A dynamic evaluation method for guarantee degree of ecological flow of cascade hydropower discharge

Abstract

This invention relates to a dynamic assessment method for the ecological flow guarantee level of cascade hydropower discharges, belonging to the field of hydrological, water resources, and ecological protection technology. The method includes: collecting multi-source data from a group of cascade hydropower stations to construct a basic database; classifying hydrological year types into high, average, and low hydrological years based on historical runoff data; calculating multi-scale guarantee rates and dynamic damage depths; constructing a Bayesian network to analyze the cascade linkage impact; establishing dual-constraint criteria to classify guarantee levels; and revising targets and scheduling schemes based on ecological monitoring data. This invention, through hydrological year type classification, dynamic damage depth correction, cascade linkage analysis, and closed-loop feedback optimization, achieves a systematic and multi-dimensional scientific assessment of the ecological flow guarantee level of cascade hydropower, providing precise decision support for the ecological scheduling of cascade hydropower stations and river ecological protection. It has the advantages of comprehensive assessment, intuitive results, and dynamic optimization.

Description

Technical Field

[0001] This invention belongs to the field of hydrology, water resources and ecological protection technology, and specifically relates to a dynamic assessment method for the ecological flow guarantee level of cascade hydropower discharge. Background Technology

[0002] With the rapid advancement of hydropower development, river ecosystems are facing increasingly severe challenges. To mitigate the adverse impacts of hydropower development on river ecosystems, both domestically and internationally, it is generally required that hydropower stations release a certain amount of ecological flow. However, existing ecological flow assurance assessment methods mostly focus on a single power station or a single cross-section, using a simple compliance rate as the core indicator, which is insufficient to effectively assess the actual assurance effect of ecological flow under a cascade development model. In a cascade hydropower system, the scheduling method of the upstream power station directly determines the downstream inflow conditions, and there are complex hydraulic connections and linkages between upstream and downstream. Traditional fragmented assessments cannot reveal this cascade impact. Furthermore, the assessment indicators in existing technologies are too simplistic, ignoring the differences in inflow conditions, the severity of ecological water shortages, and the cumulative and lag effects after ecosystem damage, resulting in assessment results that cannot comprehensively and accurately reflect the ecological flow assurance situation. At the same time, the assessment work is disconnected from ecological monitoring data, lacking a closed-loop mechanism to feed back assessment results to revise ecological flow targets and scheduling schemes, making it difficult to provide a scientific basis for the refined scheduling and ecological protection of cascade hydropower. Therefore, there is an urgent need for a method that can systematically and multidimensionally assess the ecological flow guarantee of cascade hydropower projects in order to solve the problems of one-sided assessment, lack of systematicness and dynamic feedback in existing technologies. Summary of the Invention

[0003] To address the aforementioned problems in the existing technology, this invention provides a method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge.

[0004] The objective of this invention can be achieved through the following technical solutions: A dynamic assessment method for ensuring the ecological flow guarantee of cascade hydropower discharge includes: Collect runoff data, engineering operation data, and ecological flow target requirements from each section of the cascade hydropower station group to construct a basic database for ecological flow guarantee assessment; Based on historical long-term runoff data, the hydrological frequency analysis method is used to calculate the inflow frequency of each period during the assessment period, and the assessment period is divided into three hydrological year types: high-water year, normal-water year, or low-water year according to the inflow frequency. Based on the measured discharge flow data, the hourly guarantee rate, daily guarantee rate, monthly guarantee rate and annual guarantee rate are calculated respectively. The discharge flow includes the power generation flow of the power plant unit and the discharge flow of the water spillway. The depth of damage when ecological flow fails to meet the standard is calculated, including the maximum depth of damage and the cumulative depth of damage, and the ecosystem memory effect is introduced to dynamically correct the depth of damage; Construct a Bayesian network for ecological flow protection of cascade hydropower, analyze the impact of upstream hub scheduling on the protection level of downstream sections, and calculate the overall protection level of the cascade. Based on the inflow frequency and the damage depth, a dual-constraint criterion is established, a graded protection assessment function is constructed, and the ecological flow protection level of each section and the entire cascade is determined. Based on the assessment results and combined with ecological monitoring data, the ecological flow targets and scheduling schemes were revised.

[0005] In a further embodiment of the present invention, the step of "collecting runoff data, engineering operation data, and ecological flow target requirements from each section of the cascade hydropower station group, and constructing a basic database for ecological flow guarantee assessment" specifically includes: Collect measured daily average runoff data, upstream water intake data, and upstream engineering water storage data for each cross-section during the assessment period; The measured runoff was reconstructed using the hydrological reconstruction method to obtain the natural runoff data of the cross section during the assessment period, and a monthly average natural runoff data matrix for the assessment period was constructed. Collect historical long-series natural monthly average runoff data and historical long-series measured monthly average runoff data for no less than 30 years; Determine the target values ​​for ecological flow at each cross-section for different months; The above data will be stored uniformly to form a basic database for ecological flow guarantee assessment, which includes a matrix of monthly average natural runoff data during the assessment period, daily average measured runoff data during the assessment period, historical long-term series of monthly average natural runoff data, historical long-term series of monthly average measured runoff data, ecological flow targets for each section, water intake data from upstream river channels, and water storage data of upstream engineering projects.

[0006] In a further embodiment of the present invention, the step of "calculating the inflow frequency of each period in the assessment period based on historical long-term runoff data using hydrological frequency analysis methods, and dividing the assessment period into three hydrological year types—high-water year, normal-water year, or low-water year—according to the inflow frequency" includes: Extract at least 30 years of historical long-series monthly average natural runoff data from the database to construct a historical long-series monthly-scale natural runoff data matrix R. a×12 where a is the number of years; The theoretical probability distribution curve of the average flow of the driest month during the water transition period is established using Pearson Type III curves. For each month i, the runoff sequence of that month is extracted from historical data, and the theoretical frequency curve is obtained by fitting the curve. The monthly runoff Q during the assessment period i Input the corresponding frequency curve to obtain the incoming water frequency P. i And based on Pi Identifying hydrological year types: When P i A year with less than 90% is considered a wet year, when P i A year with a water level of not less than 90% and less than 97% is considered a normal water year. i A year with a water level of at least 97% is considered a dry year. A frequency drift compensation mechanism is introduced to correct the incoming water frequency: , Q i To evaluate the monthly runoff in month i of the assessment period, P i Let σp be the inflow frequency corresponding to the runoff in month i of the evaluation period. i S represents the standard deviation of the instantaneous frequency of daily flow within the month. k skewness, k is the compensation coefficient, P i comp The frequency of incoming water after drift compensation, sign(S) k ) is the sign function for skewness.

[0007] In a further embodiment of the present invention, the step of "calculating the hourly guarantee rate, daily guarantee rate, monthly guarantee rate, and annual guarantee rate based on measured discharge flow data, wherein the discharge flow includes the power plant unit's power generation flow and the discharge flow of the spillway facility" includes: The process of obtaining the ecological flow target of the cross section (EF) i，n Where i is the month and n is the day number, the ecological flow target is determined in different time periods based on fish spawning needs and the suitability of aquatic habitats, and adopts the form of a Gaussian impulse function: , Collect discharge flow data from each power station during the assessment period to obtain the total discharge flow: , Calculate the guarantee rate at each time scale; Among them, EF i，n For the ecological flow target on day n of month i, EF i Let Q be the target value for ecological flow in month i. base Let A be the basic ecological flow, A be the pulse flow amplitude, and t be the time variable. p Let Q be the pulse center time, σ be the pulse width parameter, and Q be... total (t) represents the total discharge flow at time t, Q turbine (t): Unit power generation flow rate at time t, Q release (t) represents the discharge flow rate of the spillway at time t.

