Ecological benefit assessment method for cascade reservoir operation based on habitat model

Abstract

The invention belongs to the technical field of water ecological protection and water resource management, and particularly provides a cascade reservoir operation ecological benefit evaluation method based on a habitat model, and the method comprises the steps: collecting the topographic data of a downstream fish spawning site of a cascade reservoir, the actual measurement hydrological data of a hydrological station, and the biological data of target fishes; performing unstructured triangular mesh division on the research river reach by adopting a finite volume method, and simulating flow velocity and water depth distribution of a research area through a continuity equation and a momentum equation; according to the biological data of the target fish, a suitability curve of the flow velocity and the water depth is constructed, and the habitat suitability index HIS of each grid is calculated in combination with the flow velocity and water depth data output by the hydrodynamic module; and calculating an effective available area WUA and an overall suitability index OSI based on the HSI value for ecological benefit assessment. The method comprehensively considers the influence of the cascade reservoirs on the correlation factors, accurately evaluates the ecological benefits, and provides a scientific basis for ecological scheduling of the cascade reservoirs and fish resource protection.

Description

Technical Field

[0001] This invention belongs to the field of water ecological protection and water resource management technology, specifically, it relates to a method for evaluating the ecological benefits of cascade reservoir operation based on a habitat model. Background Technology

[0002] Fish spawning grounds are the core areas for the renewal and maintenance of aquatic biological populations, and their habitat quality directly affects the success rate of fish reproduction. The construction and operation of cascade reservoirs have altered the hydrological processes, hydrodynamic conditions, water temperature, and bottom structure of downstream rivers, significantly impacting fish spawning grounds. For example, they can weaken the flood pulse effect, reduce flow velocity, and change the pattern of water level fluctuations, thus hindering the reproduction of drifting-egg-laying fish.

[0003] Currently, fish habitat assessment methods mostly focus on the impact analysis of single reservoirs, lacking a systematic assessment of spawning ground habitats under the joint operation of cascade reservoirs. Existing models often simplify hydrodynamic processes or ignore the coupling relationship between fish biological characteristics and environmental factors, resulting in limited assessment accuracy. Therefore, it is necessary to construct an ecological benefit assessment method that comprehensively considers the regulation characteristics of cascade reservoirs, hydrodynamic processes, and the ecological needs of fish. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for assessing the ecological benefits of cascade reservoir operation based on habitat model, so as to achieve accurate assessment of the ecological benefits of cascade reservoirs.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for assessing the ecological benefits of cascade reservoir operation based on a habitat model, comprising the following steps: S1. Data collection: Collect topographic data of fish spawning grounds downstream of the cascade reservoirs, measured hydrological data from hydrological stations, and biological data of target fish species. The biological data of target fish species include spawning period, suitable flow velocity, and water depth range. S2. Hydrodynamic Module Construction: Based on hydrodynamic and hydrological simulation software, the finite volume method is used to divide the study river section into unstructured triangular meshes, set inlet, outlet and solid wall boundary conditions, and simulate the velocity and water depth distribution in the study area through continuity equation and momentum equation. S3. Habitat Module Construction: Based on the biological data of the target fish, construct the suitability curves of current velocity and water depth, and combine the current velocity and water depth data output by the hydrodynamic module to calculate the habitat suitability index (HSI) for each grid. S4. Ecological Benefit Assessment: Based on the HSI value, the effective usable area (WUA) and the overall suitability index (OSI) are calculated for ecological benefit assessment. The effective usable area (WUA) is the sum of the products of the HSI values ​​of all grid cells in the study area and the corresponding grid areas. The overall suitability index (OSI) is the ratio of the effective usable area (WUA) to the total area of ​​the spawning area.

[0006] In a preferred embodiment, in step S1, the topographic data includes cross-sectional and longitudinal profile data of the river channel of the study section, which is used for unstructured triangular mesh generation in step S2; the hydrological data includes daily flow and water level data, with a time span covering the spawning period of the target fish.

[0007] In the preferred embodiment, in step S2, the inlet boundary condition is based on the daily flow data measured by the hydrological station, and the outlet boundary condition is based on the daily water level data measured by the hydrological station.

