A method for constructing a prediction model for relative length of the shore line under low water flow of an alluvial river

Abstract

The application discloses a kind of alluvial river dry flow under shore line relative length prediction model construction method.Belongs to the technical field of water conservancy and hydropower engineering, specific steps include: collecting the hydrological data of the hydrological year of the upstream hydrological station of alluvial river and the measured terrain data after flood season;According to the actual length of the shore line measured by remote sensing image;Utilize the ratio of the average value of left and right shore lines and the river section flat water depth, construct the relative length of river channel shore line, analyze and calculate the correlation between the relative length of shore line under dry flow and the average sediment transport rate of the previous 6 years of hydrological station, and establish the prediction model of the relative length of shore line under dry flow of alluvial river.The application proposes a method for determining the relative length of shore line based on measured terrain and remote sensing image data, fully considers the cumulative influence of water and sediment conditions, proposes a new type of shore line relative length prediction model, which can accurately predict the trend of the relative length of shore line under dry flow of alluvial river, and has far-reaching guiding significance for river management and river regulation planning.

Description

Technical Field

[0001] This invention belongs to the field of water conservancy and hydropower engineering technology, and relates to a method for constructing a prediction model of the relative length of the shoreline under low water flow in alluvial rivers. Background Technology

[0002] Riverbanks are the boundary between alluvial river water and the land on both banks, and their changing trends have a significant impact on river flood control, the aquatic ecological environment, and industrial and agricultural water use. Therefore, constructing models to predict the relative length of riverbanks is of great importance for watershed management and river regulation planning. Currently, research on riverbanks mainly falls into two categories: one is based on the analysis of measured data or remote sensing imagery to study the erosion and collapse processes of the banks, thereby predicting the trend of changes in the length of alluvial riverbanks; the second is based on two-dimensional hydro-sediment mathematical models to simulate local changes in the riverbank. However, the first type of method is usually suitable for studying long-term, large-scale riverbank changes, while the second type is suitable for studying localized riverbank adjustments and cannot predict long-term, large-scale changes in riverbank length. Therefore, it is necessary to combine measured data with remote sensing imagery, fully consider the influence of hydro-sediment conditions, and propose a new predictive model for the relative length of riverbanks. Summary of the Invention

[0003] The purpose of this invention is to propose a new statistical prediction model based on satellite-measured shoreline data, measured topographic data and water and sediment data of river sections after the flood season, so as to more accurately predict the relative length of shoreline under the annual dry season of alluvial rivers.

[0004] The technical solution of the present invention: The method for constructing a prediction model of the relative length of the shoreline under low flow conditions in alluvial rivers, as described in the present invention, comprises the following specific construction steps:

[0005] Step (1): Collect hydrological data from hydrological stations in the upper reaches of alluvial rivers for the year and measured topographic data of each sedimentation section in the river after the flood season;

[0006] Step (2): Select an upstream hydrological station 500m away. 3 / s represents the low-water flow rate. Satellite remote sensing images meeting the low-water flow rate requirements were selected based on the daily average flow data. Preprocessing of the selected remote sensing images, including geometric correction, radiometric calibration, atmospheric correction, image enhancement, and batch cropping, was performed using ENVI and ArcGIS software. The riverbank was then drawn using ArcGIS software, and the actual left bank distance L1 and the actual right bank distance L2 were measured. The average value of these two values ​​was calculated.

[0007] Step (3): Using the average value With the river section flat beach water depth The ratio of the two values ​​is used to construct the relative length I of the riverbank;

[0008] Step (4): Calculate the annual average sediment transport rate Q of the hydrological station in the hydrological year. s The analysis yielded the relationship between the relative length of the shoreline (I) under low water flow and the average sediment transport rate of the hydrological station over the previous 6 years. Based on the relationship, a predictive model for the relative length of the shoreline under low-flow conditions in alluvial rivers is constructed.

[0009] Furthermore, in step (1), the hydrological data includes the average daily flow and average daily sediment concentration of the hydrological station in the upper reaches of the alluvial river during the hydrological year;

[0010] The measured topographic data after the flood includes the distance and elevation of each siltation section from the left bank.

