A method for determining the outflow threshold of river channels in river-controlled estuaries based on improved entropy weight method

Abstract

The present invention discloses a method for determining the outflow threshold value of a river channel in a river-controlled estuary based on an improved entropy weight method, comprising the following steps: S1: collecting historical topographic data of a fixed section of a main stream channel at the tail end of a river-controlled estuary, and historical daily average hydrological data of hydrological stations along the channel; S2: applying the improved entropy weight method to the main stream channel at the tail end of the estuary based on the hydrological and topographic data, calculating the contribution weights of different indicators in water-sediment conditions and riverbed boundary conditions to the outflow of the channel, and identifying the main controlling factors of the outflow of the channel according to the calculation results; S3: establishing a prediction model for the outflow threshold value of an estuary channel under the joint control of riverbed boundary conditions and water-sediment conditions based on the main controlling factors of the outflow; the present invention simplifies the calculation method of the outflow threshold value and greatly improves the applicability of the method; the present invention proposes a method for determining the outflow threshold value of an estuary channel by considering water-sediment and boundary conditions at the same time, which can be applied to river-controlled estuaries with different outflow periods, and provides guidance for estuary flood control and river channel management.

Description

Technical Field

[0001] The present invention belongs to the technical field of water conservancy and hydropower engineering, and in particular relates to a method for determining a river channel outflow threshold value at a tail section based on an improved entropy weight method. Background Art

[0002] Channel divergence in river-controlled estuaries typically results from localized avulsions in the upper tailgate of an estuarine delta. This phenomenon occurs when the channel near the tailgate suddenly abandons its original path to the sea and enters the sea through a new outlet. From a geological and geomorphological perspective, channel divergence, a crucial process in riverbed evolution in the tailgate of an estuary, significantly influences channel morphology, as it determines the distribution of sediment and water within the channel. From a socioeconomic perspective, frequent channel divergence in estuaries significantly harms the ecological benefits of the delta. The channel divergence threshold is a key parameter used to quantitatively determine whether a channel diverges in an estuary. Therefore, research on methods to determine this threshold is crucial.

[0003] There are few research results on the threshold of river channel outflow in river-controlled estuaries at home and abroad. The existing results not only use complex parameter combinations, but also have great difficulties in practical application. Most of them use indicators related to riverbed boundary conditions to determine the threshold of river channel outflow in estuaries. This is because the time period of river channel outflow in most estuaries in the world is generally 10 2 -10 3 The period is long, so when constructing river channel branching indicators, the non-constant water and sediment conditions in natural rivers are often ignored. It can be seen that these methods for determining the river channel branching threshold value at the estuary based on riverbed boundary conditions are bound to have certain limitations when applied to rivers with shorter river channel branching time periods. For example, the river channel branching threshold determination method applicable to the Mississippi River Estuary and the Madagascar River Estuary can have a certain degree of discrimination accuracy under branching time periods of thousands of years, but for the tail section of the Yellow River Estuary with a river channel branching time period of about 10 years, this method is not completely applicable. At this stage, it is urgent to propose a river channel branching threshold determination method that comprehensively considers riverbed boundary conditions and water and sediment conditions and is applicable to various branching time periods. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for determining the branching threshold of a river channel in a river-controlled estuary based on an improved entropy weight method. Based on this method, the branching threshold of a specific estuary channel is calculated, and it is possible to quantitatively determine whether a estuary channel will branch out.

[0005] To achieve the above objectives, the technical solution of the present invention is:

[0006] The method for determining the outflow threshold of a river channel in a river-controlled estuary based on the improved entropy weight method includes the following steps:

[0007] S1: Collect historical topographic data of fixed sections of the main stream of the river-controlled estuary, and historical daily average hydrological data of hydrological stations along the river;

[0008] S2: Based on hydrological and topographic data, the improved entropy weight method is applied to the main channel of the estuary tailwater, and the contribution weights of different indicators in water and sediment conditions and riverbed boundary conditions to the river outflow are calculated. The main controlling factors of the river outflow are identified based on the calculation results;

[0009] S3: Based on the main controlling factors of branching, a prediction model for the branching threshold of the estuary river channel is established under the joint control of riverbed boundary conditions and water and sediment conditions.

[0010] Furthermore, in the above-mentioned step S1, the topographic data include the starting point distance and elevation of the cross-section measuring point, as well as the cross-section spacing; the hydrological data include the average daily flow and sediment content.

