Ecological flow assessment method for fish tidal river network migration channel maintenance

Abstract

The invention relates to an ecological flow assessment method for fish tidal river network migration channel maintenance. The method comprises the following steps: constructing a one-dimensional tidal river network hydrodynamic model by using river network data; setting different incoming water flows and tidal condition scenes, inputting a one-dimensional tidal river network hydrodynamic model, and outputting the flow velocity of each river channel of the river network; obtaining a flow velocity suitability curve of the target fishes, and substituting the flow velocity of each river channel of the river network into the flow velocity suitability curve to obtain a suitable migration river channel; according to the river network water flow direction, the water system circulation between the suitable migration rivers is calculated; calculating the adjusted total length of the suitable migration river channel by taking the water system connectivity as a weight; and determining the fish migration ecological flow according to the adjusted mapping relation between the total length of the suitable migration river channel and the incoming water flow. The method solves the problem that in the prior art, only the longest total length of the river channel suitable for fish migration is considered for the ecological flow, the connectivity between the river channels is not considered, and the local optimum problem is caused, so that the fish migration requirement is difficult to meet.

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 migration channel of a tidal river network for fish. Background Art

[0002] Due to the influence of tides, tidal river networks present unique and complex hydrodynamic characteristics, and hydraulic elements such as water level and water flow velocity are constantly changing. Such a complex and changing environment is not only a special challenge for fish migration, but also an important ecological background for them to adapt to and rely on. However, with the increasing intensity of human activities, factors such as water conservancy project construction, overexploitation and utilization of water resources, and the discharge of various pollutants in the basin have caused significant changes in the hydrological conditions of tidal river networks, which in turn have caused varying degrees of interference and damage to the fish migration channels. As a result, many fish populations are facing survival crises such as blocked migration, failed reproduction, and sharp decline in numbers, which also indirectly affects the balance and sustainable development of the entire river network ecosystem. Accurately assessing the ecological flow required to maintain the migration channels of fish tidal river networks has become a key issue that needs to be urgently addressed in the current field of ecological protection and water resources management.

[0003] Chinese patent CN113468825A provides a method and device for determining the ecological flow of fish migration. The steps include: based on field observations or indoor experiments of the fish to be studied, exploring the hydrological conditions that stimulate migration, and establishing the fish migration velocity suitability curve and the 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 where the fish to be studied is 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 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 is more concerned with maximizing the total length of suitable river channels for fish migration, which can easily lead to local optimal problems. For example, when the river network has insufficient water connectivity, even if the total length of suitable river channels for fish migration is maximized, the suitable river channels are intermittent, making it difficult for fish to migrate between different waters.

[0005] The water system connectivity has an important impact on the migration process of fish in tidal river networks. For tidal river networks, numerous internal rivers and tributaries are interconnected to form a complex network. The water system connectivity is directly related to whether fish can successfully find suitable migration paths and corresponding habitats and breeding grounds. Under the periodic action of tidal ebb and flow, the water level difference and water flow direction in each part of the river network change constantly. Good water system connectivity can ensure that fish can complete their migration behavior along unobstructed channels at different tidal stages. If this factor is ignored, even if other conditions such as flow rate seemingly meet the migration needs of fish, due to blockages and poor connectivity between local rivers, fish may still be trapped in a certain area and unable to reach the target location, thereby affecting their life activities such as reproduction and foraging, and ultimately posing a serious threat to the survival and reproduction of the entire fish population. Summary of the Invention

[0006] The present invention provides an ecological flow assessment method for maintaining the migration channels of fish in tidal river networks, aiming to simulate the flow velocities of each river in the river network under different incoming water flow rates and tidal conditions; determine the suitable migration rivers according to the velocity suitability curve of the target fish; then calculate the water system connectivity between the suitable migration rivers; and finally, taking the water system connectivity as the weight, calculate the total length of the adjusted suitable migration rivers to solve the problem that the ecological flow in the prior art only considers the longest total length of the suitable migration channels for fish migration and falls into the local optimal problem, resulting in difficulty in meeting the migration needs of fish.

[0007] The object of the present invention can be achieved through the following technical solutions:

[0008] The present application provides an ecological flow assessment method for maintaining the migration channels of fish in tidal river networks, including the following steps:

[0009] S1. Collect the river network data of the research area from the hydrological yearbook and the national surface water assessment section network. The river network data includes daily flow data, tide level data of high and low tides, and section water quality data;

[0010] S2. Use the river network data to construct a one-dimensional tidal river network hydrodynamic model to simulate the hydrodynamic situation of the research area;

[0011] S3. Set different incoming water flow rates and tidal condition scenarios, input them into the one-dimensional tidal river network hydrodynamic model, and output the flow velocities of each river in the river network;

[0012] S4. Obtain the velocity suitability curve of the target fish, substitute the flow velocities of each river in the river network into the velocity suitability curve, and obtain the suitable migration rivers;

[0013] S5. Calculate the water system connectivity between the suitable migration rivers according to the water flow direction of the river network;

[0014] S6. Using the water system connectivity as the weight, calculate the total length of the adjusted suitable migration channels.

[0015] S7. According to the mapping relationship between the total length of the adjusted suitable migration channels and the incoming water flow, determine the ecological flow for fish migration.

[0016] 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:

[0017] S21. River network generalization: Sort out the actual river network in the study area, select the main channels according to the terrain, determine the river network skeleton structure, and divide nodes at key positions, discretize the continuous channels into interconnected calculation units to form a network topology structure convenient for model description and calculation; the key positions include river channel intersection points and width change points.