[0011] Furthermore, in step (2), the formula for calculating the average value of the actual lengths of the left and right banks of the river is:

[0012]

[0013] In the formula: The values ​​represent the average actual lengths of the left and right banks of the river, in meters. L1 represents the actual length of the left bank, in meters; L2 represents the actual length of the right bank, in meters.

[0014] Wherein: the flat water depth H of the siltation observation section is equal to the arithmetic mean of the water depths of all nodes below the flat water level of the section.

[0015] Furthermore, in step (3), the flat-shoal water depth at the river section scale... The calculation formula is:

[0016]

[0017] In the formula: This indicates the average depth of the riverbed in the flat area, in meters (m) or liters (L). X The total length of the river segment is expressed in km; K represents the number of measured cross-sections within the river segment; Δx j H represents the distance between two adjacent cross sections (j, j+1), in km. j H j+1 This indicates the water depth at the flat beach at sections j and j+1, in meters.

[0018] Furthermore, in step (3), the formula for calculating the relative length I of the riverbank is:

[0019]

[0020] In the formula: I represents the relative length of the riverbank; This represents the average actual length of the left and right banks of the river, in meters (m). This indicates the average depth of the riverbed in the flat area, in meters (m).

[0021] Furthermore, in step (4), the annual average sediment transport rate Q of the hydrological station in the hydrological year is... s The calculation formula is:

[0022] Q s =Q×S

[0023] In the formula: Q represents the annual average flow rate of the hydrological station in a given year, in cubic meters per second (m³). 3 / s, where S represents the annual average sediment concentration of the hydrological station in the hydrological year, in kg / m³. 3 .

[0024] Among them: the average sediment transport rate of the hydrological station in the previous 6 years This is the arithmetic average of the sediment transport rate for that year and the previous five years at the hydrological station.

[0025] Furthermore, in step (4), the prediction model for the relative length of the shoreline under low flow conditions in the alluvial river includes the upstream hydrological station 500m. 3 The low-water flow rate of / s was used as the standard to download a qualified satellite remote sensing image. The actual lengths of the left and right banks of the alluvial river were obtained from the remote sensing image, and the average value was calculated. Using the average value With the river section flat beach water depth The ratio of the two values ​​is used to construct the relative length I of the riverbank; based on the annual average flow Q and annual average sediment concentration S of the upstream hydrological station, the average sediment transport rate of the hydrological station in the previous 6 years is calculated. The correlation between the relative length of the riverbank and the average sediment transport rate over the previous 6 years was analyzed, and a prediction model for the relative length of the shoreline under low flow conditions in alluvial rivers was established.

[0026] The method for constructing the prediction model for the relative length of the shoreline under low water flow in alluvial rivers includes:

[0027]

[0028] In the formula, k represents the coefficient and m represents the exponent.

[0029] Furthermore, based on the alluvial river shoreline length data obtained from satellite images, hydrological data from upstream hydrological stations, and measured topographic data of various siltation sections in the river section after the flood season, a nonlinear regression analysis strategy was adopted to calibrate and verify the k and m parameters in the prediction model.

[0030] The beneficial effects of this invention are as follows: This invention utilizes remote sensing imagery and topographic data to propose a method for determining the relative length of the shoreline under low-flow conditions in alluvial rivers. It fully considers the cumulative impact of previous water and sediment conditions on the relative length of the shoreline and establishes a statistical model of the relative length of the shoreline and the average sediment transport rate of the upstream hydrological station over the previous 6 years. The constructed statistical model can accurately reflect and predict the changing trend of the relative length of the shoreline under low-flow conditions in alluvial rivers over a long time scale, and has profound guiding significance for river management and river channel regulation planning. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the method for determining the post-flood plain water depth at the Xiagujie siltation observation section in the lower reaches of the Yellow River, which is a method for constructing a prediction model for the relative length of the shoreline under low-water flow in alluvial rivers, as provided in an embodiment of the present invention.

