Recycled water replenishing flow control method and system based on industrial wastewater recycling

Abstract

The invention discloses a reclaimed water replenishing flow control method and system based on industrial wastewater recycling, and the method comprises the steps: dividing a river into a plurality of water replenishing regions according to the terrain height of a river landscape, collecting basic ecological data of different water replenishing regions, and inputting the basic ecological data and future weather data into a flow prediction model, outputting the water replenishing flow required by each water replenishing area; the water replenishing priority is determined according to the water replenishing flow needed by each water replenishing area, and the water replenishing flow speed is determined according to the river channel width and gradient of the water replenishing area; water flow supply is conducted according to the water supply priority and the water supply flow speed; and monitoring ecological change data of each water replenishing area, feeding back the ecological change data to the flow prediction model, carrying out continuous training optimization, and applying the optimized model to the next water replenishing period. According to the method, multivariate data are integrated, the water supplementing flow can be accurately predicted, the supplementing amount needed by each water supplementing area is dynamically adjusted by combining future weather data with basic ecological data, the water supplementing strategy can be continuously optimized, and effective utilization of water resources is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of river ecological protection, and in particular to a method and system for controlling the flow rate of recycled water replenishment based on industrial wastewater recycling. Background Art

[0002] Industrial wastewater contains a large amount of recyclable substances. Treating it to meet the standards and then reusing it for water resource replenishment is an effective means of water resource management. Although the traditional industrial wastewater recycling system can alleviate the pressure on water resources to a certain extent, there are still many challenges in practical application. For example, traditional wastewater treatment methods often ignore the coupling effect between wastewater recycling and natural water ecosystems, and cannot accurately assess the size of the replenishment flow, resulting in a large deviation between the replenishment strategy and actual demand, affecting the replenishment effect. In addition, most traditional water replenishment methods lack dynamic adjustment mechanisms and effective feedback mechanisms, and cannot adjust the replenishment strategy in real time according to external factors, resulting in inefficient water resource utilization. Summary of the invention

[0003] In order to solve at least one of the technical problems mentioned above, the present invention provides a method and system for controlling the flow rate of recycled water replenishment based on industrial wastewater recycling.

[0004] In a first aspect, the present invention provides a method for controlling the flow rate of recycled water replenishment based on industrial wastewater recycling, the method comprising: The river is divided into multiple water replenishment areas according to the terrain of the river landscape, and basic ecological data of different water replenishment areas are collected, including vegetation coverage, water flow velocity, water evaporation and groundwater recharge in each water replenishment area; Obtain future weather data, input future weather data and basic ecological data into the trained flow prediction model, and output the water replenishment flow required for each water replenishment area; Determine the duration of the current water replenishment cycle, determine the water replenishment priority according to the water replenishment flow required by each water replenishment area, and determine the water replenishment flow rate according to the river width and slope of different water replenishment areas; replenish water flow for each water replenishment area according to the water replenishment priority and the corresponding water replenishment flow rate; After the water flow replenishment is completed, the ecological change data of each water replenishment area is monitored, wherein the ecological change data includes a fish reproduction capacity change curve, a water quality change curve, and a water level change curve; The ecological change data is fed back to the flow prediction model and continuous training and optimization are carried out, and the optimized flow prediction model is used for the next water replenishment cycle.

[0005] Preferably, the method of determining the water replenishment flow rate according to the width and slope of the river in different water replenishment areas includes: ; In the formula, Indicates the required water replenishment flow rate of the water replenishment area, represents the width of the river, represents the slope of the river channel, represents the friction factor, represents the acceleration due to gravity, , represents the adjustment factor, , .

[0006] Preferably, the method further comprises training a traffic prediction model, comprising: The weather data, vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area in the historical period were collected as data sets. After reducing the dimension of the data sets, the feature quantities with the greatest correlation with the water replenishment flow were selected as training samples. The GRU network and the Transformer network are trained using training samples, and the trained GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively; Determine the initial weights of the base classifiers, obtain the classification error of each base classifier through parallel training, iteratively optimize the initial weights according to the classification error, and use the final integrated classifier with the updated weights to obtain the traffic prediction model.