[0018] S22. Cross-section file production: Collect the measured cross-section terrain 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 depict the geometric characteristics of the river channel according to the change of the cross-section shape over time.

[0019] S23. Boundary condition setting: Set the upstream flow boundary, select appropriate stations according to the daily flow data and import the flow data of different time periods, and at the same time set the downstream tidal boundary, input the water level change data at the estuary cross-section using the tidal high and low water level data of each tide to comprehensively simulate the actual conditions of various water flows entering and leaving the river network.

[0020] S24. Hydrodynamic parameter setting: Determine the key physical characteristic parameters affecting the water flow movement, set the river channel roughness, combine the field situation and experience to take values and optimize the parameters, and at the same time set the gravitational acceleration, bend resistance coefficient and wind resistance coefficient as required.

[0021] S25. Simulation calculation: According to the set time step, based on the hydrodynamic equations, calculate the changes of water level and flow velocity in each river channel unit over time step by step from the initial moment, and realize information transfer and interaction through nodes to simulate the dynamic evolution process of the river network water flow.

[0022] S26. Result comparison: Collect the measured water level and flow velocity data at each key position, compare the measured results with the simulation output results, and use the coefficient of determination and Nash-Sutcliffe efficiency coefficient to evaluate the simulation accuracy. If the requirements are not met, return to adjust the relevant settings until the results meet the accuracy requirements.

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

[0024]

[0025] The momentum equation has the following calculation formula:

[0026]

[0027] In the formula: Q is the flow rate; q is the unit-width flow rate of lateral inflow or outflow; A is the cross-sectional area of flow; h is the water level; R is the hydraulic radius; C is the Chezy coefficient; α is the momentum correction coefficient; t represents time; x represents the mileage direction along the river channel; g represents the acceleration due to gravity.

[0028] Furthermore, in step S26, the determination coefficient has the following calculation formula:

[0029]

[0030] The Nash-Sutcliffe efficiency coefficient has the following calculation formula:

[0031]

[0032] In the formula: Q sim is the simulated value, Q obs is the observed value, is the average observed value, is the average simulated value, t is the number of months; Ens is the Nash-Sutcliffe efficiency coefficient, which ranges from 0 to 1, and the closer it is to 1, the better the fitting effect; R 2 is the determination coefficient, which ranges from 0 to 1, and the closer it is to 1, the better the fitting effect.

[0033] Furthermore, in step S5, calculating the water system connectivity between suitable migration channels includes the following steps:

[0034] S51. Calculate the connectivity factor of all channels in the river network;

[0035] S52. Construct the adjacency matrix between all channels according to the water flow direction of the river network;

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

[0037] Furthermore, the connectivity factor has the following calculation formula:

[0038]

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

[0040] Further, in step S53, the calculation formula for determining the water system connectivity between any two suitable migratory river channels is as follows:

[0041]

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

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

[0044]

[0045] μ k = d k / d sum ,

[0046] In the formula, L sum represents the total length of the adjusted suitable migratory river channel; W k represents the average flow velocity suitability index of the k-th suitable migratory river channel, N is the number of suitable migratory river channels; L k represents the length of the k-th suitable migratory river channel; μ k represents the connectivity weight of the k-th suitable migratory river channel; d k represents the sum of the connectivity degrees between the k-th suitable migratory river channel and the nearest other suitable migratory river channels; d sum represents the total sum of the connectivity degrees between all suitable migratory river channels and the nearest other suitable migratory river channels.

[0047] Further, in step S7, a Bayesian network model between the incoming water flow rate, the water system connectivity, and the total length of the adjusted suitable migratory river channel is also constructed to determine the comprehensive influence of the incoming water flow rate and the water system connectivity on the total length of the adjusted suitable migratory river channel; for the Bayesian network model, the model structure has the incoming water flow rate and the water system connectivity as the parent nodes, and the total length of the adjusted suitable migratory river channel as the child node; at the same time, with the incoming water flow rate as the parent node and the water system connectivity as the child node, the parent node and the child node are connected by directed edges.

[0048] Advantages of the present invention:

[0049] (1) Construct a one-dimensional tidal river network hydrodynamic model using river network data; set different scenarios of incoming water flow and tidal conditions, input them into the one-dimensional tidal river network hydrodynamic model, and output the flow velocities of each river channel in the river network; obtain the flow velocity suitability curve of the target fish, substitute the flow velocities of each river channel in the river network into the flow velocity suitability curve to obtain the suitable migration channels; calculate the water system connectivity between the suitable migration channels according to the water flow direction of the river network; use the water system connectivity as the weight to calculate the total length of the adjusted suitable migration channels; determine the ecological flow for fish migration according to the mapping relationship between the total length of the adjusted suitable migration channels and the incoming water flow. The present invention solves the problem in the prior art that only the longest total length of the suitable channels for fish migration is considered for the ecological flow, without considering the connectivity between the channels, resulting in a local optimal problem and making it difficult to meet the fish migration requirements.

[0050] (2) By constructing a Bayesian network model among the incoming water flow, water system connectivity, and the total length of the adjusted suitable migration channels, determine the comprehensive influence of the incoming water flow and water system connectivity on the total length of the adjusted suitable migration channels, thereby improving the accuracy of ecological flow assessment. Description of the Drawings

[0051] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0052] Figure 1 It is a flow chart of an ecological flow assessment method for maintaining fish migration channels in a tidal river network according to the present invention.

[0053] Figure 2 It is a flow chart for calculating the water system connectivity between suitable migration channels in an embodiment of the present invention.

