An ecological flow evaluation method for tidal river network migration passage maintenance of fish

Abstract

The present application relates to a kind of ecological flow evaluation method for tidal river network migration channel maintenance of fishery, utilize river network data to build one-dimensional tidal river network hydrodynamic model;Set different water inflow and tidal conditions scenarios, input one-dimensional tidal river network hydrodynamic model, output river network each river flow velocity;Obtain the flow velocity suitability curve of target fish, the flow velocity suitability curve of each river of river network is substituted, and suitable migration river is obtained;According to river network flow direction, the water system flow between suitable migration river is calculated;With water system connectivity as weight, the total length of adjusted suitable migration river is calculated;According to the mapping relationship between adjusted suitable migration river total length and water inflow, determine fish migration ecological flow.The present application solves the prior art to ecological flow only considers the longest total length of suitable migration river of fishery and does not consider the connectivity between river, falls into local optimum problem and leads to difficult to meet the needs of fish migration.

Description

Technical Field

[0001] The invention belongs to the technical field of water ecology and relates to an ecological flow assessment method for maintaining a migratory channel for fish in a tidal river network. Background Art

[0002] Tidal river networks, influenced by tidal forces, exhibit unique and complex hydrodynamic characteristics, with hydraulic elements such as water level and flow velocity constantly changing. This complex and ever-changing environment presents both unique challenges for fish migration and a crucial ecological context for their adaptation and dependence. However, with increasing human activity, factors such as water conservancy project construction, overexploitation of water resources, and the discharge of various pollutants within the basin have significantly altered the hydrological conditions of tidal river networks, causing varying degrees of disruption and damage to fish migration pathways. As a result, many fish populations face survival crises such as blocked migration, reproductive failure, and drastic population declines, indirectly impacting the balance and sustainable development of the entire river ecosystem. Accurately assessing the ecological flows required to maintain fish migration pathways in tidal river networks has become a critical issue in ecological protection and water resources management.

[0003] Chinese patent CN113468825A provides a method and device for determining the ecological flow rate of fish migration. The steps include: exploring the hydrological conditions that stimulate the migration of the fish to be studied based on field observations or indoor experiments, and establishing a fish migration velocity suitability curve and a fish migration depth suitability curve corresponding to the fish to be studied; establishing a hydrodynamic model based on the river network information and cross-sectional information of the river channel where the fish to be studied are located; calculating the total length of the suitable river channel for fish migration under different flow rates based on the fish migration velocity suitability curve, the fish migration depth suitability curve, and the hydrodynamic simulation results; establishing a mapping relationship between the total length of the suitable river channel for fish migration and the flow rate, and determining the fish migration ecological flow rate based on the mapping relationship between the total length of the suitable river channel for fish migration and the flow rate.

[0004] However, this method of determining ecological flow primarily prioritizes maximizing the total length of suitable river channels for fish migration, which can easily lead to local optimality. For example, when river network connectivity is insufficient, even if the total length of suitable river channels for fish migration is maximized, the suitable channels will be intermittent, making it difficult for fish to migrate between different waterways.

[0005] The water system connectivity has an important influence on the tidal river network migration of fish. For the tidal river network, the internal numerous river channels and tributaries are connected to form a complex network, and the water system connectivity is directly related to whether the fish can successfully find a suitable migration path and the corresponding habitat and breeding site. Under the periodic action of tidal rise and fall, the water level difference and the flow direction of each part of the river network change all the time, and good water system connectivity can ensure that the fish can complete the migration behavior along the unobstructed channel at different tidal stages. If this factor is ignored, even if the flow and other conditions seem to meet the needs of fish migration, the fish may still be trapped in a certain area due to the blockage and poor connectivity between local river channels, and cannot reach the target location, thereby affecting the life activities such as breeding and foraging of the fish, and finally causing serious threat to the survival and reproduction of the entire fish population. SUMMARY

[0006] The application provides an ecological flow evaluation method for maintaining fish tidal river network migration channels, which aims to simulate the flow rates of each river channel of the river network under different water inflow and tidal conditions; determine the suitable migration river channel according to the flow rate suitability curve of the target fish; calculate the water system connectivity between the suitable migration river channels; and finally calculate the adjusted total length of the suitable migration river channel by taking the water system connectivity as the weight, so as to solve the problem that the ecological flow of the prior art only considers the longest total length of the suitable fish migration river channel and falls into a local optimum, which leads to the difficulty in meeting the needs of fish migration.

[0007] The object of the application can be achieved by the following technical solutions.

[0008] The application provides an ecological flow evaluation method for maintaining fish tidal river network migration channels, which includes the following steps:

[0009] S1, collecting river network data of a research area from a hydrological yearbook and a national surface water examination section network, wherein the river network data includes daily flow data, high and low tide level data and section water quality data;

[0010] S2, constructing a one-dimensional tidal river network hydrodynamic model by using the river network data to simulate the hydrodynamic conditions of the research area;

[0011] S3, setting different water inflow and tidal conditions, inputting the one-dimensional tidal river network hydrodynamic model, and outputting the flow rates of each river channel of the river network;

[0012] S4, obtaining the flow rate suitability curve of the target fish, substituting the flow rates of each river channel of the river network into the flow rate suitability curve, and obtaining the suitable migration river channel;

[0013] S5, calculating the water system connectivity between the suitable migration river channels according to the flow direction of the river network;

[0014] S6, taking the water system connectivity as a weight, calculate the adjusted total length of suitable migration river channel;

[0015] S7, according to the mapping relationship between the adjusted total length of suitable migration river channel and the inflow, determine the fish migration ecological flow.