[0008] In a further embodiment of the present invention, the step of "calculating the depth of damage when ecological flow fails to meet the standard, including the maximum depth of damage and the cumulative depth of damage, and introducing the ecosystem memory effect to dynamically correct the depth of damage" specifically includes: Calculate daily damage depth: When Q total (d) <EF i = when, ; When Q total (d)≥EF i hour, ; Calculate the maximum and cumulative depth of damage during the assessment period; , , Introducing the ecosystem memory effect, a memory decay function is constructed. , Calculate the dynamic damage depth on day t: , D d Depth of destruction on day dd, Q total (d): Average total discharge on day dd, EF i For the ecological flow target of month i, D max D represents the maximum depth of damage during the assessment period. cum The cumulative depth of damage during the assessment period is given by τ, where n is the total number of days in the assessment period, M(τ) is the memory decay function, τ is the time interval, and T is the total depth of damage during the assessment period. memory D is the ecological restoration time constant. t dynamic Let D be the dynamic damage depth on day t. t instant Let be the instantaneous damage depth on day t, α be the memory influence coefficient, k be the number of days for memory review, and D be... t j dynamic For the tth The dynamic destruction depth after j days, M(j) is the memory decay function value after an interval of j days.

[0009] In a further embodiment of the present invention, the step of "constructing a Bayesian network for ecological flow protection of cascade hydropower, analyzing the impact of upstream hub scheduling on the protection level of downstream sections, and calculating the overall protection level of the cascade" specifically includes: Construct a Bayesian network for cascade hydropower, with each cross section of the cascade as a network node and the relationship between upstream discharge flow and downstream support level as a directed edge; Upstream nodes include the downstream discharge flow Q at the upstream section. up Upstream ecological flow guarantee status S up Intermediate nodes include the water inflow Q within the interval. interval and river channel loss Q loss Downstream nodes include the downstream section protection status S. down ; Calculate the conditional probability of the downstream section's guaranteed state: Construct a tiered linkage guarantee transmission coefficient to represent the change in the downstream guarantee rate when the upstream guarantee rate changes by 1%. , Calculate the overall protection level of the cascade: , in, Q up S is the discharge flow rate at the upstream section. up To ensure the upstream ecological flow status, Q interval Q represents the inflow rate of the interval. loss S down To ensure the downstream section is in a safe condition, λ up→down ΔR is the upstream-to-downstream guarantee transmission coefficient. down ΔR represents the change in the downstream coverage rate. up R represents the change in the upstream coverage rate. cascade To represent the overall protection level of the cascade, n is the total number of cascade break sections, and w is the total number of break sections. i R represents the weight of the i-th cross section. i Let be the guarantee rate for the i-th cross section.

[0010] In a further embodiment of the present invention, the step of "establishing a dual-constraint criterion based on the inflow frequency and the damage depth, constructing a graded protection assessment function, and determining the ecological flow protection level of each cross section and the entire cascade" specifically includes: A dual-constraint judgment function based on inflow frequency and damage depth is constructed, and different constraints are set for different hydrological year types: For high-water years, the constraint is that both the maximum damage depth and the cumulative damage depth are zero; For a normal water year, the constraints are that the maximum damage depth is less than the first threshold function and the cumulative damage depth is less than the second threshold function. The first threshold function and the second threshold function are respectively quadratic relationships with the water inflow frequency. For dry years, the constraint is that the cumulative damage depth does not exceed the preset upper limit of cumulative damage depth; Ecological flow guarantee levels are classified according to the degree to which constraints are met: Level 1: Meets the constraints of a high-water year, or the maximum depth of damage is zero and the annual guarantee rate is not lower than the first guarantee rate threshold; Level 2: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the second guarantee rate threshold; Level 3: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the third guarantee rate threshold; Level 4: Meets one of the dual constraints of the corresponding hydrological year type, or the annual guarantee rate is not lower than the fourth guarantee rate threshold; Level 5: The dual constraints of the corresponding hydrological year type are not met, or the annual guarantee rate is lower than the fourth guarantee rate threshold. Calculate the overall protection index of the cascade, which is the value of the protection rate of each section after weighting the section weight and the hydrological year type adjustment coefficient.

[0011] In a further embodiment of the present invention, the step of "correcting the ecological flow target and scheduling scheme based on the evaluation results and combined with ecological monitoring data" specifically includes: Construct an ecological response database for the level of protection, collect ecological monitoring data during the assessment period, and calculate the correlation between the level of protection and ecological health indicators; When the ecological health index is below the preset threshold and the guarantee rate is above the preset threshold, the ecological flow target is deemed too lenient; when the ecological health index is above the preset threshold and the guarantee rate is below the preset threshold, the ecological flow target is deemed too strict. Based on the Bayesian update principle, the posterior distribution of the ecological flow target is updated according to the measured ecological response data, and the ecological flow target correction coefficient is calculated. The correction coefficient is the ratio of the posterior expected value to the prior value. Based on the revised ecological flow target, an optimized scheduling plan is generated, including: increasing the discharge flow of the spillway or adjusting the operation mode of the generating units for periods when the guarantee rate is lower than the preset threshold; adjusting the upstream hub scheduling plan for sections with a damage depth greater than the preset threshold; and formulating joint scheduling rules for river sections with a cascade linkage effect coefficient greater than the preset threshold.

[0012] In a further embodiment of the present invention, the specific implementation process of water inflow frequency analysis includes: based on historical long-series natural monthly average runoff data, using Pearson type III curves for parameter estimation and fitting, to obtain the theoretical probability distribution curve of the average flow of the driest month in each month; The specific implementation process of introducing the ecosystem memory effect includes: obtaining the ecological restoration time constant by fitting historical ecological monitoring data, constructing a memory function in the form of exponential decay, and calculating the dynamic damage depth based on the historical damage depth sequence; The specific implementation process of the cascade linkage guarantee assessment includes: constructing a Bayesian network with each cross section as a node and water flow connection as a directed edge, or using a graph neural network to generalize the cascade hydropower hub group into a graph structure, and learning the transmission law of guarantee insufficiency between cascades through graph convolutional networks.

[0013] In a further embodiment of the present invention, a visualization step is also included, the specific implementation process of which includes: generating guarantee rate change curves for each cross section at hourly, daily, monthly and yearly time scales; generating time series diagrams of damage depth for each cross section, and marking the maximum damage depth and cumulative damage depth; generating ecological flow guarantee level distribution maps for each cross section and the entire cascade; dynamically updating and displaying the charts on the monitoring platform; and automatically generating an assessment report containing data on each indicator and level rating based on the assessment results.

[0014] This invention has at least the following beneficial effects: 1. By constructing a basic assessment database containing multi-source data and using hydrological reconstruction technology to restore the natural runoff process of the cross section, the interference of human activities such as upstream water intake and engineering regulation on the runoff sequence is effectively eliminated, providing real and reliable data support for subsequent hydrological frequency analysis and assurance level assessment.

[0015] 2. Based on historical long-term runoff data, monthly hydrological frequency analysis is carried out, a frequency drift compensation mechanism is introduced to correct the inflow frequency, and three hydrological year types (abundant, normal, and dry) are divided according to the corrected frequency to achieve differentiated assessment standards for different inflow conditions, thereby improving the scientificity and fairness of the assessment results under different hydrological scenarios.