[0054] Figure 3 It is a structural diagram of a Bayesian network model in an embodiment of the present invention. Detailed Embodiments

[0055] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will describe in detail the specific embodiments, structures, features, and their effects of the present invention with reference to the accompanying drawings and preferred embodiments.

[0056] Please refer to Figures 1 - 3 , the present application provides an ecological flow assessment method for maintaining fish migration channels in a tidal river network, including the following steps:

[0057] S1. Collect river network data of the research area from the hydrological yearbook and the national surface water assessment section network. The river network data includes daily flow data, tidal high and low water level data, and cross-section water quality data;

[0058] In this embodiment, the Hydrological Yearbook, as an authoritative data integration in the hydrological field, is formed after long-term, systematic, and standardized data collection and compilation by professional hydrological observation institutions. The daily flow data therein is the result of continuously recording the flow rates of river network water at different times using rigorous measurement techniques and equipment based on hydrological stations distributed at key nodes of the river network. In the form of a time series, it accurately depicts the characteristics of dynamic recharge, runoff changes, and seasonal fluctuations of water resources in the river network, providing indispensable basic data support for in-depth exploration of the movement laws of river network water flow and analysis of its internal hydrodynamic mechanisms.

[0059] The tidal high and low water level data focuses on the unique phenomenon of the tidal influence on the tidal river network. Given that the periodic ebb and flow of tides have significant and complex impacts on hydrodynamic elements such as river network water levels, flow velocities, and flow directions, this data provides a key foundation for restoring the true hydrodynamic environment of the tidal river network and constructing an actual hydrodynamic model through accurate recording of water levels at each tidal stage, and plays an irreplaceable role in understanding the migratory behaviors and adaptive strategies of fish under tidal drive.

[0060] Meanwhile, the cross-section water quality data provided by the national surface water assessment section network, relying on its extensive and reasonably distributed monitoring section system, uses professional water quality analysis methods and instruments to regularly and accurately detect multiple key water quality indicators such as dissolved oxygen, pH value, and concentrations of various pollutants in the river network water body. The water quality status is directly related to the survival suitability and migratory feasibility of fish. These data can provide important reference bases for subsequent comprehensive assessment of the river network ecological environment and accurate determination of ecological flow thresholds, thereby ensuring the effective maintenance of fish migration channels under good water quality conditions.

[0061] S2. Use the river network data to construct a one-dimensional tidal river network hydrodynamic model to simulate the hydrodynamic situation of the study area;

[0062] In this embodiment, the one-dimensional tidal river network hydrodynamic model is based on the basic theory of hydraulics. It reasonably simplifies and abstracts the complex tidal river network system, regarding it as a network structure composed of multiple interconnected river channel units. In this model, the water flow movement is described one-dimensionally along the main flow direction of the river channel, and the Saint-Venant equations (including the continuity equation and the momentum equation) are used to accurately depict the mass conservation and momentum change laws of the water flow in the river channel. The continuity equation ensures that the inflow and outflow water volumes are in mass balance at any cross-section of the river channel, while the momentum equation comprehensively considers the impacts of various factors such as river channel slope, roughness, upstream and downstream water level differences, and tidal forces on the changes in water flow velocity and water level.

[0063] River network data plays a fundamental role in the model construction process. Among them, daily flow data can provide the water volume input boundary conditions for the model at different times, helping to determine the initial flow state of the river and its changing trend over time; tide-level data of high and low tides is used to accurately characterize the tidal boundary conditions. By quantifying the periodic influence of ocean tides on the river network, it can accurately simulate the water level fluctuations at each node in the river network during the flood tide and ebb tide stages and the resulting changes in water flow velocity; although cross-section water quality data mainly focuses on reflecting the chemical characteristics of water bodies, in some extended applications of hydrodynamic simulations involving material transport and diffusion, it can also provide basic parameters for simulating the migration process of pollutants and other substances with the water flow in the river network.

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

[0065] Furthermore, 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 reasonably simplify and abstract the complex actual river network system, making it more convenient to use the model for analysis and calculation while meeting the accuracy requirements. First, it is necessary to sort out and screen the river channels in the river network according to the topography, river channel distribution, and water flow connectivity in the study area. Identify the main trunk rivers, tributaries, and river channel sections that are crucial for fish migration, and remove those relatively minor small ditches or short branch channels that have little impact on the overall hydrodynamics, so as to determine the river network skeleton structure to be considered in the model. For example, in a large estuarine tidal river network area, several main seaward channels directly connected to the ocean and with frequent fish migration and their important tributaries can be retained, and some river branches with small flow and relatively isolated surroundings can be simplified.

[0068] Then, the river channel is divided into nodes according to its flow characteristics and connectivity, and the continuous river channel is discretized into interconnected calculation units. Nodes are usually set at key positions such as river confluences, changes in the width of the river channel, and the locations of hydraulic structures (such as sluice dams). These nodes are not only the key control points where the flow state changes but also the connection points for transmitting flow information in subsequent model calculations. Through such generalization, the originally complex and intertwined river network is transformed into a network topology structure composed of nodes and river channel units, which is convenient for mathematical description and computational simulation on the MIKE HYDRO RIVER platform.

[0069] S22. Cross-section file production:

[0070] The production of cross-section files 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 water flow movement in the hydrodynamic model.

