediment transport modulus and the correlation between the underlying surface characteristic index and the watershed sediment transport modulus, the sub-rainfall spatial differentiation characterization index whose correlation with the watershed sediment transport exceeds the correlation threshold is screened out to obtain a highly correlated characterization index.

[0054] In step 103, Pearson correlation analysis is used to determine the correlation between the spatially differentiated rainfall indicators and the watershed sediment transport modulus. This accurately identifies the most significantly correlated rainfall indicators. The correlation threshold, which measures the significance of the correlation, can be set based on actual needs.

[0055] Step 104: Use the principal component analysis method to convert the highly correlated characterization indicators into mutually independent principal components, and determine the indicator with the highest explanatory variable among multiple principal components as the dominant secondary rainfall spatial differentiation indicator of the basin sediment transport modulus.

[0056] In step 104, principal component analysis (PCA) was used to convert the sub-rainfall spatial differentiation indicators that were significantly correlated with the basin sediment transport modulus into independent principal components (PCs). Each PC was then analyzed in depth, and the indicator with the highest explanatory variable was selected as the dominant sub-rainfall spatial differentiation indicator for the basin sediment transport modulus.

[0057] Step 105: Using the dominant secondary rainfall spatial differentiation index as the independent variable and the basin secondary rainfall sediment transport modulus as the dependent variable, a basin sediment transport prediction model integrating the secondary rainfall spatial differentiation information is constructed through multiple regression analysis, and basin sediment transport is predicted using the basin sediment transport prediction model.

[0058] In the above step 105, the determined dominant secondary rainfall spatial differentiation index is used as the independent variable, the basin sediment transport modulus is used as the dependent variable, and a multiple regression analysis method is used to construct a basin sediment transport prediction model that integrates the secondary rainfall spatial differentiation information.

[0059] In order to test the rationality and reliability of the basin sediment yield prediction model based on the spatial differentiation characteristics of rainfall, the present invention uses traditional rainfall indicators as independent variables to establish a basin sediment yield prediction model that does not consider the spatial differentiation of rainfall. R 2 ), root mean square error (RMSE), Nash efficiency coefficient (NSE) and model comparison index (MCI) were used to evaluate the prediction accuracy and effectiveness of the two constructed basin sediment transport prediction models.

[0060] Coefficient of determination ( R 2 ), the root mean square error (RMSE), Nash efficiency coefficient (NSE) and model comparison index (MCI) are calculated as follows: (8) (9) (10) Where m is the number of erosive rainfall events in the basin (j = 1, 2, 3, …m); j and P j are the observed and predicted values of the sediment yield modulus of the jth rainfall event in the basin; It is the average of the observed values of sediment yield modulus of rainfall events in the basin.

[0061] R2 The higher the value, the lower the RMSE and the higher the NSE, the better the prediction performance of the model, and vice versa. The present invention aims to solve the problem that existing methods for predicting sediment transport in watersheds by secondary rainfall generally fail to consider the spatial differentiation characteristics of secondary rainfall. Through multi-dimensional analysis, a series of secondary rainfall spatial differentiation characterization indicators are constructed, and based on these indicators, a watershed sediment transport forecasting method that integrates secondary rainfall spatial differentiation information is proposed, which effectively improves the accuracy and comprehensiveness of watershed sediment transport prediction. Starting from multiple dimensions such as the spatial variability of secondary rainfall in the watershed, rainfall characteristics in the rainfall core area, and underlying surface characteristics in the rainfall core area, the present invention innovatively constructs a series of secondary rainfall spatial differentiation characterization indicators. These indicators can comprehensively and effectively reflect the main influencing mechanism of secondary rainfall spatial differentiation on watershed sediment production and transport, and provide a solid foundation for the construction of subsequent sediment transport forecasting models. Based on the constructed secondary rainfall spatial differentiation characterization indicators, a watershed secondary rainfall sediment transport prediction method is established. This method incorporates the spatial differentiation characteristics of secondary rainfall into the model system. Compared with the traditional method of predicting sediment transport by sub-rainfall in a watershed, the method proposed in the present invention not only covers more key factors that affect sediment production and transport in a watershed, but also can more accurately capture the complex relationship between the spatial differentiation of sub-rainfall and sediment production and transport in a watershed, significantly improving the accuracy and reliability of the prediction model. In addition, the present invention also provides a strong technical support for in-depth revelation of the mechanism of the impact of spatial differentiation of sub-rainfall in a watershed on sediment production and transport. By integrating and applying the information on spatial differentiation of sub-rainfall, we can more accurately understand the sediment production and transport process in a watershed, and provide a scientific basis and technical guarantee for the ecological environment protection and water and soil resource management of the watershed. In order to further explain the present invention, the following specific examples are provided.