[0011] Furthermore, the step S2 specifically includes the following steps:

[0012] S2.1: Determine the water, sediment and boundary condition index system;

[0013] S2.2: Using the theory and method of information entropy, we introduce the information entropy and grouping of indicators related to the outflow of the river channel at the tail end of the estuary. The grouping refers to the actual observation data of the natural river channel grouped by year, and establish an initial matrix of water, sediment and boundary condition indicators;

[0014] S2.3: Normalize the indicators related to water and sediment conditions and riverbed boundary conditions;

[0015] S2.4: Logistic regression analysis method was used to obtain and The outgoing probability P between the outgoing code Y;

[0016] S2.5: Calculate the proportions and entropy values ​​of different indicators in water-sediment conditions and riverbed boundary conditions.

[0017] Furthermore, the specific calculation method of the proportion and entropy value of different indicators in the water and sediment conditions and riverbed boundary conditions is:

[0018] Let the proportion of the βth index value under the αth index in the αth index be P' αβ , let the information entropy of the β-th indicator be E β φ represents the index with the largest contribution weight in the riverbed boundary conditions, and ψ represents the index with the largest contribution weight in the water and sediment conditions. That is, φ and ψ are the main controlling factors of river outflow;

[0019] The proportion of the βth index value under the αth index in the αth index is P' αβ The information entropy of the β-th index is E β The calculation formula is:

[0020] P' αβ and E β The calculation formula is:

[0021]

[0022] Where: y αβ Indicates g αβ or q αβ The formula for calculating the contribution weight of water and sediment conditions and riverbed boundary conditions to the river outflow is:

[0023]

[0024] Where: k is the number of indicators.

[0025] Furthermore, the S3 step specifically includes the following steps:

[0026] S3.1: Use φ and ψ to construct the channel boundary equation:

[0027] φ=aψ b

[0028] Where: a, b are unknown coefficients;

[0029] φ represents the index with the largest contribution weight in the riverbed boundary conditions, and ψ represents the index with the largest contribution weight in the water and sediment conditions. φ and ψ are the main controlling factors of river outflow.

[0030] S3.2: Evaluate the reliability of the estuary-channel boundary equation; introduce the parameter λ to evaluate the reliability of the boundary equation:

[0031]

[0032] Where: λ is the boundary parameter; N c is the number of points in the correct boundary area in the coordinate system; N w The number of points in the wrong boundary area of ​​the coordinate system; N T is the total number of points;

[0033] When the value of λ is greater than 0.5, the equation of the river branch boundary is accurate and reasonable;

[0034] S3.3: Obtain the threshold value of the estuary channel; Under the premise of λ>0.5, the channel channel boundary equation is transformed to obtain the estuary channel channel threshold prediction model ACI=φψ -b =a;

[0035] Where: ACI refers to the "river channel branching index value", a is the river channel branching threshold, φ represents the index with the largest contribution weight in the riverbed boundary conditions, and ψ represents the index with the largest contribution weight in the water and sediment conditions. When the river channel branching index value ACI of a certain year is ≥ a, it means that the estuary river channel has branched.

[0036] Furthermore, in the step S3.3, the values ​​of a and b are calculated based on the historical data values ​​of φ and ψ, and the value of a is the threshold value for determining whether the river has branched.

[0037] ACI YRE =Фψ -b ,ACI YRE Calculate ACI for the river outflow index value in a certain year YRE When the value is calculated, take the main control factor φ value in the water and sediment index system of that year and the main control factor ψ value in the boundary condition index system, such as the calculated ACI YRE When it is greater than or equal to the value a, it is determined that the river has branched out in the corresponding year.

[0038] The beneficial effects of the present invention are:

[0039] (1) The present invention adopts the logistic regression analysis method suitable for describing and testing binary result variables to improve the traditional entropy weight method, which can better objectively and quantitatively identify the control factors of estuary river channel outflow, making up for the defect that the influencing factors of estuary river channel outflow can only be studied qualitatively based on historical data in the past; and the parameter combination used in previous studies is relatively complex, which leads to great difficulties in practical application. The improved entropy weight method used in the present invention to quantitatively identify the main controlling factors of river channel outflow can simplify the calculation method of obtaining the outflow threshold, greatly improving the applicability of the method.

[0040] (2) Previous studies only emphasized the role of riverbed boundary conditions in the process of estuary river channel branching. The present invention takes into account both water and sediment and boundary conditions and proposes a method for determining the estuary river channel branching threshold. This method can be well applied to river-controlled estuaries with different branching cycles, and provides guidance for estuary flood control and river channel management. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of the present invention.