[0071] Collect the measured cross-section topographic data of each river channel in the study area. These data are generally obtained through professional topographic survey methods (such as total station survey, depth sounder sounding combined with GPS positioning, etc.). The measurement points are distributed along the cross-section direction of the river channel, which can reflect the elevation changes at the bottom of the river channel and the topographic conditions on both banks. Based on these measured data, the cross-section shapes corresponding to each river channel unit are constructed in the software platform. Usually, geometric figures such as trapezoids and rectangles are used for approximate fitting. For the cross-sections of irregular natural river channels, their true shapes are detailedly depicted through the coordinates of multiple measurement points. At the same time, it is also necessary to consider the possible changes in the river channel cross-section over time, such as seasonal scouring and silting changes, and cross-section changes caused by human activities (such as river dredging, levee construction, etc.). If there is relevant information, corresponding parameter settings or multi-temporal cross-section data can be imported into the cross-section file to more accurately reflect the actual geometric characteristics of the river network and provide a reliable basis for simulating the interaction between water flow and river channel boundaries in subsequent hydrodynamic calculations.

[0072] S23. Boundary condition setting:

[0073] The setting of boundary conditions determines the input driving factors for model simulation and the boundary constraints of the calculation range, and is one of the key links affecting the accuracy of model simulation results. For the one-dimensional tidal river network hydrodynamic model, it mainly involves the setting of upstream flow boundaries and downstream tidal boundary conditions. In terms of upstream flow boundaries, based on the collected daily flow data, a suitable hydrological station is selected as the representative point for the upstream boundary, and the flow data at different time periods recorded at this station are imported into the model according to the time series to provide water volume input conditions for the river network and simulate the incoming water situation under natural river conditions. Or, according to research needs, various scenarios such as constant flow and variable flow with different flow magnitudes can be set to analyze the impact of different incoming water conditions on the hydrodynamic characteristics of the river network.

[0074] For the setting of downstream tidal boundary conditions, using the high and low tide level data for each tide, select cross-sections directly connected to the ocean such as estuaries as downstream boundary nodes, and input the measured tidal water level process lines (including water level change data corresponding to different tidal types such as spring tides, neap tides, and small tides) into the model, enabling the model to simulate the periodic propping and pulling effects of ocean tides on the river network, and accurately reproduce the dynamic change characteristics of water levels and water flow velocities in the tidal river network with the ebb and flow of tides. In addition, if there are lateral inflows or outflows of tributaries, artificial water replenishment or drainage, etc. in the study area, corresponding lateral boundary conditions need to be set to ensure that the model comprehensively considers the actual situations of various water inflows and outflows from the river network.

[0075] S24. Hydrodynamic parameter setting:

[0076] The setting of hydrodynamic parameters aims to determine the key physical characteristic parameters that affect the movement of water flow in the river channel, enabling the model to accurately calculate based on the characteristics of water flow resistance, momentum transfer, etc. in the actual river network. Among them, the channel roughness is a core parameter, which characterizes the frictional resistance of the river channel boundary to the water flow, and its value is closely related to factors such as the riverbed material of the river channel (such as sand, silt, etc.), the vegetation coverage of the bank slope, and whether the river channel has been artificially lined. It is necessary to reasonably set the roughness values for different river channel units in the model by combining on-site river channel survey data and the empirical value ranges of similar river channels in the past, and optimize the values through multiple trial calculations and verifications to make the simulated results such as water levels and flow velocities match the measured data.

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

[0078] S25. Simulation calculation:

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

[0080] According to the set time step (which is generally reasonably selected according to the speed of river network water flow change in the study area and the required simulation accuracy, such as ranging from several minutes to dozens of minutes), starting from the initial moment, the model gradually calculates the changes in water flow state variables such as water level and flow velocity in each river channel unit at each time step according to the physical laws described by the hydrodynamic equations (such as the Saint-Venant equations). During the calculation process, through the water flow continuity condition and momentum conservation condition at the nodes, the transfer and interaction of water flow information between each river channel unit are realized, and the dynamic evolution process of the water flow in the entire river network over time under the given boundary conditions and parameters is simulated. The entire simulation calculation process may take a long time, depending specifically on the total simulation duration and the computing power of the computer. For the simulation of long time series or complex river networks, high-performance computing resources are often required to improve the calculation efficiency.

[0081] Further, the hydrodynamic equations, configured as the Saint-Venant equations, include a continuity equation and a momentum equation; the continuity equation, the calculation formula is:

[0082]

[0083] The momentum equation, the calculation formula is:

[0084]

[0085] In the formula: Q is the flow rate; q is the unit-width flow rate of lateral inflow or outflow; A is the cross-sectional area of flow; h is the water level; R is the hydraulic radius; C is the Chezy coefficient; α is the momentum correction coefficient; t represents time; x represents the mileage direction along the river channel; g represents the acceleration due to gravity.

[0086] S26. Result comparison:

[0087] By comparing and analyzing the results obtained from the simulation calculation with the actual observed data, it is judged whether the model accurately reflects the hydrodynamic situation in the study area.

[0088] Collect the measured data such as water level and flow velocity at key positions in each river channel in the study area (such as pre-set hydrological stations, important fish migration nodes, etc.), and compare these measured values with the results at the corresponding positions and corresponding times output by the model simulation. Various statistical analysis methods can be used, such as calculating the coefficient of determination (R 2) Use indicators such as the Nash-Sutcliffe efficiency coefficient to quantitatively evaluate the difference between the simulation results and the measured data. If the error indicators are within a reasonable range and the correlation coefficient is high, it indicates that the model can reproduce the actual hydrodynamic situation well and can be used for subsequent analysis and research; otherwise, it is necessary to re-examine each setting link of the model (such as boundary conditions, parameter values, etc.), make corresponding adjustments and optimizations, and perform simulation calculations and result comparisons again until the model simulation results meet the satisfactory accuracy requirements.