[0062] like Figure 2 As shown, Figure 2 a is the Tianshui Soil and Water Conservation Experiment Station, and b is the Lüergou Basin. First, in the arid and semi-arid area of the Loess Plateau, Lüergou (12.01 km 2) A typical small watershed was selected for the Lüergou Basin. Topographic, soil, and land use data were collected for the basin, as well as sequential rainfall, runoff, and sediment measurement data from 1982 to 2020. Sequential rainfall process data were obtained from measurements at multiple rain gauges located within and outside the basin. Traditional rainfall indicators such as rainfall amount, duration, and intensity during each period were calculated from the individual rainfall process data. The basin-wide rainfall index value was calculated using the Thiessen polygon method based on the rainfall index data from each rain gauge. Runoff and sediment data for individual rainfall events were measured by hydrological stations located at the mouth of the basin. The sub-rainfall spatial differentiation characterization index constructed by the present invention was used to calculate the sub-rainfall spatial differentiation characterization index values under successive erosive rainfall events from 1982 to 2020 in the Lüergou Basin. Based on correlation analysis, the sub-rainfall spatial differentiation characterization index with the most significant correlation with the basin sediment transport modulus was screened out. These sub-rainfall spatial differentiation characterization indicators were used to construct a basin sediment transport forecasting method that integrates sub-rainfall spatial differentiation information. Traditional sub-rainfall indicators were used to construct a basin sediment yield forecasting method that does not consider sub-rainfall spatial differentiation. The forecast accuracy and effectiveness of the two basin sediment transport forecasting methods were evaluated. After correlation analysis, it was found that, in addition to traditional secondary rainfall indicators, the spatial differentiation characterization indicators of secondary rainfall in the basin proposed in this paper are also important factors affecting the secondary rainfall runoff depth and sediment transport modulus of the basin. In addition, compared with the surface rainfall indicators, the correlation between rainfall characteristics in the core area of the rainfall and the secondary rainfall runoff depth and secondary rainfall sediment transport modulus of the basin is stronger. Among all rainfall indicators, the rainfall duration in the core area of the basin with the maximum 30-minute rainfall intensity (T CA-I30 ) is most significantly correlated with runoff depth, followed by rainfall duration (T), and then rainfall duration in the core area of the basin (T CA-P ); Basin surface rainfall dispersion coefficient ( C V-P ) has the most significant correlation with the single rainfall sediment transport modulus, followed by the basin single rainfall unevenness coefficient (η -P ) and the maximum 30-minute rainfall intensity in the core area of the basin (I 30CA-P ).

[0063] Table 1 Correlation analysis between water and sediment variables and rainfall indicators in the basin

[0064] By adopting the basin's submaximal 30-minute rainfall intensity unevenness coefficient (η -I30 ), the maximum 30-minute rainfall intensity in the core area of the basin (I 30CA-P ) and sediment connectivity in the core area of the basin's maximum 30-minute rainfall intensity (IC CA-I30) to predict the sub-rainfall sediment transport modulus (SSY) of a watershed. Based on this, a watershed sub-rainfall sediment transport prediction method (SM0, see Table 2) was developed that incorporates information on the spatial variation of sub-rainfall. Furthermore, a watershed sub-rainfall sediment transport prediction method (SM1) that does not consider spatial variation of rainfall was constructed using the basin-averaged maximum 30-minute rainfall intensity and connectivity index. This allows for a comparative study of the impact of sub-rainfall spatial variation on watershed sediment transport.

[0065] Compared with the prediction method SM1 which does not consider the spatial differentiation of rainfall ( R 2 The results of the SM0 method for predicting sediment transport in a watershed by integrating the spatial differentiation information of rainfall are shown in Table 2. R 2 The results show that the prediction value of the integrated spatial variation of rainfall is more accurate and significantly better than SM1. The above results show that the basin sediment transport prediction method that integrates the spatial variation of rainfall is more effective.