[0016] Further, in step S2, the one-dimensional tidal river network hydrodynamic model is based on the MIKE HYDRO RIVER platform, and the steps include:

[0017] S21, river network generalization: combing the actual river network of the research area, selecting the main river channel according to the terrain, determining the skeleton structure of the river network, and dividing the nodes at the key positions, the continuous river channel is discretized into interconnected calculation units, forming a network topology structure convenient for model description and calculation; the key positions include river intersection points and width change positions;

[0018] S22, section file making: collecting the measured section topographic data of each river channel, using the measurement point information to build and fit the section shape of the river channel unit in the platform, and according to the change of the section shape with time, the geometric characteristics of the river channel are described;

[0019] S23, boundary condition setting: setting the upstream flow boundary, selecting appropriate measurement station to import flow data at different time periods according to daily flow data, and setting the downstream tidal boundary at the same time, using high and low tide data to input water level change data at the river mouth section, and comprehensively simulating the actual conditions of various water flows entering and leaving the river network;

[0020] S24, hydrodynamic parameter setting: determining the key physical characteristic parameters affecting water flow movement, setting the river channel roughness, combining the field situation and experience value and optimizing the parameters, and setting the gravitational acceleration, bend resistance coefficient and wind resistance coefficient as needed.

[0021] S25, simulation calculation: according to the set time step, the hydrodynamic equation set is used to calculate the change of water level and flow velocity in each river channel unit with time from the initial time, the information transmission and interaction are realized through the nodes, and the dynamic evolution process of river network flow is simulated;

[0022] S26, result comparison: collecting the measured water level and flow velocity data at the key positions, comparing the measured results with the simulation output results, using the determination coefficient and Nash-Sutcliffe efficiency coefficient to evaluate the simulation accuracy, if it does not meet the requirements, return to adjust the related settings, until the results meet the accuracy requirements.

[0023] Further, in step S25, the hydrodynamic equation set is configured as Saint-Venant equation set, including continuity equation and momentum equation; the continuity equation has the following calculation formula:

[0024]

[0025] The momentum equation is calculated by the following formula:

[0026]

[0027] In the formula, Q represents flow rate; q represents single-width flow rate of lateral inflow or outflow; A represents water area; h represents water level; R represents hydraulic radius; C represents coefficient of determination; a represents momentum correction coefficient; t represents time; x represents distance along the river; and g represents gravity acceleration.

[0028] Further, in step S26, the coefficient of determination is calculated by the following formula:

[0029]

[0030] The Nash-Sutcliffe efficiency coefficient is calculated by the following formula:

[0031]

[0032] In the formula, Q sim represents simulation value, Q obs represents observation value, represents observation average value, represents simulation average value, t represents month number; Ens represents Nash-Sutcliffe efficiency coefficient, which is between 0 and 1, and the closer to 1, the better the fitting effect is; and R 2 represents coefficient of determination, which is between 0 and 1, and the closer to 1, the better the fitting effect is.

[0033] Further, in step S5, the water system connectivity between suitable migration river channels is calculated, including the following steps.

[0034] S51, a connectivity factor of all river channels in the river network is calculated.

[0035] S52, an adjacency matrix between all river channels is constructed according to the water flow direction of the river network.

[0036] S53, the connectivity factor is substituted into the adjacency matrix to obtain a judgment matrix of the water system connectivity between suitable migration river channels; the judgment matrix is used to judge the water system connectivity between any two suitable migration river channels.

[0037] Further, the connectivity factor is calculated by the following formula:

[0038]

[0039] In the formula, ω ij represents the connectivity factor of the suitable migration river channel from the starting point i to the ending point j along the water flow direction; and H ijThe time average flow rate represents a suitable migratory river channel; a is the average runoff of the river network in the study area for N years.

[0040] Further, in step S53, the water system connectivity between any two suitable migratory river channels is judged, and the calculation formula is:

[0041]

[0042] In the formula, d mn The water system connectivity between two suitable migratory river channels; P mn The sum of the connectivity of all river channels from the end point m of the suitable migratory river channel in the upstream to the start point n of the suitable migratory river channel in the downstream; P mn The number of river channels from the end point m of the suitable migratory river channel in the upstream to the start point n of the suitable migratory river channel in the downstream.

[0043] Further, in step S6, the total length of the adjusted suitable migratory river channel is adjusted, and the calculation formula is:

[0044]

[0045] μ k = d k / d sum ,

[0046] In the formula, L sum The total length of the adjusted suitable migratory river channel; W k The average flow rate suitability index of the kth suitable migratory river channel, and N is the number of suitable migratory river channels; L k The length of the kth suitable migratory river channel; μ k The connectivity weight of the kth suitable migratory river channel; d k The sum of the connectivity of the kth suitable migratory river channel and the other closest suitable migratory river channel; d sum The total number of the sum of the connectivity of all suitable migratory river channels and the other closest suitable migratory river channel.

[0047] Further, in step S7, a Bayesian network model between the inflow, the water system connectivity and the total length of the adjusted suitable migratory river channel is also constructed, which is used to determine the comprehensive influence of the inflow and the water system connectivity on the total length of the adjusted suitable migratory river channel; the Bayesian network model has a model structure that takes the inflow and the water system connectivity as parent nodes, and takes the total length of the adjusted suitable migratory river channel as a child node; meanwhile, the inflow is taken as a parent node, and the water system connectivity is taken as a child node, and the parent node and the child node are connected through a directed edge.

[0048] The beneficial effects of the present application are:

[0049] (1) Construct a one-dimensional tidal river network hydrodynamic model by using river network data; set different water inflow and tidal conditions scenarios, input the one-dimensional tidal river network hydrodynamic model, output the flow velocity of each river channel of the river network; obtain the flow velocity suitability curve of the target fish, and substitute the flow velocity of each river channel of the river network into the flow velocity suitability curve to obtain the suitable migration river channel; calculate the water system connectivity between the suitable migration river channels according to the water flow direction; take the water system connectivity degree as the weight to calculate the adjusted total length of the suitable migration river channel; determine the fish migration ecological flow according to the mapping relationship between the adjusted total length of the suitable migration river channel and the water inflow. The present application solves the problem that the prior art only considers the longest total length of the suitable migration river channel of fish and does not consider the connectivity between the river channels, falls into a local optimal problem and is difficult to meet the migration demand of fish.