[0007] Preferably, the river is divided into a plurality of water replenishment areas according to the terrain height of the river landscape, including: The GIS system is used to obtain the topographic map of the river landscape, and the DEM model is used to obtain the elevation data along the river; According to the elevation data along the river channel, the river channel is divided into several elevation intervals, and each interval corresponds to a water replenishment area.

[0008] In a second aspect, the present invention also provides a reclaimed water replenishment flow control system based on industrial wastewater recycling, the system comprising: The ecological data collection unit is used to divide the river into multiple water replenishment areas according to the terrain of the river landscape, and collect basic ecological data of different water replenishment areas, including vegetation coverage, water flow velocity, water evaporation and groundwater recharge of each water replenishment area; The water replenishment flow prediction unit is used to obtain future weather data, input the future weather data and basic ecological data into the trained flow prediction model, and output the water replenishment flow required for each water replenishment area; The water replenishment strategy determination unit is used to determine the duration of the current water replenishment cycle, determine the water replenishment priority according to the size of the water replenishment flow required by each water replenishment area, and determine the water replenishment flow rate according to the river width and slope of different water replenishment areas; and replenish water flow for each water replenishment area according to the water replenishment priority and the corresponding water replenishment flow rate; A change curve collection unit is used to monitor the ecological change data of each water replenishment area after the water flow replenishment is completed, and the ecological change data includes a fish reproduction capacity change curve, a water quality change curve, and a water level change curve; The prediction model optimization unit is used to feed back ecological change data to the flow prediction model and conduct continuous training and optimization, and use the optimized flow prediction model for the next water replenishment cycle.

[0009] Preferably, the water replenishment strategy determination unit is used to determine the water replenishment flow rate according to the river width and slope of different water replenishment areas, including: ; In the formula, Indicates the required water replenishment flow rate of the water replenishment area, represents the width of the river, represents the slope of the river channel, represents the friction factor, represents the acceleration due to gravity, , represents the adjustment factor, , .

[0010] Preferably, the water replenishment flow prediction unit is also used to train a flow prediction model, including: The weather data, vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area in the historical period were collected as data sets. After reducing the dimension of the data sets, the feature quantities with the greatest correlation with the water replenishment flow were selected as training samples. The GRU network and the Transformer network are trained using training samples, and the trained GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively; Determine the initial weights of the base classifiers, obtain the classification error of each base classifier through parallel training, iteratively optimize the initial weights according to the classification error, and use the final integrated classifier with the updated weights to obtain the traffic prediction model.

[0011] Preferably, the ecological data collection unit is also used for: The GIS system is used to obtain the topographic map of the river landscape, and the DEM model is used to obtain the elevation data along the river; According to the elevation data along the river channel, the river channel is divided into several elevation intervals, and each interval corresponds to a water replenishment area.

[0012] In a third aspect, the present invention further provides an electronic device comprising a processor and a memory, wherein the memory is used to store computer program code, and the computer program code comprises computer instructions. When the processor executes the computer instructions, the electronic device executes the method as described in the first aspect above and any possible implementation thereof.

[0013] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, wherein the computer program includes program instructions, and when the program instructions are executed by a processor of an electronic device, the processor executes the method as described in the first aspect above and any possible implementation thereof.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method for controlling the replenishment flow of recycled water based on the recycling of industrial wastewater, comprising dividing a river into a plurality of replenishment areas according to the terrain height of the river landscape, collecting basic ecological data of different replenishment areas, including vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each replenishment area; obtaining future weather data, inputting the future weather data and basic ecological data into a trained flow prediction model, and outputting the replenishment flow required for each replenishment area; determining the duration of a current replenishment cycle, determining the replenishment priority according to the size of the replenishment flow required for each replenishment area, and determining the replenishment flow rate according to the width and slope of the river in different replenishment areas; replenishing water flow for each replenishment area according to the replenishment priority and the corresponding replenishment flow rate; monitoring ecological change data of each replenishment area after the water flow replenishment is completed, wherein the ecological change data includes a fish reproduction capacity change curve, a water quality change curve and a water level change curve; feeding back the ecological change data to the flow prediction model and performing continuous training optimization, and using the optimized flow prediction model for the next replenishment cycle.