[0016] 3. Construct an assessment index system that combines multi-scale protection rate and dynamic damage depth from the two dimensions of time and intensity. By introducing the ecosystem memory effect to dynamically correct the damage depth, the assessment results can truly reflect the cumulative effect of ecological water shortage and the ecosystem recovery process, effectively making up for the shortcomings of the traditional single protection rate index in characterizing the degree of ecological damage. Attached Figure Description

[0017] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of a method provided in one embodiment of the present invention; Figure 2 This is a flowchart illustrating the construction process of the ecological flow guarantee assessment basic database provided in one embodiment of the present invention. Detailed Implementation

[0019] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0020] Please refer to Figure 1-2 In one embodiment, the present invention provides a method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge, comprising: Collect runoff data, engineering operation data, and ecological flow target requirements from each section of the cascade hydropower station group to construct a basic database for ecological flow guarantee assessment; Based on historical long-term runoff data, the hydrological frequency analysis method is used to calculate the inflow frequency of each period during the assessment period, and the assessment period is divided into three hydrological year types: high-water year, normal-water year, or low-water year according to the inflow frequency. Based on the measured discharge flow data, the hourly guarantee rate, daily guarantee rate, monthly guarantee rate and annual guarantee rate are calculated respectively. The discharge flow includes the power generation flow of the power plant unit and the discharge flow of the water spillway. The depth of damage when ecological flow fails to meet the standard is calculated, including the maximum depth of damage and the cumulative depth of damage, and the ecosystem memory effect is introduced to dynamically correct the depth of damage; Construct a Bayesian network for ecological flow protection of cascade hydropower, analyze the impact of upstream hub scheduling on the protection level of downstream sections, and calculate the overall protection level of the cascade. Based on the inflow frequency and the damage depth, a dual-constraint criterion is established, a graded protection assessment function is constructed, and the ecological flow protection level of each section and the entire cascade is determined. Based on the assessment results and combined with ecological monitoring data, the ecological flow targets and scheduling schemes were revised.

[0021] In this embodiment, the specific steps include: The first step is data collection and database construction. For the target cascade hydropower station group, comprehensive basic data is collected from each key cross-section. This data includes: long-term historical daily average runoff data, measured runoff data during the assessment period, generating flow of each power station's units, real-time discharge flow data from spillways and ecological discharge gates, upstream industrial and agricultural water consumption, and reservoir storage changes. Simultaneously, ecological flow target requirements for each cross-section in different months or time periods are defined. After cleaning, verifying, and standardizing the format of all the above data, it is stored in a relational database or time-series database to construct the basic database for ecological flow guarantee assessment.

[0022] The second step is the classification of hydrological year types. Historical long-term natural monthly average runoff data are extracted from the database, and hydrological frequency analysis is used to calculate the frequency of water inflow for each month within the assessment period. Based on the calculated water inflow frequencies, the assessment period is divided into three hydrological year types: high-water years, normal-water years, and low-water years. This classification lays the foundation for subsequently establishing differentiated assessment standards.

[0023] The third step is to calculate the multi-scale guarantee rate. Based on the measured power plant discharge flow data, the guarantee rate is calculated at different time scales. For example, the hourly guarantee rate is obtained by calculating the proportion of minutes within an hour that meet the ecological flow target; the daily guarantee rate is obtained by calculating the proportion of hours within a day that meet the requirements; and so on, the monthly and annual guarantee rates are calculated. This provides a multi-time-dimensional view of the guarantee situation.

[0024] The fourth step is the calculation and correction of the depth of damage. Ecological damage is defined as occurring when the actual outflow is lower than the ecological flow target. The depth of damage for each event is calculated, and the maximum and cumulative depths of damage during the assessment period are statistically analyzed. More importantly, this step introduces the ecosystem memory effect, meaning that ecosystems need time to recover after damage, and early damage has a lasting impact on later ecosystem health. By constructing a memory decay function, historical damage depths are weighted to calculate the dynamic depth of damage, thus more accurately reflecting the cumulative and lag effects of ecological damage.

[0025] The fifth step is to analyze the impact of cascade hydropower linkage. A Bayesian network model for ecological flow guarantee of cascade hydropower projects is constructed. The downstream discharge and guarantee status of each cross-section in the cascade are treated as network nodes, and the outflow from the upstream cross-section is considered as a factor influencing the guarantee status of the downstream cross-section. Through this network, the probability and degree of influence of the scheduling mode of the upstream hub on the guarantee level of the downstream cross-section can be quantitatively analyzed, and finally, the overall guarantee level of the cascade considering the upstream-downstream linkage effect can be calculated.

[0026] Step 6: Graded Protection Assessment. Based on the hydrological year patterns defined in Step 2, the damage depth calculated in Step 4, and the cascade protection level obtained in Step 5, a dual-constraint criterion of inflow frequency and damage depth is established. Differentiated constraints are set for different hydrological year patterns (abundant, normal, and dry). By constructing a graded protection assessment function, the assessment results of each cross section and the entire cascade are divided into several protection levels.

[0027] Step 7: Target and Scheduling Scheme Revision. The assessment results are combined with concurrently conducted ecological monitoring data for correlation analysis. If ecological health indicators are poor but the guarantee rate is high, it indicates that the ecological flow target may be set too low; conversely, if ecological health indicators are good but the guarantee rate is low, it indicates that the target may be set too high. Based on the Bayesian update principle, the original ecological flow target value is revised using measured ecological response data, and an optimized joint scheduling scheme for the cascade hydropower stations is generated accordingly, forming a closed-loop management process of assessment, feedback, and optimization.

[0028] The dynamic assessment method for ensuring the ecological flow guarantee of cascade hydropower outflow proposed in this embodiment breaks through the limitations of traditional single-point, single-indicator assessments. First, by constructing a basic database containing multi-dimensional data, a solid data foundation is provided for the assessment. Second, by classifying hydrological year types, differentiated assessment standards are achieved, making the assessment results more scientific and fair. Third, the introduction of multi-scale guarantee rates and dynamic damage depth comprehensively characterizes the ecological flow guarantee situation from both quantitative and qualitative dimensions. In particular, the consideration of the ecosystem memory effect makes the assessment results closer to the true laws of ecological response. Through Bayesian network analysis of the cascade linkage effect, key influencing nodes and transmission paths in cascade scheduling can be accurately identified, providing decision support for optimizing joint scheduling. The final hierarchical assessment results are clear and intuitive, and through closed-loop correction using ecological monitoring data, adaptive optimization of the assessment method and ecological flow targets is achieved, significantly improving the precision of ecological scheduling of cascade hydropower stations and the effectiveness of ecological protection.

[0029] In a further embodiment of the present invention, the step of "collecting runoff data, engineering operation data, and ecological flow target requirements from each section of the cascade hydropower station group, and constructing a basic database for ecological flow guarantee assessment" specifically includes: Collect measured daily average runoff data, upstream water intake data, and upstream engineering water storage data for each cross-section during the assessment period; The measured runoff was reconstructed using the hydrological reconstruction method to obtain the natural runoff data of the cross section during the assessment period, and a monthly average natural runoff data matrix for the assessment period was constructed. Collect historical long-series natural monthly average runoff data and historical long-series measured monthly average runoff data for no less than 30 years; Determine the target values ​​for ecological flow at each cross-section for different months; The above data will be stored uniformly to form a basic database for ecological flow guarantee assessment, which includes a matrix of monthly average natural runoff data during the assessment period, daily average measured runoff data during the assessment period, historical long-term series of monthly average natural runoff data, historical long-term series of monthly average measured runoff data, ecological flow targets for each section, water intake data from upstream river channels, and water storage data of upstream engineering projects.

[0030] In this embodiment, the first step is to collect basic data for the assessment period. For each assessment section in the cascade hydropower station group, three types of core data are systematically collected: The first type is measured runoff data, i.e., the average daily flow data of the section during the assessment period, usually from the monitoring records of hydrological stations. The second type is upstream water intake data, which statistically analyzes the water intake and pumping from outside the river for all industrial, agricultural, and domestic production and other purposes upstream of the section during the assessment period, requiring daily or monthly statistics. The third type is upstream engineering water storage data, which collects the inflow, outflow, and storage capacity changes of all reservoirs, dams, and other engineering projects with regulation and storage capacity upstream of the section during the assessment period, in order to calculate the regulation and storage capacity of the engineering projects on the river.