[0050] (2) By constructing a Bayesian network model among the water inflow, water system connectivity and the adjusted total length of the suitable migration river channel, the comprehensive influence of the water inflow and the water system connectivity on the adjusted total length of the suitable migration river channel is determined, so as to improve the accuracy of the ecological flow evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to facilitate the understanding of those skilled in the art, the present application will be further described below with reference to the accompanying drawings.

[0052] Fig. 1 The flow chart of the ecological flow evaluation method for the fish tidal river network migration channel maintenance in the present application.

[0053] Fig. 2 The flow chart of calculating the water system connectivity between the suitable migration river channels in an embodiment of the present application.

[0054] Fig. 3 The structure diagram of the Bayesian network model in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific embodiments, structures, features and effects according to the present application will be described in detail below with reference to the accompanying drawings and preferred embodiments.

[0056] Please refer to Figs. 1-3 The present application provides an ecological flow evaluation method for fish tidal river network migration channel maintenance, which comprises the following steps:

[0057] S1, collecting river network data of the research area from the hydrological yearbook and the national surface water examination section network, wherein the river network data includes daily flow data, high and low tide level data and section water quality data;

[0058] In this embodiment, the hydrological yearbook is an authoritative data integration in the field of hydrology, which is formed after long-term, systematic and standardized data collection and compilation by professional hydrological observation institutions. The daily flow data is based on the hydrological stations distributed at the key nodes of the river network, and the flow of the river network at different time periods is recorded continuously by using rigorous measurement technology and equipment. It accurately describes the dynamic replenishment of water resources, runoff change and seasonal fluctuation in the river network in the form of time series, and provides indispensable basic data support for in-depth study of the law of river network flow movement and analysis of the internal hydrodynamic mechanism.

[0059] The tidal high and low water level data focuses on the unique phenomenon of the tidal river network affected by tides. Due to the periodic rise and fall of tides, which has a significant and complex impact on water power factors such as water level, flow velocity and direction in the river network, this data accurately records the water level at each tidal stage, laying a key foundation for restoring the real hydrodynamic environment of the tidal river network and building a realistic hydrodynamic model, and plays an irreplaceable role in understanding the migratory behavior and adaptive strategies of fish under the driving of tides.

[0060] At the same time, the water quality data provided by the national surface water assessment section network, relying on its extensive and reasonable monitoring section system, uses professional water quality analysis methods and instruments to regularly and accurately detect key water quality indicators such as dissolved oxygen, pH, and concentrations of various pollutants in river water. The water quality is directly related to the survival suitability and migratory feasibility of fish, and these data can provide important reference for subsequent comprehensive evaluation of river network ecological environment and accurate determination of ecological flow threshold, thereby ensuring that the fish migration channel can be effectively maintained under good water quality conditions.

[0061] S2, using river network data to build a one-dimensional tidal river network hydrodynamic model to simulate the water dynamic situation of the research area;

[0062] In this embodiment, the one-dimensional tidal river network hydrodynamic model is based on the basic theory of hydraulics, and reasonably simplifies and abstracts the complex tidal river network system, which is regarded as a network structure composed of multiple connected river units. In this model, the water flow movement is described one-dimensionally along the main flow direction of the river, and the Saint-Venant equation set (including continuity equation and momentum equation) is used to accurately describe the mass conservation and momentum variation law of water flow in the river. The continuity equation ensures that the inflow and outflow water volume at any cross section of the river is in mass balance, and the momentum equation considers the influence of factors such as river slope, roughness, upstream and downstream water level difference, and tidal action force on water flow velocity and water level change.

[0063] River network data plays a key role in the model construction process. Among them, daily flow data can provide water input boundary conditions at different times for the model, help determine the initial flow state of the river and the trend over time; high and low tide data are used to accurately characterize the tidal boundary conditions, quantify the periodic effects of ocean tides on the river network, and accurately simulate the water level fluctuations at each node in the river network during the rising tide and ebb tide stages, as well as the resulting changes in water flow velocity; although cross-section water quality data mainly focuses on reflecting the chemical properties of the water body, in some water dynamic simulation applications involving material transport and diffusion, it can also provide basic parameters for simulating the migration process of pollutants and other substances in the river network along with the water flow.

[0064] By reasonably integrating and using these data, substituting them into the corresponding mathematical model framework, and going through a rigorous parameter calibration and model verification process, a one-dimensional tidal river network hydrodynamic model can be constructed to accurately reproduce the actual hydrodynamic conditions in the study area, including water level fluctuations, water flow velocity and direction changes, etc. at different locations in the river, providing a reliable simulation analysis tool for further research on the relationship between fish migration behavior and river network hydrodynamic conditions, and evaluating the ecological flow required to maintain fish migration channels.

[0065] Further, in step S2, the one-dimensional tidal river network hydrodynamic model is constructed based on the MIKE HYDRO RIVER platform, and the steps include:

[0066] S21, river network generalization:

[0067] River network generalization aims to simplify and abstract the complex actual river network system so that it can be more easily analyzed and calculated using the model while meeting the accuracy requirements. First, the river channels in the river network need to be sorted and selected based on the topography, river distribution, and water flow connectivity of the study area. Identify the main trunk, tributaries, and river sections that play a key role in fish migration, remove small ditches or short branches that are relatively minor and have little impact on the overall hydrodynamics, and determine the river network skeleton structure that needs to be considered in the model. For example, in a large estuary tidal river network area, several main inlets that directly connect to the ocean and are frequently used by fish for migration, as well as their important tributaries, can be retained, while some small rivers with little flow and relatively isolated branches can be simplified.

[0068] Then, the river channel is divided into nodes according to its flow characteristics and connection relationship, and the continuous river channel is discretized into a plurality of interconnected calculation units. The nodes are usually arranged at the intersection of the river channel, the position of the change of the width of the river channel, the position of the hydraulic structure (such as a gate dam) and the like. These nodes are not only the key control points at which the flow state changes, but also the connection points at which the flow information is transmitted in subsequent model calculation. Through such generalization processing, the originally complex and interlaced river network is converted into a network topology structure composed of nodes and river channel units, which is convenient for mathematical description and calculation simulation in the MIKE HYDRO RIVER platform.