[0066] Table 2 Prediction method of sediment transport modulus of a single rainfall event in a watershed

[0067] The method for predicting watershed sediment transport by integrating sub-rainfall spatial differentiation information provided by the present invention establishes multiple sub-rainfall spatial differentiation characterization indicators based on multi-dimensional features; constructs underlying surface characteristic indicators corresponding to the rainfall core area based on sub-rainfall and underlying surface characteristics; through the correlation between sub-rainfall spatial differentiation characterization indicators and watershed sediment transport modulus and the correlation between underlying surface characteristic indicators and watershed sediment transport modulus, screens out sub-rainfall spatial differentiation characterization indicators whose correlation with watershed sediment transport exceeds a correlation threshold, and obtains highly correlated characterization indicators; and uses principal component analysis to convert highly correlated characterization indicators into mutually independent The principal components of the main components were selected, and the indicator with the highest explanatory variable among the multiple principal components was identified as the dominant secondary rainfall spatial differentiation indicator of the basin sediment transport modulus. Using the dominant secondary rainfall spatial differentiation indicator as the independent variable and the basin secondary rainfall sediment transport modulus as the dependent variable, a basin sediment transport prediction model incorporating secondary rainfall spatial differentiation information was constructed through multiple regression analysis. Basin sediment transport was then predicted using this model. A series of indicators representing secondary rainfall spatial differentiation were innovatively constructed based on multiple dimensions, including the degree of spatial variability of secondary rainfall in the basin, rainfall characteristics in the rainfall core area, and underlying surface characteristics in the rainfall core area. These indicators can comprehensively and effectively reflect the main influencing mechanisms of secondary rainfall spatial differentiation on basin sediment production and transport, providing a solid foundation for the construction of subsequent sediment transport forecast models and effectively improving the accuracy and comprehensiveness of basin sediment transport predictions.

[0068] The following describes a watershed sediment transport prediction device that integrates the spatial differentiation information of sub-rainfalls provided by the present invention. The watershed sediment transport prediction device that integrates the spatial differentiation information of sub-rainfalls described below and the watershed sediment transport prediction method that integrates the spatial differentiation information of sub-rainfalls described above can be referenced to each other.

[0069] Figure 3 This is one of the flow diagrams of the basin sediment transport prediction device that integrates the spatial differentiation information of rainfall provided by the present invention, such as Figure 3 As shown, the device includes the following: The characterization index establishment module 301 is used to establish multiple rainfall spatial differentiation characterization indices based on multi-dimensional features; wherein the multi-dimensional features include the degree of rainfall spatial variability and rainfall characteristics in the core area of the basin; An underlying surface characteristic index construction module 302 is used to construct an underlying surface characteristic index corresponding to the rainfall core area based on the rainfall and underlying surface characteristics; The correlation determination module 303 is used to screen out the sub-rainfall spatial differentiation characterization indicators whose correlation with the basin sediment transport modulus exceeds a correlation threshold based on the correlation between the sub-rainfall spatial differentiation characterization indicators and the basin sediment transport modulus and the correlation between the underlying surface characteristic indicators and the basin sediment transport modulus, thereby obtaining high-correlation characterization indicators; The module 304 for determining the dominant secondary rainfall spatial differentiation index is used to convert the highly correlated characterization indexes into mutually independent principal components using the principal component analysis method, and to determine the index with the highest explanatory variable among the multiple principal components as the dominant secondary rainfall spatial differentiation index of the basin sediment transport modulus; The watershed sediment transport prediction model construction module 305 is used to take the dominant secondary rainfall spatial differentiation index as the independent variable and the watershed secondary rainfall sediment transport modulus as the dependent variable, and to construct a watershed sediment transport prediction model that integrates the secondary rainfall spatial differentiation information through multiple regression analysis, and to predict the watershed sediment transport through the watershed sediment transport prediction model.

[0070] Optionally, the present invention provides a basin sediment transport prediction device that integrates information on spatial differentiation of rainfall events, wherein the device further includes: The basin rainfall core area determination module is used to calculate the rainfall variables of multiple rain gauges in the basin during a secondary runoff rainfall event; the rainfall variables include rainfall amount, rainfall duration, and rainfall intensity; the control area of each rain gauge is obtained using the Thiessen polygon method; the rainfall threshold is determined, and the rain gauges whose rainfall variable values are greater than the rainfall threshold are determined as selected rain gauges, and the control areas of the selected rain gauges are determined as the basin rainfall core area.

[0071] Optionally, the present invention provides a watershed sediment transport prediction device that integrates secondary rainfall spatial differentiation information, wherein the secondary rainfall spatial differentiation characterization index includes a relative rainfall variable value in the watershed rainfall core area, and a characterization index establishment module is used to establish the relative rainfall variable value in the watershed rainfall core area based on multi-dimensional characteristics; establishing the relative rainfall variable value in the watershed rainfall core area based on multi-dimensional characteristics is achieved by the following formula: Among them, SCR is the ratio of the surface rainfall variable value in the core area of the basin to the average rainfall index value of the entire basin; HCA is the average rainfall variable value in the core area of the basin; is the area average of a rainfall variable in the basin.