[0042] Figure 2 This is a schematic diagram of the boundary of the Yellow River estuary's tail section. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the invention clearer, the present invention is further described below with reference to the accompanying drawings.

[0044] The magnitude of the channel branching threshold in river-controlled estuaries is related to water and sediment conditions and riverbed boundary conditions. In natural rivers, channel branching generally needs to meet two basic requirements: first, the riverbed boundary conditions reach a certain critical state, such as a decrease in the channel's flow capacity or increased instability in a local river section; second, the flood magnitude during the flood season is large enough or lasts for a long time, such as a major flood event. The closer the river channel at the tail end of the estuary approaches these two basic requirements during its evolution, the more likely the channel branching will swing. Therefore, the channel branching threshold at the estuary can be obtained from water and sediment conditions and boundary conditions, but the difficulty lies in how to quantitatively determine the main controlling factors of channel branching, thereby establishing a convenient, concise and effective method for determining the channel branching threshold.

[0045] The present invention adopts an improved entropy weight method to identify the main controlling factors of estuarine river channel outflow; firstly, based on the main controlling factors of outflow, a prediction model of the outflow threshold of estuarine river channel is established under the joint control of riverbed boundary conditions and water and sediment conditions; secondly, the parameters in the model are calibrated and verified using the measured historical water, sediment and topographic data of river-controlled estuary channels to prove the applicability of this method.

[0046] To achieve the above-mentioned object, the present invention provides a method for determining the outflow threshold of a river channel in a river-controlled estuary based on an improved entropy weight method, comprising the following steps:

[0047] Step 1: Collect historical topographic data of fixed sections of the main stream of the river at the tail section of the river-controlled estuary, as well as historical daily average hydrological data of hydrological stations along the river;

[0048] Topographic data include the starting point distance and elevation of the section measuring points, as well as the section spacing; hydrological data include the average daily flow and sediment content; the present invention takes the Yellow River Estuary as the research object and collects historical topographic data of 41 fixed sections from 1996 to 2018; at the same time, the historical average daily hydrological data of the Lijin Hydrological Station are collected, and 19 sets of measured water, sediment and topographic data of physical models based on the Yellow River Estuary as the prototype are also collected. The measured water, sediment and topographic data of the physical model are restored at scale to make up for the shortage of measured data of natural estuaries.

[0049] Step 2: Based on hydrological and topographic data, the improved entropy weight method is applied to the main channel of the estuary tail stream to calculate the contribution weights of different indicators in the water and sediment conditions and riverbed boundary conditions to the river outflow. Then, based on the calculation results, the main controlling factors of the river outflow are quantitatively identified. The indicator with the highest weight is the main controlling factor. This step further includes:

[0050] Step 2.1, determine the water, sediment and boundary condition index system;

[0051] It should be noted that in actual application, a more complex or simpler indicator system can be designed according to needs. The indicators are shown in Table 1:

[0052] Table 1 Water, sediment and boundary condition index system related to river outflow

[0053]

[0054] It should be noted that the flat-shoal flow of the river section is calculated based on the flow and sediment content data of the Lijin Station and the topographic data of 41 sections of the study river section. For detailed calculation methods, please refer to the references in the indicator source.

[0055] In step 2.2, the information entropy theory and method are used to introduce the information entropy and grouping of the indicators related to the outflow of the river channel at the tail end of the estuary. The grouping refers to the actual observation data of the natural river channel grouped by year to establish the initial indicator matrix.

[0056] The information entropy and grouping of the indicators related to the estuary and the river channel are introduced to adopt the theory and method of information entropy; the initial matrix of indicators is established and realized as follows:

[0057] Based on the indicators listed in Table 1, an m×n initial matrix A is constructed with n years or n groups of m indicators. 水沙 and A 河床 ,The subscripts “water-sand” and “riverbed” respectively represent the water-sand conditions and the riverbed boundary conditions, which are expressed as:

[0058]

[0059] Where: Since the number of water and sediment conditions and riverbed boundary conditions related to the present invention are five and six respectively, the water and sediment conditions correspond to m=5, the riverbed boundary conditions correspond to m=6, and n is the number of year groups; mn and b mn Indicates the size of indicators related to water and sediment conditions and riverbed boundary conditions.

[0060] In step 2.3, since the dimensions and magnitudes of different indicators are different, in order to eliminate the influence caused by the different dimensions and magnitudes, the indicators related to water and sediment conditions and riverbed boundary conditions are normalized. The normalized calculation formula is:

[0061]

[0062] Where: x mn Indicates a mn or b mn , thus obtaining the normalized matrix B of the index value 水沙 and B 河床 :

[0063]

[0064] Where: and Amn and b mn Normalized value.