[0015] The present invention collects diversified basic ecological data, including the vegetation coverage rate, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area, and then combines future weather data with basic ecological data. Through regional division and flow prediction model, the water replenishment flow required for different water replenishment areas is accurately predicted, and the dynamic adjustment of the replenishment amount required for each water replenishment area is achieved to ensure the effective use of water resources. After replenishment, the ecological change data, including the fish reproduction capacity change curve, water quality change curve and water level change curve, are monitored; and these data are fed back to the flow prediction model for continuous training and optimization to ensure that the replenishment strategy is continuously improved to adapt to the changing needs of the ecological environment. Therefore, the method provided by the present invention improves the accuracy and efficiency of water resource replenishment and reduces the waste of water resources. The flexibility and adaptability of the replenishment system are enhanced, enabling it to cope with complex natural and socio-economic conditions. At the same time, the quality of the ecological environment is also improved, and the health and sustainable development of the ecosystem are promoted.

[0016] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0018] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0019] Figure 1 A schematic flow chart of a method for controlling the flow rate of recycled water replenishment based on industrial wastewater recycling provided by an embodiment of the present invention; Figure 2 A schematic structural diagram of a reclaimed water replenishment flow control system based on industrial wastewater recycling provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0022] See also Figure 1 , Figure 1 The present invention provides a flow chart of a method for controlling the flow rate of recycled water replenishment based on industrial wastewater recycling. Figure 1 As shown, the method includes: S10. Divide the river into multiple water replenishment areas according to the terrain of the river landscape, and collect basic ecological data of different water replenishment areas, including vegetation coverage, water flow velocity, water evaporation and groundwater recharge in each water replenishment area.

[0023] River ecosystems are often diverse, and different river sections may have significant differences. For example, some river sections may have lush vegetation, while others may be relatively dry; some river sections may have abundant groundwater, while others may be relatively barren. Therefore, different river sections have different needs for water replenishment. Zoning water replenishment can be personalized according to the specific ecological conditions and needs of each section, thereby better maintaining ecological balance.

[0024] Preferably, the river is divided into a plurality of water replenishment areas according to the terrain height of the river landscape, including: The GIS system is used to obtain the topographic map of the river landscape, and the DEM model is used to obtain the elevation data along the river; According to the elevation data along the river channel, the river channel is divided into several elevation intervals, and each interval corresponds to a water replenishment area.

[0025] In this embodiment, a geographic information system (GIS) tool is first used to perform terrain analysis on the river channel to identify areas with different altitudes. The river channel is divided into several water replenishment areas according to the different terrain heights. Each water replenishment area can correspond to different terrain features. Finally, corresponding data collection points are set in each water replenishment area to facilitate the subsequent collection of basic ecological data.

[0026] Furthermore, basic ecological data of different water replenishment areas were collected, including: Vegetation coverage rate: Obtain data on vegetation coverage in each water replenishment area through remote sensing satellite images or drone aerial photography.

[0027] Water flow velocity: Install water flow velocity meters at selected collection points to record water flow velocity data regularly.

[0028] Water flow evaporation: Use weather station data or dedicated evaporation monitoring equipment to record evaporation data for each water replenishment area.

[0029] Groundwater recharge: The groundwater recharge of each recharge area is calculated through groundwater level monitoring wells or groundwater flow models.