[0069] S22, cross-section file making:

[0070] The cross-section file making is to accurately describe the geometric shape characteristics of each river channel unit in the river network, which is crucial for the accurate simulation of the water flow movement by the hydrodynamic model.

[0071] The measured cross-section topographic data of each river channel in the research area are collected. These data are generally obtained by professional topographic measurement means (such as total station measurement, depth measurement combined with GPS positioning and the like). The measurement points are distributed along the cross-section direction of the river channel, and can reflect the elevation change of the river bottom and the topographic conditions of the two banks. Based on these measured data, the cross-section shape corresponding to each river channel unit is constructed in the software platform. Generally, trapezoidal, rectangular and other geometric figures are used for approximate fitting. For irregular natural river cross-sections, a plurality of measurement point coordinates are used to describe the true shape in detail. At the same time, the possible changes of the river cross-section with time, such as seasonal scouring and silting changes, human activities (such as river dredging, dike building and the like) causing cross-section changes and the like, are also considered. If there are relevant data, corresponding parameter settings or multi-period cross-section data import can be performed in the cross-section file, so as to more accurately reflect the actual geometric characteristics of the river network, and provide a reliable basis for the simulation of the interaction between the water flow and the river boundary in the subsequent hydrodynamic calculation.

[0072] S23, boundary condition setting:

[0073] The boundary condition setting determines the input driving factors of the model simulation and the boundary constraint conditions of the calculation range, and is one of the key links affecting the accuracy of the simulation results of the model. For the one-dimensional tidal river network hydrodynamic model, the setting of the upstream flow boundary and the downstream tidal boundary condition is mainly involved. In terms of the upstream flow boundary, according to the collected daily flow data, a suitable hydrological station is selected as the representative point of the upstream boundary, and the flow data recorded at different time periods by the station are imported into the model in time sequence to provide water input conditions for the river network, to simulate the incoming water conditions under the natural state of the river, or to set constant flow, variable flow and the like of different flow levels according to the research requirements, so as to analyze the influence of different incoming water conditions on the river network hydrodynamics.

[0074] For the setting of downstream tidal boundary conditions, the high and low tidal level data are used to select the cross-sections located in the estuary and directly connected to the sea as the downstream boundary nodes. The measured tidal water level process line (including water level change data corresponding to different tidal types such as spring tide, mean tide, and neap tide) is input into the model, so that the model can simulate the periodic lifting and pulling effect of ocean tides on the river network, and accurately reproduce the dynamic change characteristics of water level and flow velocity in the tidal river network with the rise and fall of tides. In addition, if there are lateral inflow or outflow tributaries, artificial water supply or drainage, etc. in the study area, the corresponding lateral boundary conditions also need to be set to ensure that the model fully considers the actual situation of water flow into and out of the river network.

[0075] S24, water force parameter setting:

[0076] The water force parameter setting aims to determine the key physical characteristic parameters that affect the movement of water flow in the river channel, so that the model can accurately calculate according to the water flow resistance, momentum transfer, etc. of the actual river network. Among them, the river roughness is a core parameter, which represents the frictional resistance of the river boundary to water flow. Its value is closely related to the riverbed material (such as sand, silt, etc.), vegetation coverage of the bank slope, whether the river channel is artificially lined, etc. It is necessary to combine the field investigation data of the river channel and the experience value range of similar river channels in the past to reasonably set the roughness value for different river channel units in the model. Through multiple trial calculations and verifications, the value is optimized to match the simulated water level, flow velocity, etc. with the measured data.

[0077] In addition, other related parameters also need to be set, such as the acceleration of gravity, which is usually set according to the actual standard value of local gravity acceleration; for the river channel with bends, the centrifugal force effect of the water flow in the bend needs to be considered, and the corresponding bend resistance coefficient needs to be set; if the interaction between water flow and atmosphere is involved (such as the influence of wind waves on the water surface), the wind resistance coefficient and other parameters also need to be set. These parameters work together to ensure that the model can accurately simulate the momentum change and motion state of water flow in the river network under various complex conditions.

[0078] S25, simulation calculation:

[0079] After completing the above-mentioned river network generalization, cross-section file production, boundary condition setting, and water force parameter setting, etc. the preliminary preparation work, the simulation calculation process can be started on the MIKE HYDRO RIVER platform.

[0080] According to the set time step (generally reasonably selected according to the speed of change of the river network flow in the study area and the required simulation accuracy, such as several minutes to tens of minutes), the model starts from the initial time, and according to the physical law described by the hydrodynamic equation set (such as the Saint-Venant equation set), the changes of water level, flow velocity and other flow state variables in each river unit at each time step are calculated step by step. In the calculation process, through the water flow continuity condition and momentum conservation condition at the node, the transmission and interaction of water flow information between each river unit are realized, and the dynamic evolution process of the water flow in the whole river network with the given boundary conditions and parameters over time is simulated. The whole simulation calculation process may last for a long time, which depends on the total simulation time and the computing power of the computer. For long time series or complex river network simulation, high-performance computing resources are often needed to improve the calculation efficiency.

[0081] Further, the hydrodynamic equation set is configured as a Saint-Venant equation set, including a continuity equation and a momentum equation; the continuity equation has a calculation formula as follows:

[0082]

[0083] The momentum equation has a calculation formula as follows:

[0084]

[0085] In the formula, Q is the flow rate, q is the lateral inflow or outflow per unit width, A is the flow area, h is the water level, R is the hydraulic radius, C is the Chezy coefficient, a is the momentum correction coefficient, t represents time, x represents the distance along the river, and g represents the acceleration of gravity.

[0086] S26, result comparison:

[0087] By comparing and analyzing the results obtained by simulation calculation with the actual observation data, it is judged whether the model accurately reflects the hydrodynamic conditions of the study area.