[0032] Figure 2 The diagram shows the variation of the average sediment transport rate of the Huayuankou hydrological station in the lower reaches of the Yellow River from 1986 to the first six years of 2018, which is a method for constructing a prediction model of the relative length of the shoreline under low flow in alluvial rivers provided in this embodiment of the invention.

[0033] Figure 3 The diagram shows the correlation between the relative length of the meandering section of the lower Yellow River and the average sediment transport rate of the Huayuankou section over the previous 6 years, as part of a method for constructing a prediction model for the relative length of the shoreline under low flow conditions in alluvial rivers, as provided in this embodiment of the invention.

[0034] Figure 4 This is a comparison chart of calculated and measured values ​​of the relative length of the shoreline in the wandering section of the lower Yellow River, which is a method for constructing a prediction model of the relative length of the shoreline under low flow conditions in an alluvial river, as provided in an embodiment of the present invention.

[0035] Figure 5 This is a flowchart illustrating the operation of the present invention. Detailed Implementation

[0036] To more clearly illustrate the technical solution of the present invention, the technical solution of the present invention will be further described in detail below with reference to the accompanying drawings:

[0037] Example 1

[0038] Reference Figures 1-2 As an embodiment of the present invention, a method for constructing a prediction model of the relative length of the shoreline under low flow conditions in alluvial rivers is provided, and the specific construction steps are as follows:

[0039] S1: Collect hydrological data from hydrological stations in the upper reaches of alluvial rivers for the hydrological year, as well as the distance and elevation of each sedimentary section from the left bank after the flood season; it should be noted that:

[0040] Hydrological data includes the daily average flow and daily average sediment concentration of the hydrological station for the hydrological year. The annual average flow and annual average sediment concentration for the hydrological year are calculated from the daily average data. The upstream hydrological station is selected at a depth of 500m. 3 / s represents the low water flow rate. Satellite remote sensing images that meet the low water flow rate requirements are selected based on the daily average flow data. In this embodiment, the wandering section of the lower Yellow River is taken as the research section. The annual average flow and annual average sediment concentration of the Neihuayuankou Hydrological Station from 1986 to 2018 are collected. Measured topographic data of 28 siltation sections in the wandering section of the lower Yellow River are also collected.

[0041] S2: Based on the satellite remote sensing image, identify the left and right shorelines and measure their actual lengths, then calculate the average of the actual lengths of the left and right shorelines; it should be noted that:

[0042] In this embodiment, the satellite remote sensing image is preprocessed using ENVI software, and then ArcGIS software is used to mark the left and right bank lines in the preprocessed satellite remote sensing image and complete the distance measurement. By marking the left bank line L1 of the wandering section of the lower Yellow River in 1986, L1 = 335.253 km was measured in 1986. This step was repeated to measure L2 = 331.019 km in 1986, until the distance measurement of the satellite remote sensing image in 2018 was completed.

[0043] The formula for calculating the average actual length of the left and right banks of a river is:

[0044]

[0045] In the formula: L1 is the actual length of the left bank of the river; L2 is the actual length of the right bank of the river.

[0046] S3: Determine the floodplain water depth at each siltation section based on measured topographic data, and calculate the average floodplain water depth of the river segment using a segment averaging strategy; it should be noted that:

[0047] In this embodiment, as Figure 1 As shown, the water level at which the river floodplain is level with the floodplain is called the floodplain water level. Based on the measured topography, the water depth of all nodes below the floodplain water level is calculated by arithmetic average to obtain the floodplain water depth of the siltation section. Therefore, the floodplain water depth H of Xiagujie after the flood in 2018 was 3.91m.

[0048] The surface water depth of 28 siltation observation sections in the wandering section of the lower Yellow River was determined using the above method.

[0049] The average depth of the flatlands at 28 siltation sections in the meandering section of the lower Yellow River is calculated using the following formula:

[0050]

[0051] In the formula: This indicates the average depth of the riverbed in the flat area, in meters (m) or liters (L). X K represents the total length of the river segment, in km; K represents the number of measured cross-sections within the river segment; Δx j H represents the distance between two adjacent cross sections (j, j+1), in km. j H j+1 The depth of the flat beach at sections j and j+1 is expressed in meters.