[0030] Therefore, through the above steps, we can fully understand the basic ecological conditions of each water replenishment area, and provide solid data support for the subsequent formulation of scientific and reasonable water replenishment strategies. This will not only improve the level of refined water resource management, but also effectively promote ecological protection and restoration work.

[0031] S20, obtaining future weather data, inputting the future weather data and basic ecological data into the trained flow prediction model, and outputting the water replenishment flow required for each water replenishment area.

[0032] When obtaining future weather data, you can access the weather forecast API provided by the authority to obtain weather data for a certain period of time in the future, including but not limited to temperature, precipitation, wind speed, humidity, etc. Preferably, you can also combine local weather station data, especially small automatic weather stations (AWS) data, to improve the accuracy and locality of weather forecasts.

[0033] In one embodiment, in order to quickly and accurately predict the water replenishment flow required for each water replenishment area, a flow prediction model needs to be trained in advance so that after obtaining future weather data and basic ecological data, they can be directly input into the model to output the predicted results of the water replenishment flow.

[0034] Specifically, training the traffic prediction model includes: The weather data, vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area in the historical period were collected as data sets. After reducing the dimension of the data sets, the feature quantities with the greatest correlation with the water replenishment flow were selected as training samples. The GRU network and the Transformer network are trained using training samples, and the trained GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively; Determine the initial weights of the base classifiers, obtain the classification error of each base classifier through parallel training, iteratively optimize the initial weights according to the classification error, and use the final integrated classifier with the updated weights to obtain the traffic prediction model.

[0035] In this embodiment, a large amount of historical data needs to be collected first, including weather data, vegetation coverage, water flow velocity, water flow evaporation, and groundwater recharge in each water replenishment area in the historical period as the original data set. Then, in order to improve the quality, outliers are removed first, any obviously wrong data points are checked and removed, and then interpolation, mean filling or other methods are used to handle missing data. After that, all features are scaled to the same scale to avoid some features dominating the model due to their large dimensions.

[0036] After data preprocessing, periodic features such as seasonal changes are extracted from the time series data. Then, new features are created through cross-features, such as the product of vegetation coverage and precipitation, to capture the interactions between different features to enrich the feature types. Then, principal component analysis (PCA) is used to reduce the dimensionality of the data while retaining the most important information.

[0037] After data dimension reduction, feature selection is required, that is, calculating the correlation coefficient between each feature and the target variable (water replenishment flow) and selecting the feature with the highest correlation. The recursive feature elimination method is used to gradually remove the features that contribute the least to the model until the most relevant features are retained. Finally, the feature with the greatest correlation with the water replenishment flow is selected as the input feature of the training sample.

[0038] When training the prediction model, use the training samples to train the GRU network and the Transformer network respectively, and use the trained GRU network and Transformer network as the base classifiers of the ensemble classifier. The GRU network is a special RNN (recurrent neural network) suitable for processing time series data. Transformer is a model based on the self-attention mechanism, which is very suitable for processing long sequence data. When training the ensemble classifier, use the two as the base classifiers of Bagging and train them in parallel. When training, you need to set appropriate training parameters, such as learning rate, batch size, number of iterations, etc. Choose a loss function suitable for the regression task, such as mean square error or root mean square error. Use a suitable optimizer, such as Adam, SGD, etc. To avoid overfitting, you can set an early stopping strategy to stop training when the performance on the validation set no longer improves.

[0039] Furthermore, the initial weights of the base classifiers are determined. Usually, the initial weights of the GRU network and the Transformer network can be set to 0.5. The classification error of each base classifier is obtained through parallel training. The initial weights are iteratively optimized according to the classification error. The final integrated classifier with the updated weights is used to obtain the traffic prediction model.

[0040] Specifically, the classification error of the classifier is: ; in, represents the classification error, represents the training sample of the jth base classifier in the i-th hidden layer, represents the sample weight of the jth base classifier in the i-th hidden layer, y represents the label corresponding to the training sample, represents the jth base classifier, represents the number of training samples, Represents the indicator function, satisfying: ; Through classification error Recalculate the classifier weights of the jth classifier in the i-th hidden layer : ; ; in, is a constant, set to 0.15.