[0072] The present invention provides a basin sediment transport prediction device that integrates the spatial differentiation information of secondary rainfall. It establishes multiple secondary rainfall spatial differentiation characterization indicators based on multi-dimensional features; constructs underlying surface characteristic indicators corresponding to the rainfall core area based on secondary rainfall and underlying surface characteristics; through the correlation between the secondary rainfall spatial differentiation characterization indicators and the basin sediment transport modulus and the correlation between the underlying surface characteristic indicators and the basin sediment transport modulus, the secondary rainfall spatial differentiation characterization indicators whose correlation with the basin sediment transport exceeds the correlation threshold are screened out to obtain highly correlated characterization indicators; and the principal component analysis method is used to convert the highly correlated characterization indicators into mutually correlated ones. Independent principal components were used. The indicator with the highest explanatory variable among multiple principal components was identified as the dominant secondary rainfall spatial differentiation indicator for the basin sediment transport modulus. Using the dominant secondary rainfall spatial differentiation indicator as the independent variable and the basin secondary rainfall sediment transport modulus as the dependent variable, a basin sediment transport prediction model incorporating secondary rainfall spatial differentiation information was constructed through multiple regression analysis. Basin sediment transport was then predicted using this model. A series of indices representing secondary rainfall spatial differentiation were innovatively constructed based on multiple dimensions, including the degree of spatial variability of secondary rainfall in the basin, rainfall characteristics in the rainfall core area, and underlying surface characteristics in the rainfall core area. These indices can comprehensively and effectively reflect the primary influencing mechanisms of secondary rainfall spatial differentiation on basin sediment production and transport, providing a solid foundation for the construction of subsequent sediment transport forecast models and effectively improving the accuracy and comprehensiveness of basin sediment transport predictions.

[0073] Figure 4 An example of a physical structure diagram of an electronic device is shown below. Figure 4 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. The processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call logic instructions in the memory 830 to execute a watershed sediment transport prediction method that incorporates information on spatial variation of rainfall events.

[0074] Furthermore, the logic instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0075] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the basin sediment transport prediction method that integrates the spatial differentiation information of sub-rainfall provided by the above methods.

[0076] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the basin sediment transport prediction method provided by the above-mentioned methods that integrates the spatial differentiation information of sub-rainfall.

[0077] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0078] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A basin sediment transport prediction method integrating spatial differentiation information of rainfall events, characterized by: include: Establish multiple rainfall spatial differentiation characterization indicators based on multi-dimensional characteristics; wherein the multi-dimensional characteristics include the degree of rainfall spatial variability and rainfall characteristics in the core area of the basin; Based on the rainfall and underlying surface characteristics, the underlying surface characteristic index corresponding to the rainfall core area is constructed; Through the correlation between the spatial differentiation characterization index of rainfall and the watershed sediment transport modulus and the correlation between the underlying surface characteristic index and the watershed sediment transport modulus, the spatial differentiation characterization index of rainfall whose correlation with the watershed sediment transport exceeds the correlation threshold is screened out to obtain a high correlation characterization index; The principal component analysis method is used to convert the highly correlated characterization indicators into mutually independent principal components, and the indicator with the highest explanatory variable among the plurality of principal components is determined as the dominant secondary rainfall spatial differentiation indicator of the sediment transport modulus of the basin; Taking the dominant secondary rainfall spatial differentiation index as the independent variable and the secondary rainfall sediment transport modulus of the watershed as the dependent variable, a watershed sediment transport prediction model integrating the secondary rainfall spatial differentiation information is constructed through multiple regression analysis, and the basin sediment transport is predicted using the watershed sediment transport prediction model.

2. The basin sediment transport prediction method integrating spatial differentiation information of rainfall events according to claim 1 is characterized in that: Also includes: Calculating rainfall variables at multiple rain gauges in a watershed during a secondary runoff rainfall event; wherein the rainfall variables include: rainfall amount, rainfall duration, and rainfall intensity; The control area of each rain gauge was obtained using the Thiessen polygon method; A rainfall threshold is determined, a rain gauge station whose value of the rainfall variable is greater than the rainfall threshold is determined as a selected rain gauge station, and a control area of the selected rain gauge station is determined as a rainfall core area of the watershed.

3. The basin sediment transport prediction method integrating spatial differentiation information of rainfall events according to claim 1 is characterized in that: The secondary rainfall spatial differentiation characterization index includes a relative rainfall variable value in the core area of the basin rainfall. The establishment of multiple secondary rainfall spatial differentiation characterization indexes based on multi-dimensional features includes: establishing a relative rainfall variable value in the core area of the basin rainfall based on the multi-dimensional features; the establishment of the relative rainfall variable value in the core area of the basin rainfall based on the multi-dimensional features is achieved by the following formula: Among them, SCR is the ratio of the surface rainfall variable value in the core area of the basin to the average rainfall index value of the entire basin; HCA is the average rainfall variable value in the core area of the basin; is the area average of a rainfall variable in the basin.