[0008] In the preferred embodiment, in step S2, if there is no outlet hydrological station, the outlet water level is estimated by establishing a water level-discharge relationship curve using the HEC-RAS one-dimensional model.

[0009] In the preferred embodiment, in step S2, the expressions for the continuity equation and the momentum equation are: The continuity equation is: ; The momentum equation in the x-direction is: ; The momentum equation in the y-direction is: ; In the formula: and They are fluids in , Velocity component in the direction; For water depth; It is time; It is the acceleration due to gravity; This refers to the water surface elevation. It is the density of water; These are Coriolis parameters; and It is the shear stress in the riverbed; , , and It is Reynolds stress.

[0010] In the preferred embodiment, in step S3, the suitability curves for flow velocity and water depth are in univariate curve format, with the vertical axis representing the suitability index SI, which ranges from 0 to 1, and the horizontal axis representing either flow velocity or water depth.

[0011] In the preferred embodiment, the habitat suitability index (HSI) is calculated using the following formula: ; In the formula: For the first Habitat suitability index for each grid; and These are the suitability indices for flow velocity and water depth, respectively.

[0012] In a preferred embodiment, in step S3, the habitat quality is divided into three suitability levels: high, medium, and low, based on the HSI value. The HSI value range for the high suitability level is 0.7~1.0, for the medium suitability level it is 0.3~0.7, and for the low suitability level it is 0.0~0.3. Habitat quality is further divided into three categories: High Suitability Percentage (HSP), Medium Suitability Percentage (MSP), and Low Suitability Percentage (LSP), representing the percentage of ideal, moderate, and unsuitable habitat areas in the total area of ​​the study area, respectively. The formulas for each suitability percentage are as follows: ; ; ; In the formula: For the first Each grid area; The area of ​​the grid with an HSI value ≤ 0.3; The area of ​​the grid with an HSI value of 0.3 < HSI value ≤ 0.7; The area of ​​the grid with an HSI value > 0.7; The number of grids in the spawning river section was determined in the study.

[0013] In the preferred embodiment, in step S4, the formulas for calculating the effective usable area (WUA) and the overall suitability index (OSI) are as follows: ; ; In the formula: For the first Each grid area; To determine the number of grids in the spawning river section of the study; For the first The habitat suitability index of each grid; the larger the WUA, the larger the area suitable for fish spawning.

[0014] The preferred scheme also includes S5, model validation: comparing the flow velocity and water depth data simulated by the hydrodynamic module with the measured data, and comparing the HSI distribution calculated by the habitat module with the historical spawning ground distribution of the target fish to verify the accuracy of the model.

[0015] The present invention provides a method for evaluating the ecological benefits of cascade reservoir operation based on a habitat model, which has the following beneficial effects: 1. In the data collection phase, this invention specifically covers the core data of fish spawning grounds downstream of cascade reservoirs: topographic data includes river cross-section and longitudinal profile data, providing accurate topographic support for unstructured triangular grid division; hydrological data uses daily flow and water level measured by hydrological stations, and the time span completely covers the spawning period of the target fish, ensuring the capture of hydrological dynamics during the critical spawning period; at the same time, biological data such as the spawning period of the target fish and the suitable flow velocity / water depth range are included to achieve coordinated matching of hydrological, topographic and biological data.

[0016] 2. The hydrodynamic module of this invention employs the finite volume method to divide unstructured triangular meshes. Compared to traditional structured meshes, this method can more flexibly adapt to the complex terrain of the studied river section (such as meandering channels and transition zones between shallow and deep water areas), enabling adaptive mesh refinement and improving the simulation accuracy of key local areas (such as fish spawning core areas). Simultaneously, the boundary conditions are set with both practicality and flexibility: measured daily flow rates are used at the inlet, and measured daily water levels are prioritized at the outlet. When no measured outlet data is available, the water level is estimated using the HEC-RAS one-dimensional model, effectively solving the boundary input problem under different hydrological monitoring conditions. Through continuity and momentum equations, the flow velocity and water depth distribution are accurately simulated, providing high spatial resolution and high accuracy hydrodynamic foundation data for subsequent habitat suitability index (HSI) calculations, avoiding habitat assessment biases caused by hydrodynamic simplification.