[0041] In this embodiment, the GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively. By training the integrated classifier, the classification error is calculated to iteratively optimize the initial weights of the base classifier, thereby ultimately improving the generalization ability of the prediction model and ensuring the prediction accuracy.

[0042] Finally, after the flow prediction model is trained, you only need to input future weather data and basic ecological data into the model to quickly and accurately output the water replenishment flow required for each water replenishment area.

[0043] S30. Determine the duration of the current water replenishment cycle, determine the water replenishment priority according to the size of the water replenishment flow required by each water replenishment area, and determine the water replenishment flow rate according to the river width and slope of different water replenishment areas; replenish water flow for each water replenishment area according to the water replenishment priority and the corresponding water replenishment flow rate.

[0044] Usually, the impact of surrounding social and economic activities can be considered, such as the peak hours of urban water use, and then a reasonable water replenishment cycle can be determined, such as replenishment once every half a month or a month. According to the required replenishment flow rate of each replenishment area predicted in the previous step, the replenishment areas are sorted from large to small according to the required replenishment flow rate, and the replenishment priority list is determined. For areas with special needs (such as ecologically sensitive areas, drinking water source protection areas, etc.), even if the required replenishment flow rate is not the largest, their priority can be appropriately increased.

[0045] Furthermore, the replenishment flow rate is determined. The replenishment flow rate is usually related to the width and slope of the river in each replenishment area. Areas with wider river channels may require lower flow rates to prevent the water flow from being too dispersed and unable to achieve the expected replenishment effect. Considering the slope of the river channel, the flow rate needs to be controlled in areas with larger slopes to avoid erosion or scour caused by too fast water flow. Therefore, the most suitable replenishment flow rate is determined by comprehensively considering factors such as river channel width and slope.

[0046] In one embodiment, determining the water replenishment flow rate according to the river width and slope of different water replenishment areas includes: ; In the formula, Indicates the required water replenishment flow rate of the water replenishment area, represents the width of the river, represents the slope of the river channel, represents the friction factor, represents the acceleration due to gravity, , represents the adjustment factor, , .

[0047] In the above formula, It indicates the relationship between the required water replenishment flow and the width of the river at a certain width, and reflects the relationship between flow velocity, flow and river width. This indicates the effect of friction factor on flow velocity under the influence of gravity acceleration and slope. This part reflects the relationship between flow velocity, slope and friction. , This allows the formula to be flexibly applied under different geographical and climatic conditions to adapt to the specific conditions of various rivers.

[0048] Therefore, by accurately calculating the water replenishment flow rate, we can ensure that the water replenishment volume matches the actual needs of the river, avoiding water resource waste or ecological damage caused by excessive or insufficient water replenishment. A reasonable water replenishment flow rate helps maintain the balance of the river ecosystem and prevents changes in aquatic habitats caused by too fast or too slow water flow.

[0049] Finally, according to the determined priorities and flow rates, a detailed water replenishment plan is developed, including the start time, end time and specific water replenishment amount. Then, water replenishment facilities such as pump stations and pipeline valves are started according to the plan to ensure replenishment at the predetermined flow rate. During the entire replenishment process, sensors and other equipment are used to monitor parameters such as water level and flow rate in real time to ensure that the replenishment process proceeds as planned.

[0050] In summary, this embodiment can ensure that limited water resources are reasonably allocated and waste is avoided by accurately calculating the water demand of each water replenishment area and sorting them according to the water demand. Through the above steps, accurate water replenishment management based on scientific prediction and comprehensive consideration can be achieved, which not only improves the utilization efficiency of water resources, but also enhances the health and stability of the ecosystem and ensures the smooth progress of social and economic activities. This method is not only applicable to the current water replenishment cycle, but also can provide continuous support for future water resource management through continuous optimization and adjustment.