[0088] The measured water level, flow velocity and other data of the key positions (such as the pre-set hydrological stations, important fish migration nodes, etc.) in the study area are collected, and these measured values are compared with the results of the corresponding positions and time output by the model simulation. Various statistical analysis methods can be used, such as calculating the determination coefficient (R 2If the error index is within a reasonable range and the correlation coefficient is high, it means that the model can well reproduce the actual hydrodynamic conditions and can be used for subsequent analysis and research; otherwise, the settings of the model (such as boundary conditions, parameter values, etc.) need to be re-examined, adjusted and optimized, and the simulation calculation and result comparison are performed again until the simulation result of the model reaches the satisfactory accuracy requirement.

[0089] Further, in step S26, the determination coefficient is calculated according to the following formula:

[0090]

[0091] The Nash-Sutcliffe efficiency coefficient is calculated according to the following formula:

[0092]

[0093] In the formula, Q sim is the simulation value, Q obs is the observation value, is the observation average value, is the simulation average value, t is the month number; Ens is the Nash-Sutcliffe efficiency coefficient, which is between 0 and 1, and the closer to 1, the better the fitting effect; R 2 is the determination coefficient, which is between 0 and 1, and the closer to 1, the better the fitting effect.

[0094] S3, set different incoming water flow and tidal condition scenarios, input the one-dimensional tidal river network hydrodynamic model, and output the flow rate of each river channel in the river network;

[0095] In this embodiment, when setting the inflow scenario, multiple aspects need to be considered comprehensively. First, the historical hydrological data of the study area is thoroughly investigated, such as extracting the average annual flow, dry flow and wet flow under different guarantee rates (such as 90% Q, 75% Q, 50% Q, etc.) from authoritative hydrological yearbooks. These data provide a basic framework for scenario setting. At the same time, closely around the research purpose, such as analyzing the migration status of fish in different water quantity environment, some targeted flow values are specially set. Among them, the constant flow scenario is a common setting method, which selects a fixed flow value as the input condition of the model, for example, adopts a constant value close to the average annual flow, in order to observe the state of the river network internal flow under the condition of regular water supply, and judge whether it meets the needs of fish migration; or set the representative constant flow in dry season and wet season, and then compare the different characteristics of the river network under different water quantity conditions. In addition, the variable flow scenario is also indispensable, according to the law of flow change with time obtained by actual observation, the flow process line with periodic or non-periodic change is constructed, and it is introduced into the model as the input condition. For example, according to the complete daily flow data of a year for simulation, the response state of river network flow under the dynamic change of flow in natural state is truly restored; or according to the specific research needs, some special variable flow processes are artificially constructed, such as simulating the special situation of step change of flow caused by the regulation of upstream reservoir, and deeply exploring the influence mechanism of this complex and variable flow change on the flow velocity of each river of the river network.

[0096] The setting of the tidal condition scenario is mainly based on the actual tidal characteristics of the estuary where the study area is located. Through extensive collection of high and low tide data, and in-depth analysis of tidal types (including semi-diurnal tide, diurnal tide, irregular semi-diurnal tide, etc.), a scientific and reasonable setting is made. In terms of different tidal type scenarios, independent simulation is carried out for different types of semi-diurnal tide and diurnal tide, and the significant differences in river flow velocity in the river network during the rising tide and falling tide under these typical tidal actions are carefully compared. For example, in the semi-diurnal tide scenario, since there are two high tides and two low tides in a lunar day (about 24 hours and 50 minutes), it is necessary to closely observe the detailed variation of the flow velocity in each river of the river network during each rising and falling tide. In the diurnal tide scenario, since there is only one high tide and one low tide in a day, the differences between the river network flow response at this time and that in the semi-diurnal tide are highlighted. In terms of different tidal range scenarios, according to the variation range of the tidal range (the difference between high tide and low tide) in the actual tidal data, different tidal range scenarios such as spring tide, medium tide, and small tide are set. In the spring tide, the tidal range is large, and the tidal water has strong lifting and pulling effect on the river network, which will cause the flow velocity in the river network to change dramatically. At this time, the extreme value of the flow velocity in each river, the change of the flow direction, and the possible significant impact on fish migration under the action of such strong tide can be analyzed in depth. In the small tide, the tidal range is small, and the corresponding water flow power is relatively weak. By comparing the river network flow velocity under the small tide and the spring tide scenarios, the fish migration adaptation strategies under different tidal dynamic intensity can be explored in depth.

[0097] After setting the inflow and tidal condition scenarios as described above, the specific format and parameter setting rules required by the model are strictly followed, and they are sequentially input into the one-dimensional tidal river network hydrodynamic model based on MIKE HYDRO RIVER and other professional platforms. The model will consider the mutual superposition and mutual influence effect between the inflow and tidal action, as well as their synergistic effect with the river network structure (such as the width, curvature, etc. of the river) based on its built-in hydrodynamic calculation module (module based on classical theories such as Saint-Venant equation set) and pre-set river network generalization, section file, boundary condition, hydrodynamic parameter, etc. Detailed information, gradually deduce the water flow state change in each river of the river network at each time step under the corresponding scenario.

[0098] After the complex simulation process of the model, the flow velocity results of each river in the river network at different times and different locations under different inflow and tidal conditions can be finally output. These flow velocity data can be visually displayed through various visualization methods (such as generating flow velocity contour maps and flow velocity vector maps), clearly presenting the spatial distribution characteristics of flow velocity in the river network and the dynamic changes over time. For example, from the flow velocity contour map, it can be seen at a glance which areas have faster flow velocity and which areas have slower flow velocity. Combined with subsequent analysis of fish migration flow velocity suitability curves, it can accurately determine which river is more suitable for fish migration under specific conditions. The flow velocity vector map can clearly show the flow direction of each river, which helps to understand important information such as the upstream and downstream conditions of fish migration during the tidal rise and fall process, thereby providing indispensable key data basis for further research on fish migration channel maintenance and determination of scientific and reasonable ecological flow in the tidal river network.