[0031] Secondly, hydrological reconstruction calculations are performed. Using the principle of water balance, the measured runoff at the cross-section is reconstructed to estimate the natural runoff. The calculation formula is: natural runoff equals measured runoff plus upstream water intake from outside the river channel plus upstream engineering water storage variables. Through daily calculations, daily natural runoff data for this cross-section during the assessment period can be obtained. Based on this, a monthly average natural runoff data matrix for the assessment period is further generated.

[0032] Next, long-term historical data are collected. For hydrological frequency analysis, it is necessary to collect at least thirty years of historical long-term natural monthly average runoff data and historical long-term measured monthly average runoff data for this section. These data constitute the historical context and benchmark for the assessment.

[0033] Finally, ecological flow targets are integrated with other data. The ecological flow target values ​​for each cross-section are defined for different months and hydrological periods. This target may not be a fixed value, but rather a process line that changes over time. All the above data—including the monthly average natural runoff data matrix for the assessment period, the daily average measured runoff data for the assessment period, historical long-term series of monthly average natural runoff data, historical long-term series of monthly average measured runoff data, ecological flow targets for each cross-section, and upstream water intake and storage data—are standardized in format and quality controlled before being uniformly stored in a database, forming a complete basic database for ecological flow guarantee assessment. This database provides a single, reliable data source for all subsequent analyses and calculations.

[0034] In a further embodiment of the present invention, the step of "calculating the inflow frequency of each period in the assessment period based on historical long-term runoff data using hydrological frequency analysis methods, and dividing the assessment period into three hydrological year types—high-water year, normal-water year, or low-water year—according to the inflow frequency" includes: Extract at least 30 years of historical long-series monthly average natural runoff data from the database to construct a historical long-series monthly-scale natural runoff data matrix R. a×12 where a is the number of years; The theoretical probability distribution curve of the average flow of the driest month during the water transition period is established using Pearson Type III curves. For each month i, the runoff sequence of that month is extracted from historical data, and the theoretical frequency curve is obtained by fitting the curve. The monthly runoff Q during the assessment period i Input the corresponding frequency curve to obtain the incoming water frequency P. i And based on P i Identifying hydrological year types: When P i A year with less than 90% is considered a wet year, when P i A year with a water level of not less than 90% and less than 97% is considered a normal water year. i A year with a water level of at least 97% is considered a dry year. A frequency drift compensation mechanism is introduced to correct the incoming water frequency: , Q i To evaluate the monthly runoff in month i of the assessment period, P i Let σp be the inflow frequency corresponding to the runoff in month i of the evaluation period. i S represents the standard deviation of the instantaneous frequency of daily flow within the month. k skewness, k is the compensation coefficient, P i comp The frequency of incoming water after drift compensation, sign(S) k ) is the sign function for skewness.

[0035] In this embodiment, the specific steps include: The first step is to construct a historical natural runoff matrix. Extract at least thirty years of historical long-term natural monthly runoff data and organize them into a matrix with the number of years multiplied by twelve. Each row represents the twelve monthly average flow for a given year, and each column represents the flow sequence for a given month across all years.

[0036] The second step is to establish monthly frequency curves. Using the Pearson Type III curve, widely applied in hydrology, frequency analysis is performed on each column of the matrix. The specific process includes: estimating the parameters of the monthly flow series, and then determining the optimal theoretical frequency curve using the fitting method, i.e., the theoretical probability distribution curve of the average flow of the driest month for that month.

[0037] The third step is to initially classify the hydrological year type. Substituting the monthly runoff of the month in the assessment period into the theoretical frequency curve obtained in the second step, the inflow frequency corresponding to that monthly runoff can be calculated. Then, based on preset thresholds, the hydrological year type is identified: if the inflow frequency is less than 90%, it is a wet year; if the inflow frequency is not less than 90% but less than 97%, it is a normal year; if the inflow frequency is not less than 97%, it is a dry year.

[0038] The fourth step involves introducing a frequency drift compensation mechanism. To correct the frequency calculation bias caused by runoff non-stationarity, this embodiment proposes a compensation mechanism. Considering the fluctuation of daily flow within a month, the instantaneous frequency of all daily flow within the assessment period is calculated, and its standard deviation is obtained to characterize the degree of intra-day fluctuation in monthly flow. Simultaneously, the skewness of the monthly flow sequence is calculated to reflect the symmetry of the sequence distribution. A drift compensation formula is constructed: the compensated inflow frequency equals the original frequency plus the sign function of the skewness multiplied by the compensation coefficient, and then multiplied by the standard deviation of the instantaneous daily flow frequency within the month. This formula means that when the flow distribution is right-skewed and the intra-month fluctuations are severe, the actual risk of drought may be higher than the result of traditional frequency calculations. Therefore, the frequency value needs to be adjusted upwards, making it easier to classify as a drought year, and vice versa. Finally, the compensated inflow frequency is used to re-identify or confirm the hydrological year type.

[0039] In a further embodiment of the present invention, the step of "calculating the hourly guarantee rate, daily guarantee rate, monthly guarantee rate, and annual guarantee rate based on measured discharge flow data, wherein the discharge flow includes the power plant unit's power generation flow and the discharge flow of the spillway facility" includes: The process of obtaining the ecological flow target of the cross section (EF) i，n Where i is the month and n is the day number, the ecological flow target is determined in different time periods based on fish spawning needs and the suitability of aquatic habitats, and adopts the form of a Gaussian impulse function: , Collect discharge flow data from each power station during the assessment period to obtain the total discharge flow: , Calculate the guarantee rate at each time scale; Among them, EF i，n For the ecological flow target on day n of month i, EF i Let Q be the target value for ecological flow in month i. base Let A be the basic ecological flow, A be the pulse flow amplitude, and t be the time variable. p Let Q be the pulse center time, σ be the pulse width parameter, and Q be... total (t) represents the total discharge flow at time t, Q turbine (t): Unit power generation flow rate at time t, Q release (t) represents the discharge flow rate of the spillway at time t.

[0040] In this embodiment, the specific steps are as follows: The first step is to determine the dynamic ecological flow target process curve. Instead of using a single monthly average as the target, a target process curve reflecting the time-varying characteristics of ecological water demand is constructed, where the first subscript represents the month, and the second subscript represents the day of that month. This process curve can be determined in time periods based on the needs of key ecological behaviors such as fish spawning and migration. This embodiment uses a Gaussian impulse function to simulate the natural impulse characteristics of ecological flow. This function includes parameters such as basic ecological flow, impulse flow amplitude, time variable, impulse center time, and impulse width. This function can generate a smooth process curve with peaks, more closely resembling the rise and fall of a natural river.

[0041] The second step is to collect total discharge flow data. This involves frequently collecting the generating flow of the generating units and the discharge flow of the spillway facilities from the power plant monitoring system or database during the assessment period. The total discharge flow at any given time is calculated; it equals the sum of the generating flow of the generating units and the discharge flow of the spillway facilities.

[0042] The third step is to calculate the guarantee rate at each time scale. For the hourly guarantee rate, calculate the proportion of the total outflow at all times within that hour that meets the ecological flow target process line for that time moment; that is, the duration of compliance divided by one hour. For the daily guarantee rate, calculate the proportion of hours with a 100% hourly guarantee rate out of the total number of hours; or compare the average total outflow for that day with the ecological flow target for that day, but the first method is more precise. For the monthly guarantee rate, calculate the proportion of days with a 100% daily guarantee rate out of the total number of days in that month, or compare the average flow for that month with the average monthly target. For the annual guarantee rate, calculate the proportion of months with a 100% monthly guarantee rate out of the total number of months in that year, or use a weighted average.