[0052] S4: Construct the relative length I of the shoreline using the average of the actual lengths of the left and right shorelines and the water depth of the riverbed. It should be noted that:

[0053] The formula for calculating the relative length I of the shoreline is:

[0054]

[0055] In the formula: This is the average of the actual lengths of the left and right banks of the river, in meters. The average depth of the riverbed in the flat area, in meters;

[0056] S5: The annual average sediment transport rate of the Huayuankou hydrological station is calculated using the annual average flow and annual average sediment concentration for each hydrological year. It should be noted that:

[0057] The formula for calculating the annual average sediment transport rate of this hydrological station is as follows:

[0058] Q s =Q×S

[0059] In the formula: Q is the annual average flow rate of the hydrological station in the hydrological year, in m³. 3 / s, where S is the annual average sediment concentration of the hydrological station in the hydrological year, in kg / m³. 3 The arithmetic average of the sediment transport rates of that year and the previous five years at the hydrological station is used to obtain the average sediment transport rate for the preceding six years. like Figure 2 The above;

[0060] S6: The correlation between the relative length of the riverbank and the average sediment transport rate over the previous 6 years was analyzed and calculated, and a predictive model for the relative length of the shoreline under low-flow conditions in alluvial rivers was constructed; it should be noted that:

[0061] Constructing a predictive model for the relative length of the shoreline under low-flow conditions in alluvial rivers includes:

[0062] (1) After preprocessing the satellite remote sensing image using ENVI software, ArcGIS software is used to mark the left and right shorelines in the preprocessed satellite remote sensing image and complete the distance measurement to obtain the values ​​of the left shoreline L1 and the right shoreline L2.

[0063] (2) such as Figure 1 and Figure 2 As shown, based on the topographic data of the 28 post-flood sedimentation observation sections, the flat-shoal water depth of each sedimentation observation section was determined, and the flat-shoal water depth at the river section scale was calculated by substituting the data into the formula. Based on the annual average flow and annual average sediment concentration of the upstream hydrological station, the average sediment transport rate of Huayuankou over the previous 6 years was calculated.

[0064] (3) By constructing the relative length I of alluvial river shoreline and the average sediment transport rate of the previous 6 years. Based on the correlation, a predictive model for the relative length of the shoreline under low flow conditions in alluvial rivers was established;

[0065] The average sediment transport rate of the upstream Huayuankou hydrological station over the previous 6 years Using the relative length I of the meandering shoreline in the lower reaches of the Yellow River as the dependent variable, a predictive model for the relative length of the shoreline under low-water flow conditions in alluvial rivers is constructed:

[0066]

[0067] In the formula, k represents the coefficient and m represents the exponent;

[0068] (4) Based on the annual average flow and annual average sediment concentration data of the hydrological station and the flat beach water depth data obtained from the topographic data of each sedimentation observation section after the flood season, the k and m parameters in the prediction model are calibrated and verified by nonlinear regression analysis strategy.

[0069] Example 2

[0070] Reference Figure 3 This embodiment is the second embodiment of the present invention. Unlike the first embodiment, this embodiment provides a verification and testing method for constructing a prediction model of the relative length of the shoreline under low flow conditions in alluvial rivers. The technical effects of the method are verified and explained. Based on the average sediment transport rate data and the relative length data of the shoreline of the wandering section of the lower Yellow River from 1986 to 2018 at the Huayuankou hydrological station, a nonlinear regression analysis strategy is used to calibrate the k and m parameters in the prediction model. The calibrated k and m are 6122.584 and 0.362, respectively. The model is verified using data from 2002 to 2004.

[0071] The calibration and validation results of the model show that: Figure 3 The correlation coefficient between the relative length of the shoreline of the wandering section in the lower reaches of the Yellow River and the average sediment transport rate over the previous 6 years reached 0.91. Therefore, the constructed model can predict the adjustment trend of the relative length of the shoreline under low flow conditions in the wandering section of the lower reaches of the Yellow River.