[0099] S4, obtaining the flow velocity suitability curve of the target fish species, and substituting the flow velocity of each river in the river network into the flow velocity suitability curve to obtain suitable migration rivers;

[0100] In this embodiment, the acquisition of the flow velocity suitability curve of the target fish species is based on a large amount of scientific research and field observation. It is usually necessary to carry out targeted fish behavior experiments and field monitoring work. In the laboratory, the behavior response of the target fish species under different flow velocity conditions is simulated, and its swimming ability, activity range, and survival state, etc. are observed. Through accurate measurement and data recording, the relationship framework between flow velocity and fish behavior response is preliminarily established. For example, for some anadromous fish species, when the flow velocity is low, they may exhibit slow swimming speed and relatively limited activity range. With the gradual increase of flow velocity, their swimming vigor may be stimulated, and they may start to show more active exploration behavior. However, when the flow velocity exceeds its tolerance limit, the fish may appear fatigue, breathing difficulty, or even loss of control due to water flow impact, etc.

[0101] Field monitoring work further supplements and verifies laboratory data. In the natural river network environment, the actual distribution, migration path and group behavior characteristics of target fish in different river flow velocity areas are tracked and recorded for a long time by using monitoring equipment such as acoustic Doppler current profiler and underwater video monitoring system. Combining the data results of laboratory and field, mathematical modeling and statistical analysis method is used to finally draw a curve that can accurately reflect the flow velocity suitability of target fish in different life stages (such as juvenile stage, adult stage, breeding stage, etc.). The curve generally presents a specific shape, for example, in a certain suitable flow velocity range, the suitability of fish is higher, which is manifested as higher appearance frequency, stable behavior pattern and good physiological state; while in the area with too low or too high flow velocity, the suitability gradually decreases, indicating that these flow velocity conditions have certain degree of limitation or adverse effects on the survival and migration of fish.

[0102] After obtaining the flow velocity suitability curve of the target fish, the flow velocities of each river in the river network are substituted into the curve for analysis and calculation. For each river in the river network, due to the influence of factors such as inflow, tidal action and its own river characteristics, different flow velocities will be presented at different positions and different times. These flow velocity data are input into the flow velocity suitability curve one by one, and the suitability function corresponding to the curve is calculated and judged. If the suitability corresponding to the flow velocity of a river position reaches or exceeds the pre-set suitability threshold (the threshold is determined according to the basic requirements for the survival and migration of fish and the accuracy requirements of the research), the river is determined as a suitable migration river; otherwise, if the suitability corresponding to the flow velocity is lower than the threshold, it is considered that the river is not suitable for fish migration under the current flow velocity condition.

[0103] S5、According to the river network flow direction, the water system connectivity between the suitable migration rivers is calculated;

[0104] In this embodiment, the river network flow direction data mainly comes from the output of the previously constructed one-dimensional tidal river network hydrodynamic model. The model considers factors such as inflow, tide and river topography to simulate the water flow direction of each river at different times, which is the basis for subsequent calculation.

[0105] When constructing the river connection network, the topological relationship between the suitable migration rivers is analyzed by using geographic information system and other tools, which is abstracted into a network node graph. Each node represents a suitable river, and the connection line reflects the connection and the direction consistent with the water flow, which helps to intuitively present the association architecture between rivers.

[0106] Among the indicators for calculating the flow connectivity of the water system, the connectivity coefficient is one of the key indicators, which reflects the overall connectivity by comparing the actual number of connected suitable river channels with the theoretically possible number. For example, the closer the coefficient is to 1, the better the connectivity. The flow-weighted connectivity indicator further takes into account the flow factor, and the connected river channel pairs are weighted and summed according to the flow, because in the actual river network, the flow size will affect the transmission efficiency of matter and organisms between river channels. This indicator can more accurately depict the flow characteristics of the water system under the synergistic action of water flow and flow.

[0107] The application of graph theory algorithm is also indispensable. The depth-first or breadth-first search algorithm starts from a river node, traverses the network along the water flow, records the number of reachable nodes and the path length, and then obtains the reachability indicator and path connectivity indicator. The reachability indicator shows the proportion of the range of river channels that can be reached from a specific node, reflecting the connectivity breadth; the path connectivity indicator reflects the depth and continuity of the connectivity, which evaluates the water system connectivity from different dimensions.

[0108] For the tidal river network, due to the periodic influence of tides, the flow connectivity of the water system needs to be calculated in different time periods. During the rising tide and falling tide stages, the change of water flow direction and flow will cause the water system connectivity to change dynamically. By comparing the various connectivity indicators at different tidal stages, the complex influence of tides on the flow connectivity of fish migration channels can be deeply understood, providing a strong basis for comprehensive and accurate evaluation of fish migration ecological conditions.

[0109] Further, in step S5, the calculation of the flow connectivity between suitable migration river channels includes the following steps:

[0110] S51, calculate the connectivity factor of all river channels in the river network;

[0111] Further, the connectivity factor is calculated by the following formula:

[0112]

[0113] ωij= |log (N) - log (ni)| ij ωij= |log (N) - log (ni)| ij ωij= |log (N) - log (ni)|

[0114] It should be noted that due to the particularity of the tidal river network in the study area, the flow is large and there is a reciprocating flow, and the connectivity factor is calculated by scaling down the multi-year average runoff by the same proportion and taking the absolute value.

[0115] S52, according to the water flow direction of the river network, construct the adjacency matrix between all river channels;

[0116] In the embodiment, the adjacency matrix is a mathematical expression based on graph theory, which is used to clearly present the connection relationship between elements (here, suitable migratory river channels). According to the key information of the river network flow direction, it is determined whether there is a direct connection between all river channels and the flow direction. If there is a direct water flow connection between two river channels, and the flow direction is consistent with the set (for example, from the upstream river channel to the downstream river channel), mark 1 at the corresponding position of the adjacency matrix, indicating that they are adjacent and have water flow connection; if there is no such direct connection, mark 0. By constructing the adjacency matrix, the complex connection between the entire river channel can be intuitively and normatively presented, which is convenient for subsequent mathematical operation and connectivity analysis.

[0117] S53, the connectivity factor is substituted into the adjacency matrix to obtain a judgment matrix of the water system connectivity between suitable migratory river channels; the judgment matrix is used to judge the water system connectivity between any two suitable migratory river channels.