[0043] In a further embodiment of the present invention, the step of "calculating the depth of damage when ecological flow fails to meet the standard, including the maximum depth of damage and the cumulative depth of damage, and introducing the ecosystem memory effect to dynamically correct the depth of damage" specifically includes: Calculate daily damage depth: When Q total (d) <EF i = when, ; When Q total (d)≥EF i hour, ; Calculate the maximum and cumulative depth of damage during the assessment period; , , Introducing the ecosystem memory effect, a memory decay function is constructed. , Calculate the dynamic damage depth on day t: , D d Depth of destruction on day dd, Q total (d): Average total discharge on day dd, EF i For the ecological flow target of month i, D max D represents the maximum depth of damage during the assessment period. cum The cumulative depth of damage during the assessment period is given by τ, where n is the total number of days in the assessment period, M(τ) is the memory decay function, τ is the time interval, and T is the total depth of damage during the assessment period. memory D is the ecological restoration time constant. t dynamic Let D be the dynamic damage depth on day t. t instant Let be the instantaneous damage depth on day t, α be the memory influence coefficient, k be the number of days for memory review, and D be... t j dynamic For the tth The dynamic destruction depth after j days, M(j) is the memory decay function value after an interval of j days.

[0044] This embodiment illustrates how to calculate and correct the depth of ecological flow destruction and introduce the ecosystem memory effect. The specific steps are as follows: The first step is to calculate the daily damage depth. For day , first obtain the average total discharge flow for that day and the ecological flow target value for that month. The damage depth for that day is defined as follows: If the average total outflow on a given day is less than the ecological flow target for that month, it indicates that the ecological flow for that day is insufficient. The depth of damage is the ratio of the water shortage to the target flow, i.e., the target flow minus the actual flow, divided by the target flow. This value ranges from zero to one; the larger the value, the more severe the damage.

[0045] If the average total outflow on that day is not less than the ecological flow target for that month, it means that the ecological flow target for that day has been met and the depth of damage is zero.

[0046] The second step is to calculate the cumulative and maximum damage depth. During the assessment period, the following calculations are performed: The maximum damage depth is the highest value among all daily damage depths during the assessment period, reflecting the most severe ecological water shortage event during the assessment period.

[0047] Cumulative damage depth is the sum of all daily damage depths during the assessment period, reflecting the overall degree of ecological water shortage during the assessment period.

[0048] The third step involves introducing the ecosystem memory effect for dynamic correction. After an ecosystem is damaged, its structure and function require time to recover, meaning that damage from one day will affect the ecosystem's health the following day. This embodiment simulates this process by constructing a memory decay function, which is exponentially decaying and includes an ecological recovery time constant.

[0049] Based on this, the dynamic damage depth of day 1 is calculated, which comprehensively considers the instantaneous damage of that day and the historical legacy damage effects. The dynamic damage depth equals the instantaneous damage depth of that day plus the memory effect coefficient multiplied by the cumulative sum of the dynamic damage depths of the past several days after memory decay. This recursive relationship shows that the current dynamic damage depth depends not only on the current damage but also on the cumulative effect of all dynamic damage depths over a past period in an exponentially decaying manner.

[0050] In a further embodiment of the present invention, the step of "constructing a Bayesian network for ecological flow protection of cascade hydropower, analyzing the impact of upstream hub scheduling on the protection level of downstream sections, and calculating the overall protection level of the cascade" specifically includes: Construct a Bayesian network for cascade hydropower, with each cross section of the cascade as a network node and the relationship between upstream discharge flow and downstream support level as a directed edge; Upstream nodes include the downstream discharge flow Q at the upstream section. up Upstream ecological flow guarantee status S up Intermediate nodes include the water inflow Q within the interval. interval and river channel loss Q loss Downstream nodes include the downstream section protection status S. down ; Calculate the conditional probability of the downstream section's guaranteed state: Construct a tiered linkage guarantee transmission coefficient to represent the change in the downstream guarantee rate when the upstream guarantee rate changes by 1%. , Calculate the overall protection level of the cascade: , in, Q up S is the discharge flow rate at the upstream section. up To ensure the upstream ecological flow status, Q interval Q represents the inflow rate of the interval. loss S down To ensure the downstream section is in a safe condition, λ up→down ΔR is the upstream-to-downstream guarantee transmission coefficient. down ΔR represents the change in the downstream coverage rate. up R represents the change in the upstream coverage rate. cascadeTo represent the overall protection level of the cascade, n is the total number of cascade break sections, and w is the total number of break sections. i R represents the weight of the i-th cross section. i Let be the guarantee rate for the i-th cross section.

[0051] In this embodiment, the specific steps are as follows: The first step is to construct the Bayesian network topology. Each key evaluation section in the cascade is abstracted as a network node. Directed edges connect upstream and downstream nodes, representing the direction of water flow and the influence relationship. For example, a directed edge from an upstream section node to a downstream section node indicates that the outflow situation upstream will affect the downstream protection status.

[0052] The second step is to define the network node variables. The guaranteed state of each node is affected not only by upstream water flow but also by interval factors. Therefore, the node variables in a Bayesian network include: Upstream nodes include the downstream flow at upstream sections and the ecological flow guarantee status at upstream sections.

[0053] Intermediate nodes include the inflow and channel loss between the upstream and downstream sections.

[0054] The downstream node, i.e. the protection status of the downstream section, is the target variable to be predicted.

[0055] The third step is to calculate the conditional probabilities and transmission coefficients. Based on historical data and expert experience, conditional probability tables for each node in the network can be learned or defined. For example, the conditional probability of the downstream section's safeguard status can be calculated given the upstream safeguard status, the inflow rate, and the river channel loss.

[0056] To more intuitively reflect the quantitative impact of upstream on downstream, this embodiment constructs a "tiered linkage guarantee transmission coefficient." This coefficient represents the change in downstream guarantee rate caused by a one percent change in upstream guarantee rate. The larger the coefficient, the stronger the downstream's dependence on upstream, and the more significant the impact of upstream scheduling on downstream.

[0057] The fourth step is to calculate the overall protection level of the cascade. Based on the protection rate of each cross-section and the upstream-downstream relationship revealed by the Bayesian network, the overall protection level of the cascade can be calculated. The overall protection level of the cascade is defined as the weighted sum of the protection rates of each cross-section after weighting the cross-sections. The cross-section weights can be determined comprehensively based on factors such as the ecological importance of the cross-section and the controlled watershed area.

[0058] In a further embodiment of the present invention, the step of "establishing a dual-constraint criterion based on the inflow frequency and the damage depth, constructing a graded protection assessment function, and determining the ecological flow protection level of each cross section and the entire cascade" specifically includes: A dual-constraint judgment function based on inflow frequency and damage depth is constructed, and different constraints are set for different hydrological year types: For high-water years, the constraint is that both the maximum damage depth and the cumulative damage depth are zero; For a normal water year, the constraints are that the maximum damage depth is less than the first threshold function and the cumulative damage depth is less than the second threshold function. The first threshold function and the second threshold function are respectively quadratic relationships with the water inflow frequency. For dry years, the constraint is that the cumulative damage depth does not exceed the preset upper limit of cumulative damage depth; Ecological flow guarantee levels are classified according to the degree to which constraints are met: Level 1: Meets the constraints of a high-water year, or the maximum depth of damage is zero and the annual guarantee rate is not lower than the first guarantee rate threshold; Level 2: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the second guarantee rate threshold; Level 3: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the third guarantee rate threshold; Level 4: Meets one of the dual constraints of the corresponding hydrological year type, or the annual guarantee rate is not lower than the fourth guarantee rate threshold; Level 5: The dual constraints of the corresponding hydrological year type are not met, or the annual guarantee rate is lower than the fourth guarantee rate threshold. Calculate the overall protection index of the cascade, which is the value of the protection rate of each section after weighting the section weight and the hydrological year type adjustment coefficient.