[0072] To verify the empirical formula, Figure 4 The calculated and measured values ​​of the relative length of the shoreline under low flow in the meandering section of the lower Yellow River are given. As can be seen from the figure, the changing trends of the calculated and measured values ​​of the relative length of the shoreline under low flow in the meandering section of the lower Yellow River are basically consistent.

[0073] Finally, it should be understood that the embodiments described in this invention are only used to illustrate the principles of the embodiments of this invention; other variations may also fall within the scope of this invention; therefore, as examples rather than limitations, alternative configurations of the embodiments of this invention can be regarded as consistent with the teachings of this invention; correspondingly, the embodiments of this invention are not limited to the embodiments explicitly introduced and described in this invention.

Claims

1. A method for constructing a prediction model for the relative length of shoreline in alluvial rivers under low-water flow conditions, characterized in that, The specific design steps are as follows: Step (1): Collect hydrological data from hydrological stations in the upper reaches of alluvial rivers for the hydrological year and measured topographic data after the flood season; Step (2): Select an upstream hydrological station 500m away. 3 / s represents the low-water flow rate. Satellite remote sensing images meeting the low-water flow rate requirements are selected based on daily average flow data. Using ENVI and ArcGIS software, the required remote sensing images undergo geometric correction, radiometric calibration, atmospheric correction, image enhancement, and batch cropping preprocessing. The coordinate system of the processed remote sensing images is the WGS84 projected coordinate system. The riverbank lines are drawn, and the actual left bank distance L1 and actual right bank distance L2 are measured. The average value of these two distances is then calculated. Step (3): Using the average value With the river section flat beach water depth The ratio of the two values ​​is used to construct the relative length I of the riverbank; The river section has shallow water depth. The calculation formula is: In the formula, L represents the average depth of the riverbed in the flat area. X K represents the total length of the river section; K represents the number of measured cross sections within the river section; Δx j H represents the distance between two adjacent cross sections (j, j+1); j H j+1 This represents the water depth at the flat beach at sections j and j+1. The formula for calculating the relative length I of the riverbank is: In the formula, I represents the relative length of the riverbank; This represents the average actual length of the left and right banks of the river. This indicates the average depth of the riverbed in the flat area. Step (4): Calculate the annual average sediment transport rate Q of the hydrological station in the hydrological year. s The analysis yielded the relationship between the relative length of the shoreline (I) under low water flow and the average sediment transport rate of the hydrological station over the previous 6 years. Based on the relationship, a predictive model for the relative length of the shoreline under low flow conditions in alluvial rivers is constructed; The average annual sediment transport rate Q of the hydrological station in the hydrological year s The calculation formula is: Q s =Q×S In the formula: Q represents the annual average flow rate of the hydrological station in a hydrological year; S represents the annual average sediment concentration of the hydrological station in a hydrological year; Among them, the average sediment transport rate of the hydrological station in the previous 6 years This is the arithmetic average of the sediment transport rate for that year and the previous five years at the hydrological station; The specific formula for predicting the relative length of the shoreline under low water flow in alluvial rivers is as follows: In the formula, k represents the coefficient and m represents the exponent; The average sediment transport rate for the previous 6 years was calculated based on the annual average flow and annual average sediment concentration of the hydrological station. The k and m parameters in the prediction model were calibrated and verified using a nonlinear regression analysis strategy.

2. The method for constructing a prediction model for the relative length of shoreline under low-flow conditions in alluvial rivers according to claim 1, characterized in that, In step (1), the hydrological data includes the daily average flow and daily average sediment concentration of the hydrological station in the upper reaches of the alluvial river during the hydrological year; The measured topographic data after the flood includes the distance and elevation of each siltation section from the left bank.

3. The method for constructing a prediction model for the relative length of shoreline under low flow conditions in alluvial rivers according to claim 1, characterized in that: In step (2), the formula for calculating the average value of the actual lengths of the left and right banks of the river is: In the formula: L1 represents the actual length of the left bank of the river; L2 represents the actual length of the right bank of the river.

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