[0051] S40, monitoring the ecological change data of each water replenishment area after the water flow replenishment is completed, wherein the ecological change data includes a fish reproduction capacity change curve, a water quality change curve, and a water level change curve.

[0052] Water quality monitoring equipment, such as pH meters, dissolved oxygen detectors, turbidity meters, etc., are deployed in each water replenishment area to monitor water quality parameters in real time; water level sensors are installed to record water level changes in real time; video monitoring and sonar equipment are used to monitor the activities of fish and other aquatic organisms, and manual sampling is combined to investigate the number and species of fish. Based on the monitored data, data analysis tools are used to draw curves of changes in fish reproduction capacity, water quality, and water level.

[0053] S50, feeding back the ecological change data to the flow prediction model and performing continuous training and optimization, and using the optimized flow prediction model for the next water replenishment cycle.

[0054] Integrate the monitored ecological change data with historical water replenishment data, weather data, etc. to form a complete data set. Eliminate outliers and fill in missing values ​​to ensure the integrity and accuracy of the data. Construct new features based on ecological change data, such as fish reproductive capacity index and water quality health index. Filter out the most relevant features for flow prediction through correlation analysis, recursive feature elimination and other methods. Use the integrated data to retrain the flow prediction model, and adjust the model's hyperparameters through methods such as cross-validation and grid search. Finally, evaluate the performance of the updated model to ensure the generalization ability of the model. Compare the prediction results of the new and old models to analyze the improvement effect.

[0055] After the iterative update, the optimized flow prediction model is applied to the prediction of the next water replenishment cycle and continuously optimized, that is, new ecological change data is collected regularly and the above process is repeated to achieve continuous iterative optimization of the model. By continuously collecting ecological change data and feeding it back to the flow prediction model, the hyperparameters of the model are adjusted through methods such as cross-validation and grid search to improve the accuracy of the model's prediction of water demand in each water replenishment area. By monitoring ecological change data and adjusting the water replenishment strategy accordingly, the ecological balance of the water area can be better maintained, water quality can be improved, fish reproduction can be promoted, and biodiversity can be increased. Instead of just meeting the demand for water replenishment flow, it helps to achieve sustainable use of water resources and ensure the health and stability of the ecosystem.

[0056] In summary, the present invention collects diversified basic ecological data, including the vegetation coverage rate, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area, and then combines future weather data with basic ecological data. Through regional division and flow prediction model, the water replenishment flow required for different water replenishment areas is accurately predicted, and the dynamic adjustment of the replenishment amount required for each water replenishment area is achieved to ensure the effective use of water resources. After replenishment, the ecological change data, including the fish reproduction capacity change curve, the water quality change curve and the water level change curve, are monitored; and these data are fed back to the flow prediction model for continuous training and optimization to ensure that the replenishment strategy is continuously improved to adapt to the changing needs of the ecological environment. Therefore, the method provided by the present invention improves the accuracy and efficiency of water resource replenishment and reduces the waste of water resources. The flexibility and adaptability of the replenishment system are enhanced, enabling it to cope with complex natural and socio-economic conditions. At the same time, it also improves the quality of the ecological environment and promotes the health and sustainable development of the ecosystem.

[0057] See also Figure 2 In one embodiment, the present invention further provides a reclaimed water replenishment flow control system based on industrial wastewater recycling, the system comprising: The ecological data collection unit 100 is used to divide the river into multiple water replenishment areas according to the terrain height of the river landscape, and collect basic ecological data of different water replenishment areas, including vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area; The water replenishment flow prediction unit 200 is used to obtain future weather data, input the future weather data and basic ecological data into the trained flow prediction model, and output the water replenishment flow required for each water replenishment area; The water replenishment strategy determination unit 300 is used to determine the duration of the current water replenishment cycle, determine the water replenishment priority according to the size of the water replenishment flow required by each water replenishment area, and determine the water replenishment flow rate according to the river width and slope of different water replenishment areas; and replenish water flow for each water replenishment area according to the water replenishment priority and the corresponding water replenishment flow rate; The change curve collection unit 400 is used to monitor the ecological change data of each water replenishment area after the water flow replenishment is completed, and the ecological change data includes the fish reproduction capacity change curve, the water quality change curve and the water level change curve; The prediction model optimization unit 500 is used to feed back the ecological change data to the flow prediction model and perform continuous training optimization, and use the optimized flow prediction model for the next water replenishment cycle.