[0017] 3. In the habitat module construction process of this invention, a univariate curve format is used to construct flow velocity and water depth suitability curves. The vertical axis SI value intuitively reflects the suitability of the target fish species to environmental factors, while the horizontal axis precisely corresponds to the flow velocity / water depth parameters. By integrating flow velocity and water depth suitability indices through the HSI calculation formula, the habitat quality of a single grid is quantified. Furthermore, three suitability levels—high, medium, and low—are divided according to HSI values, and the proportions of high suitability (HSP), medium suitability (MSP), and low suitability (LSP) are calculated. This allows for precise identification of the spatial distribution and area proportion of ideal, moderate, and unsuitable habitats within the study river section, achieving a refined and differentiated assessment of habitat quality.

[0018] 4. This invention innovatively adopts a dual-indicator system of effective usable area and overall suitability index for benefit evaluation. WUA directly quantifies the actual scale of the suitable area for fish spawning by accumulating the HSI values ​​of all grids and multiplying them by the grid area. OSI reflects the proportion of suitable habitat in the entire spawning area by the ratio of WUA to the total area of ​​the spawning area. The two indicators work together to quantify ecological benefits from two dimensions: absolute area and relative proportion, avoiding the one-sidedness of a single indicator.

[0019] 5. Taking into account the impact of cascade reservoir regulation on hydrological and hydrodynamic factors, the assessment is more in line with actual scenarios.

[0020] 6. By coupling hydrodynamic simulation with fish biological characteristics, ecological benefits are quantified through multiple indicators such as HSI, WUA, and OSI, thereby improving the accuracy of the assessment.

[0021] 7. It can guide the ecological management of cascade reservoirs and provide a scientific basis for the protection of fish spawning grounds. Attached Figure Description

[0022] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a flowchart of the process of this invention; Figure 2 This is a schematic diagram of the study area in the Yibin section of the river. Figure 3 This data represents the average daily outflow and reservoir water level at Xiangjiaba Reservoir from May to June, from 2017 to 2023. Figure 4 The grid division of the Yibin section of the river; Figure 5 The flow velocity and water depth suitability curves; Figure 6 The daily average WUA, HSP, MSP, and LSP levels of the round-mouthed copper fish in the Yibin section of the river during the ecological regulation period in 2017; Figure 7 The daily average WUA, HSP, MSP, and LSP levels of the round-mouthed copper fish in the Yibin section of the river during the ecological regulation period in 2018; Figure 8 The daily average WUA, HSP, MSP, and LSP levels of the round-mouthed copper fish in the Yibin section of the river during the 2019 ecological regulation period; Figure 9 The daily average WUA, HSP, MSP, and LSP levels of the round-mouthed copper fish in the Yibin section of the river during the ecological regulation period in 2020; Figure 10 The daily average WUA, HSP, MSP, and LSP levels of the round-mouthed copper fish in the Yibin section of the river during the ecological dispatching period in 2022; Figure 11The daily average WUA, HSP, MSP, and LSP levels of the round-mouthed copper fish in the Yibin section of the river during the ecological dispatching period in 2023; Figure 12 To verify the comparison between the simulated water level and the measured water level at the Yibin Hydrological Station during the period. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0024] Example 1: like Figure 1 As shown, a method for assessing the ecological benefits of cascade reservoir operation based on a habitat model includes the following steps: S1, Data Collection.

[0025] Collect topographic data of fish spawning grounds downstream of cascade reservoirs, measured hydrological data from hydrological stations, and biological data of target fish species. The biological data of target fish species include spawning period, suitable flow velocity, and water depth range.

[0026] Topographic data includes cross-sectional and longitudinal profile data of the river channel in the study section, which are used for unstructured triangular mesh generation in step S2.

[0027] The hydrological data includes daily flow and water level data, covering the spawning period of the target fish species.

[0028] S2, Hydrodynamic Module Construction.

[0029] Based on hydrodynamic and hydrological simulation software, the finite volume method was used to divide the study river section into unstructured triangular meshes, and inlet, outlet and solid wall boundary conditions were set. The velocity and water depth distribution in the study area were simulated through continuity equation and momentum equation.