[0118] Further, in step S53, the water system connectivity between any two suitable migratory river channels is calculated according to the following formula:

[0119]

[0120] In the formula, d mn represents the water system connectivity between two suitable migratory river channels; P mn represents the sum of the connectivity of all river channels from the end point m of the suitable migratory river channel in the upstream to the start point n of the suitable migratory river channel in the downstream; P mn represents the number of river channels from the end point m of the suitable migratory river channel in the upstream to the start point n of the suitable migratory river channel in the downstream.

[0121] S6, the water system connectivity is used as a weight to calculate the adjusted total length of the suitable migratory river channel;

[0122] In the embodiment, the water system connectivity is used as a weight to adjust the total length of the suitable migratory river channel. The adjusted total length of the suitable migratory river channel pays more attention to the connectivity between river channels. The suitable migratory river channel with the strongest connectivity to the nearest suitable migratory river channel can obtain a higher weight, indicating that the two suitable migratory river channels have more continuity and are more conducive to fish migration.

[0123] Further, in step S6, the adjusted total length of the suitable migratory river channel is calculated according to the following formula:

[0124]

[0125] μ k = d k / d sum ,

[0126] wherein L sum represents the adjusted total length of suitable migratory river channels; W k represents the average flow rate suitability index of the kth suitable migratory river channel, and N is the number of suitable migratory river channels; L k represents the length of the kth suitable migratory river channel; μ k represents the connectivity weight of the kth suitable migratory river channel; d k represents the sum of the connectivity of the kth suitable migratory river channel and the nearest suitable migratory river channel; d sum represents the total sum of the connectivity of all suitable migratory river channels and the nearest suitable migratory river channel.

[0127] S7, determining the fish migration ecological flow according to the mapping relationship between the adjusted total length of suitable migratory river channels and the incoming water flow.

[0128] In this embodiment, establishing the mapping relationship between the adjusted total length of suitable migratory river channels and the incoming water flow is a complex and key link. A large amount of data obtained in the previous simulation under different incoming water flow and tidal conditions needs to be deeply mined and analyzed. For example, under low flow conditions, the total length of suitable migratory river channels may be greatly reduced due to the decrease of water level, the slowing down of water flow in some river channels, or even the interruption of water flow. When the flow is high, although the overall water quantity is abundant, the flow rate in some areas is too fast, exceeding the suitable range for fish, which also causes changes in the suitable length. Mathematical statistical methods, such as multiple linear regression, nonlinear curve fitting (such as quadratic function, exponential function, etc.), are used to try to construct a quantitative relationship model between the two.

[0129] After determining the mapping relationship model, the fish migration ecological flow is determined according to the biological characteristics and ecological needs of fish. From the perspective of fish migration habits, different fish have specific requirements for river flow rate, depth and continuity at different life stages (such as the foraging migration of juvenile fish and the reproductive migration of adult fish). For example, some fish need a relatively stable and moderate flow rate of continuous river channels to successfully reach the spawning ground during reproductive migration. From the perspective of reproductive needs, suitable water flow conditions are helpful for the hatching of fish eggs and the survival of juvenile fish. If the flow rate is too large, the fish eggs may be dispersed, and if the flow rate is too small, problems such as oxygen deficiency may occur.

[0130] Further, in step S7, a Bayesian network model between the water flow, the water system connectivity and the adjusted total length of suitable migratory river channels is also constructed to determine the comprehensive influence of the water flow and the water system connectivity on the adjusted total length of suitable migratory river channels; the Bayesian network model has a model structure in which the water flow and the water system connectivity are parent nodes and the adjusted total length of suitable migratory river channels is a child node; and the water flow is a parent node and the water system connectivity is a child node, and the parent node and the child node are connected by a directed edge.

[0131] In the present embodiment, the Bayesian network is a powerful probabilistic graphical model that excels in handling uncertainty and complex causal relationships. Structurally, it is a directed acyclic graph. Nodes represent random variables, such as the water flow, the water system connectivity and the adjusted total length of suitable migratory river channels in this ecological scenario. The directed edges between these nodes represent conditional dependencies between variables. The direction of the directed edge embodies the direction of causality or influence, for example, in this model, the edge pointing from the parent node to the child node indicates that changes in the parent node variable will have an impact on the child node variable. At the probabilistic level, the Bayesian network is based on Bayes' theorem. It describes the relationships between variables through conditional probability distributions. Taking this model as an example, for the adjusted total length of suitable migratory river channels as a child node, its probability distribution is determined based on the values of the two parent nodes, the water flow and the water system connectivity. Specifically, if the water flow is known to be in a certain specific range and the water system connectivity is in a certain specific state, the probability of the total length of suitable migratory river channels being in the corresponding range can be calculated according to the conditional probabilities stored in the Bayesian network. In the present embodiment, the water flow and the water system connectivity are parent nodes and the total length of suitable migratory river channels is a child node, which means that these two factors have a direct impact on the total length of suitable migratory river channels. Changes in the water flow will affect the water flow velocity, water level and other factors of the river channel, and in turn affect the migration conditions of fish and other organisms. For example, when the water flow increases, the water flow velocity increases, which may carry more nutrients, benefiting the survival and migration of fish, thereby increasing the total length of suitable migratory river channels. The water system connectivity affects the connectivity between river channels and the smoothness of water flow. High connectivity can make water exchange between different river channels more frequent, providing more migration paths for fish and increasing the total length of suitable migratory river channels. At the same time, the water flow is a parent node and the water system connectivity is a child node, and they are connected by a directed edge, which embodies the influence of the water flow on the water system connectivity. For example, an increase in the water flow may break through some blocked river channel connections, increasing the water system connectivity; while a decrease in the water flow may cause some river channels to dry up, reducing the water system connectivity.

[0132] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, as long as the changes or modifications do not deviate from the technical solution of the present application. Any modification, change, equivalent change and modification of the above embodiments made according to the technical essence of the present application still belong to the scope of the technical solution of the present application.