[0089] Furthermore, in step S26, the calculation formula for the coefficient of determination is:

[0090]

[0091] The calculation formula for the Nash-Sutcliffe efficiency coefficient is:

[0092]

[0093] Where: Q sim is the simulated value, Q obs is the observed value, is the average observed value, is the average simulated value, t is the number of months; Ens is the Nash-Sutcliffe efficiency coefficient, which is between 0 and 1, and the closer it is to 1, the better the fitting effect; R 2 is the coefficient of determination, which is between 0 and 1, and the closer it is 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 velocities of each river channel in the river network;

[0095] In this embodiment, when setting the water flow scenario, comprehensive considerations are required from many aspects. First, the historical hydrological data of the study area are deeply excavated, such as extracting key data such as multi-year average flow, low-water flow and high-water 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 focusing on the research purpose, such as analyzing the migration status of fish under different water volume environments, some targeted flow values ​​are deliberately set. Among them, the constant flow scenario is a more common setting method. A fixed flow value is selected as the input condition of the model, such as a constant value close to the multi-year average flow, so as to carefully observe the state of water flow inside the river network under the condition of conventional water supply, and judge whether it meets the migration needs of fish; or set a representative constant flow in the dry season and the flood season, and then compare the different characteristics presented by the river network under different water volume conditions. In addition, variable flow scenarios are also indispensable. Based on the law of flow changes over time obtained from actual observations, flow process lines with periodic or non-periodic changes are constructed and imported into the model as input conditions. For example, simulations are performed based on the complete daily flow data of a certain year to truly restore the response of river network water flow when the flow changes dynamically under natural conditions; or according to specific research needs, some special variable flow processes are artificially constructed, such as simulating special situations such as step-by-step changes in flow caused by upstream reservoir regulation, and in-depth exploration of the impact mechanism of this complex and variable flow change on the flow velocity of each river channel in the river network.

[0096] For the setting of tidal condition scenarios, it is mainly carried out based on the actual tidal characteristics of the estuary where the study area is located. By widely collecting the data of high and low tide levels for each tide and deeply analyzing the tidal types (covering various types such as semi-diurnal tide, diurnal tide, and irregular semi-diurnal tide), a scientific and reasonable setting is made. In terms of different tidal type scenarios, independent simulations are carried out for different types such as semi-diurnal tide and diurnal tide respectively, and the significant differences in the flow velocities of each river channel in the river network during the flood tide and ebb tide stages 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 within one lunar day (about 24 hours and 50 minutes), it is necessary to closely observe the detailed variation laws of the flow velocities of each river channel in the river network during each flood and ebb tide process; while in the diurnal tide scenario, because there is only one high tide and one low tide within a day, the differences in the water flow response of the river network at this time compared with that in the semi-diurnal tide are mainly analyzed. In terms of different tidal range scenarios, according to the variation range of the tidal range (i.e., the difference between the high tide level and the low tide level) in the actual tidal data, scenarios with different tidal ranges such as spring tide, neap tide, and small tide are set. During spring tide, the tidal range is relatively large, and the pushing and pulling effects of the tide on the river network are strong, which will cause drastic changes in the water flow velocity in the river network. At this time, the extreme values of the flow velocities of each river channel, the changes in the flow directions, and the possible significant impacts on fish migration under such strong tidal actions can be deeply analyzed; during small tide, the tidal range is relatively small, and the corresponding water flow power is relatively weak. By comparing the water flow velocities in the river network in the small tide and spring tide scenarios, the migration adaptation strategies of fish under different tidal power intensities can be deeply explored.

[0097] After completing the setting of the above incoming water flow and tidal condition scenarios, in strict accordance with the specific format and parameter setting rules required by the model, they are successively input into the one-dimensional tidal river network hydrodynamic model constructed based on professional platforms such as MIKE HYDRO RIVER. The model will, based on its built-in hydrodynamic calculation module (a module constructed based on classical theories such as the Saint-Venant equations) and the detailed information such as the pre-set river network generalization, cross-section files, boundary conditions, and hydrodynamic parameters, fully consider the superposition and mutual influence effects between the incoming water flow and the tidal action, as well as their synergistic effects with the structure of the river network itself (such as the width and bending degree of the river channels), and gradually deduce the changes in the water flow states of each river channel in the river network at each time step under the corresponding scenarios.

[0098] After the complex simulation calculation process of the model, it can finally output the flow velocity results of each river channel in the river network at different times and positions under different incoming water flow rates and tidal conditions. These flow velocity data can be intuitively displayed through diverse visualization methods (such as generating flow velocity contour maps, flow velocity vector maps, etc.), clearly presenting the spatial distribution characteristics of the flow velocity in the river network and its dynamic changes over time. For example, it can be clearly seen from the flow velocity contour map which areas have a faster flow velocity and which areas have a slower flow velocity. Combining with subsequent analysis work such as the flow velocity suitability curve of fish migration, it is possible to accurately judge which river channels are more suitable for fish migration under specific scenarios; the flow velocity vector map can clearly show the flow direction of the water in each river channel, helping to deeply understand important information such as the upstream and downstream water conditions of fish migration during the ebb and flow of tides, thus providing an indispensable key data basis for further in-depth exploration of research work such as maintaining the migration channels of fish in the tidal river network and determining scientific and reasonable ecological flow rates.