[0030] The specific description is as follows: Mesh generation: The finite volume method was used to generate unstructured triangular meshes for the study river section, and adaptive densification was carried out based on the principle of balancing accuracy and efficiency (e.g., the Yibin river section has 62,524 mesh nodes and 119,826 cells).

[0031] Boundary conditions are set as follows: the inlet boundary uses the daily flow rate measured by hydrological stations (such as the inflow data of the Jinsha River, Minjiang River, and Hengjiang River); the outlet boundary uses the daily water level measured by actual measurements. If no actual measurement data is available, the water level-flow relationship is calculated by establishing a water level-flow relationship through the HEC-RAS model; the solid wall boundary is set as a non-slip condition.

[0032] Hydrodynamic simulation: Based on TELEMAC-MASCARET software, the flow velocity and water depth distribution are simulated through the continuity equation and momentum equation. The shear stress of the riverbed is calculated using the Manning formula, and the Reynolds stress is solved using the k-ε turbulence model.

[0033] The expressions for the continuity equation and the momentum equation are: The continuity equation is: ; The momentum equation in the x-direction is: ; The momentum equation in the y-direction is: ; In the formula: and They are fluids in , Velocity component in the direction (m / s); Water depth (m); It is time (s); Acceleration due to gravity (m / s²) 2 ); Water surface elevation (m); It is the density of water (kg / m³) 3 ); It is the Coriolis parameter (related to the Earth's rotation, in most cases, = 0); and Riverbed shear stress (kg / ms) 2 ); , , and It is the Reynolds stress (kg / ms) 2 ).

[0034] S3, Habitat Module Construction.

[0035] Based on the biological data of the target fish species, a suitability curve for flow velocity and water depth is constructed. Combined with the flow velocity and water depth data output by the hydrodynamic module, the habitat suitability index (HIS) for each grid is calculated.

[0036] Specifically, it includes: Suitability curve construction: Using a univariate curve format, and combining literature and field data, a suitability curve (SI curve) for the target fish species to current velocity and water depth was constructed. The SI value ranged from 0 to 1, reflecting the degree of suitability.

[0037] The fitness curves for flow velocity and water depth are in univariate curve format, with the vertical axis representing the fitness index SI, ranging from 0 to 1, and the horizontal axis representing flow velocity or water depth.

[0038] HSI Calculation: For each grid, the habitat suitability index is calculated by combining the hydrodynamic simulation results with the SI curve, and the suitability level is divided: HSI 0.7-1.0 is high suitability, 0.3-0.7 is medium suitability, and 0.0-0.3 is low suitability; the proportions of high, medium and low suitability (HSP, MSP, LSP) are calculated, that is, the area proportion of each level.

[0039] The habitat suitability index (HIS) is calculated using the following formula: ; In the formula: For the first Habitat suitability index for each grid; and These are the suitability indices for flow velocity and water depth, respectively.

[0040] Habitat quality was classified into three categories: High Suitability (HSP), Medium Suitability (MSP), and Low Suitability (LSP), representing the percentage of ideal, moderate, and unsuitable habitat areas in the study area relative to the total area. The formulas for each suitability percentage are as follows: ; ; ; In the formula: For the first Each grid area; The area of ​​the grid with an HSI value ≤ 0.3; The area of ​​the grid with an HSI value of 0.3 < HSI value ≤ 0.7; The area of ​​the grid with an HSI value > 0.7; The number of grids in the spawning river section was determined in the study.

[0041] S4. Ecological benefit assessment.

[0042] The effective usable area (WUA) and overall suitability index (OSI) are calculated based on the HSI value for ecological benefit assessment. The effective usable area (WUA) is the sum of the products of the HSI value of all grid cells in the study area and the corresponding grid area. The overall suitability index (OSI) is the ratio of the effective usable area (WUA) to the total area of ​​the spawning area.

[0043] The formulas for calculating the Effective Usable Area (WUA) and the Overall Suitability Index (OSI) are as follows: ; ; In the formula: For the first Each grid area; To determine the number of grids in the spawning river section of the study; For the first The habitat suitability index of each grid; the larger the WUA, the larger the area suitable for fish spawning.