[0058] In one embodiment, the water replenishment strategy determination unit 300 is used to determine the water replenishment flow rate according to the river width and slope of different water replenishment areas, including: ; In the formula, Indicates the required water replenishment flow rate of the water replenishment area, represents the width of the river, represents the slope of the river channel, represents the friction factor, represents the acceleration due to gravity, , represents the adjustment factor, , .

[0059] In one embodiment, the water replenishment flow prediction unit 200 is also used to train a flow prediction model, including: The weather data, vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area in the historical period were collected as data sets. After reducing the dimension of the data sets, the feature quantities with the greatest correlation with the water replenishment flow were selected as training samples. The GRU network and the Transformer network are trained using training samples, and the trained GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively; Determine the initial weights of the base classifiers, obtain the classification error of each base classifier through parallel training, iteratively optimize the initial weights according to the classification error, and use the final integrated classifier with the updated weights to obtain the traffic prediction model.

[0060] In one embodiment, the ecological data collection unit 100 is further used for: The GIS system is used to obtain the topographic map of the river landscape, and the DEM model is used to obtain the elevation data along the river; According to the elevation data along the river channel, the river channel is divided into several elevation intervals, and each interval corresponds to a water replenishment area.

[0061] It can be understood that the functions or modules included in the system provided in this embodiment can be used to execute the method described in the above method embodiment. Its specific implementation can refer to the description of the above method embodiment. For the sake of brevity, it will not be repeated here.

[0062] The present invention also provides an electronic device, including a processor and a memory, wherein the memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes a method as described in any possible implementation manner.

[0063] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes a method as described in any possible implementation manner.

[0064] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0065] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

Claims

1. A method for controlling the flow rate of recycled water based on industrial wastewater recycling, characterized in that: The method comprises: The river is divided into multiple water replenishment areas according to the terrain of the river landscape, and basic ecological data of different water replenishment areas are collected, including vegetation coverage, water flow velocity, water evaporation and groundwater recharge in each water replenishment area; Obtain future weather data, input future weather data and basic ecological data into the trained flow prediction model, and output the water replenishment flow required for each water replenishment area; Determine the duration of the current water replenishment cycle, determine the water replenishment priority according to the water replenishment flow required by each water replenishment area, and determine the water replenishment flow rate according to the river width and slope of different water replenishment areas; replenish water flow for each water replenishment area according to the water replenishment priority and the corresponding water replenishment flow rate; After the water flow replenishment is completed, the ecological change data of each water replenishment area is monitored, wherein the ecological change data includes a fish reproduction capacity change curve, a water quality change curve, and a water level change curve; The ecological change data is fed back to the flow prediction model and continuous training and optimization are carried out, and the optimized flow prediction model is used for the next water replenishment cycle.

2. The method for controlling the flow rate of recycled water based on industrial wastewater recycling according to claim 1 is characterized in that: Determining the water replenishment flow rate according to the river width and slope of different water replenishment areas includes: ； In the formula, Indicates the required water replenishment flow rate of the water replenishment area, represents the width of the river, represents the slope of the river channel, represents the friction factor, represents the acceleration due to gravity, , represents the adjustment factor, , .