[0099] S4. Obtain the flow velocity suitability curve of the target fish, substitute the flow velocity of each river channel in the river network into the flow velocity suitability curve, and obtain the suitable migration river channels.

[0100] In this embodiment, the acquisition of the flow velocity suitability curve of the target fish is based on a large amount of scientific research and field observations. Usually, targeted fish ethology experiments and field monitoring work need to be carried out. In the laboratory, simulate the behavioral responses of the target fish under different flow velocity conditions, observe its swimming ability, activity range, survival status and other aspects of performance, and initially construct a relationship framework between the flow velocity and the fish's behavioral response through accurate measurement and data recording. For example, for some anadromous fish, when the flow velocity is low, it may show a relatively slow swimming speed and a relatively limited activity range; as the flow velocity gradually increases, its swimming vitality may be stimulated and it begins to show more active exploration behaviors; but when the flow velocity exceeds its tolerance limit, the fish will experience adverse situations such as fatigue, difficulty in breathing, and even being washed away by the water flow and losing control.

[0101] Field monitoring work further supplements and validates laboratory data. In the natural river network environment, using monitoring equipment (such as acoustic Doppler current profilers, underwater video monitoring systems, etc.), long-term tracking records are made of the actual distribution, migration paths, and group behavior characteristics of target fish in different river channel velocity regions. Combining the data results of the laboratory and the field, using mathematical modeling and statistical analysis methods, a curve that can accurately reflect the velocity suitability of target fish at different life stages (such as the juvenile stage, adult stage, breeding stage, etc.) is finally drawn. This curve generally shows a specific form. For example, within a certain suitable velocity range, the suitability of fish is relatively high, manifested as a high occurrence frequency, stable behavior patterns, and good physiological states; while in areas with too low or too high velocities, the suitability gradually decreases, indicating that these velocity conditions have certain limitations or adverse effects on the survival and migration of fish.

[0102] After obtaining the velocity suitability curve of the target fish, the water velocities of each river channel in the river network are substituted into it for analysis and calculation. For each river channel in the river network, due to factors such as incoming water flow, tidal effects, and its own river channel characteristics at different positions and different times, different velocity values will be presented. These velocity data are input into the velocity suitability curve one by one, and calculations and judgments are made through the corresponding suitability function of the curve. If the suitability corresponding to the velocity at a certain river channel position reaches or exceeds a pre-set suitability threshold (this threshold is determined according to the basic requirements for fish survival and migration and the accuracy requirements of the research), then this river channel is determined as a suitable migration river channel; conversely, if the suitability corresponding to the velocity is lower than the threshold, it is considered that this river channel is not very suitable for fish migration under the current velocity conditions.

[0103] S5. Calculate the water system connectivity between suitable migration river channels according to the water flow direction of the river network;

[0104] In this embodiment, the water flow direction data of the river network mainly comes from the output of a previously constructed one-dimensional tidal river network hydrodynamic model. This model comprehensively considers factors such as incoming water flow, tides, and river channel topography, and simulates the water flow directions of each river channel at different times. These data are the basis for subsequent calculations.

[0105] When constructing the river channel connection network, tools such as geographic information systems are used to analyze the topological relationship between suitable migration river channels and abstract it into a network node diagram. Each node represents a suitable river channel, and the connection lines reflect the connection and the direction is the same as the water flow, which helps to intuitively present the connection structure between river channels.

[0106] In calculating the water system connectivity index, the connectivity coefficient is one of the key indicators. It reflects the overall connectivity by comparing the number of pairs of suitable channels that are actually connected with the theoretically possible number of pairs. For example, the closer the coefficient is to 1, the better the connectivity. The flow-weighted connectivity index further considers the flow factor, assigns weights to the connected channel pairs according to the flow and sums them up. Because in the actual river network, the flow magnitude will affect the transmission efficiency of substances and organisms between channels, this index can more accurately depict the water system connectivity characteristics under the combined action of water flow and flow.

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

[0108] For a tidal river network, due to the periodic influence of tides, it is necessary to calculate the water system connectivity by time period. During the flood tide and ebb tide stages, the change of water flow direction and flow will cause the water system connectivity to show dynamic changes. Comparing various connectivity indicators in different tidal stages can deeply understand the complex influence law of tides on the water system connectivity of fish migration channels, providing a strong basis for comprehensively and accurately evaluating the ecological conditions of fish migration.

[0109] Furthermore, in step S5, the calculation of the water system connectivity between suitable migration channels includes the following steps:

[0110] S51. Calculate the connectivity factor of all channels in the river network;

[0111] Furthermore, the formula for the connectivity factor is:

[0112]

[0113] In the formula: ω ij represents the connectivity factor of the suitable migration channel from the starting point i to the ending point j along the water flow direction; H ij represents the time-averaged flow of the suitable migration channel; a is the average annual runoff of the river network in the study area for N years.

[0114] It should be noted that due to the particularity of the tidal river network in the study area, where the flow is large and there are reciprocating flows, the connectivity factor is calculated by taking the absolute value after being scaled down in proportion according to the average annual runoff over the years.

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

[0116] In this embodiment, the adjacency matrix is a mathematical expression based on graph theory, which is used to clearly present the connection relationships between elements (here, the suitable migration channels). Based on the key information of the water flow direction of the river network, it is determined whether there is a direct connection between all channels and the flow direction of the water. If there is a direct water connection between two channels and the flow direction conforms to the setting (for example, flowing from the upstream channel to the downstream channel), the corresponding position in the adjacency matrix is marked as 1, indicating that they are adjacent and have a water connection; if there is no such direct connection relationship, it is marked as 0. By constructing the adjacency matrix, the intricate connection situation between the entire channels can be visually and normatively presented, facilitating subsequent mathematical operations and connectivity analysis.