[0059] In this embodiment, the specific steps are as follows: The first step is to establish dual-constraint criteria. Differentiated constraints are set for different hydrological year types; this is the core of the tiered assessment.

[0060] In years with abundant water flow, theoretically there should be no instances of ecological flow falling short of standards. Therefore, the constraints are set at zero for both the maximum and cumulative depth of damage.

[0061] For normal water years, a certain degree of ecological water shortage is permissible, but it must be kept within acceptable limits. The constraints are that the maximum depth of damage is less than a first threshold function, and the cumulative depth of damage is less than a second threshold function. Both the first and second threshold functions have a quadratic relationship with the frequency of incoming water; that is, the higher the frequency of incoming water, the more relaxed the permissible depth of damage threshold can be; conversely, the lower the frequency of incoming water, the stricter the threshold.

[0062] In dry years, water resources are naturally scarce, and completely avoiding water shortages is almost impossible. At this time, the main constraint is controlling the cumulative depth of damage, requiring it not to exceed a preset upper limit for cumulative damage depth, in order to prevent long-term ecological cumulative effects from exceeding the ecological threshold.

[0063] The second step is to classify the ecological flow guarantee levels. Based on the degree to which the dual constraints are met, and combined with the annual guarantee rate, the guarantee levels are divided into five levels: Level 1: Meets the constraints of a high-water year, or the maximum depth of damage is zero and the annual guarantee rate is not lower than the first guarantee rate threshold. This level indicates that the ecological flow guarantee is excellent, essentially achieving zero damage.

[0064] Level 2: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the second guarantee rate threshold. This level indicates that the guarantee status is good and meets the design requirements.

[0065] Level 3: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the third guarantee rate threshold. This level indicates that the requirements have been basically met, but there is still some room for improvement.

[0066] Level 4: Meets one of the dual constraints of the corresponding hydrological year type, or the annual guarantee rate is not lower than the fourth guarantee rate threshold. This level indicates a significant guarantee problem that requires attention.

[0067] Level 5: The dual constraints of the corresponding hydrological year type are not met, or the annual guarantee rate is lower than the fourth guarantee rate threshold. This level indicates a serious inadequacy in ecological flow guarantee, and intervention measures must be taken.

[0068] The third step is to calculate the overall protection index of the cascade. To evaluate the entire cascade from a macro perspective, the overall protection index is calculated. This index is the weighted sum of the protection rates of each cross-section, adjusted by cross-section weights and hydrological year type adjustment coefficients. The cross-section weights reflect the ecological importance of that cross-section, while the hydrological year type adjustment coefficients are used to balance the protection difficulty of each cross-section under different hydrological year types, ensuring the comparability of the comprehensive index across different years.

[0069] In a further embodiment of the present invention, the step of "correcting the ecological flow target and scheduling scheme based on the evaluation results and combined with ecological monitoring data" specifically includes: Construct an ecological response database for the level of protection, collect ecological monitoring data during the assessment period, and calculate the correlation between the level of protection and ecological health indicators; When the ecological health index is below the preset threshold and the guarantee rate is above the preset threshold, the ecological flow target is deemed too lenient; when the ecological health index is above the preset threshold and the guarantee rate is below the preset threshold, the ecological flow target is deemed too strict. Based on the Bayesian update principle, the posterior distribution of the ecological flow target is updated according to the measured ecological response data, and the ecological flow target correction coefficient is calculated. The correction coefficient is the ratio of the posterior expected value to the prior value. Based on the revised ecological flow target, an optimized scheduling plan is generated, including: increasing the discharge flow of the spillway or adjusting the operation mode of the generating units for periods when the guarantee rate is lower than the preset threshold; adjusting the upstream hub scheduling plan for sections with a damage depth greater than the preset threshold; and formulating joint scheduling rules for river sections with a cascade linkage effect coefficient greater than the preset threshold.

[0070] In this embodiment, the specific steps are as follows: The first step is to construct an ecological response database for the level of protection. The system collects ecological monitoring data closely related to ecological flow during the assessment period, such as fish species and numbers, spawning ground size, benthic animal diversity, and riparian vegetation coverage—all ecological health indicators. The assessment indicators, such as the protection rate and damage depth of each cross section calculated in the previous steps, are then matched temporally and spatially with this ecological monitoring data to construct a paired dataset containing "level of protection - ecological response."

[0071] The second step is to assess the rationality of the ecological flow target. Based on the aforementioned database, the correlation between the level of protection and ecological health indicators is calculated. If the ecological health index is lower than the preset health threshold, while the protection rate is higher than a very high preset threshold, this means that even with good protection, the ecology is still unhealthy. The possible reason is that the ecological flow target is set too low, failing to meet the true needs of the ecosystem. Conversely, if the ecological health index is higher than the preset health threshold, while the protection rate is lower than a relatively low preset threshold, this means that the ecology is still healthy despite poor protection. The possible reason is that the ecological flow target is set too high, creating unnecessary economic burdens.

[0072] The third step is to revise the ecological flow target. When the target is deemed unreasonable, it needs to be revised. This embodiment is based on the Bayesian update principle. The original ecological flow target value is used as the prior distribution, and the "guarantee level - ecological response" data collected in step one is used as new evidence to calculate the posterior distribution of the ecological flow target. Then, the ratio of the posterior expected value to the prior value is calculated as the ecological flow target revision coefficient. Multiplying this coefficient by the original target value yields the revised ecological flow target. For example, if new evidence indicates that the original target is too lenient, the posterior expected value will increase, the revision coefficient will be greater than one, and the ecological flow target will be increased.

[0073] The fourth step is to generate an optimized scheduling plan. Based on the revised ecological traffic target, a targeted optimized scheduling plan is generated. This includes: For periods when the guarantee rate is lower than the preset threshold, increase the discharge flow of the spillway facilities or adjust the unit operation mode to ensure the target flow. For sections with a damage depth greater than the preset threshold, analyze the main influencing factors and adjust the scheduling plan of the upstream hub, such as specifying the minimum discharge flow of the upstream reservoir during a specific period.

[0074] For river sections where the cascade linkage effect coefficient is greater than a preset threshold, i.e., river sections where the upstream impact is particularly significant, special joint scheduling rules are formulated, requiring upstream and downstream power stations to coordinate operations and jointly ensure ecological flow.

[0075] In a further embodiment of the present invention, the specific implementation process of water inflow frequency analysis includes: based on historical long-series natural monthly average runoff data, using Pearson type III curves for parameter estimation and fitting, to obtain the theoretical probability distribution curve of the average flow of the driest month in each month; The specific implementation process of introducing the ecosystem memory effect includes: obtaining the ecological restoration time constant by fitting historical ecological monitoring data, constructing a memory function in the form of exponential decay, and calculating the dynamic damage depth based on the historical damage depth sequence; The specific implementation process of the cascade linkage guarantee assessment includes: constructing a Bayesian network with each cross section as a node and water flow connection as a directed edge, or using a graph neural network to generalize the cascade hydropower hub group into a graph structure, and learning the transmission law of guarantee insufficiency between cascades through graph convolutional networks.

[0076] In this embodiment, the first step is the specific implementation process of inflow frequency analysis. Based on a database, historical long-series natural monthly average runoff data are extracted. Pearson's three-type curves are used for frequency analysis. Specific steps include: for each month, calculating the mean, coefficient of variation, and skewness coefficient of the historical flow series as initial values; then, adjusting the parameters using optimization algorithms or visual fitting methods to achieve the best fit between the theoretical frequency curve and the empirical data, thus obtaining the theoretical frequency curve for that month. The fitting process can be implemented using hydrological frequency analysis software or programming languages. Finally, twelve theoretical frequency curves for the twelve months are obtained and stored in the model library.