3. The method for controlling the flow rate of recycled water based on industrial wastewater recycling according to claim 1 is characterized in that: The method also includes training a traffic prediction model, including: The weather data, vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area in the historical period were collected as data sets. After reducing the dimension of the data sets, the feature quantities with the greatest correlation with the water replenishment flow were selected as training samples. The GRU network and the Transformer network are trained using training samples, and the trained GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively; Determine the initial weights of the base classifiers, obtain the classification error of each base classifier through parallel training, iteratively optimize the initial weights according to the classification error, and use the final integrated classifier with the updated weights to obtain the traffic prediction model.

4. The method for controlling the flow rate of recycled water based on industrial wastewater recycling according to claim 1 is characterized in that: The river is divided into multiple water replenishment areas according to the terrain of the river landscape, including: The GIS system is used to obtain the topographic map of the river landscape, and the DEM model is used to obtain the elevation data along the river; According to the elevation data along the river channel, the river channel is divided into several elevation intervals, and each interval corresponds to a water replenishment area.

5. A reclaimed water replenishment flow control system based on industrial wastewater recycling, characterized in that: The system comprises: The ecological data collection unit is used to divide the river into multiple water replenishment areas according to the terrain of the river landscape, and collect basic ecological data of different water replenishment areas, including vegetation coverage, water flow velocity, water evaporation and groundwater recharge of each water replenishment area; The water replenishment flow prediction unit is used to obtain future weather data, input the future weather data and basic ecological data into the trained flow prediction model, and output the water replenishment flow required for each water replenishment area; The water replenishment strategy determination unit is used to determine the duration of the current water replenishment cycle, determine the water replenishment priority according to the size of the water replenishment flow required by each water replenishment area, and determine the water replenishment flow rate according to the river width and slope of different water replenishment areas; and replenish water flow for each water replenishment area according to the water replenishment priority and the corresponding water replenishment flow rate; A change curve collection unit is used to monitor the ecological change data of each water replenishment area after the water flow replenishment is completed, and the ecological change data includes a fish reproduction capacity change curve, a water quality change curve, and a water level change curve; The prediction model optimization unit is used to feed back ecological change data to the flow prediction model and conduct continuous training and optimization, and use the optimized flow prediction model for the next water replenishment cycle.

6. The reclaimed water replenishment flow control system based on industrial wastewater recycling according to claim 5 is characterized in that: The water replenishment strategy determination unit is used to determine the water replenishment flow rate according to the river width and slope of different water replenishment areas, including: ； In the formula, Indicates the required water replenishment flow rate of the water replenishment area, represents the width of the river, represents the slope of the river channel, represents the friction factor, represents the acceleration due to gravity, , represents the adjustment factor, , .

7. The reclaimed water replenishment flow control system based on industrial wastewater recycling according to claim 5 is characterized in that: The water replenishment flow prediction unit is also used to train a flow prediction model, including: The weather data, vegetation coverage, water flow velocity, water flow evaporation and groundwater recharge of each water replenishment area in the historical period were collected as data sets. After reducing the dimension of the data sets, the feature quantities with the greatest correlation with the water replenishment flow were selected as training samples. The GRU network and the Transformer network are trained using training samples, and the trained GRU network and the Transformer network are used as base classifiers of the integrated classifier respectively; Determine the initial weights of the base classifiers, obtain the classification error of each base classifier through parallel training, iteratively optimize the initial weights according to the classification error, and use the final integrated classifier with the updated weights to obtain the traffic prediction model.

8. The reclaimed water replenishment flow control system based on industrial wastewater recycling according to claim 5 is characterized in that: The ecological data collection unit is also used for: The GIS system is used to obtain the topographic map of the river landscape, and the DEM model is used to obtain the elevation data along the river; According to the elevation data along the river channel, the river channel is divided into several elevation intervals, and each interval corresponds to a water replenishment area.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store computer program codes, wherein the computer program codes include computer instructions. When the processor executes the computer instructions, the electronic device executes the method for controlling the reclaimed water replenishment flow rate based on industrial wastewater recycling as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the method for controlling the reclaimed water replenishment flow rate based on industrial wastewater recycling as described in any one of claims 1 to 4.

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