[0065] Step 2.4, calculate the probability of river channel outflow at the tail section of the estuary under different indicator changes.

[0066] Whether the tail section of the river will branch out has only two results: "branch out" and "no branch out", so it is a typical binary result variable; the river section flat flow in the riverbed boundary condition index is used as the Take the dichotomous variable Y of the river branch as an example, Y is the branch code, Y = 1 when the branch is formed, and Y = 0 when the branch is not formed. The result of plotting the relationship between Y must be two parallel lines, each of which corresponds to a value of Y. Since the variable Y is dichotomous, it is difficult to describe these two parallel lines using an ordinary least squares regression equation. Logistic regression analysis is suitable for describing and testing the relationship between a binary outcome variable and one or more categorical or continuous variables.

[0067] In step 2.4, logistic regression analysis was used to obtain and The probability P of the branching code between Y and the branching code is:

[0068]

[0069] Where: X indicates the branching event, x is the numerical value of the branching event, i.e. the probability, and the value of x is between 0 and 1; ν is the logistic regression coefficient; e is a natural number, e = 2.71828; thus, the α×β probability matrix P of the branching event probability P is obtained. 水沙 and P 河床 :

[0070]

[0071] Where: Exp. represents the measured data of the estuary physical model, Fie. represents the measured data of the prototype natural estuary; q αβ and g αβ They respectively represent and The probability value P between the dichotomy result variable Y and the river outlet.

[0072] Step 2.5, calculate the proportion and entropy value of different indicators in water-sediment conditions and riverbed boundary conditions.

[0073] Let the proportion of the βth index value under the αth index in the αth index be P' αβ , let the information entropy of the β-th indicator be E βφ represents the index with the largest contribution weight in the riverbed boundary conditions, and ψ represents the index with the largest contribution weight in the water and sediment conditions. φ and ψ are the main controlling factors of river outflow.

[0074] The proportion of the βth index value under the αth index in the αth index is P' αβ The information entropy of the β-th index is E β The calculation formula is:

[0075] P' αβ and E β The calculation formula is:

[0076]

[0077] Where: y αβ Indicates g αβ or q αβ The contribution weights of water and sediment conditions and riverbed boundary conditions to the river outflow are calculated using the following formula:

[0078]

[0079] Wherein: k is the number of indicators. The present invention selects 5 indicators related to water and sediment conditions, so the corresponding k=5, and 6 indicators related to riverbed boundary conditions, so the corresponding k=6.

[0080] Table 2 shows the calculation results of the information entropy E value and contribution weight w of the Yellow River Estuary. As can be seen from Table 2, the riverbed boundary condition that contributes most to the outflow of the Yellow River Estuary is the river phase coefficient (w=0.356), the water and sediment condition that contributes most to the outflow of the river is the average water flow scouring intensity during the flood season. (w=0.383), that is is φ, is ψ, and the main controlling factor of the river outlet is and Therefore, these two indicators are used to establish the boundary equation of the estuary and river channel.

[0081] Table 2 Calculation results of information entropy and contribution weight of water and sediment conditions and riverbed boundary conditions on river outflow

[0082]

[0083] Step 3: Based on the main controlling factors of the outflow, a prediction model for the outflow threshold of the estuary river channel is established under the joint control of the riverbed boundary conditions and the water and sediment conditions. This step further includes:

[0084] Step 3.1, construct the river channel boundary equation using φ and ψ:

[0085] φ=aψ b

[0086] Where: a and b are unknown coefficients, which need to be calibrated using actual observation data of estuaries and rivers.

[0087] As shown in Table 2, the Yellow River Estuary channel φ is the main controlling factor of the river channel outflow and the river phase coefficient of the river section ψ is the main controlling factor of the river outlet, the average water flow intensity during the flood season The equation form of the Yellow River estuary channel boundary line should be expressed as:

[0088]

[0089] In the formula It indicates the intensity of water flow in the river and the sediment transport capacity of the river. It characterizes the lateral stability of the riverbed and the mobility of the riverbank. Therefore, when the lateral stability of the riverbed deteriorates, it is more likely to cause the river to branch out. Next A value above the threshold line indicates that a river has branched out, and a value below the threshold line indicates that no river has branched out. Based on 21 years of measured water, sediment and topography data from the Yellow River Estuary from 1996 to 2016 and 19 sets of generalized physical model test data of the Yellow River Estuary, 40 sets of river phase coefficients were obtained. and water flow intensity Data; such as Figure 2 As shown, by plotting the relationship between river phase coefficient and water flow scour intensity, we can see that the data points have obvious boundaries. and water flow intensity In the case of specific values, combining the above formula yields a=38.16, b=-0.39.