4. The basin sediment transport prediction method integrating spatial differentiation information of rainfall events according to claim 1 is characterized in that: The sub-rainfall spatial differentiation characterization index includes a sediment connectivity index value of the basin rainfall core area. The establishment of multiple sub-rainfall spatial differentiation characterization indexes based on multi-dimensional characteristics includes: establishing a sediment connectivity index value of the basin rainfall core area based on multi-dimensional characteristics; the establishment of the sediment connectivity index value of the basin rainfall core area based on multi-dimensional characteristics is achieved by the following formula: IC is the sediment connectivity index, which ranges from [-∞, +∞]. The larger the value, the better the sediment connectivity and the stronger the sediment production and transport capacity. D up 、 D dn represent the upslope and downslope components respectively; W i For the i The weight factor of each grid cell is assigned using the C factor of RUSLE, which mainly reflects the influence of vegetation cover; S i For the i The slope of the grid unit (m / m); A is the i The upslope catchment area of each grid cell (m 2 ); d i For the i Length of the confluence path from each grid cell to the nearest river channel or sedimentation area (m); For the i The average upslope weight factor of each grid cell; For the i The average upslope slope of each grid cell (m / m).

5. A basin sediment transport prediction device integrating spatial differentiation information of rainfall events, characterized in that: include: A characterization index establishment module is used to establish multiple rainfall spatial differentiation characterization indicators based on multi-dimensional features; wherein the multi-dimensional features include the degree of rainfall spatial variability and rainfall characteristics in the core area of the basin; The underlying surface characteristic index construction module is used to construct the underlying surface characteristic index corresponding to the rainfall core area based on the rainfall and underlying surface characteristics; a correlation determination module for screening out the sub-rainfall spatial differentiation characterization index having a correlation with the watershed sediment transport modulus exceeding a correlation threshold through the correlation between the sub-rainfall spatial differentiation characterization index and the watershed sediment transport modulus and the correlation between the underlying surface characteristic index and the watershed sediment transport modulus, thereby obtaining a highly correlated characterization index; A module for determining the dominant secondary rainfall spatial differentiation index is used to convert the highly correlated characterization indexes into mutually independent principal components using a principal component analysis method, and determine the index with the highest explanatory variable among the plurality of principal components as the dominant secondary rainfall spatial differentiation index of the basin sediment transport modulus; A watershed sediment transport prediction model construction module is used to take the dominant secondary rainfall spatial differentiation index as the independent variable and the watershed secondary rainfall sediment transport modulus as the dependent variable, and to construct a watershed sediment transport prediction model integrating the secondary rainfall spatial differentiation information through multiple regression analysis, and to predict the watershed sediment transport through the watershed sediment transport prediction model.

6. The basin sediment transport prediction device integrating spatially differentiated rainfall information according to claim 5 is characterized in that: Also includes: The basin rainfall core area determination module is used to calculate the rainfall variables of multiple rain gauges in the basin during a secondary runoff rainfall event; wherein the rainfall variables include: rainfall amount, rainfall duration and rainfall intensity; obtain the control area of each rain gauge using the Thiessen polygon method; determine the rainfall threshold, and determine the rain gauge whose value of the rainfall variable is greater than the rainfall threshold as the selected rain gauge, and determine the control area of the selected rain gauge as the basin rainfall core area.

7. The basin sediment transport prediction device integrating the spatial differentiation information of rainfall events according to claim 5 is characterized in that: The secondary rainfall spatial differentiation characterization index includes a relative rainfall variable value in the core area of the basin rainfall. The characterization index establishment module is used to establish the relative rainfall variable value in the core area of the basin rainfall based on multi-dimensional features. The establishment of the relative rainfall variable value in the core area of the basin rainfall based on multi-dimensional features is achieved by the following formula: Among them, SCR is the ratio of the surface rainfall variable value in the core area of the basin to the average rainfall index value of the entire basin; HCA is the average rainfall variable value in the core area of the basin; is the area average of a rainfall variable in the basin.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the basin sediment transport prediction method integrating sub-rainfall spatial differentiation information as described in any one of claims 1 to 4 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for predicting watershed sediment transport by integrating spatial differentiation information of sub-rainfall is implemented as claimed in any one of claims 1 to 4.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for predicting watershed sediment transport by integrating spatial differentiation information of sub-rainfall is implemented as claimed in any one of claims 1 to 4.

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