[0044] S5. Model Validation: Compare the flow velocity and water depth data simulated by the hydrodynamic module with the measured data, and compare the HSI distribution calculated by the habitat module with the historical spawning ground distribution of the target fish to verify the accuracy of the model.

[0045] Example 2: This embodiment uses a habitat model-based method for assessing the ecological benefits of cascade reservoir operation to evaluate the ecological benefits of fish spawning grounds during the peak spawning period of the round-mouthed copper fish in the Yibin section of the Yangtze River upstream rare and endemic fish national nature reserve downstream of Xiangjiaba. The method includes the following steps.

[0046] Step 1: Collect underwater topographic data for this river section, see... Figure 2 .

[0047] The ecological scheduling data of Xiangjiaba Reservoir is shown in Table 1.

[0048] Daily flow and water level data for Xiangjiaba, Gaochang, and other hydrological stations from 2017 to 2023 can be found here. Figure 3 The peak spawning period for the round-mouthed copper fish is from early May to late June.

[0049]

[0050] Step 2: Construction of the hydrodynamic module Mesh generation: An unstructured triangular mesh was generated using the finite volume method, adhering to the principle of balancing accuracy control and computational efficiency. Adaptive mesh refinement was performed based on the spatial scale and resolution requirements of the study area, ultimately generating a total of 62,524 mesh nodes and 119,826 elements. (See...) Figure 4 .

[0051] Boundary conditions: The inlet boundary is the daily flow rate from May to July at the Xiangjiaba (Jinsha River), Gaochang (Minjiang River), and Hengjiang hydrological stations; the outlet boundary is the daily water level at the Lizhuang hydrological station.

[0052] Step 3: Habitat Module Construction Suitability Curves: The suitable flow velocity for spawning of the round-mouthed copper fish was determined to be 0.1~1.7 m / s, with an optimal flow velocity of 0.3~1.3 m / s. The suitable water depth was determined to be 0.3~19.5 m, with an optimal water depth of 1.2~11.5 m. Based on the preferred flow velocity and water depth ranges, flow velocity SI curves and water depth SI curves were plotted. (See...) Figure 5 .

[0053] HSI Calculation: For each grid, extract the simulated flow velocity and water depth, look up the SI value based on the fitness curve, and then calculate the HSI value according to the formula.

[0054] Step 4: Ecological Benefit Assessment Calculation of Wildlife Area (WUA) and Organismic Isophora (OSI): During the ecological regulation of Xiangjiaba Reservoir from 2017 to 2023, the overall WUA in the spawning grounds of the roundmouth copperfish in the Yibin section of the river showed a daily upward trend, indicating that ecological regulation helped to improve WUA and habitat quality. The WUA distribution range was 8.14–13.01 km. 2 The median and mean were 9.50 km. 2 and 9.73 km 2 .

[0055] Suitability ratio: The HSP and LSP of the spawning grounds of the round-mouthed copper fish in the Yibin section of the river are both relatively high, remaining at around 40% for many years, with fluctuations depending on the outflow from Xiangjiaba; the MSP, on the other hand, has remained below 20%, and the MSP further decreases when the outflow from Xiangjiaba is large. See details. Figures 6-11 .

[0056] Step 5: Model Validation The model was validated using daily water level data from the Yibin hydrological station from April 1 to June 30, 2023, with a roughness coefficient of 0.55 selected. Figure 12 The figure shows the comparison between the simulated water level and the measured water level at the Yibin Hydrological Station during the verification period. The results show that the root mean square error between the simulated water level and the measured water level is 0.25 m, indicating that the model accurately reflects the hydrodynamic characteristics of the studied river section and is consistent with the actual situation.

[0057] The average hydrological process during the peak spawning period of each target fish species before the construction of the cascade reservoirs in the lower reaches of the Jinsha River (2001-2012) was used to simulate the HSI of the study section. The HSI distribution was highly consistent with the historical spawning ground locations of the target fish species, verifying the rationality of the model and the fish fitness curve.