[0077] Second, the specific implementation process of the ecosystem memory effect is introduced. The core of the ecosystem memory effect is the recursive calculation of the memory decay function and the dynamic damage depth. First, it is necessary to determine the ecological recovery time constant, which can be obtained by fitting historical ecological monitoring data. For example, after a known ecological damage event, the biomass recovery process can be tracked and monitored for a period of time afterward, and the recovery time constant can be fitted by an exponential decay model. If there is no measured data, the initial value can be given by referring to the ecological research results of similar rivers or expert experience. Then, an exponential decay form of the memory function is constructed, with the function value being a power of the natural constant e as the base and the negative time interval divided by the recovery time constant as the exponent. When calculating the daily dynamic damage depth, it is calculated day by day according to the recursive formula starting from the first day of the assessment period, where the number of memory review days and the memory impact coefficient can be adjusted according to the model validation results.

[0078] Third, the specific implementation process of cascade linkage guarantee assessment. Besides Bayesian networks, this embodiment also provides another advanced technical solution: graph neural networks. In specific implementation, the cascade hydropower hub group is first generalized as a graph structure, with each hydropower station as a node and upstream and downstream river connections as edges. The weights of the edges can be set as water flow propagation time or the degree of hydraulic connection. Then, the historical downstream discharge, guarantee status, and inflow of each node are used as node features, and historical cascade linkage data are used as training samples to construct a graph convolutional network model. Through training, the graph convolutional network can automatically learn the transmission law of guarantee insufficiency between cascades, that is, how the guarantee status of upstream nodes affects the guarantee status of downstream nodes through the graph structure. The trained graph convolutional network can be used to predict the guarantee situation of downstream given an upstream scheduling scheme, and can also be used to identify key nodes and vulnerable river sections in the cascade.

[0079] In a further embodiment of the present invention, a visualization step is also included, the specific implementation process of which includes: generating guarantee rate change curves for each cross section at hourly, daily, monthly and yearly time scales; generating time series diagrams of damage depth for each cross section, and marking the maximum damage depth and cumulative damage depth; generating ecological flow guarantee level distribution maps for each cross section and the entire cascade; dynamically updating and displaying the charts on the monitoring platform; and automatically generating an assessment report containing data on each indicator and level rating based on the assessment results.

[0080] This embodiment describes the specific implementation process of the visualization step, which aims to present the evaluation results intuitively in the form of charts and graphs and automatically generate an evaluation report. The specific steps are as follows: The first step is to generate multi-scale guarantee rate variation curves. Based on the hourly, daily, monthly, and yearly guarantee rate data calculated in the above embodiments, guarantee rate variation curves for each cross-section at different time scales are plotted. For example, by plotting time on the horizontal axis and guarantee rate on the vertical axis, a daily guarantee rate curve can be drawn, clearly showing which periods experience troughs in the guarantee rate. The curves can be overlaid with ecological flow target process lines for a direct comparison of the actual discharge with the target. The second step is to generate a time series graph of damage depth. Based on the daily damage depth calculated in claim 5, a time series bar chart or line chart of damage depth for each cross-section is plotted. The maximum damage depth and its occurrence date, as well as the cumulative damage depth value, are clearly marked on the graph. A dynamic damage depth curve can also be plotted simultaneously and compared with the instantaneous damage depth to demonstrate the smoothing and lag effects of the memory effect.

[0081] The third step is to generate a protection level distribution map. Based on the ecological flow protection levels of each cross-section and the entire cascade as defined in the above embodiments, different colors are used to fill or mark each cross-section on the cascade geographic information map or topology map to generate a spatial distribution map of protection levels. This map can clearly show which cross-sections in the entire cascade have good protection status and which are weak links. The overall protection index of the cascade can be displayed in the form of a dashboard.

[0082] The fourth step is dynamic display updates. The generated charts are integrated into a monitoring platform or large-screen display system, and a data interface is established with the real-time / scheduled assessment calculation module. Whenever a new assessment period is completed, the charts on the platform automatically refresh, enabling dynamic updates and real-time monitoring of the protection status.

[0083] Step 5: Automatically generate the assessment report. After each assessment, the system automatically summarizes all indicator data and grade evaluation results, and generates an assessment report according to a preset report template. The report should include: basic information for the assessment period, inflow frequency and hydrological year type for each cross-section, statistical values ​​of multi-scale protection rate, maximum / cumulative damage depth, key values ​​of dynamic damage depth, overall protection level of each cross-section and cascade, grade distribution map, analysis of major problems, and recommendations. The report can be exported as a PDF or Word document for easy archiving and distribution.

[0084] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge, characterized in that, include: Collect runoff data, engineering operation data, and ecological flow target requirements from each section of the cascade hydropower station group to construct a basic database for ecological flow guarantee assessment; Based on historical long-term runoff data, the hydrological frequency analysis method is used to calculate the inflow frequency of each period during the assessment period, and the assessment period is divided into three hydrological year types: high-water year, normal-water year, or low-water year according to the inflow frequency. Based on the measured discharge flow data, the hourly guarantee rate, daily guarantee rate, monthly guarantee rate and annual guarantee rate are calculated respectively. The discharge flow includes the power generation flow of the power plant unit and the discharge flow of the water spillway. The depth of damage when ecological flow fails to meet the standard is calculated, including the maximum depth of damage and the cumulative depth of damage, and the ecosystem memory effect is introduced to dynamically correct the depth of damage; Construct a Bayesian network for ecological flow protection of cascade hydropower, analyze the impact of upstream hub scheduling on the protection level of downstream sections, and calculate the overall protection level of the cascade. Based on the inflow frequency and the damage depth, a dual-constraint criterion is established, a graded protection assessment function is constructed, and the ecological flow protection level of each section and the entire cascade is determined. Based on the assessment results and combined with ecological monitoring data, the ecological flow targets and scheduling schemes were revised.

2. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "collecting runoff data, engineering operation data, and ecological flow target requirements from each section of the cascade hydropower station group to construct a basic database for ecological flow guarantee assessment" specifically includes: Collect measured daily average runoff data, upstream water intake data, and upstream engineering water storage data for each cross-section during the assessment period; The measured runoff was reconstructed using the hydrological reconstruction method to obtain the natural runoff data of the cross section during the assessment period, and a monthly average natural runoff data matrix for the assessment period was constructed. Collect historical long-series natural monthly average runoff data and historical long-series measured monthly average runoff data for no less than 30 years; Determine the target values ​​for ecological flow at each cross-section for different months; The above data will be stored uniformly to form a basic database for ecological flow guarantee assessment, which includes a matrix of monthly average natural runoff data during the assessment period, daily average measured runoff data during the assessment period, historical long-term series of monthly average natural runoff data, historical long-term series of monthly average measured runoff data, ecological flow targets for each section, water intake data from upstream river channels, and water storage data of upstream engineering projects.

3. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "based on historical long-term runoff data, using hydrological frequency analysis to calculate the inflow frequency for each period of the assessment period, and dividing the assessment period into three hydrological year types—high-water year, normal-water year, or low-water year—according to the inflow frequency" includes: Extract at least 30 years of historical long-series monthly average natural runoff data from the database to construct a historical long-series monthly-scale natural runoff data matrix R. a×12 where a is the number of years; The theoretical probability distribution curve of the average flow of the driest month during the water transition period is established using Pearson Type III curves. For each month i, the runoff sequence of that month is extracted from historical data, and the theoretical frequency curve is obtained by fitting the curve. The monthly runoff Q during the assessment period i Input the corresponding frequency curve to obtain the incoming water frequency P. i And based on P i Identifying hydrological year types: When P i A year with less than 90% is considered a wet year, when P i A year with a water level of not less than 90% and less than 97% is considered a normal water year. i A year with a water level of at least 97% is considered a dry year. A frequency drift compensation mechanism is introduced to correct the incoming water frequency: ， Q i To evaluate the monthly runoff in month i of the assessment period, P i Let σp be the inflow frequency corresponding to the runoff in month i of the evaluation period. i S represents the standard deviation of the instantaneous frequency of daily flow within the month. k skewness, k is the compensation coefficient, P i comp The frequency of incoming water after drift compensation, sign(S) k ) is the sign function for skewness.

4. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "calculating hourly, daily, monthly, and annual guarantee rates based on measured discharge flow data, wherein the discharge flow includes the power plant unit's generating flow and the discharge flow from the spillway facilities" includes: The process of obtaining the ecological flow target of the cross section (EF) i，n Where i is the month and n is the day number, the ecological flow target is determined in different time periods based on fish spawning needs and the suitability of aquatic habitats, and adopts the form of a Gaussian impulse function: ， Collect discharge flow data from each power station during the assessment period to obtain the total discharge flow: ， Calculate the guarantee rate at each time scale; Among them, EF i，n For the ecological flow target on day n of month i, EF i Let Q be the target value for ecological flow in month i. base Let A be the basic ecological flow, A be the pulse flow amplitude, and t be the time variable. p Let Q be the pulse center time, σ be the pulse width parameter, and Q be... total (t) represents the total discharge flow at time t, Q turbine (t): Unit power generation flow rate at time t, Q release (t) represents the discharge flow rate of the spillway at time t.

5. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "calculating the depth of damage when ecological flow fails to meet standards, including the maximum depth of damage and the cumulative depth of damage, and introducing the ecosystem memory effect to dynamically correct the depth of damage" specifically includes: Calculate daily damage depth: When Q total (d) <EF i = when, ； When Q total (d)≥EF i hour, ； Calculate the maximum and cumulative depth of damage during the assessment period; ， ， Introducing the ecosystem memory effect, a memory decay function is constructed. ， Calculate the dynamic damage depth on day t: ， D d Depth of destruction on day dd, Q total (d): Average total discharge on day dd, EF i For the ecological flow target of month i, D max D represents the maximum depth of damage during the assessment period. cum The cumulative depth of damage during the assessment period is given by τ, where n is the total number of days in the assessment period, M(τ) is the memory decay function, τ is the time interval, and T is the total depth of damage during the assessment period. memory D is the ecological restoration time constant. t dynamic Let D be the dynamic damage depth on day t. t instant Let be the instantaneous damage depth on day t, α be the memory influence coefficient, k be the number of days for memory review, and D be... t j dynamic For the tth The dynamic destruction depth after j days, M(j) is the memory decay function value after an interval of j days.

6. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "constructing a Bayesian network for ecological flow protection of cascade hydropower, analyzing the impact of upstream hub scheduling on the protection level of downstream sections, and calculating the overall protection level of the cascade" specifically includes: Construct a Bayesian network for cascade hydropower, with each cross section of the cascade as a network node and the relationship between upstream discharge flow and downstream support level as a directed edge; Upstream nodes include the downstream discharge flow Q at the upstream section. up Upstream ecological flow guarantee status S up Intermediate nodes include the water inflow Q within the interval. interval and river channel loss Q loss Downstream nodes include the downstream section protection status S. down ; Calculate the conditional probability of the downstream section's guaranteed state: Construct a tiered linkage guarantee transmission coefficient to represent the change in the downstream guarantee rate when the upstream guarantee rate changes by 1%. ， Calculate the overall protection level of the cascade: ， in, Q up S is the discharge flow rate at the upstream section. up To ensure the upstream ecological flow status, Q interval Q represents the inflow rate of the interval. loss S down To ensure the downstream section is in a safe condition, λ up→down ΔR is the upstream-to-downstream guarantee transmission coefficient. down ΔR represents the change in the downstream coverage rate. up R represents the change in the upstream coverage rate. cascade To represent the overall protection level of the cascade, n is the total number of cascade break sections, and w is the total number of break sections. i R represents the weight of the i-th cross section. i Let be the guarantee rate for the i-th cross section.

7. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "establishing a dual-constraint criterion based on the inflow frequency and the damage depth, constructing a graded protection assessment function, and determining the ecological flow protection level of each section and the entire cascade" specifically includes: A dual-constraint judgment function based on inflow frequency and damage depth is constructed, and different constraints are set for different hydrological year types: For high-water years, the constraint is that both the maximum damage depth and the cumulative damage depth are zero; For a normal water year, the constraints are that the maximum damage depth is less than the first threshold function and the cumulative damage depth is less than the second threshold function. The first threshold function and the second threshold function are respectively quadratic relationships with the water inflow frequency. For dry years, the constraint is that the cumulative damage depth does not exceed the preset upper limit of cumulative damage depth; Ecological flow guarantee levels are classified according to the degree to which constraints are met: Level 1: Meets the constraints of a high-water year, or the maximum depth of damage is zero and the annual guarantee rate is not lower than the first guarantee rate threshold; Level 2: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the second guarantee rate threshold; Level 3: Meets the dual constraints of the corresponding hydrological year type, and the annual guarantee rate is not lower than the third guarantee rate threshold; Level 4: Meets one of the dual constraints of the corresponding hydrological year type, or the annual guarantee rate is not lower than the fourth guarantee rate threshold; Level 5: The dual constraints of the corresponding hydrological year type are not met, or the annual guarantee rate is lower than the fourth guarantee rate threshold. Calculate the overall protection index of the cascade, which is the value of the protection rate of each section after weighting the section weight and the hydrological year type adjustment coefficient.

8. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The phrase "adjusting the ecological flow target and scheduling scheme based on the assessment results and combined with ecological monitoring data" specifically includes: Construct an ecological response database for the level of protection, collect ecological monitoring data during the assessment period, and calculate the correlation between the level of protection and ecological health indicators; When the ecological health index is below the preset threshold and the guarantee rate is above the preset threshold, the ecological flow target is deemed too lenient; when the ecological health index is above the preset threshold and the guarantee rate is below the preset threshold, the ecological flow target is deemed too strict. Based on the Bayesian update principle, the posterior distribution of the ecological flow target is updated according to the measured ecological response data, and the ecological flow target correction coefficient is calculated. The correction coefficient is the ratio of the posterior expected value to the prior value. Based on the revised ecological flow target, an optimized scheduling plan is generated, including: increasing the discharge flow of the spillway or adjusting the operation mode of the generating units for periods when the guarantee rate is lower than the preset threshold; adjusting the upstream hub scheduling plan for sections with a damage depth greater than the preset threshold; and formulating joint scheduling rules for river sections with a cascade linkage effect coefficient greater than the preset threshold.

9. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, The specific implementation process of water inflow frequency analysis includes: based on historical long-term natural monthly average runoff data, using Pearson type III curves for parameter estimation and fitting, and obtaining the theoretical probability distribution curve of the average flow of the driest month in each month; The specific implementation process of introducing the ecosystem memory effect includes: obtaining the ecological restoration time constant by fitting historical ecological monitoring data, constructing a memory function in the form of exponential decay, and calculating the dynamic damage depth based on the historical damage depth sequence; The specific implementation process of the cascade linkage guarantee assessment includes: constructing a Bayesian network with each cross section as a node and water flow connection as a directed edge, or using a graph neural network to generalize the cascade hydropower hub group into a graph structure, and learning the transmission law of guarantee insufficiency between cascades through graph convolutional networks.

10. The method for dynamically assessing the ecological flow guarantee level of cascade hydropower discharge according to claim 1, characterized in that, It also includes a visualization step, the specific implementation process of which includes: generating guarantee rate change curves for each cross section at hourly, daily, monthly, and yearly time scales; generating time series diagrams of damage depth for each cross section, and marking the maximum damage depth and cumulative damage depth; generating ecological flow guarantee level distribution maps for each cross section and the entire cascade; dynamically updating and displaying the charts on the monitoring platform; and automatically generating an assessment report containing data on each indicator and level rating based on the assessment results.

Images