[0090] Step 3.2: Evaluate the reliability of the estuary-branch boundary equation. Introduce the parameter λ to evaluate the reliability of the boundary equation:

[0091]

[0092] Where: λ is the outgoing branch boundary parameter; N c is the number of points in the correct boundary area in the coordinate system; N w The number of points in the wrong boundary area of ​​the coordinate system; N T The total number of points.

[0093] like Figure 2 The coordinate system shown in FIG. 1 shows that the horizontal axis of the coordinate system is the average water flow scouring intensity during the flood season. The vertical axis of the coordinate system is the river phase coefficient The curve is the branching boundary line. Above the boundary line indicates that the river branching has occurred, and below the boundary line indicates that the river branching has not occurred.

[0094] The 40 sets of river phase coefficients obtained and water flow intensity The data is depicted in Figure 2 In the coordinate system, points above the boundary line indicate that a river has branched out, and points below the boundary line indicate that no river has branched out. By comparing this with the records of whether a river has branched out in the corresponding year in the historical data, the number of points N in the correct boundary area in the coordinate system is calculated. c and the number of points N in the wrong boundary area in the coordinate system w .

[0095] By adjusting the unknown parameters a and b in the boundary equation, the number of points N distributed in the correct boundary area is c At most, N points in the error boundary area can be controlled at the same time w According to the paper Criteria for evaluating flowclasses in alluvial channels, when the value of λ is greater than 0.5, the channel branch boundary equation can be considered accurate and reasonable.

[0096] The above λ calculation formula yields the boundary parameter λ = 0.74 (> 0.5) of the Yellow River Estuary channel branch boundary equation. Therefore, the expression of the Yellow River Estuary channel branch boundary equation is as follows:

[0097]

[0098] The above formula can be used to determine whether river branching will occur at the Yellow River estuary under the combined influence of water and sediment conditions and riverbed boundary conditions.

[0099] Step 3.3: Obtain the estuary-channel branch threshold. Under the premise of λ>0.5, transform the estuary-channel branch boundary equation to obtain the estuary-channel branch threshold prediction model:

[0100] ACI=φψ -b =a

[0101] Where: ACI is the abbreviation of "Avulsion Criterion Index", which refers to "river branching index", a is the threshold of river branching, and the larger the ACI value, the greater the possibility of river branching. YRE When ≥a, it indicates that the estuary river channel has branched out.

[0102] Under the premise of λ>0.5, the channel branch boundary equation is deformed to obtain the channel branch index of the Yellow River estuary tail section:

[0103]

[0104] Where: ACI YREis the river channel outflow index value in a certain year. According to the calibration result of the river channel outflow boundary equation, the outflow threshold value a of the Yellow River estuary tail section is YRE is 38.16; calculate the ACI for that year YRE When the value is set, the Yellow River estuary phase coefficient of that year is taken. and water flow intensity Value, such as the calculated ACI YRE When the index is ≥38.16, it can be determined that the Yellow River estuary has branched out in the tail section in the corresponding year. In summary, the physical meaning of the branching index is: when the riverbed stability does not differ much, the river section with greater water flow intensity is closer to the branching threshold; or under the same water flow intensity, the river section with worse riverbed stability is closer to the branching threshold, that is, it is more likely to branch out.

[0105] Different branching causes of different river channels are different, that is, the main controlling factors of river channel branching are different, and the maximum weight index calculated by the improved information entropy method of the present invention will also be different; the improved information entropy method of the present invention is used to quantitatively identify the main controlling factor φ in the river channel water and sediment index system and the main controlling factor ψ in the boundary condition index system of the river channel branching, and use φ and ψ to construct the river channel branch boundary equation φ = aψ b , according to the historical data values ​​of φ and ψ, calculate the values ​​of a and b, the value of a is the threshold of whether the river is branching; let ACI YRE =Фψ -b ,ACI YRE Calculate ACI for the river outflow index value in a certain year YRE When the value is calculated, take the main control factor φ value in the water and sediment index system of that year and the main control factor ψ value in the boundary condition index system, such as the calculated ACI YRE When it is greater than or equal to the value a, it is determined that the river has branched out in the corresponding year.