[0117] S53. Substitute the connectivity factor into the adjacency matrix to obtain a judgment matrix for the water system connectivity between suitable migration channels; the judgment matrix is used to judge the water system connectivity between any two suitable migration channels.

[0118] Further, in step S53, for judging the water system connectivity between any two suitable migration channels, the calculation formula is:

[0119]

[0120] In the formula, d mn represents the water system connectivity between two suitable migration channels; P mn represents the sum of the connectivity degrees of all channels passed from the end point m of the suitable migration channel located upstream to the starting point n of the suitable migration channel located downstream; P mn represents the number of channels passed from the end point m of the suitable migration channel located upstream to the starting point n of the suitable migration channel located downstream.

[0121] S6. Using the water system connectivity as the weight, calculate the adjusted total length of the suitable migration channels;

[0122] In this embodiment, using the water system connectivity as the weight to adjust the total length of the suitable migration channels, the adjusted total length of the suitable migration channels pays more attention to the connectivity between the channels. The suitable migration channels with stronger connectivity to other nearest suitable migration channels can obtain a higher weight, indicating that two suitable migration channels are more continuous and more conducive to fish migration.

[0123] Further, in step S6, for the adjusted total length of the suitable migration channels, the calculation formula is:

[0124]

[0125] μ k =d k / d sum ,

[0126] In the formula, L sum represents the total length of the adjusted suitable migration channels; W k represents the average flow velocity suitability index of the k-th suitable migration channel, and N is the number of suitable migration channels; L k represents the length of the k-th suitable migration channel; μ k represents the connectivity weight of the k-th suitable migration channel; d k represents the sum of the connectivity of the k-th suitable migration channel with the nearest other suitable migration channels; d sum represents the total sum of the connectivity of all suitable migration channels with the nearest other suitable migration channels.

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

[0128] In this embodiment, establishing the mapping relationship between the total length of the adjusted suitable migration channels and the incoming water flow is a complex and crucial step. It is necessary to deeply mine and analyze a large amount of data obtained from previous scenario simulations of different incoming water flows and tidal conditions. For example, in the low-flow scenario, due to the decrease in water level, the slowdown or even interruption of the water flow in some channels, the total length of the suitable migration channels may be significantly reduced; while in the high-flow scenario, although the overall water volume is sufficient, the flow velocity in some areas is too fast, exceeding the suitable range for fish, which will also cause changes in the suitable length. Mathematical statistical methods, such as multiple linear regression and non-linear curve fitting (such as quadratic functions, exponential functions, etc.), are used to try to construct a quantitative relationship model between the two.

[0129] After determining the mapping relationship model, determine the ecological flow for fish migration based on the biological characteristics and ecological needs of fish. From the perspective of fish migration habits, different fish have specific requirements for the water flow velocity, depth, and continuity of the river channel at different life stages (such as the foraging migration of juvenile fish and the reproductive migration of adult fish). For example, when some fish are on reproductive migration, they need a continuous river channel with a relatively stable and moderate flow velocity to reach the spawning ground smoothly. Considering the breeding requirements, suitable water flow conditions are conducive to the hatching of fish eggs and the survival of juvenile fish. If the flow velocity is too large, it may wash away the fish eggs, and if it is too small, it may cause problems such as hypoxia.

[0130] Further, in step S7, a Bayesian network model is also constructed among the incoming water flow rate, the water system connectivity, and the total length of the adjusted suitable migration channels to determine the comprehensive influence of the incoming water flow rate and the water system connectivity on the total length of the adjusted suitable migration channels. The Bayesian network model has a model structure where the incoming water flow rate and the water system connectivity are the parent nodes, and the total length of the adjusted suitable migration channels is the child node. At the same time, the incoming water flow rate is the parent node and the water system connectivity is the child node, and the parent node and the child node are connected by a directed edge.

[0131] In this embodiment, the Bayesian network is a powerful probabilistic graphical model, which performs excellently in dealing with uncertainty and complex causal relationships. Structurally, it is a directed acyclic graph. The nodes represent random variables, such as the incoming water flow rate, the water system connectivity, and the total length of the adjusted suitable migration channels in this ecological scenario. The directed edges between these nodes represent the conditional dependence relationships between the variables. The direction of the directed edge reflects the direction of causality or influence. For example, in this model, the edge pointing from the parent node to the child node indicates that a change in the parent node variable will have an impact on the child node variable. At the probability level, the Bayesian network is based on Bayes' theorem. It describes the relationship between variables through conditional probability distributions. Taking this model as an example, for the total length of the adjusted suitable migration channels as the child node, its probability distribution is determined based on the values of the two parent nodes, the incoming water flow rate and the water system connectivity. Specifically, if it is known that the incoming water flow rate is within a certain specific range and the water system connectivity is in a certain specific state, the probability that the total length of the suitable migration channels is within the corresponding range can be calculated according to the conditional probabilities stored in the Bayesian network. In this embodiment, taking the incoming water flow rate and the water system connectivity as the parent nodes and the total length of the suitable migration channels as the child node means that these two factors have a direct impact on the total length of the suitable migration channels. The change in the incoming water flow rate will affect the water flow velocity, water level, etc. of the river channel, and thus affect the migration conditions of organisms such as fish. For example, when the incoming water flow rate increases, the water flow velocity speeds up, which may carry more nutrients, is beneficial to the survival and migration of fish, and thus increases the total length of the suitable migration channels. The water system connectivity affects the connectivity between river channels and the smoothness of water flow. High connectivity allows for more frequent water flow exchange between different river channels, provides more migration paths for fish, and also increases the total length of the suitable migration channels. At the same time, taking the incoming water flow rate as the parent node and the water system connectivity as the child node, and connecting them by a directed edge reflects the influence of the incoming water flow rate on the water system connectivity. For example, an increase in the incoming water flow rate may flush open some blocked river channel connections, improving the water system connectivity; while a decrease in the incoming water flow rate may cause some river channels to dry up, reducing the water system connectivity.