[0058] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating ecological benefits of cascade reservoir operation based on a habitat model, characterized in that, The method comprises the following steps: S1, data collection: collecting topographic data of fish spawning grounds downstream of cascade reservoirs, hydrological station measured hydrological data, and biological data of target fish, including spawning period, suitable flow velocity and water depth range; S2, water power module construction: based on hydrodynamics and hydrology simulation software, unstructured triangular mesh is divided for the research reach by using finite volume method, inlet, outlet and solid wall boundary conditions are set, and flow velocity and water depth distribution of the research area is simulated through continuity equation and momentum equation; S3, habitat module construction: according to the biological data of the target fish, the suitability curve of flow velocity and water depth is constructed, and the habitat suitability index HSI of each grid is calculated by combining the flow velocity and water depth data output by the water power module; S4, ecological benefit evaluation: based on the HSI value, the effective available area WUA and the overall suitability index OSI are calculated, which are used for ecological benefit evaluation, the effective available area WUA is the sum of the product of the HSI value of all grid units in the research area and the corresponding grid area, and the overall suitability index OSI is the ratio of the effective available area WUA to the total area of the spawning area.

2. The method according to claim 1, characterized in that, In the step S1, the topographic data includes the river cross section and longitudinal section data of the research reach, which are used for unstructured triangular mesh division in the step S2; the hydrological data includes daily flow and water level data, and the time span covers the spawning period of the target fish.

3. The method according to claim 2, wherein, In the step S2, the daily flow data measured by the hydrological station is used as the inlet boundary condition, and the daily water level data measured by the hydrological station is used as the outlet boundary condition.

4. The method according to claim 3, characterized in that, In the step S2, if there is no outlet hydrological station, the outlet water level is calculated by establishing the water level-flow relationship curve through the HEC-RAS one-dimensional model.

5. The method according to claim 1, characterized in that, In the step S2, the expressions of the continuity equation and the momentum equation are as follows: The continuity equation is: ； The momentum equation in x direction is: ； The momentum equation in y direction is: ； where: and are the velocity components of the fluid in the , directions; is the water depth; is time; is the acceleration of gravity; is the water surface elevation; is the water density; is the Coriolis parameter; and are the bed shear stresses; , , and are the Reynolds stresses.

6. The method according to claim 1, wherein, In the step S3, the suitability curve of flow velocity and water depth adopts the univariate curve format, the vertical axis is the suitability index SI, and the horizontal axis is the flow velocity or water depth.

7. The method according to claim 1, wherein, The calculation formula of the habitat suitability index HSI is: ； where: is the habitat suitability index for the nth grid cell; and are the suitability indices for flow velocity and water depth, respectively.​ 8. The method according to claim 7, wherein, In the step S3, the HSI value is divided into high, medium and low suitability grades, the HSI value range corresponding to the high suitability grade is 0.7-1.0, the HSI value range corresponding to the medium suitability grade is 0.3-0.7, and the HSI value range corresponding to the low suitability grade is 0.0-0.3; the habitat quality is divided into three types: high suitability proportion HSP, medium suitability proportion MSP and low suitability proportion LSP, which represent the percentage of ideal, medium and unsuitable habitat area in the overall area, and the suitability proportion formula is as follows: ； ； ； In the formula: For the first Each grid area; The area of ​​the grid with an HSI value ≤ 0.3; The area of ​​the grid with an HSI value of 0.3 < HSI value ≤ 0.7; The area of ​​the grid with an HSI value > 0.7; The number of grids in the spawning river section was determined in the study.

9. The method according to claim 1, characterized in that, In the step S4, the calculation formula of the effective available area WUA and the overall suitability index OSI is as follows: ； ； where: is the number of the grid area; is the number of the grid area; is the number of the grid area for the spawning river section in the study; is the number of the grid area for the spawning river section in the study; is the habitat suitability index of the grid; the larger the WUA, the larger the area suitable for fish spawning.

10. The method according to claim 1, characterized in that, S5, model verification: the flow velocity and water depth data simulated by the water power module are compared with the measured data, the HSI distribution calculated by the habitat module is compared with the historical spawning ground distribution of the target fish, and the accuracy of the model is verified.

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