[0106] Finally, it should be noted that the contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field. The above description is only the preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to replace some of the technical features therein with equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A method for determining the outflow threshold of a river channel in a river-controlled estuary based on an improved entropy weight method is characterized by: The following steps are included: S1: Collect historical topographic data of fixed sections of the main stream of the river-controlled estuary, and historical daily average hydrological data of hydrological stations along the river; S2: Based on hydrological and topographic data, the improved entropy weight method is applied to the main channel of the estuary tailwater, and the contribution weights of different indicators in water and sediment conditions and riverbed boundary conditions to the river outflow are calculated. The main controlling factors of the river outflow are identified based on the calculation results; S3: Based on the main controlling factors of the outflow, a prediction model for the outflow threshold of the estuary river channel is established under the joint control of the riverbed boundary conditions and the water and sediment conditions; The S2 step specifically includes: S2.1: Determine the water, sediment and boundary condition index system; S2.2: Using the theory and method of information entropy, we introduce the information entropy and grouping of indicators related to the outflow of the river channel at the tail end of the estuary. The grouping refers to the actual observation data of the natural river channel grouped by year, and establish an initial matrix of water, sediment and boundary condition indicators; S2.3: Normalize the indicators related to water and sediment conditions and riverbed boundary conditions; S2.4: Logistic regression analysis method was used to obtain and and the probability P of branching between the branching code Y; S2.5: Calculate the proportion and entropy value of different indicators in the water and sediment conditions and riverbed boundary conditions; The specific calculation method for the proportion and entropy value of different indicators in the water and sediment conditions and riverbed boundary conditions in step S2.5 is: Let the proportion of the βth index value under the αth index in the αth index be P' αβ , let the information entropy of the β-th indicator be E β φ represents the index with the largest contribution weight in the riverbed boundary conditions, and ψ represents the index with the largest contribution weight in the water and sediment conditions. That is, φ and ψ are the main controlling factors of river outflow; The proportion of the βth index value under the αth index in the αth index is P' αβ The information entropy of the β-th index is E β The calculation formula is: Where: y αβ Indicates g αβ or q αβ The formula for calculating the contribution weight of water and sediment conditions and riverbed boundary conditions to the river outflow is: Where: k is the number of indicators.

2. The method for determining the outflow threshold of a river channel in a river-controlled estuary based on the improved entropy weight method according to claim 1, characterized in that: In the above-mentioned step S1, the topographic data include the starting point distance and elevation of the cross-section measuring points, as well as the cross-section spacing; the hydrological data include the average daily flow and sediment content.

3. The method for determining the outflow threshold of a river channel in a river-controlled estuary based on the improved entropy weight method according to claim 1, characterized in that: The S3 step specifically includes the following steps: S3.1: Use φ and ψ to construct the channel boundary equation: φ = aψ b Where: a, b are unknown coefficients; φ represents the index with the largest contribution weight in the riverbed boundary conditions, and ψ represents the index with the largest contribution weight in the water and sediment conditions. φ and ψ are the main controlling factors of river outflow. S3.2: Evaluate the reliability of the estuary-channel boundary equation; introduce the parameter λ to evaluate the reliability of the boundary equation: Where: λ is the boundary parameter; N c is the number of points in the correct boundary area in the coordinate system; N w The number of points in the wrong boundary area of ​​the coordinate system; N T is the total number of points; When the value of λ is greater than 0.5, the equation of the river branch boundary is accurate and reasonable; S3.3: Obtain the threshold value of the estuary channel; Under the premise of λ>0.5, the channel channel boundary equation is transformed to obtain the estuary channel channel threshold prediction model ACI=φψ -b =a; Where: ACI refers to the "river channel outflow index value", a is the river channel outflow threshold, φ represents the index with the largest contribution weight in the riverbed boundary condition, and ψ represents the index with the largest contribution weight in the water and sediment condition.

4. The method for determining the outflow threshold of a river channel in a river-controlled estuary based on the improved entropy weight method according to claim 3, characterized in that: In step S3.3, the values ​​of a and b are calculated based on the historical data values ​​of φ and ψ, where the value of a is the threshold for determining whether the river has branched. ACI YRE =Фψ -b ,ACI YRE Calculate ACI for the river outflow index value in a certain year YRE When the value is calculated, take the main control factor φ value in the water and sediment index system of that year and the main control factor ψ value in the boundary condition index system, such as the calculated ACI YRE When it is greater than or equal to the value a, it is determined that the river has branched out in the corresponding year.

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