[0132] The above are only the preferred embodiments of the present invention and do not impose any formal limitations on the present invention. Although the present invention has been disclosed above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments by using the disclosed technical content within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. An ecological flow assessment method for maintaining a fish tidal river network migration channel, characterized by: The following steps are involved: S1. Collect river network data of the study area from the hydrological yearbook and the national surface water assessment cross-section network, including 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 in the study area; S3, setting different scenarios of water flow and tidal conditions, inputting the one-dimensional tidal river network hydrodynamic model, and outputting the flow velocity of each river channel in the river network; S4, obtaining the flow velocity suitability curve of the target fish, substituting the flow velocity of each river channel in the river network into the flow velocity suitability curve, and obtaining the suitable migratory river channel; S5. Calculate the flow of water between suitable migratory rivers according to the direction of water flow in the river network; S6. Using the water system connectivity as the weight, calculate the total length of the river suitable for migration after adjustment; S7. Determine the fish migration ecological flow based on the mapping relationship between the adjusted total length of the river channel suitable for migration and the inflow flow.

2. The ecological flow assessment method for maintaining a tidal river network migration channel for fish according to claim 1, characterized in that: 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: sort out the actual river network in the study area, select the main river channels according to the terrain, determine the skeleton structure of the river network, divide nodes at key locations, discretize the continuous river channels into interconnected calculation units, and form a network topology structure that is convenient for model description and calculation; the key locations include river channel intersections and places where width and narrowness change; S22. Production of cross-section files: Collect the 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 according to the change of the cross-section shape over time; S23, boundary condition setting: set the upstream flow boundary, select appropriate measuring stations according to daily flow data to import flow data of different periods, set the downstream tidal boundary at the same time, use the high and low tide data of each tide to input water level change data at the estuary section, and fully simulate the actual conditions of various water flows entering and leaving the river network; S24, hydrodynamic parameter setting: determine the key physical characteristic parameters that affect water flow movement, set the river roughness, select and optimize the parameters based on actual conditions and experience, and set the gravity acceleration, curve resistance coefficient and wind resistance coefficient as needed; S25, simulation calculation: according to the set time step, based on the hydrodynamic equations, gradually calculate the changes of water level and flow velocity in each river unit over time from the initial moment, realize information transmission interaction through nodes, and simulate the dynamic evolution process of river network water flow; S26. Result comparison: Collect the 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 method for evaluating ecological flow for maintaining a tidal river network migration channel for fish according to claim 2, characterized in that: In step S25, the hydrodynamic equations are configured as Saint-Venant equations, including a continuity equation and a momentum equation; the continuity equation is calculated as follows: The momentum equation is calculated as follows: In the formula: Q is the flow rate; q is the single-width flow rate of lateral inflow or outflow; A is the water flow area; h is the water level; R is the hydraulic radius; C is the Xie Cai coefficient; α is the momentum correction coefficient; t represents time; x represents the mileage direction along the river channel; g represents the acceleration of gravity.

4. The ecological flow assessment method for maintaining a tidal river network migration channel for fish according to claim 1, characterized in that: In step S5, the calculation of the water system flowability between the suitable migratory rivers includes the following steps: S51, calculating the connectivity factors of all rivers in the river network; S52, constructing an adjacency matrix between all river channels according to the water flow direction of the river network; S53, substituting the connectivity factor into the adjacency matrix to obtain a judgment matrix of the water system connectivity between suitable migratory rivers; the judgment matrix is ​​used to judge the water system connectivity between any two suitable migratory rivers.

5. The ecological flow assessment method for maintaining a tidal river network migration channel for fish according to claim 4 is characterized by: The connectivity factor is calculated as follows: Where: ij H represents the connectivity factor of the suitable migratory river along the flow direction from the starting point i to the end point j; ij represents the time-averaged flow rate of the river channel suitable for migration; a is the average runoff of the river network in the study area over N years.

6. The ecological flow assessment method for maintaining a tidal river network migration channel for fish according to claim 4, characterized in that: In step S53, the water system connectivity between any two suitable migratory rivers is determined by the calculation formula: Where, d mn P represents the connectivity of the water system between two suitable migratory rivers; mn P represents the sum of the connectivity of all the rivers from the end point m of the upstream suitable migratory river to the starting point n of the downstream suitable migratory river; mn It represents the number of rivers passed from the end point m of the suitable migratory river upstream to the starting point n of the suitable migratory river downstream.

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

8. The method for evaluating ecological flow for maintaining a tidal river network migration channel for fish according to claim 1, characterized in that: In step S7, a Bayesian network model between the incoming water flow, the water system connectivity and the adjusted total length of the suitable migratory river channel is also constructed 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 in which the incoming water flow and the water system connectivity are parent nodes, and the adjusted total length of the suitable migratory river channel is a child node; 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.

Images