Claims

1. An ecological flow assessment method for maintaining fish migration channels in tidal river networks, characterized by: The following steps are involved: S1. Collect river network data of the study area from hydrological yearbooks and the national surface water assessment cross-section network. The river network data includes daily flow data, tidal high and low tide data, and cross-section water quality data. S2. Use river network data to construct a one-dimensional tidal river network hydrodynamic model to simulate the hydrodynamic conditions of the study area; S3, setting different water flow and tidal condition scenarios, inputting the one-dimensional tidal river network hydrodynamic model, and outputting the flow velocity of each river channel in the river network; S4. Obtain a flow velocity suitability curve for target fish species, substitute the flow velocity of each river channel in the river network into the flow velocity suitability curve, and obtain a suitable migratory river channel; S5. Calculate the flow characteristics of the water system between the suitable migratory rivers according to the flow direction of the river network; S6. Using the water system connectivity as the weight, calculate the adjusted total length of the suitable migratory river channel; S7. Determine the ecological flow rate for fish migration based on the mapping relationship between the adjusted total length of the suitable migratory river channel and the inflow flow rate; In step S5, the calculation of the flowability of the water system between the suitable migratory rivers includes the following steps: S51. Calculate the connectivity factor of all rivers in the river network. The connectivity factor is calculated using the following formula: ， Where: ω ij Indicates that the suitable migratory river is along the direction of water flow from the starting point i To the end j Connectivity factor; H ij represents the hourly average flow of the river suitable for migration; a River network in the study area N Average annual runoff; S52. Construct an adjacency matrix between all river channels according to the flow direction of the river network; S53, substituting the connectivity factor into the adjacency matrix to obtain a judgment matrix of water system connectivity between suitable migratory rivers; the judgment matrix is ​​used to judge the water system connectivity between any two suitable migratory rivers; The calculation formula for determining the water system connectivity between any two suitable migratory rivers is: ， Where, d mn It indicates the connectivity of the water system between two suitable migratory rivers; P mn Indicates the end point of the suitable migratory river located upstream m To the starting point of the downstream suitable migratory river n , the sum of the connectivity of all the rivers it passes through; P mn Indicates the end point of the suitable migratory river located upstream m To the starting point of the downstream suitable migratory river n , the number of rivers passed through.

2. The ecological flow assessment method for maintaining fish migration channels in tidal river networks according to claim 1 is characterized by: In step S2, the one-dimensional tidal river network hydrodynamic model is constructed based on the MIKE HYDRO RIVER platform, and the steps include: S21. River Network Generalization: The actual river network in the study area is sorted out, and major river channels are selected based on the terrain. The skeleton structure of the river network is determined, and nodes are divided at key locations. Continuous river channels are discretized into interconnected computational units to form a network topology that facilitates model description and calculation. Key locations include river intersections and places where river widths change. S22. Cross-section file preparation: Collect measured cross-section topographic data of each river channel, use the measurement point information to construct and fit the cross-section shape of the river channel unit in the platform, and characterize the geometric characteristics of the river channel based on the change of the cross-section shape over time; S23. Boundary Condition Setting: Set the upstream flow boundary, select appropriate measuring stations based on daily flow data to import flow data for different time periods, and simultaneously set the downstream tidal boundary. Use the tidal high and low tide data to input water level change data at the estuary section to fully simulate the actual conditions of various water flows entering and leaving the river network. S24. Hydrodynamic parameter setting: Determine the key physical parameters that affect water flow, set the river channel roughness, select and optimize parameters based on field conditions and experience, and set gravity acceleration, curve resistance coefficient, and wind resistance coefficient as needed; S25. Simulation calculation: Based on the set time step and the hydrodynamic equations, the water level and flow velocity in each river unit are calculated step by step from the initial moment. Information transmission and interaction are achieved through nodes to simulate the dynamic evolution of river network water flow. S26. Result comparison: Collect measured water level and flow rate data at each key location, compare the measured results with the simulation output results, and use the determination coefficient and Nash-Sutcliffe efficiency coefficient to evaluate the simulation accuracy. If it does not meet the requirements, return to adjust the relevant settings until the results meet the accuracy requirements.

3. The ecological flow assessment method for maintaining fish migration channels in tidal river networks according to claim 2 is characterized by: In step S25, the hydrodynamic equations are configured as the Saint-Venant equations, including the continuity equation and the momentum equation; the calculation formula of the continuity equation is: ， The momentum equation is calculated as follows: ， Where: Q For traffic; q Single width flow for lateral inflow or outflow; A is the water flow area; h is the water level; R is the hydraulic radius; C is the Xiecai coefficient; α is the momentum correction factor; t Indicates time; x Indicates the mileage direction along the river; g Represents the acceleration due to gravity.

4. The ecological flow assessment method for maintaining fish migration channels in tidal river networks according to claim 1 is characterized by: In step S6, the adjusted total length of the suitable migratory river channel is calculated as follows: ， ， Where, L sum It represents the total length of the river suitable for migration after adjustment; W k Indicates the k The average flow velocity suitability index of a suitable migratory river, N The number of rivers suitable for migration; L k Indicates the k The length of a suitable migratory channel; μ k Indicates the k The connectivity weight of a suitable migratory river; d k Indicates the k The sum of the connectivity between a suitable migratory river and the nearest suitable migratory river; d sum It represents the sum of the connectivity between all suitable migratory rivers and the nearest suitable migratory rivers.

5. The ecological flow assessment method for maintaining fish migration channels in tidal river networks according to claim 1 is characterized by: In step S7, a Bayesian network model is also constructed between the incoming water flow, the water system connectivity and the adjusted total length of the suitable migratory river channel to determine the comprehensive impact of the incoming water flow and the water system connectivity on the adjusted total length of the suitable migratory river channel; the Bayesian network model has a model structure with the incoming water flow and the water system connectivity as parent nodes and the adjusted total length of the suitable migratory river channel as child nodes; at the same time, the incoming water flow is the parent node, the water system connectivity is the child node, and the parent node and the child node are connected by directed edges.

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